DRAFT, DO NOT CITE 

Re-Evaluation of Human Health Effects of Atrazine: Review of 

Experimental Animal and In vitro Studies and Drinking Water 

Monitoring Frequency 

Presented Jointly To The FIFRA Scientific Advisory Panel By:

U.S. Environmental Protection Agency 

Office of Pesticide Programs 

Health Effects Division 

and 

Environmental Fate and Effects Division 

in collaboration with the 

Office of Water 

and 

Office of Research and Development 

Presented On:

April 26-30, 2010
Page 2 of 263 

TABLE OF CONTENTS 

1. INTRODUCTION..................................................................................12

2. 2003 HUMAN HEALTH RISK ASSESSMENT ....................................16

3. MAMMALIAN TOXICITY .....................................................................18

3.2 MODE OF ACTION (MOA)......................................................................................................... 21

3.2.1 Background.................................................................................................................. 21

3.2.2 2003 Key Events – HPG axis................................................................................... 22

3.2.3 Effect of Atrazine on the hypothalamic‐pituitary‐gonadal function. ...................23

3.2.4 2010 Key Events – HPA axis ................................................................................... 24

3.2.5 Effect of Atrazine on the regulation of the hypothalamic‐pituitary‐adrenal axis25

3.2.6 Linking the hypothalamic‐pituitary‐adrenal and hypothalamic pituitary‐ovarian

responses. ............................................................................................................................. 26

3.3 REPRODUCTIVE/DEVELOPMENTAL TOXICITY ......................................................................... 30

3.3.1 Female Reproductive/Developmental Toxicity .......................................................... 30

3.3.2 Male Reproductive/Developmental Toxicity......................................................... 32

3.3.2.1  Delayed Puberty Onset ......................................................................................................32

3.3.2.2 Prostatitis............................................................................................................................35

3.3.2.3 Effects on Aromatase and steroidogenesis ........................................................................37

3.3.2.4  Andrology ...........................................................................................................................39

3.4 NEUROTOXICITY............................................................................................................... 41

3.5 IMMUNOTOXICITY............................................................................................................ 44

3.6 GENOTOXICITY AND CARCINOGENESIS ................................................................................. 48

3.7 INSULIN RESISTANCE AND MITOCHONDRIAL FUNCTION IMPAIRMENT........................................ 51

4. SUMMARY OF MAMMALIAN TOXICITY............................................51

5. APPROACHES TO EVALUATING WATER SAMPLING 

STRATEGIES AND FREQUENCY OF MONITORING............................53

5.1. INTRODUCTION ....................................................................................................................... 53

5.2 THE NATURE OF PESTICIDE OCCURRENCE IN SURFACE WATER ........................................................... 54

5.3 SAMPLING FREQUENCY IN MONITORING: IMPLICATIONS FOR PESTICIDE EXPOSURE ASSESSMENTS ............57

5.3.1 General Monitoring Strategies..................................................................................... 57

5.3.2 Data Quality Objectives................................................................................................ 58

5.3.3 Monitoring Strategies Related to Pesticides ................................................................ 59

5.4 APPROACHES TO ANALYZING AND INTERPRETING MONITORING DATA COLLECTED AT DIFFERENT SAMPLING

FREQUENCIES.................................................................................................................................61

5.4.1 Characterizing Exposure Time Series From Less Frequent Monitoring Data................ 61

5.4.2 Determining Confidence Bounds on Exposure Estimates From Monitoring Data........65

5.5  EXAMINING THE PERFORMANCE OF VARIOUS SAMPLING STRATEGIES WITH DATA FROM THE ATRAZINE

MONITORING PROGRAM (AMP)....................................................................................................... 66

5.5.1 Profiles of Community Water Systems in the AMP ...................................................... 66

5.5.2. Approaches from the 2007 and 2009 SAP Meetings on Monitoring in Surface Water

Streams in the Corn and Sorghum Growing Region of the US .............................................. 68

5.5.3 Current Methods .......................................................................................................... 69

5.5.3.1 Comparing Upper Percentile Values from Different Sampling Strategies with those of the

“True” Profile ...................................................................................................................................69

5.5.3.2. Examining the Ranges of Maximum Running Averages of Different Durations for Various

Sampling Strategies..........................................................................................................................74
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5.5.3.3 Results..................................................................................................................................76

5.5.4. Summary of Initial Analyses ........................................................................................ 93

5.6. ARTIFICIAL NEURAL NETWORK (ANN) MODELING OF ATRAZINE OCCURRENCE PATTERNS ..................... 95

5.6.1 Time Series Plots Using Frequent Monitoring Data...................................................... 95

5.6.2 Artificial Neural Network Modeling ............................................................................. 98

5.6.3. Predictive Analytics ................................................................................................... 100

5.6.4. Simulating Daily Levels.............................................................................................. 102

5.6.5 Evaluating a Monitoring Strategy .............................................................................. 103

5.6.7. Summary – Advantages and Disadvantages of Using the ANN Models.................... 105

5.7 SUMMARY OF WATER MONITORING FREQUENCY METHODS ........................................................... 105

5.7.1. Planned Approach to Evaluate the Methods and Models for Estimating Pesticide

Concentrations From Less Frequent Monitoring Data ........................................................ 106

APPENDIX A .........................................................................................110

EVALUATION OF ARTICLES ON ATRAZINE AND ATRAZINE METABOLITES RELATED TO

MAMMALIAN TOXICITY STUDIES SUGGESTING POTENTIAL ADVERSE HUMAN HEALTH

OUTCOMES.............................................................................................................................. 110

A.1 CONTENT OF THIS APPENDIX..........................................111

A.2 EFFECTS ON FEMALES ....................................................112

A.2.1 Dooley, G.P., Reardon, K.F., Prenni, J.E., Tjalkens, R.B., Legare, M.E., Foradori,

C.D., Tessari, J.E., Hanneman, W.H. (2008).  Proteomic analysis of diaminochlorotriazine

adducts in Wistar rat pituitary glands and LβT2 rat pituitary cells.  Chem Res Toxicol

21:844‐851.......................................................................................................................... 112

A.2.2 Fraites, M.J.P., Cooper, R.L., Buckalew, A., Jayaraman, S., Mills, L., and Laws, S.C.

(2009). Characterization of the Hypothalamic‐Pituitary‐Adrenal Axis Response to Atrazine

and Metabolites in the Female Rat.  Tox. Sci. 112(1):88‐99.............................................. 113

A.2.3 Gojmerac, T., Pleadin, J., Zuric, M., Rajkovic‐Janje, R., and Korsic, M.,  2004.

Serum Luteinizing Hormone Response to Administration of Gonadotropin‐Releasing

Hormone to Atrazine‐Treated Gilts. Vet Human Toxicol. 46(5): 245‐247......................... 116

A.2.4 Juliani, C., Silva‐Zacarin, E., Santos, D. and Boer, P. 2008. Effects of Atrazine on

Female Wistar Rats: Morphological Alterations in Ovarian Follicles and

Immunocytochemical Labeling of 90 kDa Heat Shock Protein.  Micron. 39:607‐616.......117

A.2.5 Laws, S., Farrell, J., Stoker, T. and Cooper, R. (2003) Pubertal Development in

Female Wistar Rats following Exposure to Propazine and Atrazine Biotransformation By‐

Products, Diamino‐S‐Chlorotriazine and Hydroxyatrazine. Toxicological Sciences 76:190‐

200. .............................................................................................................................. 119

A.2.6 McMullin, T.S., Andersen, M.E., Nagahara, A. Lund, T.D., Pak, T., Handa, R.J.,

Hanneman, W.H. (2004).  Evidence that atrazine and diaminochlorotriazine inhibit the

estrogen/progesterone induced surge of luteinizing hormone in female Sprague Dawley

rats without changing estrogen receptor action. Tox. Sci. 79:278‐286. ........................... 120

A.2.7 Shibayama, H.  Kotera, T., Shinoda, Y., Hanada, T. Kajihara, T., Ueda, M.,

Tamura, H., Ishibashi, S., Ymashita, Y., and Ochi, S.  2009. Collaborative Work on

Evaluation of Ovarian Toxicity Two‐ or Four‐week Repeated Dose Studies and Fertility

Study of Atrazine in Female  Rats. ..................................................................................... 121

A.3 REPRODUCTIVE EFFECTS IN MALES .............................124

A.3.1 Betancourt, M., Reséndiz, A., Casas, E. and Fierro, R. (2006) Effect of two

insecticides and two herbicides on the porcine sperm motility patterns using computer‐

assisted semen analysis (CASA) in vitro. Repro. Tox. 22:508‐512..................................... 124
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A.3.2 Friedmann, AS. 2002. Atrazine inhibition of testosterone production in rat males

following peripubertal exposure. Reproductive Toxicology 16: 275‐279. ........................ 125

A.3.3 Hase Y, Tatsuno M, Nishi T, Kataoka K, Kabe Y, Yamaguchi Y, Ozawa N, Natori

M, Handa H and Watanabe H. (2008)  Atrazine binds to F1F0‐ATP synthase and inhibits

microchondrial function in sperm.  Biochem Biophy Research Comm 366: 66‐72. ..........126

A.3.4 Kandori, H, Suzuki S, Asamoto M, et al.  2005.  Influence of atrazine

administration and reduction of calorie intake on prostate carcinogenesis in

probasin/SV40 T antigen transgenic rats.  Cancer Sci:  96:  221 – 226............................. 127

A.3.6 Laws, SC, Stoker, TE, Ferrell, JM, Hotchkiss, MG, and Cooper RL.  2007. Effects of

Altered Food Intake During Pubertal Development in Male and Female Wistar Rats.

Toxicol. Sci. 100(1): 194‐202............................................................................................... 130

A.3.7 Maravilla‐Galvan, R., Fierro, R., Gonzáles‐Marquez, H. Gómez‐Arroyo, S.,

Jiménez, Ir and Betancourt, M. 2009. Effects of Atrazine and Fenoxaprop‐Ethyl on

Capacitation and the Acrosomal Reaction in Boar Sperm. International Journal of

Toxicology. Volume 2, Number 1. pp. 24‐32...................................................................... 132

A.3.9 Pogrmic K, Fa S, Dakic V, Kaisarevic S, and Kovacevic R.  2009.  Atrazine Oral

Exposure of Peripubertal Male Rats Downregulates Steroidogenesis Gene Expression in

Leydig Cells. Toxicological Sciences 111(1):189‐197.......................................................... 134

A.3.10 Rayner J L., Enoch R R, et al.  2007.  Atrazine‐induced reproductive tract

alterations after transplacental and/or lactational exposure in male Long‐Evans rats.  Tox

Appl Pharmacol:  218:  238 – 248....................................................................................... 136

A.3.11 Rosenberg, B.G., Chen, H., Folmer, J., Liu, J., Papadopoulos, V., and Zirkin,

B.R. (2008).  Gestational Exposure to Atrazine: Effects on the Postnatal Development of

Male Offspring.  J. Andrology 29(3):304‐311..................................................................... 138

A.3.12 Stoker TE, Guidici DL, Laws SC, Cooper RL. 2002. The Effects of Atrazine

Metabolites on Puberty and Thyroid Function in the Male Wistar Rat. Toxicological

Sciences 67: 198‐206........................................................................................................... 139

A.3.13 Stoker, T.E., Laws, S.C., Guidici, D., and Cooper, R.L. 2000.  The effects of

atrazine on puberty in male wistar rats: An evaluation of a protocol for the assessment of

pubertal development and thyroid function.   Toxicological Sciences.  58: 50‐59. ..........141

A.3.14 Trentacoste, S V.. Friedmann, AS, Youker, RT, Breckenridge, CB, and  Zirkin,

BR.  2001.  Atrazine Effects on Testosterone Levels and Androgen‐Dependent

Reproductive Organs in Peripubertal Male Rats. Journal of Andrology, Vol. 22, No. 1,

January/February 2001 ; pp. 142‐148................................................................................ 142

A.3.15 Victor‐Costa, AB, Bandeira SMC, Oliveira AG, Mahecha GAB, Oliveira, CA.  

2010. Changes in Testicular Morphology and Steroidogenesis in Adult Rats Exposed to

Atrazine. Reproductive Toxicology.  oi10.1016/j.reprotox.2009.12.006.......................... 143

A.4 AROMATASE ......................................................................145

A.4.1 Albanito L, Lappano R, Madeo A, Chimento A, Prossnitz ER, Cappello AR, Dolce V,

Abonante S, Pezzi V, Maggiolini M. (2008). G‐protein‐coupled receptor 30 and estrogen

receptor‐α are involved in the proliferative effects induced by atrazine in ovarian cancer

cells. Environ Health Perspect. 116(12):1648‐55. .............................................................. 145

A.4.2 Benachour N, Moslemi S, Sipahutar H, Seralini GE.  (2007). Cytotoxic effects of

aromatase inhibition by xenobiotic endocrine disrupters alone and in combination.  

Toxicology and Applied Pharmacology.   222:129‐140. .................................................... 147

A.4.3 Fan W, Yanase T, Morinaga H, Gonda S, Okabe T, Nomura M, Hayes T,

Takayanagi R, Nawata H. (2007a). Herbicide atrazine activates SF‐1 by direct affinity and

concomitant co‐activators recruitments to induce aromatase expression via promoter II.  

Biochemical and Biophysical  Research Communications. 355:1012‐1018. ..................... 148

A.4.4 Fan W, Yanase T, Morinaga H, Gondo S, Okabe T, Nomura M, Komatsu T,

Morohashi K, Hayes TB, Takayanagi R, Nawata H. (2007b). G Atrazine‐induced aromatase
Page 5 of 263 

expression is SF‐1 dependent: implications for endocrine disruption in wildlife and

reproductive cancers in humans. Environ Health Perspect. 115(5):720‐7. ....................... 149

A.4.5 Heneweer M, van den Berg M, Sanderson JT.  (2004). A comparison of human

H295R and rat R2C cell lines as in vitro screening tolls for effects on aromatase.  Toxicol.

Lett. 149(2):183‐194. .......................................................................................................... 150

A.4.6 Higley EB, Newsted JL, Zhang X, Giesy JP, Hecker M.  (2010). Assessment of

chemicals effects on aromatase activity using the H295R cell line.  Environ Sci Pollut Res

Int. Jan 20. (Epub ahead of print)....................................................................................... 152

A.4.7 Holloway, A. Anger, D., Crankshaw, D., Wu, M, and Foster, W.  2008. Atrazine‐

induced Changes in Aromatase Activity in Estrogen Sensitive Target Tissues. Journal of

Applied Toxicology. 28:260‐270......................................................................................... 154

A.4.8 Laville N, Balaguer P, Brion F, Hinfray N, Casellas C, Porcher JM, Ait‐Aissa S.

(2006). Modulation of aromatase activity and mRNA by various selected pesticides in the

human choriocarcinoma JEG‐3 cell line.  Toxicology. 228:98‐108. ................................... 155

A.4.9 Rayner, J., Wood, C., and Fenton, S. (2003)  Exposure Parameters Necessary for

Delayed Puberty and Mammary Gland Development in Long‐Evans Rats Exposed in Utero

to Atrazine. Toxicology and Applied Pharmacology 195:23‐34........................................ 156

A.4.10 Suzawa, M and Ingraham, HA.  2008.  The herbicide atrazine activates

endocrine gene networks via non‐steroidal NR5A nuclear receptors in fish and

mammalian cells.  PLoS ONE 3(5):  e2117.  doi:10.1371/journal.pone.0002117. ............157

A.4.11 Yi D K, Kim P J, et al.  2010.  Dose‐ and time‐dependent effect of atrazine or

its metabolites on aromatase mRNA in vitro.   Only a preprint of article available........159

A.4.12 Yi, KD, Perez, EJ, Breckenridge, CB, and Simpkins, JW (2010?) Ex vivo effects

of atrazines or metabolites on phosphodiesterase activity.............................................. 160

A.5. NEUROTOXICITY................................................................161

A.5.1 Belloni V, Alleva E, et al.  2007.  Effects of low doses of atrazine on the

neurobehavioural development of mice.  Ethology Ecology & Evolution 19:  309 – 322. 161

A.5.2 Coban A, and Filipov, N M.  2007.  Dopaminergic toxicity associated with oral

exposure to the herbicide atrazine in juvenile male C57BL/6 mice.  Journal of

Neurochemistry 100:  1177‐1187....................................................................................... 163

A.5.3 Filipov N M, Stewart M A et al. 2007.  Dopaminergic toxicity of the herbicide

atrazine in rat striatal slices.  Toxicology 232:  68 – 78..................................................... 165

A.5.4 Foradori, C D, Hinds, L R, et al. 2009.  Atrazine inhibits pulsatile luteinizing

hormone release without altering pituitary sensitivity to a gonadotropin‐releasing

hormone receptor agonist in female wistar rats.  Biology of Reproduction.  81:  40 – 45.....

...........................................................................................................................................166

A.5.5 Foradori, C D, Hinds, L R, et al.  2009.  Effects of atrazine on GnRH

neuroendocrine function after its withdrawal in the adult female wistar rat. Biology of

Reproduction 81(6):  1099 – 1105. ..................................................................................... 167

A.5.6 Giusi G, Facciolo RM, et al.  2006.  The endocrine disruptor atrazine accounts for

a dimorphic somatostatinergic neuronal expression pattern in mice.  Toxicological

Sciences 89(1):  257 – 264................................................................................................... 169

A.5.7 Hossain M M and Filipov N M.  2008.  Alteration of dopamine uptake into rat

striatal vesicles and synaptosomes caused by an in vitro exposure to atrazine and some of

its metabolites.  Toxicology 248:  52 – 58.......................................................................... 171

A.5.8 Rodriguez V M, Thiruchelvam M, Cory‐Slechta D A.  2005. Sustained Exposure to

the widely used herbicide atrazine:  altered function and loss of neurons in brain

monoamine systems.  Environmental Health Perspectives.  113(6):  708‐715.................172
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A.6 IMMUNOTOXICITY..............................................................174

A.6.1 Cimino‐Reale, G., Ferrario, D., Casati, B., Brustio, R. Diodovich, C., Collotta, A.,

Vahter, M., Gribaldo, L.  (2008).  Combined in utero and juvenile exposure of mice and

atrazine in drinking water modulates gene expression and clonogenicity of myeloid

progenitors.  Toxicol. Letters 180:59‐66. ........................................................................... 174

A.6.2 Devos S, Bosscher K De, et al.  2003.  Inhibition of cytokine production by the

herbicide atrazine – Search for nuclear receptor targets.  Biochemical Pharmacology 65:  

303 – 308............................................................................................................................. 175

A.6.3 Devos S, Van Den Heuvel R, et al.  2004.  Limited effect of selected organic

pollutants on cytokine production by peripheral  blood leukocytes.  Eur. Cytokine Netw:   

15:  145 – 151...................................................................................................................... 177

A.6.4 Filipov, N M, Pinchuk, L M, et. al.  2005.  Immunotoxic effects of short‐term

atrazine exposure in young male C57BL/6 mice.  Toxicological Sciences:  86(2):  324‐332. ..

...........................................................................................................................................177

A.6.5 Karrow, N A, McCay, J A, et. al. 2005.   Oral exposure to atrazine modulates cell‐

mediated immune function and decreases host resistance to the B16F10 tumor model in

female B6C3F1 mice.  Toxicology:  15‐28........................................................................... 178

A.6.6 Mizota K and Ueda H.  2006.  Endocrine disrupting chemical atrazine causes

degranulation through Gq/11 protein‐coupled neurosteroid receptor in mast cells.  

Toxicological Sciences 90(2):  362 – 368. ........................................................................... 179

A.6.7 Pinchuk L M, Lee S‐R, and Filipov N M.  2007.  In vitro atrazine exposure affects

the phenotypic and functional maturation of dendritic cells.  Toxicology and Applied

Pharmacology 223:  206 – 217........................................................................................... 181

A.6.8 Pruett, S B,  Fan, R, et al.  2003.  Modeling and predicting immunological effects

of chemical stressors:  characterization of a quantitative biomarker for immunological

changes caused by atrazine and ethanol.   Toxicological Sciences:  75:  343‐354............182

A.6.9 Pruett, S B,  Fan, R, et al.  2009.  Patterns of immunotoxicity associated with

chronic as compared with acute exposure to chemical or physical stressors and their

relevance with regard to the role of stress and with regard to immunotoxicity testing.  

Toxicological Sciences:  109(2):  265‐275........................................................................... 183

A.6.10 Rooney, A A, Matulka R, and Luebke, R. 2003.  Developmental atrazine

exposure suppresses immune function in male, but not female Sprague‐Dawley rats.  

Toxicological Sciences 76:  366‐375. .................................................................................. 184

A.6.11 Rowe, A M, Brundage, K M, Schafer, R, and Barnett J B.   2006.  

Immunomodulatory effects of maternal atrazine exposure on male Balb/c mice.  

Toxicology and applied Pharmacology 21:  69 – 77. ......................................................... 185

A.6.12. Rowe A M, Brundage K M and Barnett J B.  2007.  In vitro atrazine‐exposure

inhibits human natural killer cell lytic granule release.  Toxicology and Applied

Pharmacology 221:  179 – 188........................................................................................... 187

A.6.13 Schwab, C L, Fan R, et al. 2005.  Modeling and predicting stress‐induced

immunosuppression in mice using blood parameters.  Toxicological Sciences 83:  101 –

113. ......................................................................................................................... 188

A.6.14 Whalen M M,  Loganathan B G, et al.  2003.  Immunomodulation of human

natural killer cell cytotoxic function by triazine and carbamate pesticides.  Chemico‐

Biological Interactions 145:  311 – 319.............................................................................. 188

A.7 CARCINOGENESIS/GENOTOXICITY.................................189
Page 7 of 263 

A.7.1 Fujimoto, N and Honda, H.  (2003).  Effects of Environmental Estrogenic

Compounds on Growth of a Transplanted Estrogen Responsive Pituitary Tumor Cell Line in

Rats.  Food Chem. Toxicol. 41:1711‐1717.......................................................................... 189

A.7.2 Fukamachi, K., Han, B.S., Kim, C.K., Takasuka, N., Matsuoka, Y., Matsuda, E.,

Yamasaki, T., and Tsuda, H. (2004). Possible enhancing effects of atrazine and

nonylphenol on 7,2‐dimethylbenz[a]anthracene‐induced mammary tumor development

in human c‐Ha‐ras proto‐oncogene transgenic rats. Cancer Sci. 95(5):404‐410. .............190

A.7.3 Garaj‐Vrhovac, V. and Zeijezic, D. (2004) Genotoxicity evaluation of pesticide

formulations containing alachlor and atrazine in multiple mouse tissues (blood, kidney,

liver, bone marrow, spleen) by comet assay. Neoplasma 51.3:198‐203. ......................... 191

A.7.4 Kmetic, I., Srcek, G., Slivac, I., Simic, B., Knlewald, Z., Kniewald, J.  2008. Atrazine

Exposure Decreases Cell Proliferation in Chinese Hamster Ovary (CHO‐K1) Cell Line.  Bull

Environ Contam Toxicol. 81: 205‐209. ............................................................................... 193

A.7.5 Malik, S. I., Terzoudi, G.I., and Pantelias, G.E. (2004).  SCE analysis in G2

lymphocytes prematurely condensed chromosomes after exposure to atrazine:  the non‐

dose‐dependent increase in homologous recombinational events does not support its

genotoxic mode of action.  Cytogenet Genome Res 104: 315‐319. .................................. 194

A.7.6 Manske, M., Beltz, L, and Dhanwada, K. 2004. Low‐Level Atrazine Exposure

Decreases Cell Proliferation in Human Fibroblasts. Arch. Environ. Contam. Toxicol. 46:438‐

444. .............................................................................................................................. 194

A.7.7 Mastrangelo, S., Tomassetti, M, Carratu, M.R., Evandri, M.G., and Bolle, P.

(2006).  Quercetin reduces chromosome aberrations induced by atrazine in the Allium

cepa test.  Environ and Mol Mutagen 47:254‐259. ........................................................... 197

A.7.8 Singh, M., Sandhir, R., and Kiran, R. 2008. Atrazine‐Induced Alterations in Rat

Erythrocyte Membranes: Ameliorating Effect of Vitamin E. J. Biochem. Molecular

Toxicology. Vol 22, No. 5: pgs. 363‐369............................................................................. 198

A.7.9 Singh, M., Kaur, P., Sandhir, R., Kiran, R. (2008).  Protective effect of vitamin E

against atrazine‐induced genotoxicity in rats.  Mutat Res 654:145‐149.......................... 199

A.7.10 Son, H‐Y., Nishikawa, A., Okazaki, K., Lee, K‐Y., Imazawa, T., and Hirose, M.

(2003).  Lack of Modifying Effects of Atrazine and/or Tamoxifen on Thyroid

Carcinogenesis in Rats Pretreated with N‐bis(2‐hydroxypropyl)nitrosamine (DHNP).  Food

Chem. Toxicol. 41:1811‐1816. ............................................................................................ 200

A.7.11 Tanaka, T., Kohno, H., Suzuki, R., Sugie, S. (2004)  Lack of modifying effects of

an estrogenic compound atrazine on 7,12‐dimethylbenz(a)anthracene‐induced ovarian

carcinogenesis in rats.  Cancer Lett. 210:129‐137. ............................................................ 201

A.7.12 Ueda, M., Imai, T., Takizawa, T., Onodera, H., Mitsumori, K., Mtsui, T. and

Hirose, M. (2005)  Possible enhancing effects of atrazine on growth of 7,12‐

dimethylbenz(a)anthracene‐induced mammary tumors in ovariectomized Sprague‐

Dawley rats. Cancer Sci. 96(1):19‐25. ................................................................................ 202

A.7.13 Yi, Kun Don, Breckenridge, Charles B, and Simpkins, James W.  2010.

Cytotoxicity of Atrazine and its Metabolites in vitro. Unpublished data. Syngenta Crop

Protection Inc...................................................................................................................... 206

A.8 INSULIN/MITOCHONDRIA FUNCTION ..............................207

A.8.1 Lim, S., Ahn, S.Y., Song, I.C., Chung, M.H., Jang, H.C., Park, K.S., Lee, K‐U, Pak,

Y.K., Lee, H.K. (2009).  Chronic Exposure to the Herbicide, Atrazine, Causes Mitochondrial

Dysfunction and Insulin Resistance. PLoS ONE 4(4): e5186, p.1‐11. ................................. 207
Page 8 of 263 

A.9 PHARMACOKINETICS: INTERNAL DOSIMETRY, METABOLISM, 

& TIME COURSE...................................................................................209

A.9.1 Dooley, G.P, Prenni, J.E., Prentiss, P.L., Cranmer, B.K., Anderson, M.E., Tessari,

J.D. (2006).  Identification of novel hemoglobin adduct in Sprague Dawley rats exposed to

atrazine.  Chem Res Toxicol 19:692‐700. ........................................................................... 209

A.9.2 Dooley, G.P., Hanneman, W.H., Carbone, D.L., Legare, M.E., Anderson, M.E.,

Tessari, J.D., (2007).  Development of an immunochemistry detection method for

atrazine‐induced albumin adducts.  Chem Res Toxicol 20:1061‐1066.............................. 210

A.9.3 Kim D. and Breckenridge C. (Syngenta). Derivation of the short‐term inhalation

NOAEL using a physiologically based pharmacokinetic model. January 29, 2010...........211

A.9.4 McMullin T.S. (2003) Pharmacokinetic modeling of disposition and time‐course

studies with [

14C]‐atrazine. J. Toxicol. Environ. Health, 66(A):941‐964. ........................... 212

A.9.5 McMullin, T.S., Hanneman, W.H., Cranmer, B.K., Tessari, J.D., and Andersen,

M.E. (2007). Oral absorption and oxidative metabolism of atrazine in rats evaluated by

physiologically modeling approaches. Toxicology 240:1‐14............................................. 213

A.9.6 Ross, M.K., Jones, T.L., and Filipov, M.N. (2009). Disposition of the herbicide 2‐

chloro‐4‐(ethylamino)‐6‐(isopropylamino)‐s‐triazine (atrazine) and its major metabolites

in mice: a liquid chromatography/mass spectrometry analysis of urine, plasma, and

tissue levels. Drug Metab. Dispos. 37(4): 776‐786. ........................................................... 215

APPENDIX B .........................................................................................217

ATRAZINE IMMUNOTOXICITY DATA.................................................................................................. 217

APPENDIX C .........................................................................................220

ARTIFICIAL NEURAL NETWORK MODELING OF ATRAZINE OCCURRENCE PATTERNS .................................. 220

ARTIFICIAL NEURAL NETWORK MODELING OF ATRAZINE OCCURRENCE PATTERNS .................................. 221

C.1 ABSTRACT....................................................................................222

C.2 BACKGROUND .............................................................................223

C.2.1 MONITORING STRATEGIES................................................................................................ 223

C.2.2 DATA QUALITY OBJECTIVES .............................................................................................. 223

C.2.3 ATRAZINE OCCURRENCE PATTERNS .................................................................................... 224

C.3 OCCURRENCE DATA...................................................................226

C.3.1 FREQUENT MONITORING DATA......................................................................................... 226

C.3.2 TIME SERIES PLOTS. ........................................................................................................ 227

C.3.3 DATASETS SUITABLE FOR MODELING.................................................................................. 231

C.4 ARTIFICIAL NEURAL NETWORK MODELING ............................233

C.4.1 ANN MODELS................................................................................................................ 233

C.4.2 ANN MODELING FOR THE MAUMEE RIVER, 1998. ............................................................... 235

C.4.3 ANN MODELING FOR THE SANDUSKY RIVER, 1995............................................................... 239

C.5 PREDICTIVE ANALYTICS.............................................................242

C.5.1 DIRECT DERIVATION OF THE EXPOSURE ............................................................................... 242

C.5.2 SCALING THE OCCURRENCE PATTERNS ................................................................................ 243

C.5.3 SIMULATING DAILY LEVELS ............................................................................................... 243

C.5.4 EVALUATING A MONITORING STRATEGY.............................................................................. 246
Page 9 of 263 

C.6 SUMMARY – ADVANTAGES AND DISADVANTAGES OF USING 

THE ANN MODELS...............................................................................247

BIBLIOGRAPHY....................................................................................248

POST 2003 REFERENCES ............................................................................................................... 248

PRE‐2003 REFERENCES................................................................................................................. 259
Page 10 of 263 

Figure 1: Atrazine and its chlorinated metabolites........................................................ 20

Figure 2: Relationship Between Duration of Exposure and No Observed Effect Levels 27

Figure 3: PROPOSED MOA SCHEMATIC.................................................................... 30

Figure 4: Concentrations of atrazine and chlorpyrifos over time in the White River, 

Indiana. Source: Gilliom et al, 2006. ...................................................................... 56

Figure 5: Comparison of daily time series for pesticide concentrations (dark blue line) to 

linear (red lines) and stair-step (light blue lines) extrapolations for samples taken at 

14- or 30-day intervals. .......................................................................................... 62

Figure 6: Conceptual illustration of the nearest neighbor approach for estimating daily 

pesticide concentrations at less frequent sampling intervals.................................. 64

Figure 7: (a-c) Profiles for Chemographs #22, #8, and #24 ......................................... 73

Figure 8: Illustration of a CWS chemograph with a single, relatively short duration 

(narrow) peak......................................................................................................... 77

Figure 9: Illustration of a CWS chemograph with a moderate duration peak and 

extended tail........................................................................................................... 81

Figure 10: Illustration of a Chemograph with a Broad or Extended Series of Peaks .... 85

Figure 11: Data for Maumee River 2001 ...................................................................... 96

Figure 12: Data for Maumee River 1998 ...................................................................... 97

Figure 13: Maumee 1998 and ANN Model with One Node .......................................... 98

Figure 14: Maumee 1998 and Max Likelihood Three-Node ANN Model .................... 100

Figure 15: Simulation Based on the Maumee 1998 Model......................................... 103

Figure 16: Effect of Atrazine Exposure on Aromatase Activity and Hormone Levels . 153

Figure 17: Treatment Groups ..................................................................................... 203

Figure 18 Atrazine Occurrence at Missouri-American Water Intake............................ 225

Figure 19: Source Water with Low Variability............................................................. 226

Figure 20: Source Water with Moderate Variability .................................................... 226

Figure 21: Data for Maumee River 2001 ................................................................... 228

Figure 22: Data for Maumee River 1998 .................................................................... 229

Figure 23: Data for a Headwater Stream.................................................................... 230

Figure 24: Data for Sandusky River 1995 .................................................................. 232

Figure 25: Maumee 1998 and ANN Model with One Node ........................................ 234

Figure 26: Maumee 1998 and Max Likelihood Four-Node ANN Model ...................... 237

Figure 27: Maumee 1998 and Max Likelihood Three-Node ANN Model .................... 238

Figure 28: Residuals for Maumee 1998 Three-Node Model....................................... 239

Figure 29: Data Contributing to Small Likelihood for Two-Node Model...................... 241

Figure 30: Simulation Based on the Maumee 1998 Model......................................... 244

Figure 31: Simulation Based on the Sandusky 1995 Model....................................... 245

Figure 32 Utility of ANN Modeling .............................................................................. 247
Page 11 of 263 

LIST OF TABLES 

Table 1: HPG Axis Perturbations: Summary of Temporal and Dose............................ 24

Table 2: HPA Axis Activation: Summary of Temporal and Dose .................................. 26

Table 3: HPA/HPG Axes Nexus: Summary of Temporal and Dose Concordance ....... 29

Table 4: Strain and Dose Comparison in Male Rats dosed peripubertally with atrazine34

Table 5: Summary of Atrazine Monitoring Program (AMP) Data for Atrazine in Raw 

Water*.................................................................................................................... 67

Table 6: Atrazine Monitoring Program Data for Atrazine in Raw Water*...................... 68

Table 7: Upper Percentile Values Derived from Different Sampling Strategies for 3 

Example CWS........................................................................................................ 71

Table 8: Percentiles of Maximum Concentrations for CWS #4 Sampled at 4-, 7-, or 14-

day Intervals........................................................................................................... 78

Table 9: Percentiles of Maximum 3-Day Average Concentrations for CWS #4 Sampled 

at 4-, 7-, or 14-day Intervals ................................................................................... 79

Table 10: Percentiles of Maximum 7-Day Average Concentrations for CWS #4 

Sampled at 4-, 7-, or 14-day Intervals.................................................................... 80

Table 11: Percentiles of Maximum Daily Concentrations for CWS #21 Sampled at 4-, 7-

, or 14-day Intervals ............................................................................................... 82

Table 12: Percentiles of Maximum 3-Day Average Concentrations for CWS #21 

Sampled at 4-, 7-, or 14-day Intervals.................................................................... 83

Table 13: Percentiles of Maximum 7-Day Average Concentrations for CWS #21 

Sampled at 4-, 7-, or 14-day Intervals.................................................................... 84

Table 14: Percentiles of Maximum Daily Concentrations for CWS #30 Sampled at 4-, 7-

, or 14-day Intervals ............................................................................................... 86

Table 15: Percentiles of Maximum 3-Day Average Concentrations for CWS #30 

Sampled at 4-, 7-, or 14-day Intervals.................................................................... 87

Table 16: Percentiles of Maximum 7-Day Average Concentrations for CWS #30 

Sampled at 4-, 7-, or 14-day Intervals.................................................................... 88

Table 17: Maximum 3-Day Average Concentrations for All CWS Sampled at 4-day 

Intervals ................................................................................................................. 89

Table 18: Single Day Concentrations for All CWS Sampled at 7-day Intervals ............ 90

Table 19: Maximum 3-Day Averages for All CWS Sampling Every Day (April thru 

August); Every 14 Days (balance of year)............................................................. 91

Table 20: 90-Day Averages for All CWS Sampling Every 7 Days (April thru August); 

Every 14 Days (balance of year)............................................................................ 92

Table 21: 75th Percentiles and Means for the Three Node Model ............................. 101

Table 22: 75th Percentiles and Means for Selected Models ...................................... 242
Page 12 of 263 

1. INTRODUCTION 

Atrazine – a chlorotriazine herbicide – is currently one of the most widely used 

agricultural herbicides in the United States, with approximately 70 million pounds of 

active ingredient applied domestically per year. The Interim Reregistration Eligibility 

Document (IRED) for atrazine was finalized in January 2003 with an addendum added 

in October 2003 (US EPA 2003). The Agency completed the reregistration eligibility 

document (RED) process for atrazine in April 2006. In recent years, numerous 

experimental toxicology and epidemiologic studies evaluating the toxicity profile and/or 

mode of action (MOA) of atrazine have become available. In order to consider the 

extent to which these new studies may impact the Agency’s human health risk 

characterization for atrazine, the Office of Pesticide Programs (OPP) in collaboration 

with the Office of Research and Development (ORD) and the Office of Water is in the 

midst of a re-evaluation of atrazine and its metabolites’ [deethyl-atrazine (DEA), 

deisopropyl-atrazine (DIA), and diamino-s-chlorotriazine (DACT)].1

 

As part of the re-evaluation of the health effects of atrazine, three meetings of the 

FIFRA Scientific Advisory Panel (SAP) are scheduled in 2010. The first of these was 

held February 2-4, 2010. The February, 2010 SAP meeting focused on a number of 

broad scientific issues related to the use of epidemiology and human incident data in 

risk assessment. As part of the February meeting, the Agency presented two case 

studies involving atrazine. The first case study considered selected epidemiology 

studies associating atrazine exposure with birth outcomes. The second case study 

described a collaborative effort between the Agency and investigators at the Agricultural 

Health Study (http://aghealth.nci.nih.gov) to compare exposure assessment approaches 

used to evaluate pesticide applicator exposure2. At the February SAP, the Agency also 

presented a draft framework for incorporating epidemiology and human incident data 

into risk assessment (USEPA, 2010). This draft framework described a proposed 

approach for developing a weight of the evidence (WOE) analysis using data from 

multiple sources (e.g., in vitro and in vivo experimental studies along with epidemiology 

studies) and from multiple levels of biological organization. The draft framework relies 

heavily on existing Agency and OPP guidance documents in addition to the concept of 

problem formulation in the 2009 National Research Council (NRC) of the National 

Academy of Science (NAS), “Science and Decisions" and the concept of understanding 

toxicity pathways in the 2007 “Toxicity Testing in the 21st Century: A Vision and A 

Strategy (2007)”. 

OPP’s proposed WOE approach for integrating epidemiologic data with 

experimental toxicology studies emphasizes pharmacokinetics (PK) and MOA as the 

scientific foundation for evaluating dose-response, species differences, lifestage 

 

1

 Henceforth mention of atrazine in this document also infers its chlorinated metabolites (DEA, DIA, and 

DACT) unless otherwise specified. 

2

 More detailed information on the Agency’s atrazine case studies from the February SAP meeting can be 

found at http://www.regulations.gov (Docket EPA-HQ-OPP-2009-0851). 
Page 13 of 263 

sensitivity, route to route differences, and biological plausibility of reported outcomes. 

Specifically, the draft framework describes the use of modified Bradford Hill criteria like 

that in the MOA Framework as a tool to organize, review, and interpret data (U.S. EPA, 

1999, 2005; Boobis et al, 2008; Sonich-Mullin et al., 2001; Meek et al., 2003; Seed et al, 

2005). Briefly, the concept of MOA involves the identification of a biologically plausible 

sequence of key events that are obligatory and quantifiable leading to an adverse 

outcome. The MOA analysis takes into account factors such as dose-response and 

temporal concordance, coherence, and consistency. In this analysis, data from humans 

and experimental in vitro and in vivo studies can be evaluated together for biological 

plausibility, to identify areas of confidence in addition to areas of uncertainty and where 

further research may be helpful. The Agency’s re-evaluation of the human health 

effects of atrazine is following OPP’s draft framework (USEPA, 2010). Specifically, prior 

to the fall, 2010 SAP meeting, the Agency will develop a draft WOE analysis for atrazine 

integrating data and information from epidemiology studies with experimental toxicology 

studies. The draft WOE analysis is also expected to include proposed, updated points 

of departure (PoDs) for extrapolating risk to atrazine along with an updated evaluation 

of the potential sensitivity to infants and children and proposed FQPA Safety Factor. 

Consistent with recommendations by the NRC in its 2009 report, OPP’s draft 

framework also describes the importance of using problem formulation at the beginning 

of a complex scientific analysis. The problem formulation stage starts with planning 

dialogue with risk managers to identify goals for the analysis and possible risk 

management strategies. This initial dialogue provides the regulatory context for the 

scientific analysis and helps define the scope of such an analysis. The problem 

formulation stage also involves consideration of the available information regarding the 

pesticide use/usage, toxicological effects of concern and exposure pathways and 

duration along with key gaps in data or scientific information. At present time, the 

Agency is still in the problem formulation stage with respect to both hazard and 

exposure assessment for atrazine. Agency scientists and risk managers have 

determined that, consistent with the RED, exposure in drinking water continues to be 

the major exposure pathway of concern for atrazine. In addition, it has been determined 

that the two key goals for the current re-evaluation are: 1) to determine the extent to 

which new science indicates a need for the Agency to develop a new human health risk 

assessment for atrazine and 2) to re-consider, as appropriate, the frequency of drinking 

water monitoring conducted by Syngenta, the atrazine registrant, as required by the 

Agency in the RED. To achieve these goals, so far, the Agency has compiled and 

reviewed approximately 100 atrazine in vivo and in vitro experimental toxicology studies 

published since 2003. With respect to drinking water exposure, the Agency is 

considering the performance of water sampling strategies for assessing human 

exposure from drinking water. 

The Agency’s scientific review of toxicology studies includes experimental 

toxicology studies available by January 30, 2010. Experimental toxicology studies 

available after January 30, 2010 will be integrated into the Agency’s draft WOE analysis 

scheduled for review by the FIFRA SAP in fall 2010. Not included in the current issue 
Page 14 of 263 

paper are studies on epidemiology and those evaluating the effect of atrazine on 

mammary gland development. Epidemiology studies will be evaluated in fall 2010 SAP 

meeting as part of the WOE analysis. A review of the literature on mammary gland 

development has been deferred to the fall 2010 meeting. Currently, there are several 

research efforts underway to further characterize the impact of atrazine exposure, if 

any, on mammary gland development. The Agency anticipates that these studies will 

be published in the spring of 2010. In order to perform an evaluation of these studies 

together with those already published, the Agency has decided to evaluate them as part 

of the fall, 2010 SAP meeting. Thus, the available data (Rayner et al., 2003 & 2005, 

Enoch et al.,2007) on the development of the mammary gland are not discussed in 

detail in this issue paper. 

This issue paper includes extensive discussion of the MOA of atrazine—this 

discussion involves data on the key events identified in the 2003 risk assessment 

related to the hypothalamic-pituitary-gonadal axis (HPG) in addition to new data on the 

hypothalamic-pituitary-adrenal (HPA) axis. As discussed in Section 2 (Previous Human 

Health Risk Assessment) below, in the 2003 IRED, the Agency identified perturbations 

of the neuroendocrine system leading to reproductive toxicity as the most biologically 

plausible and sensitive effects attributable to atrazine exposure. Specifically, in 2003, 

the Agency identified disruption of estrous cyclicity and delays in puberty onset (males 

and females) occurring as a consequence of disruptions to the HPG axis as the major 

endpoints of concern. Sections 3 and 4 (Mammalian Toxicity & Summary of 

Mammalian Toxicity) of this paper describe how the complex interaction between the 

HPA and HPG axes leads to a host of neuroendocrine-related effects – it is this 

cascade of events that are believed to result in the most sensitive effects of atrazine, 

i.e.,reproductive and developmental effects. The Agency believes that neuroendocrine 

related reproductive and developmental effects continue to be most important 

toxicological endpoints of concern for atrazine. 

This issue paper discusses new data on the immune and nervous systems, 

prostate, and the enzyme aromatase (Section 3, Mammalian Toxicity). Evidence of 

neurotoxicity and immunotoxicity either occur at doses higher than those eliciting the 

reproductive/developmental effects or are related to the neuroendocrine perturbations 

described by the MOA. The only tumorigenic response reported in the atrazine data 

base is the mammary gland tumors seen in Sprague Dawley rats after chronic exposure 

to atrazine. This tumor response is not considered relevant to humans as supported by 

the 2000 SAP review. Reproductive aging in the rat and human are driven by two 

different series of events. In rats, atrazine exposure leads to an early reproductive 

senescence marked by increases in estrogen and prolactin. Constant stimulation by 

these hormones, in turn, results in mammary tumor development. On the other hand, 

human reproductive senescence (menopause) is marked by a decrease in estrogen 

levels. Thus, the stimulus needed to cause the proliferative process in the mammary 

gland is not present. In the males, atrazine induces prostatitis and early postnatal 

exposure is a critical window of susceptibility to this effect. Atrazine exposure had also 

been linked to changes in aromatase activity in vitro. However, no evidence of atrazine-
Page 15 of 263 

induced changes in aromatase have been seen in vivo. Reported effects on the 

prostate occur at doses higher than those associated with the neuroendocrine-related 

alterations described by the MOA. 

It is prudent for the Agency to evaluate the hazard potential of atrazine and the 

drinking water monitoring strategy together. Namely, the frequency of drinking water 

monitoring is related to the temporal pattern of the toxicological endpoint of concern 

used for risk assessment. Generally, longer durations of toxicological concern (e.g., a 

long-term chronic effect) require a less frequent sampling design to approximate longer 

term exposures. However, as the duration of concern shortens, the frequency and 

timing of sampling become more important in determining how well the sample data 

capture these short-duration exposures. Depending on the aquatic resource being 

sampled, the likelihood increases that a peak exposure may be missed by less frequent 

sampling. This is most critical when the Agency is concerned about acute or very shortterm effects resulting from a single day (peak) or only a few days of exposure. 

Section 5 (Approaches for Evaluating Water Sampling Strategies & Frequency of 

Monitoring) considers several approaches for examining the issue of monitoring 

frequency for assessing exposure durations of interest in human health risk 

assessments. Two methods are discussed in greater detail than the others. The first 

approach discussed in detail looks at upper percentiles of single day estimates and 

maximum running averages of several days’ duration and compares the performance of 

different sampling strategies for deriving estimates of the “true” concentrations for these 

durations of interest. The second approach discussed in detail offers a modeling 

approach that can be applied to pesticide occurrence data and combined with different 

sampling strategies to evaluate their performance in meeting various data quality 

objectives. 

The current drinking water monitoring frequency being conducted by Syngenta 

and required by EPA, involves weekly sampling during the growing season and biweekly sampling for the remainder of the year. As discussed in Section 5, preliminary 

indications provided in this issue paper suggest that the current monitoring frequency is 

sufficient to assess the 90-day rolling average used in the most recent human health 

risk assessment (IRED, 2003). For the risk assessment, the 90-day rolling average was 

selected to correspond to: (i) the period within the year during which most peak 

concentrations are likely to occur; and (ii) the most sensitive effect (LH surge 

attenuation) occurring 4-5 months after daily dosing in a 6 month toxicity study. This 

combination represented the most conservative pairing of exposure duration with LH 

effects as seen in the available animal studies. The previous atrazine human health risk 

assessment was based on a strong science foundation, supported by significant 

external peer review, and represented the state-of-the-science at the time. The 90-day 

rolling average was believed to be a health protective duration of exposure given the 

state-of-the-science for atrazine prior to 2006. As such, the drinking water monitoring 

frequency required by the Agency in the RED was appropriate for protecting health 

given that knowledge. 
Page 16 of 263 

As part of the re-evaluation of atrazine, the Agency is placing particular emphasis 

on evaluating the PK time course and temporal pattern of key events in the MOA in 

addition to all other reported toxicity endpoints. At this time, the Agency has not made 

any conclusions on the appropriate duration of toxicological concern given the new 

science or the appropriate frequency of drinking water monitoring. However, if the 

current re-evaluation leads to a shortening of the duration of toxicological concern from 

90 days to a shorter duration (e.g., 3 or 7 days), then more frequent monitoring than the 

current sampling frequency may be needed to accurately assess atrazine 

concentrations. This issue paper concludes in Section 6 (Implications of MOA & 

Mammalian Toxicology Findings on Sampling Frequency) with a discussion how new 

knowledge of the MOA of atrazine may potentially impact drinking water monitoring 

frequency. The Agency will be soliciting comment from the SAP at the April meeting on 

the temporal aspects of atrazine toxicity and on the proposed statistical approaches for 

evaluating drinking water monitoring. The Agency will use the input from the SAP at the 

April meeting on these important science issues to inform further review and analysis in 

preparation for the fall 2010 meeting. 

This science issue paper describes the status of the Agency’s efforts to review of 

the experimental toxicology literature and to evaluate drinking water monitoring 

strategies. As such, the April SAP meeting on atrazine will focus on scientific issues 

related to the toxicity, MOA, and drinking water exposure profile. 

2. 2003 HUMAN HEALTH RISK ASSESSMENT 

The 2003 human health risk assessment for atrazine is complex and 

incorporated significant data development, regulatory evaluation, and FIFRA SAP 

review. The Agency has sought advice from the SAP on human health issues during 

three previous meetings (FIFRA SAP, 1988, 2000, 2003). Atrazine was first taken to 

the SAP for evaluation of rat mammary gland tumor response seen in adult cancer 

studies in 1988 (FIFRA SAP, 1988). At that time, the SAP noted that a “hormonal 

influence” might be an important consideration in the development of these mammary 

gland tumors in adult rats. The Agency returned to the SAP in 2000 (FIFRA SAP, 2000) 

for advice on atrazine’s MOA leading to mammary gland tumors, reproductive and 

developmental effects in rats, as well as the human relevance of these findings. 

The SAP agreed with the Agency’s proposal for atrazine’s neuroendocrine MOA, 

and they further concluded that it is unlikely that the mechanism by which atrazine 

induces mammary tumors in adult female Sprague Dawley rats could be operational in 

humans. Nevertheless, the SAP further concluded that it is not unreasonable to expect 

that atrazine might cause adverse effects on hypothalamic-pituitary function in humans 

if exposures were sufficiently high and that the MOA was relevant for developmental 

and reproductive effects (FIFRA SAP, 2000). Based on the 2000 SAP guidance, EPA 

changed its position on atrazine and reclassified it from a “possible carcinogen” to “not 

likely to be carcinogenic in humans”. 
Page 17 of 263 

In 2003, the Agency presented its evaluation on prostate cancer to the FIFRA 

SAP. At that meeting, the SAP evaluated the available epidemiology studies 

suggesting an association between atrazine and prostate cancer in workers at an 

atrazine manufacturing plant in St. Gabriel Louisiana. The SAP concurred with EPA’s 

conclusion that the data did not suggest an association between atrazine exposure and 

prostate cancer, but that the increase in incidence of prostate cancer in workers at the 

plant could likely be explained by the increase in Prostate Serum Antigen (PSA) 

screening at the plant (FIFRA SAP, 2003). The SAP also stated that a more thorough 

and systematic review of the biologic and epidemiologic literature on the topic of the 

potential or observed carcinogenic effects of atrazine exposure was required before 

concluding that atrazine exposure is an unlikely explanation for at least part of the 

excess of prostate cancer in the St. Gabriel manufacturing plant. Review of the 

epidemiologic studies with atrazine is on-going and will be considered as part of the 

draft WOE analysis and reviewed by the SAP in fall 2010. 

The 2003 EPA human health risk assessment identified non-cancer effects of 

atrazine following acute and chronic dietary exposures, short- and intermediate 

incidental oral exposures, and short-, intermediate-, and long-term dermal and 

inhalation exposures. Effects observed in developmental toxicity studies (i.e., delayed 

ossification of certain cranial bones in fetuses, and decreased body weight gain in 

adults that are not likely due to atrazine’s MOA but rather to general toxicity) were 

selected as the endpoint of concern for acute dietary exposure (NOAEL/LOAEL of 

10/70 mg/kg/day). Delayed preputial separation in male rats (which is associated with 

atrazine’s neuroendocrine MOA) was the basis for assessing the short-term oral, dermal 

and inhalation exposures (NOAEL/LOAEL of 6.25/12.5 mg/kg/day). Effects indicative of 

disruption of hypothalamic function (i.e., attenuation of pre-ovulatory luteinizing 

hormone surge) were determined to be appropriate toxicity endpoints of concern for 

chronic dietary, intermediate incidental oral, and intermediate- and long-term dermal 

and inhalation exposures (NOAEL/LOAEL of 1.8/3.65 mg/kg/day). 

The review of atrazine described in this issue paper focuses on the toxicological 

and in vitro data generated since the IRED was finalized in 2003 and thus builds upon 

the findings and conclusions drawn by Agency scientists at that time. The following 

section will describe the evolution of the state-of-the science since the IRED was 

finalized in 2003. Furthermore, it will describe how these developments have enhanced 

our understanding of the MOA that serves as the basis for the atrazine risk assessment. 

This issue paper does not propose updated PoDs for use in extrapolating human risk to 

atrazine; these values will be included in the draft WOE scheduled for review by the 

SAP in September, 2010. The Agency is, however, soliciting comment from the Panel 

on important scientific issues which will help inform the selection of such updated PoDs. 
Page 18 of 263 

3. Mammalian Toxicity 

The current evaluation has investigated the array of adverse effects reported in 

the literature over the past 7 years including reproductive/developmental toxicity in both 

males and females, neurotoxicity, immunotoxicity, carcinogenicity and most recently 

insulin resistance and mitochondrial function impairment as well as the hypotheses on 

atrazine’s mode of toxicity put forth by numerous researchers. In the 2003 IRED, the 

Agency identified perturbations of the neuroendocrine system leading to reproductive 

toxicity as the most biologically plausible and sensitive effects attributable to atrazine 

exposure. These adverse outcomes include disruption of estrous cyclicity and delays in 

puberty onset (males and females) occurring as a consequence of disruptions to the 

HPG axis. The other toxicities that have been implicated in atrazine-exposure (e.g. 

neurotoxicity, immunotoxicity) occur at doses higher than those eliciting the 

reproductive/developmental effects. Although it is reasonable to postulate that these 

effects may be related to the neuroendocrine perturbations described in the MOA, there 

are no atrazine specific data to conclusively establish this. 

The current evaluation of the post-2003 data, supports the neuroendocrine MOA 

and key events identified in the 2003 IRED but also expands our understanding by 

identifying another disrupted pathway in the MOA: activation of the hypothalamicpituitary-adrenal (HPA) axis manifested as increases in corticosterone levels. Activation 

of the HPA axis in turn leads to perturbations of the HPG axis. It is this cascade of 

events that results in the effects on LH and consequent reproductive and developmental 

effects observed after atrazine exposure. However, in the case of the aromatase data, 

while there are indications that aromatase activity increases in vitro there is no evidence 

that atrazine alters aromatase activity following in vivo exposure. Andrology 

experiments also fail to demonstrate a link between atrazine exposure and adverse 

reproductive performance. 

As was the case in the 2003 assessment, the new data on neurotoxicity and 

immunotoxicity indicate that effects reported after atrazine exposure are either linked to 

or occur at higher doses than the neuroendocrine perturbations in the MOA. No 

compelling evidence of structural or functional deficits was observed in the 

neurotoxicity. For carcinogenicity, none of the new data suggest that atrazine exposure 

contributes to tumor progression or that it makes the tumors already present in the 

system more aggressive. With regards to the suggestion that atrazine exposure may 

lead to mitochondrial dysfunction, insulin resistance, and perhaps obesity, there is only 

one published article suggesting this hypothesis. This article, however, is significantly 

flawed with numerous inconsistencies and deficiencies in the reporting and 

interpretation of the data thus rendering it of limited utility in understanding the 

toxicological profile of atrazine. 

In conclusion, the research conducted in the last seven years supports the 

neuroendocrine MOA identified in the 2003 IRED. The critical and most sensitive 

adverse effects continue to be related to the reproductive consequences of 
Page 19 of 263 

perturbations to the HPG axis. The new data, however, point to a connection between 

activation of the HPA axis and HPG axis perturbations. From the available data, it 

appears that HPA activation occurs shortly after atrazine exposure. However, the 

toxicological significance of this event remains unclear. In order to better characterize 

the temporal and dose-response relationship of changes in various events in the HPA 

and HPG axes and potential adverse health outcomes, it is critical to consider internal 

dosimetry and the temporal relationship between atrazine exposure and observable 

physiological effects. The following section will describe the most recent 

pharmacokinetic data available. This will be followed by a description and discussion of 

atrazine’s operative neuroendocrine MOA (including HPA axis activation) in the context 

of the pharmacokinetic data. This will, in turn, serve to frame the discussion and 

description of the various toxic effects observed after atrazine exposure. 

3.1 Pharmacokinetics: Internal Dosimetry, Metabolism, & Time Course

Upon entering the body via the oral route, atrazine is quickly metabolized to its 

dealkylated chlorinated metabolites deethyl-atrazine (DEA), deisopropyl-atrazine (DIA), 

and diamino-s-chlorotriazine (DACT) as illustrated in Figure 1. Following a single dose 

of 90 mg/kg atrazine administered via oral gavage, atrazine was barely detectable at 

24-h in rat plasma while DACT was the predominant species accounting for >98% of 

total chlorotriazine levels (McMullin, 2003). A plasma half-life of about 11 hours has 

been estimated for atrazine in rats (Timchalk, 1990). Oral administration of atrazine in 

rat toxicity studies has resulted in a double-peak behavior in plasma-time courses that 

have been attributed to discontinuous absorption from limited solubility of atrazine in the 

gut (McMullin, 2007). The primary routes of excretion have been identified to be the 

urinary and fecal excretion, accounting for about 67 and 18% of administered dose, 

respectively (Timchalk, 1990). 
Page 20 of 263 

Figure 1: Atrazine and its chlorinated metabolites 

Efforts to develop a physiologically based pharmacokinetic (PBPK) model for 

atrazine using rat information have focused on the liver as the primary site of 

metabolism and brain as a potential target organ for toxicity. An estimated 1.5 % of the 

administered dose has been reported to be bound to hemoglobin in red blood cells, 

although the specific interactions have not been characterized (Timchalk, 1990 and 

McMullin, 2003). 

More detailed disposition studies have been carried out in mice. Ross et al. 

examined the metabolism and disposition of atrazine in mice and how tissue levels may 

correlate with levels of atrazine and its metabolites found in plasma and urine (Ross, 

2009). Plasma levels of atrazine exhibited a biphasic behavior similar to that observed 

in rats with maximum levels seen at 0.5 hours post dose. Atrazine levels were below the 

limit of detection by 24 hrs. In contrast, levels of DACT, the major metabolite identified 

(~ 10-fold higher levels than mono-dealkylated metabolites), peaked at 2 hrs at all dose 

levels. The clearance of DACT was dose-dependent and relatively slow during the first 

24 hours (plasma half-lives of 7.5 and 42 hrs for 5 and 250 mg/kg bw atrazine, 

respectively). When plasma area under the curves (AUCs) for DACT were plotted 

versus atrazine dose, a significant linear correlation was observed (r2

 = 0.987). In urine, 

DACT levels were 2 orders of magnitude higher (as high as 5400 μM) than atrazine or 

its mono-dealkylated metabolites in the 0-24 hr time period. In liver and kidneys, 

atrazine and its metabolites were detectable at 4 hrs. DACT was the most abundant 
Page 21 of 263 

species followed by atrazine. Lower levels of each compound were found in the kidneys 

as compared to the liver. Significant levels of DACT (as much as 50 μM at the highest 

dose) were found in the brain of mice at 4 hours along with low levels of atrazine (~1 μM 

at the highest dose). Atrazine was still detectable in the brain at all dose levels at 24 

hrs, while DACT levels remained high at this time point. At the low doses of 5 and 25 

mg/kg, maximum levels of atrazine (~2-3 μM) were detected in the spleen and thymus 

at 1 hr, whereas at the two highest doses (125 and 250 mg/kg atrazine), maximum 

ATRA levels were seen at 4 hrs. Peak levels of DACT, the major species detected, 

were seen at 4 hrs at the two highest doses of atrazine. 

Stoker et al. (2007) examined the potential lactational exposure of atrazine in the 

developing suckling rat neonate following a single oral gavage dose of 2 or 4 mg/kg 

radiolabeled atrazine to the lactating dam on postnatal day 3. Following 2 1/2 hours 

post-dose, the neonates were allowed to nurse for 30 minutes. At the end of the nursing 

period, radioactivity was measured in different tissues of the dam and in the stomach 

and brains of the pups. Radioactivity accounting approximately for 0.007% and 

0.0002% of the administered dose was measured in the pup stomachs and brains, 

respectively. In the dam (at 3 hours post-dose), the highest levels of radioactivity were 

found in the liver and kidneys, and only very low levels (0.003%) were present in the 

brain. 

The kinetic profile of this pesticide is critical to understanding its toxicity profile. 

Particularly, in light of recent data indicating that corticosterone levels can be affected 

within 15 minutes of atrazine exposure. Thus, the rapid absorption and metabolism 

demonstrated in the majority of the kinetic data are consistent with the apparent time-toeffect profile seen throughout the database that are key components of the temporal 

concordance analyses supporting the neuroendocrine MOA for atrazine. 

3.2 Mode of Action (MOA) 

3.2.1 Background 

In describing and analyzing a MOA for any chemical, the Agency applies a 

framework for organizing and analyzing the available data. This framework developed 

by a working group convened by the International Program on Chemical Safety (IPCS) 

takes a systematic approach to analyzing the data (Boobis et al., 2008). This process 

allows for a more transparent assessment of a chemical’s potential to elicit an adverse 

effect. The first step in this approach is to ascertain if it is possible to establish a MOA 

by describing the key events – including an analysis of the dose-response and temporal 

concordance of the events – that lead to the adverse outcome. Following the 

description of the key events, the data are scrutinized to determine the strength, 

consistency, and specificity of the relationship between the key events and the toxic 

response. Finally, the data are analyzed to determine if the key events are biologically 

plausible in humans both on a qualitative and quantitative basis. Once the data have 

been subjected to this evaluation, other potential MOAs considered and shown to be 
Page 22 of 263 

unlikely, the analysis culminates in a statement of confidence, analysis, and implications 

that clearly articulates the uncertainties, strengths, weaknesses, and implications of the 

analysis. 

 3.2.2 2003 Key Events – HPG axis 

The review of atrazine described in this issue paper focuses on the toxicological 

and in vitro data generated since the IRED was finalized in 2003. In the 2003

evaluation of atrazine, the disruption of the LH surge was used for setting the points of 

departure for the intermediate and chronic assessments. Similarly, the effect of atrazine 

on the neuroendocrine control of reproduction was considered a key step in the 

atrazine-induced delay in pubertal development in the both sexes (Stoker et al., 2000; 

Laws et al., 2000) and the disruption of prostate function in the male offspring when the 

dam is exposed immediately following birth. 

The goal of this new analysis is to ascertain if the new data impact the 

conclusions drawn in atrazine’s previous risk assessment (2003). Initially postulated to 

elucidate the physiological events and endocrine changes leading to mammary tumor 

formation in the Sprague-Dawley (SD) rats, the operative MOA for atrazine involves a 

series of key events that ultimately lead to early reproductive senescence in SD rats 

resulting in mammary gland tumor development. The key events described in the 2003 

IRED are: 

• Hypothalamic effects resulting in changes in catecholamine function and 

regulation of the pulsatile release of GnRH. 

• Attenuation of the LH surge 

• Cessation of ovulation with the ensuing persistent release of estrogen 

• Increased prolactin release by the pituitary as a secondary consequence 

resulting from the elevated estrogen levels 

• Prolactin and estrogen-induced proliferative processes in the mammary gland 

leading to tumorigenesis. 

In addition to identifying the key events in the MOA, a dose-response and time 

concordance analysis was also part of the 2003 evaluation. The attenuation of the LH 

surge was observed at a dose of 3.65 mg/kg/day after 26 weeks of exposure (Morseth 

et al., 1996c). The dose-response and time-to-effect profile for the LH surge attenuation 

closely parallel the profile for estrous cycle disruption and ultimately mammary tumor 

formation which occurred after two years of atrazine exposure at a dose level of 3.1 

mg/kg/day. Therefore, in general there was good dose- and time- concordance 

between the key events in the MOA and mammary tumors as well as the LH surge 

attenuation and reproductive effects with the key events occurring at doses ≤ to those 

where these effects were observed. 
Page 23 of 263 

One of the objectives of the current review is to ascertain if the neuroendocrine 

MOA leading to disruption of hypothalamic-pituitary-gonadal (HPG) axis described in 

2003 is still atrazine’s primary mode of action leading to adverse consequences in light 

of the new data produced over the last 6-7 years. The lines of evidence that have 

emerged from the new data support the neuroendocrine MOA and its key events but 

also identify important atrazine-induced changes in HPA axis namely increases in 

corticosterone levels. It is proposed that the activation of the HPA axis and its 

subsequent impact on the HPG axis provide a potential point of convergence for most – 

but not all – the toxic effects associated with atrazine exposure ranging from 

reproductive effects, and perhaps to neurotoxic and immunotoxic effects. 

3.2.3 Effect of Atrazine on the hypothalamic-pituitary-gonadal 

function. 

Several investigators have reported that atrazine impairs the neuroendocrine 

regulation of ovarian function. The disruption of ovarian cycles has been attributed to 

an atrazine-induced interruption of the ovulatory surge of luteinizing hormone (LH) that 

occurs on the day of vaginal proestrus (Cooper et al., 1996; Eldridge et al., 1999; 

Cooper et al., 2000; Cooper et al., 2007, McMullin, 2004; Foradori et al., 2009). During 

the last decade, a number of studies were completed attempting to further characterize 

the cellular and neuroendocrine changes responsible for how atrazine interferes with 

the regulation of LH secretion. The preponderance of evidence provides added 

support for the hypothesis that atrazine targets the brain to modify the neuronal control 

of pituitary function. For example, evaluating the secretion of gonadotropin releasing 

hormone (GnRH) in rats revealed that atrazine alters the release of this neuropeptide 

from the brain. GnRH is essential for LH release from the pituitary (Cooper et al., 2007, 

Foradori et al., 2009a). 

Importantly, the HPG axis in humans and rodents is maintained by the activity of 

GnRH neurons, whose cells are distributed throughout the preoptic region including the 

medial preoptic area (mPOA) of the anterior hypothalamus (Rivest and Rivier, 1995). 

The nerve terminals of these neurons project to the median eminence, where GnRH is 

released into the hypophysial portal circulation. The pulsatile secretion and the 

ovulatory surge of LH depend on the activity of GnRH neurons (Kalra and Kalra, 1983).

Research from two laboratories has shown that atrazine interferes with the pattern and 

amplitude of GnRH release by slowing the frequency of the pulses and lowering the 

overall amount of GnRH released into the portal system (Cooper et al., 2007; Foradori 

et al., 2009). In contrast, the ability of the pituitary LH-secreting cells (gonadotrophs) to 

respond to GnRH does not appear to be affected by atrazine, either in vivo or ex-vivo 

(Cooper et al., 2000; Foradori et al., 2009b). Further evidence supporting this 

observation comes from the work done on pigs demonstrating that a single intravenous 

injection of GnRH (100 μg) was able to partially reverse or counteract atrazine-induced 

suppression of the LH surge (Gojmerac et al., 2004). There have been some reports 

indicating that atrazine, or its metabolites, may interfere directly with GnRH activity (e.g., 

Zorrilla et al., 2010) as well as the activity of other neurons (Das et al., 2001). While 
Page 24 of 263 

these new data enhance our understanding of the processes involved in the HPG axismediated attenuation of the LH surge and subsequent toxic effects, they do not – at this 

time – suggest a lower effect level than the one used in the 2003 IRED. 

Table 1: HPG Axis Perturbations: Summary of Temporal and Dose 

Concordance 

Axis Key Event Time Dose (NOEL/LOEL) Reference 

Hypothalamus 

↓GnRH release 4 days N.A./25 mg/kg/day‡ Cooper et al.

2007 

1 day N.A./300 mg/kg/day Cooper et al. 

2000 

3 days N.A./50 mg/kg/day Cooper et al.

2000 

4 days N.A./6.25 mg/kg/day Cooper et al.

2007 

Pituitary 

Attenuation of 

LH surge 

26weeks 1.8/3.65 mg/kg/day Morseth et al., 

1996c 

1-day N.A./300 mg/kg/day Cooper et al. 

(2000)

21 days N.A./75 mg/kg/day Cooper et al. 

(1996)

HPG Axis 

Ovary 

Estrous cyclicity 

disruption 

26 weeks 1.8/3.65 mg/kg/day Morseth 

(1996c)

‡

 NOEL not available

3.2.4 2010 Key Events – HPA axis 

The physiological interaction between the hormones in the HPA axis (e.g., 

corticotrophin releasing hormone (CRH) and adrenal corticoids) and hormones in the 

HPG axis (e.g., GnRH and LH) was described by Rivier and Rivest (1991) and Kirby et 

al. (2009). The key events in the activation of the HPA axis include: 

• Hypothalamic changes resulting in an increase in CRH release 

• Increased release of adrenocorticotropin hormone (ACTH) from the pituitary 

• Increased production of coticosterone and progesterone by the adrenals 

• Decrease in GnRH release from the hypothalamus as a result of one, or all of the 

above, noted HPA changes. 

Given that decreased GnRH release from the hypothalamus is one of the key 

events in atrazine’s neuroendocrine MOA, it is plausible that activation of the HPA axis 

may play a role in atrazine’s neuroendocrine MOA. In vitro and in vivo studies 

conducted over the last seven years support this hypothesis (Sanderson et al., 2000 & 
Page 25 of 263 

2001; Laws et al., 2009; Fraites et al., 2009; Pruett et al., 2003; Holloway and Foster; 

and Tinfo and Laws, 2009).

3.2.5 Effect of Atrazine on the regulation of the hypothalamicpituitary-adrenal axis 

Research in male and female rats (Laws et al., 2009; Fraites et al., 2009) and 

male mice (Pruett et al., 2003) has shown that atrazine and its metabolites DIA and 

DEA (but not DACT) have a clear effect on the secretion of pituitary ACTH and adrenal 

steroid hormone secretion (i.e., corticosterone and progesterone). In the rat, this 

response is rapid (i.e., blood concentrations are significantly increased within 15 

minutes after oral gavage) after exposure to either 75 mg/kg/day of atrazine or 60.2 

mg/kg/day DIA [exposure to 50.2 mg/kg/day of DACT had no effect on pituitary-adrenal 

hormone release]. The corticosterone and progesterone response was observed after 

each daily dose for at least four days in the female (Fraites et al., 2009) and for at least 

21 days in the male (Laws et al., 2009) indicating that the animal does not habituate to 

this exposure. Furthermore, this response occurred following either gavage of atrazine 

or an intravenous administration of DIA (7.8 mM solution) (Fraites et al., 2009). These 

observations strongly suggest that the atrazine-induced endocrine response is a direct, 

chemical-induced change in the hypothalamic-pituitary-adrenal tissue and not the result 

of a non-specific gastrointestinal stress response. Indeed, it has been reported that 

atrazine, DIA and DEA (but not DACT) can increase the synthesis of steroid hormones 

in vitro, including progesterone, cortisol, estradiol and estrone in human adrenocortical 

carcinoma cells (H295R) and granulosa cells obtained from humans or rats further 

supporting the argument that the chlorotriazines increase steroidogenesis at the cellular 

level (Sanderson et al., 2000 & 2001; Holloway and Foster; Tinfo and Laws, 2009). 
Page 26 of 263 

 

Table 2: HPA Axis Activation: Summary of Temporal and Dose 

Concordance 

Axis Key Event Time Dose 

(NOEL/LOEL) Reference 

Hypothalamus 

↑CRH Not measured 

15 minutes N.A./50 mg/kg‡ Laws et al.,

2009 

15 minutes 

N.A./75 mg/kg 

atrazine 

60.2 mg/kg DIA 

Fraites et al., 

2009 

1 hour N.A./200 mg/kg 

atrazine 

Pruett et al., 

2009 

6 hours N.A./100 mg/kg 

atrazine 

Pruett et al., 

2003 

Adrenals 

↑progesterone, 

corticosterone 

4 days 

N.A./12.5 

mg/kg/day atrazine 

or 10 mg/kg/day 

DIA 

Fraites et al.,

2009 

15 minutes N.A./75 mg/kg 

atrazine

60.2 mg/kg DIA 

Fraites et al., 

2009 

Pituitary

↑ ACTH 

4 days 

N.A./12.5 

mg/kg/day atrazine 

or 10 mg/kg/day 

DIA 

Fraites et al.,

2009 

HPA Axis 

Hypothalamus 

↓GnRH release 4 days N.A./25 mg/kg/day Cooper et al.

2007 

 ‡ NOEL not available

3.2.6 Linking the hypothalamic-pituitary-adrenal and hypothalamic 

pituitary-ovarian responses. 

The studies described in the preceding sections demonstrate a clear disruption of 

both the brain-pituitary-gonadal and brain-pituitary-adrenal function. The fact that both 

these important neuroendocrine axes are disrupted, often with a similar dose response, 

has led to the hypothesis that the mode of action (MOA) for the loss of reproductive 

function begins with an atrazine-induced disruption of the pituitary-adrenal axis (Fraites 

et al., 2009; Laws et al., 2009). In this case, atrazine or its metabolites influence these 

two axes sequentially rather than in parallel with the changes in adrenal hormone 

secretion driving many of the changes initially observed in the gonadal axis. The 

evidence behind this hypothesis includes the following: 

Time to effect: The increase in pituitary ACTH and adrenal hormone secretion occurs 

immediately after a single dose whereas significant changes in pituitary-gonadal 
Page 27 of 263 

function, especially the LH surge, requires a longer exposure time (e.g., three daily 

doses) (Cooper et al., 2000 and 2007). Furthermore, the longer exposure regimens 

typically have a lower LOAEL (Figure 2). In fact, the current LOAEL for the effect of 

atrazine on the LH surge is based on a 6-month exposure period. 

Figure 2: Relationship Between Duration of Exposure and No Observed Effect 

Levels

a Cooper et al., Foradori at al., and Morseth et al. NOAELs based on suppression of LH and prolactin 

surge. Stoker et al. NOAEL based on delay in preputial separation. (From Simpkins, presentation to 

EPA, Jan 2010).

 

Adrenal steroids impair the LH surge: 

The influence of the adrenal hormones on the function of the pituitary-gonadal 

axis is well documented. Thus, it should not be surprising that atrazine, through its 

stimulatory effect on the adrenal axis, can impair control of reproductive development 

and function. Consider the following: 

• Activation of the pituitary-adrenal axis has short-term and long-term effects on 

many aspects of reproductive physiology and behavior in a variety of species, 

including rats and humans (Selye, 1939; Rivier and Rivest, 1991). 

• In the rat, repeated increases in corticosterone affect the gonadal axis at the 

level of the brain, pituitary and gonads including: 
Page 28 of 263 

o Brief increases in ACTH and corticosterone for four days induced by 

other means (i.e., restraint stress for 5 minutes) at 0900 h suppresses 

LH secretion to the same extent that atrazine or DIA administered at 

0900 h does (Fraites et al., 2009). 

o Increases in corticosterone alter the activity of the neurotransmitter and 

neuropeptide of those neurons controlling GnRH (Kirby et al., 2009), 

including an increase in gonadotropin inhibiting factor, CRH and 

norepinephrine all of which are known to decrease GnRH pulses. 

o Decreased pituitary gonadotropin response to GnRH (Rivier and 

Rivest, 1991) 

o Decreased steroidogenesis within the gonads (e.g., activation of the 

glucocorticoid receptors within the Leydig cell are known to lower 

testosterone synthesis, 11 ß-HSD is protective, Gao et al., 1996). 

The postulated nexus between activation of the HPA axis and perturbations of 

the HPG axis is summarized in Table 3. Figure 3 is a graphical representation of the 

sequence of events leading to the disruption of estrous cyclicity that is the most 

sensitive adverse health outcome attributed to atrazine exposure. Although, it is wellunderstood that a continuous 3 to 4 day elevation of corticosterone leads to 

perturbations of the HPG axis, the toxicological relevance of this rapid increase is 

currently unclear (i.e., at what duration and at what doses does this perturbation lead to 

an adverse outcome). Currently, the Agency is in the process of conducting BMD 

analyses for these endpoints to more clearly define the dose-response relationship 

between atrazine exposure and the observed effects. Unlike LOELs which reflect 

different levels of response and are limited by dose selection, BMD analysis will allow 

the Agency to more accurately illustrate the dose-response relationships as they relate 

to exposure durations. 

This re-evaluation attempts to determine the link, if any, between atrazineinduced activation of the HPA axis and the suite of toxicological effects reported after 

atrazine exposure. To that effect, a brief summary of the various toxic effects 

observed after atrazine exposure follows. 
Page 29 of 263 

Table 3: HPA/HPG Axes Nexus: Summary of Temporal and Dose Concordance 

Axis Key Event Time 

Concordance

Dose Concordance 

(LOEL) Reference 

Hypothalamus 

↑CRH Not measured 

15 minutes 

N.A./75 mg/kg 

atrazine‡ 

60.2 mg/kg DIA 

Fraites et al., 

Pituitary 2009 

↑ACTH 

4 days 

N.A./12.5 mg/kg/day 

atrazine or 10 

mg/kg/day DIA 

Fraites et al.,

2009 

15 minutes N.A./50 mg/kg Laws et al., 2009 

15 minutes 

N.A./75 mg/kg 

atrazine 

60.2 mg/kg DIA 

Fraites et al., 

2009 

1 hour N.A./200 mg/kg 

atrazine 

Pruett et al., 

2009 

6 hours N.A./100 mg/kg 

atrazine 

Pruett et al., 

2003 

HPA Axis 

Adrenals 

↑progesterone, 

corticosterone 

4 days 

N.A./12.5 mg/kg/day 

atrazine or 10 

mg/kg/day DIA 

Fraites et al.,

2009 

HPA/HPG 

Axis 

Hypothalamus 

↓GnRH release 4 days N.A./25 mg/kg/day Cooper et al.2007 

1 day N.A./300 mg/kg/day Cooper et al. 

2000 

3 days N.A./50 mg/kg/day Cooper et al.

2000 

4 days N.A./6.25 mg/kg/day Cooper et al.

2007 

Pituitary 

Attenuation of 

LH surge 

26weeks 1.8/3.65 mg/kg/day Morseth et al., 

1996c 

1-day N.A./300 mg/kg/day Cooper et al. 

(2000)

21 days N.A./75 mg/kg/day‡ Cooper et al. 

(1996)

HPG Axis 

Ovary 

Estrous cyclicity 

disruption 

26 weeks 1.8/3.65 mg/kg/day Morseth (1996c)

 ‡NOEL not available 
Page 30 of 263 

Figure 3: PROPOSED MOA SCHEMATIC 

↓LH

↓prolactin

Pituitary Steroidogenesis

↓GnRH pulses

(Catecholamines

Neuropeptides)

CRH/AVP

(Catecholamines

Neuropeptides)

Adrenal

♀ and ♂

↑Progesterone

↑Corticosterone

Gonad

♀ Δ Estrogen

Δ Progesterone

♂ Δ Testosterone

?

CNS

Atrazine

1

5 6

4

2

↑ACTH

Altered

Reproductive

Function

7

3

 

Figure 3: Schematic depicting the proposed mode of action of the chlorotriazines on reproductive 

function. The key events in this MOA are noted by the numbers. (1) Following a single exposure, 

atrazine has a direct effect on the neuronal pathways regulating (2) pituitary ACTH release and (3) 

increasing adrenal steroid hormone secretion. The feedback of the adrenal steroids (corticosterone and 

perhaps progesterone) on the brain (4) dampen the pulsatile release of GnRH lowering the release of LH 

(5) and (6) altering gonadal function. (7) There is also evidence that exposure to atrazine and the two 

monodiaklyated metabolites (DIA and DEA) may directly increase steroid hormone both in vivo and in 

vitro. 

3.3 Reproductive/Developmental Toxicity 

Exposure to atrazine and/or its metabolites has been linked to a number of 

effects on reproductive function and development including delays in puberty onset in 

both male and female rats and early reproductive senescence in females. These 

effects are consistent with disruption of the HPG axis. This section will briefly 

summarize the toxicological data pertaining to atrazine-induced effects on reproductive 

performance and development and their association with the MOA. 

 

 3.3.1 Female Reproductive/Developmental Toxicity 

 

Over the last seven years, studies have been conducted to evaluate the impact 

of atrazine and/or its by-products on the development and reproductive health of 
Page 31 of 263 

females.3 In 2003 Laws et al., evaluated the effects of DACT and hydroxyatrazine (a 

plant and bacterial metabolite of atrazine) on the pubertal development of female Wistar 

rats. This study is a follow-up to the researchers’ previous findings that 20 days of 

exposure (PND 22-41) to the parent compound – atrazine – at doses ≥ 50 mg/kg/day 

induced a delay in female sexual maturation manifested as a delay in vaginal opening 

(VO) (Laws et al., 2000). DACT exposure at high doses (≥ 34 mg/kg/day) from postnatal day PND 22-41 resulted in significant delays in VO (3-7 day delay) and in some 

instances animals failed to attain VO by the time of their scheduled sacrifice on PND 41. 

Interestingly, these delays in VO were not accompanied by lower body weights thus 

they do not appear to be related to generalized growth delays. Moreover, the NOAEL 

identified for DACT is the same as equimolar equivalent NOAEL for atrazine. In 

contrast, hydroxyatrazine exposure at doses up to 183 mg/kg/day did not result in 

delays in VO. Given that atrazine is quickly metabolized to DACT, these results 

strongly suggest that DACT is the toxicologically active moiety causing the delays in 

sexual maturation induced by atrazine. 

Potential effects of atrazine on ovarian function were evaluated over a wide dose 

range (3-300 mg/kg/day) by Shibayama and colleagues (Shibayama et al., 2009). In a 

companion study these researchers attempted to correlate atrazine-induced changes in 

ovarian function to fertility impairments. Unfortunately, different dose levels were used 

for the ovarian function and fertility studies thus precluding an appropriate comparison 

between these two sets of experiments. In the ovarian function set of experiments, 

atrazine exposure for 2 or 4 weeks at a high dose (300 mg/kg/day) resulted in irregular 

estrous cycles (typically longer cycles) due primarily to a lengthened diestrus. This 

effect was accompanied by decreased numbers of corpora lutea, follicular atresia, 

uterine atrophy, as well as decreased ovarian and uterine weights. Noticeably, the 

duration of atrazine exposure (2 vs. 4 weeks) had no effect on the nature, severity, or 

dose level causing the estrous cycle disruption or the histopathology changes. In the 

fertility study, atrazine exposures at levels up to 100 mg/kg/day for a period of time 

encompassing 2 weeks prior to mating up to gestation day (GD) 7 did not result in any 

signs of impaired fertility. None of the signs typically associated with impaired fertility 

(e.g., number of implantation, corpora lutea, pre- or post-implantation loss) were 

affected. 

The studies by Laws et al., and Shibayama et al., indicate that exposure to 

atrazine or DACT results in effects related to the development and function of the 

reproductive system. The effects described by both groups are consistent with the 

postulated MOA of perturbations of the neuroendocrine system. Sexual maturation is 

the culmination of a complex cascade of sex developmental effects that ultimately leads 

to the attainment of reproductive capacity. Activation of the HPG axis resulting in the 

pulsatile secretion of GnRH and LH is critical to puberty onset. Researchers have found 

that disruption of GnRH release can lead to delays in vaginal opening. Thus, it is not 

 

3

 Studies on the potential effect of atrazine exposure on mammary gland development will be evaluated 

during the Fall meeting of the SAP. 
Page 32 of 263 

unexpected that exposure to atrazine and DACT – atrazine’s metabolite – leads to a 

delay in sexual maturation given atrazine’s effect on the HPG axis. Similarly, the 

lengthening of the diestrus stage after atrazine exposure can be readily explained by 

the disruptions to the HPG axis caused by atrazine. Even through the relatively short 

period of time evaluated by Shibayama et al., it is clear that atrazine treatment leads to 

a state of reproductive quiescence which – if sustained – would eventually result in the 

reproductive senescence characteristic of repeated atrazine exposure. It is noteworthy 

that the NOAEL for the effects reported after ≈ 3-4 weeks of exposure by Laws et al. 

(2000), and Shibayama et al., (25 and 30 mg/kg/day, respectively in atrazine molar 

equivalents) were higher than the NOAEL (1.8 mg/kg/day) for attenuation of the LH 

surge identified after a 6-month exposure and that is currently used as the point of 

departure in the Agency’s risk assessment. 

 3.3.2 Male Reproductive/Developmental Toxicity 

Since the IRED was finalized in 2003, several studies have been conducted 

assessing the effect of atrazine exposure on male reproductive function and 

development. Research has focused on a wide array of possible adverse reproductive 

effects including delayed puberty onset, prostatitis and changes in hormonal and 

andrology parameters. 

 3.3.2.1 Delayed Puberty Onset 

 There have been a number of studies demonstrating that atrazine delays male 

puberty in different strains of rats following both peripubertal and perinatal exposure 

(Stoker et al., 2000; Friedmann, 2002 ;Trentacoste et al., 2001; Rayner et al., 2006 and 

Rosenberg et al., 2008). 

 

The primary data collected following the male peripubertal exposures and 

examination of puberty outcomes (Stoker et al., 2001; Friedmann et al., 2002, 

Trentacoste et al., Pogrimic et al., 2009) is consistent with the effect of atrazine on the 

central nervous system (i.e., suppression of GnRH/decreased pituitary secretion of LH) 

and subsequent alterations in the hormonal control of pubertal development (Cooper et 

al., 2000). Decreased LH secretion would lead to insufficient stimulation of the gonads 

during puberty to produce the necessary steroids for androgen-dependent maturation of 

the sex accessory tissues in the male. Therefore, the delayed growth of the 

reproductive tract in the male supports the reported alteration of the hypothalamic 

control of pubertal progression. 

 

A reduction in testosterone levels following atrazine exposure has been reported 

in a number studies in mammals, as well as other species revealing a consistency in the 

effects of atrazine on androgens. It is well known that the development of the size of 

the penis and cornification of the epithelium of the prepuce and preputial separation in 

immature rats are regulated by androgens (Marshall, 1966). A decrease in testosterone 

secretion during the juvenile period can delay preputial separation (Lyons et al., 1942) 
Page 33 of 263 

and reduce the size of the androgen-dependent tissues, such as the ventral prostate 

and seminal vesicles. Normally, testosterone levels rise gradually from PND 20 to 40, 

and abruptly double by PND 50 (Matsumoto et al., 1986; Monosson et al., 1999). 

 In the male rat, atrazine exposure resulted in delays in the onset of puberty, as 

determined by assessment of preputial separation (PPS) (Table 4). Stoker et al. (2001) 

found that peripubertal exposure to atrazine delayed puberty for 1.5 to 2.5 days 

following exposure to 12.5 - 200 mg/kg atrazine. The NOAEL for the effect on puberty 

in the male Wistar rat was 6.25 mg/kg/day and the LOAEL was 12.5 mg/kg/day. They 

also observed significant decreases in the growth of the reproductive tract, namely the 

seminal vesicles and prostates, of the affected male rats at slightly higher doses than 

the doses required to delay puberty (NOAEL = 25 mg/kg). At PND 45, intratesticular 

testosterone was decreased by 200 mg/kg. In the studies examining the Sprague 

Dawley (SD) rat (Trentacoste et al., 2001), pubertal onset was delayed by 3 days and 4 

days following exposure to 100 and 200 mg/kg atrazine, respectively, with decreases in 

ventral prostate and seminal vesicles at the same doses (NOAEL = 50 mg/kg). 

Friedmann (2002) found a decrease in intratesticular and serum testosterone at 50 

mg/kg/day and 200 mg/kg/day following exposure to the peripubertal male SD rat. 

Thus, all three studies found decreases in either serum or intratesticular testosterone 

and Trentacoste et al. also found a decrease in LH at the 200 mg/kg/day dose. 

 Ventral prostate, seminal vesicles, lateral prostates and epididymal weights are 

significantly reduced at doses just above the doses which delay preputial separation 

(Stoker et al., 2001). These effects provide further evidence of a decrease in androgen 

stimulation. Decreases in androgen hormone concentrations also correspond with the 

effects observed on pubertal endpoints. For example, Stoker et al., 2001 demonstrated 

that intratesticular testosterone was significantly decreased following atrazine exposure 

peripubertally. This has corresponded to the work of others showing that serum 

testosterone is decreased by doses of 50, 100 and 200 mg/kg in a different strain of rat 

(SD) when dosed during a similar period of PND 22 to 47 (Trentacoste et al., 2001; 

Friedmann, 2002) as shown in Table 4. 
Page 34 of 263 

Table 4: Strain and Dose Comparison in Male Rats dosed peripubertally with 

atrazine 

EXPOSURE STRAIN EFFECT NOAEL/LOAEL REFERENCE 

PND 23 to 53 Wistar Delayed PPS 6.25/12.5 Stoker et al., 

2001 

PND 22 to 47 SD Delayed PPS 50 lowest 

dose/100 

Trentacoste et 

al., 2001 

PND 23 to 53 Wistar Decreased VP 

and SV 

25/50 Stoker et al., 

2001 

PND 22 to 47 SD Decreased VP 

and SV 

50 lowest 

dose/100 

Trentacoste et 

al., 2001 

PND 23 to 53 SD Decreased intratesticular T on 

PND 45 

150/200 Stoker et al., 

2001 

PND 22 to 47 SD Decreased T on 

PND 47 

ND/50 Trentacoste et 

al., 2001 

PND 22 to 47 SD Decreased test. 

and serum T on 

PND 47 

ND/50 Friedmann, 2002 

PND 23 to 50 Wistar Decreased 

T/DHT on PND 

50 

50/200 Pogrimic et al., 

2009 

 The study by Stoker et al., 2002 also examined the effect of the atrazine 

metabolites, DACT, DIA and DEA on pubertal development in the rat. In this study, 

equimolar doses of the metabolite were compared to the effect seen with atrazine in the 

earlier study (Stoker et al., 2000). PPS was significantly delayed by DEA and DIA at 

doses ≥ 25 mg/kg/day and by DACT at doses ≥12.5 mg/kg/day. When the males were 

sacrificed on PND 53, treatments with DEA at atrazine equivalent dose (AED) ≥100 

mg/kg/day, DIA at an AED ≥ 50 mg/kg/day, and DACT at an AED of 200 mg/kg/day 

caused a significant reduction in ventral prostate weight, while only the highest doses of 

DIA and DEA resulted in a significant decrease in lateral prostate weight. Seminal 

vesicle weight was reduced by DEA at AEDs ≥25 mg/kg/day, and by DIA and DACT at 

AEDs ≥100 mg/kg/day AED. Epididymal weights were reduced in the DEA, DIA, and 

DACT at atrazine equivalent doses of 200, 200, and ≥100 mg/kg/day, respectively. 

Serum testosterone was reduced only in the males receiving the 2 highest doses of 

DIA. This study confirmed that the chlorinated metabolites of atrazine also result in 

similar effects on pubertal development. 

 It should be mentioned that other factors, in addition to those changes within the 

HPG, can affect the timing of puberty in the male rat including nutritional status 

(leptin/body weight) and environmental (pineal gland/secretion of indole amines) 

influences. Nutritional status and body weight are known to have effects on puberty, 

which are suggested to reflect the metabolic signals in the brain that serve as indices of 

the metabolic state. These metabolic alterations associated with weight loss or 

decrease in growth rate are inhibitory to the reproductive system and may be related to 
Page 35 of 263 

substances in the body that can alter the release of GnRH such as insulin, amino acids 

necessary for precursors of neurotransmitter synthesis and essential fatty acids (Ojeda 

and Urbanski, 1994). 

 

The peripubertal exposure male study (Stoker et al., 2001) showed decrease 

body weight at the 200 mg/kg dose, but a pair-fed group was included to discern the 

effects of changes in growth. There were changes in puberty at doses in which no body 

weight decreases were observed (≥50 100 mg/kg/day in females and ≥12.5 mg/kg/day 

males). However, in the study with SD rats Trentacoste et al., found that the food 

restriction group (receiving approximately 10% less food which was equivalent to the 

100 mg/kg atrazine treatment food intake) showed the same effects on LH, testosterone 

and reproductive tract development. A recent paper examined the effects of food 

restriction on the endpoints in the pubertal male exposure period and found that 

reductions in body weight up to 10% did not influence pubertal onset or the growth of 

androgen dependent tissues in the rat (Laws et al., 2007). 

Perinatally a single 100 mg/kg atrazine dose to the dam resulted in an effect on 

pup growth that may involve changes in milk quality, as the offspring showed a 

decreased weight of 7% on PND 4 (Rayner et al., 2006). Work by Rosenberg and coworkers (2008) showed that prenatal (GD14-parturition) exposure to atrazine at doses 

≥10 mg/kg/day led to a significant delay in preputial separation (1-3 days) while 

anogenital distance on PND21 was reduced at 75 and 100 mg/kg/day. Measuring 

testosterone levels in both the serum and intratesticular fluid of PND 60 rats revealed 

that serum testosterone levels were decreased at doses ≥ 75 mg/kg/day while 

intratesticular fluid testosterone was reduced at doses ≥ 50 mg/kg/day. It should be 

noted that all of the effects on PPS and AGD occurred in conjunction with nonsignifcant 

decreases in pup body weights (Rosenberg et al., 2008). These alterations of early 

postnatal body weight could play a role in the delay in puberty in these male offspring. 

 

In summary, the MOA of altered pubertal progression in the rat and decreased 

androgen production by the testes is plausible in humans, as GnRH and the regulation 

of pituitary hormones stimulate the gonadal secretion of steroids and is critical for the 

initiation of the set of events and time course of the HPG regulation of puberty in the 

human. Thus, it is essential to take into consideration that all the effects on sexual 

maturation and altered androgen status reported after ≈ 30 days of exposure occur at 

dose levels substantially higher (≥ 12.5 mg/kg/day) than those leading to the LH surge 

disruption which serves as the basis of the Agency’s current risk assessment. 

 3.3.2.2 Prostatitis 

Prostate effects including prostatitis are oftentimes attributed to atrazine 

exposure. The increased incidence of prostatitis after atrazine exposure has been the 

subject of study for at least the last decade. Since 2003, there have been two in vivo 

studies to further explore this potential adverse health outcome. 
Page 36 of 263 

First reported in 1999, an increase in prostatitis has been linked to the 

suppression of suckling-induced prolactin release. After lactating dams are exposed to 

atrazine on PND1-4 at doses ≥ 12.5 mg/kg/day, the incidence of prostatitis in their 

offspring increased. At doses ≥ 25 mg/kg/day both the incidence and severity of the 

findings were increased. Notably, at 12.5 and 25 mg/kg/day the suckling induced 

release of prolactin was decreased in some dams while the 50 mg/kg/day dose level 

elicited a prolactin decrease in all females. Prolactin plays a crucial role in neonatal 

brain development particularly in the tuberoinfundibular dopaminergic system (TIDA). In 

the adult male, these neurons are responsible for the down-regulation of prolactin 

release from the pituitary. As a consequence of the decreased levels of maternal 

prolactin during the early lactational period, the offspring of these dams do not receive 

the perinatal amounts of prolactin necessary to activate the TIDA neurons. Therefore, 

TIDA’s regulation of prolactin in the adult male is impaired resulting in elevated prolactin 

levels which in turn lead to hyperprolactinemia. It is this elevated level of circulating 

prolactin in the adult males that has been linked to an increased incidence of prostatitis. 

Thus, an increased incidence of prostatitis in the offspring of dams exposed to atrazine 

during the critical time for TIDA neurons activation (first postnatal week) may attributed 

to decreases in circulating prolactin levels in the dam. 

Using a cross-fostering study design, Rayner et al. (2007) investigated if 

gestational exposure to atrazine could also lead to prostatitis in animals exposed in 

utero. Dams were exposed to 100 mg/kg/day atrazine from GD 15-19 and after birth 

the pups were cross-fostered resulting in the following grouping: 

• ATR-C: pups exposed to atrazine in utero only (born to atrazine-treated 

dams but nursed by control females) 

• C-ATR: pups exposed to atrazine lactationally only (i.e., born to control 

dams but nursing from atrazine-treated dams) 

• ATR-ATR: pups exposed to atrazine both in utero and through the milk 

• C-C: pups born to and nursing from control dams 

 

Consistent with the findings reported by Stoker et al., both of the groups exposed 

postnatally (i.e., C-ATR and ATR-ATR groups) exhibited indications of lateral prostate 

inflammation on (PND 120). No prostate inflammation was observed in the ATR-C or 

C-C groups suggesting that the early postnatal period encompasses the critical window 

of susceptibility to atrazine-induced prostatitis. It should be noted, however, that these 

effects occur at doses higher than those eliciting disruption of the LH surge. 

Based on the observation that atrazine exposure led to a decrease in 

testosterone production in rats, it has been suggested that this decrease would in turn 

ameliorate prostate carcinoma development. Kandori and coworkers (2005), however, 

hypothesized that rather than being a direct hormone-mediated effect, the decrease in 

prostate carcinogenesis is the secondary effect of a reduction in caloric intake. To test 

this hypothesis these researchers used a transgenic adenocarcinoma rat model 

typically used to study prostate carcinogenesis. Rats received either 33 or 61.6 
Page 37 of 263 

mg/kg/day of atrazine for a period of 13 weeks while another group was placed on a 

calorie-restricted diet. Atrazine treatment at the highest dose level (61 mg/kg/day) and 

dietary restriction elicited a slight suppression of prostate carcinogenesis. Unlike other 

researchers, testosterone levels, however, were not reduced by atrazine treatment in 

the study conducted by Kandori et al. (2005). The authors theorized that, since 

testosterone levels were unaffected by atrazine treatment, the decrease in prostate 

carcinogenesis observed after atrazine exposure was due to reduced caloric intake 

(resulting from atrazine exposure) rather than hormonal disruption. It is important to 

know, however, that it has been demonstrated by other researchers that exposure to 

atrazine at the doses used in this study leads to decreases in testosterone. It is not 

clear if the discrepancy between this study and other studies that have demonstrated 

atrazine-induced alterations of testosterone levels is due to differences in administration 

of atrazine (dietary vs. oral gavage). In addition, testosterone levels were measured 

only at the end of the study and were highly variable. Also, there was a potential 

problem with the homogeneity of the diets (concentrations of atrazine were 60 – 91% of 

target values). While this study suggests the possibility that prostate carcinogenesis 

may be a secondary effect to a reduction in caloric intake, a test system in which 

testosterone levels are altered would provide more definitive confirmation. 

In summary, the data indicate that atrazine induces prostatitis at doses ≥ 12.5 

mg/kg/day and that early postnatal exposure is a critical window of susceptibility to this 

effect 

3.3.2.3 Effects on Aromatase and steroidogenesis 

Aromatase is the enzyme that catalyzes the conversion of androgens to 

estrogens. It is expressed in the gonadal and extragonadal tissues and is critical for 

maintenance of homeostasis between the sex steroids in males and females which is 

necessary for reproductive function. Although aromatase is a product of a single gene 

(CYP19) in mammals, its expression is quite complex as it is regulated in a speciesand tissue- dependent manner by differential uses of multiple promoters (Simpson et 

al., 2002). It is well documented that environmental contaminants can inhibit the 

catalytic activity of this enzyme (Vinggaard et al., 2000; Santen et al., 2009). However, 

studies reporting an increase in the activity of aromatase are not as numerous. 

Approximately ten years ago, Sanderson and his colleagues reported that 

atrazine induces estrone production and aromatase (CYP19) mRNA in H295R adrenal 

cortical carcinoma cells (Sanderson et al. 2000; 2001). These authors reported that 

elevated aromatase activity, as measured using the tritiated water release assay, was 

observed in cells exposed to atrazine (low-effect level, LOEL, 0.3 μM) for at least 24 

hours. Since these original reports, several studies using a variety of cell lines have 

confirmed the atrazine-dependent increases in estrogen production in H295R cells 

(Heneweer et al., 2004; Higley et al., 2010) and human placental carcinoma (JEG-3) 

cells (Sanderson et al., 2001; Laville et al., 2006). Finally, Holloway et al. (2008) also 

reported that aromatase activity in human granulosa-lutein primary cell cultures 
Page 38 of 263 

following treatment with atrazine (1.0 μM) was 2-fold higher than that observed for the 

controls. A commonality among these studies is that the effects on estrogen production 

are only observed in the various cell types when exposed to atrazine for at least 24 

hours. This finding supports the hypothesis that the effects are not mediated through a 

direct alteration of the catalytic activity of aromatase, but rather likely involve gene 

transcription of the enzyme. 

To date, the cellular mechanisms responsible for the increased production of 

estrogens by aromatase have not been fully characterized. Sanderson et al (2000, 

2002) reported that the time-response profile for the induction of aromatase activity, 

CYP19 mRNA, and cyclic adenosine monophosphate (cAMP) in H295R cells following 

exposure to atrazine was similar to that of 8-bromo-cAMP, a known stimulant of the 

protein kinase-A pathway that mediates the induction of aromatase. These authors 

suggested that the atrazine-dependent induction of estrogen in H295R cells results from 

increased CYP19 mRNA synthesis, which may be stimulated by elevated intracellular 

cAMP. In contrast, Fan et al., (2007a, b) reported that atrazine binds directly to 

steroidogenic factor 1 (SF-1), an orphan receptor that serves as a transcription factor for 

the expression of CYP19 mRNA through its interaction with aromatase promoter II. 

While these studies focused primarily on the up-regulation of aromatase gene 

expression, additional studies demonstrated that other cellular target sites exist for 

atrazine and that these target sites can impact the steroidogenic process. Suzawa and 

Ingraham (2008) reported that atrazine does not bind directly to the SF-1, but instead 

stimulates three signaling pathways known to activate several of the NR5A receptors 

[SF-1,hLRH-1 (human liver receptor homolog), zff1d]. These authors also reported an 

upregulation of the expression of a group of important steroidogenic genes to include 

StAR, inhibin-α, P450scc, and11βHSD in JEG3 cells following exposure to atrazine. 

Thus, these findings demonstrate that atrazine can exert a much broader effect on 

steroidogenesis. Finally Albanito et al. (2008) reported a series of in vitro experiments 

designed to evaluate the mechanism of action for atrazine in BG-1 cells (human ovarian 

cells). Their data confirm that atrazine does not bind directly to the nuclear ERα as 

previously reported by Cooper et al. (2007). However, atrazine did not alter aromatase 

activity or gene expression in the BG-1 cultures following a 40-hr exposure, a finding 

that contrasts with Sanderson et al. (2000) for the H295R cell line and may be a 

reflection of a constitutively high aromatase activity that prevents further amplification by 

exposure to atrazine. A novel finding of this study was the stimulation of extracelluar 

signal-regulated kinase (ERK) phosphorylation and c-fos in the BG-1 cells following 

exposure to atrazine (1μM). Using specific signaling inhibitors and gene silencing, these 

authors report that this effect is mediated through the G-protein-coupled receptor 30 

(GPR30), a membrane bound orphan receptor that mediates rapid estrogen signals 

The range of the LOELs (0.3 – 1 μM) for the observed effects on cellular 

mechanisms provides a common factor among the in vitro studies. Recent studies in 

rats and mice have measured plasma and tissue concentrations of atrazine and 

metabolites following in vivo exposures (Ross et al., 2007; Laws et al. 2009, Fraites et 
Page 39 of 263 

al., 2009). Although a complete profile of serum and tissue atrazine concentrations for 

the different dosing durations tested in vivo is not available, the data reported by Fraites 

et al., for the serum concentrations of the active atrazine metabolite DIA show that it 

reaches the 2-4 μM range within 15 minutes after four daily doses of 75 mg/kg/day via 

gavage. Again, although more data would be needed to accurately assess the internal 

dose in animals treated for different durations, this data does indicate that the 

concentrations used in the in vitro studies discussed above are not excessive. However, 

these in vivo doses are still substantially higher than those selected for points of 

departure in the 2003 risk assessment. 

 

In summary, the in vitro studies demonstrate that atrazine can alter aromatase 

activity and gene transcription. The more recent studies suggest that the cellular 

responses following atrazine exposure involve a complex array of signaling events, 

Importantly, the fact that atrazine may exert a broad influence on steroidogenesis is in 

accord with the in vivo studies reporting increased adrenal (Fraites et al., 2009; Laws et 

al., 2009) and testicular (Modic, 2004) steroidogenesis following acute chlorotriazine 

dosing. It is interesting to note that although changes in the production of serum steroid 

hormones have been identified in vivo following atrazine exposure including estrogen, 

albeit at high doses (Stoker et al., 2000), alterations in aromatase gene expression or 

activity have not been observed in the rat testes (Modic 2004) or mouse reproductive 

tract (Rivest and Sanderson, 2010). Thus, suggesting that while steroidogenesis may 

be increased as a result of atrazine exposure, this event is likely not mediated by 

aromatase. 

3.3.2.4 Andrology 

Three in vitro studies have been conducted over the last seven years to evaluate 

the potential effect of atrazine exposure on sperm. Given the effects of atrazine on a 

number of hormone-dependent events including triggering early reproductive 

senescence in female rats and causing delays in puberty onset, it is hypothesized that 

atrazine may also affect sperm parameters (e.g., motility, viability). Two of the studies 

used porcine sperm while the remaining study used human sperm to explore the 

potential impact of atrazine exposure on sperm. The researchers hypothesized that 

effects seen after in vitro exposure to atrazine could be correlated with changes in 

fertility or reproductive success after in vivo exposure. 

In a study designed to evaluate the effect of atrazine exposure on sperm motility, 

semen collected from Duroc boars was subjected to a number of evaluations after 

exposure to 0, 50, 100, or 500 μM atrazine (Betancourt et al., 2006). Exposure to 

concentrations ≥ 100 μM atrazine elicited a concentration-dependent and statistically 

significant decrease in sperm viability (↓8-21%) and progressive motility (↓23-75%). 

The authors speculated that the sperm motility effects seen after in vitro exposure would 

lead to an adverse effect on the sperm’s “fertilizing ability” and hence male 

reproduction. This statement is not supported by empirical data but rather conjecture 

based on the changes in sperm motility observed after in vitro exposures. This is but 
Page 40 of 263 

one of the numerous limitations of this study. The authors did not take into 

consideration the plausibility that atrazine would come into direct contact with sperm 

after in vivo exposure. Moreover, this study does not take into account that atrazine is 

quickly metabolized in the body and therefore the substance reaching the testes is most 

likely an atrazine metabolite assuming it could reach the testes. Finally, there is no 

attempt to correlate the in vitro concentrations tested to any in vivo concentrations that 

live sperm may encounter during maturation in the testis, epididymal transit, in seminal 

fluid, or in the female oviduct where fertilization takes place. In conclusion, this study 

evaluates mature sperm in vitro and attempts to extrapolate those findings to potential 

effects on male reproductive performance. In fact the relatively high concentrations of 

atrazine suggests that it may have toxic properties at the level of the sperm membrane 

or mitochondria in vitro but shows no clear relevance to in vivo exposures or a potential 

MOA. 

A second study conducted by the same research group evaluated the effect of 

atrazine on capacitation and acrosomal reaction (Maravilla-Galvan et al., 2009). 

Capacitation is a time-dependent physiological process that is necessary for sperm to 

undergo before they become capable of fertilization. It usually takes place in the uterus 

and oviduct, but can occur under appropriate culture conditions in vitro. Capacitated 

sperm can bind the zona pellucida around the oocyte, penetrate it and fuse with 

(fertilize) the oocyte. Uncapacitated sperm cannot. Acrosome reaction (AR) consists of 

an ordered, calcium dependent vesiculation and shedding of the acrosomal vesicle that 

covers much of the sperm head. It can be visualized using chlortetracycline staining (as 

was done in this study). Only acrosome reacted sperm can fuse with the egg 

membrane. Therefore AR is used as an indicator of capacitation. Progesterone may 

directly induce acrosome reaction at the sperm membrane level in vitro. Once AR 

occurs, sperm tend to slow down and die (run out of energy). Therefore, in a mixed 

culture there will be continuously changing populations of active capacitating sperm and 

dying post capacitation/AR sperm. Changes in sperm motion called “hyperactivation” 

accompany capacitation and are also necessary for sperm to penetrate the zona 

pellucida. This study suffers from not reporting hyperactivated motility. The latter would 

help distinguish between physiologically AR sperm and dead sperm (both of which stain 

similarly with CTC because they lack an acrosome). 

 In 2009 Maravilla-Galvan and coworkers evaluated the impact of atrazine 

exposure at concentrations of 0 (control), 8, 20, and 40 μM. In general, the percentage 

of uncapacitated acrosomes (i.e., with intact acrosomes) and percentage of motile 

sperm declined in a dose-dependent manner while the percentage of acrosome reacted 

sperm increased. There could be two interpretations for this finding. The authors’ 

conclusion was that atrazine stimulated or accelerated acrosome reaction in vitro

leading to a decrease in motility. Conversely, it could be theorized that atrazine results 

in decreases in sperm viability and that the dead sperm shed their acrosome after death 

thus appearing to be acrosome reacted. In the absence of data on the proportion of 

hyperactivated sperm, it is impossible to distinguish between these two possibilities. 

Regardless, these data do not provide any information that correlates the findings to 
Page 41 of 263 

adverse reproductive performance nor does it provide any rationale for hypothesizing 

that atrazine selectively targets sperm. Consequently, the relevance of this study for 

risk assessment purposes is unclear. 

Lastly, a study by Hase et al., examined the effect of atrazine on human sperm 

motility in vitro and tested the hypothesis that decreases in sperm motility might be 

related to decreases in ATP availability needed for motility. Sperm from consenting 

males was treated with 0, 0.03, 0.1, 0.3, or 1 mM atrazine. Oligomycin (0.05 mM) – a 

sperm metabolic poison which uncouples ATP production in mitochondria – was used 

as a positive control. As expected, oligomycin decreased sperm motility by 

approximately 20%. Atrazine also caused a decrease in sperm motility but only at 

considerably higher concentrations (0.3 and 1 mM) than oligomycin. In support of the 

authors’ original hypothesis, sperm ATP levels were also decreased at the 

concentration where progressive motility was impaired. Based on these findings, the 

authors postulate that the decreases in sperm motility observed in vitro may be the 

outcome of decreases in ATP availability needed for sperm flagella to move. They also 

point out that “the effect of ATZ [atrazine] on sperm motility was seen at > 100 μM, 

exposure levels that probably do not result from normal use of the herbicide. It is 

therefore uncertain whether the observed phenomena are ecologically relevant.” Thus, 

though this is an interesting hypothesis and finding, its relevance to risk assessment is 

questionable. 

In summary, three studies evaluating andrology parameters have been published 

since the 2003 IRED. Using either porcine or human sperm samples, they evaluated 

atrazine’s potential effect on sperm parameters (motility, viability, capacitation, and 

acrosomal reaction). Although the in vitro data suggest an effect of atrazine on sperm 

motility and/or viability, there is no evidence of a correlation between these findings and 

impaired reproductive performance. Furthermore, these studies assume that atrazine 

per se reaches the testes; an assumption that has not been verified. Finally, the 

concentrations affecting sperm parameters in these studies are high (≥ 100 μM) and, as 

Hase et al. noted, an exposure level not likely to be reached as a result from use of the 

herbicide under the current restrictions. Thus, the data in andrology measures, though 

interesting, provide no information that would suggest that in vivo exposure to atrazine 

would result in a sperm-mediated deficit in reproductive performance. 

3.4 Neurotoxicity 

The preponderance of the data available to date indicates that atrazine exerts 

many of its toxicologically relevant effects through perturbations of the neuroendocrine 

system. Many of the reproductive effects seen after atrazine exposure appear to be the 

sequelae of perturbations to the HPG and/or HPA axes. Consequently, there is 

significant interest in the potential effects of atrazine exposure on the nervous system 

per se. 
Page 42 of 263 

Over the last seven years, several studies have been conducted evaluating 

potential atrazine-induced effects on the dopaminergic and somatostatinergic systems 

as well as GnRH releasing neurons. Studies on the dopaminergic system by Coban and 

Filipov (2007) and Rodriguez et al. (2005) corroborate previous findings on the effect of 

atrazine on the dopaminergic system. The work by Rodriguez et al. showed that 9-

month old male rats exposed for 6 months to 10 mg/kg/day atrazine in the diet exhibited 

increased locomotor activity, decreased striatal dopamine, reduced norepinephrine in 

the prefrontal cortex, decreased hypothalamic serotonin, and loss of tyrosine 

hydroxylase positive (TH+) and tyrosine hydroxylase negative (TH-) cells in the ventral 

tegmental area and the substantia nigra pars compacta. It should be noted that the 

changes in neurotransmitter levels were slight. In 2007, Coban and Filipov studied the 

effect of atrazine on male mice after a 14 day exposure to dose levels ≥ 5 mg/kg/day. 

The researchers reported a statistically significant reduction in the number of TH+ 

neurons in the ventral tegmental area (day 64 of the experiment) as well as a decrease 

in the number of TH+ neurons in the substantia nigra pars compacta was reported at 25 

mg/kg/day at days 22 and 64. Noticeably lacking was a dose-response for either one of 

these findings. Coban and Filipov (2007) also concluded that there was a dosedependent decrease in the levels of dopamine and its metabolites in the striatum. 

Based on these findings, both research groups suggested that exposure to atrazine 

may be related to the etiology of Parkinson’s disease. Both of these studies have 

limitations that confound the interpretation of the findings. These limitations are fully 

described in the study summaries found in Appendix A. The implication that these data 

suggest a link between atrazine and Parkinson’s disease is not supported by the data 

given the non-specificity of the atrazine-induced neuronal loss and the lack of 

histological and behavioral features characteristic of Parkinson’s Disease. 

Parkinson’s disease is a neurodegenerative disease characterized by a 

progressive loss of dopaminergic neurons in the substantia nigra. The data reported by 

Rodriguez et al. (2005) shows loss of non-dopaminergic neurons and dopaminergic 

neurons following atrazine treatment in the rat. The subpopulation of non-dopaminergic 

neurons includes GABA-ergic, calbindin, and cholecystokinin-like immunoreactive 

neurons. Other potential cell types may include glial cells. The data presented by 

Coban and Filipov (2007) reveal a statistically significant loss of dopaminergic neurons 

in the ventral tegmental area in the mouse at 5 mg/kg/day on day 64 of the experiment, 

while the loss in the substantia nigra pars compacta was significant at 25 mg/kg/day but 

not at 5 mg/kg/day. The loss of dopaminergic neurons at the high dose at day 64 was 

comparable between the two brain regions. The ventral tegmental area contains 

dopaminergic cell bodies that comprise the mesocorticolimbic system that is involved 

with functions such as cognition. The primary and major loss of dopaminergic neurons 

in Parkinson’s disease involves the substantia nigra. The nonspecific neurotoxicity of 

atrazine contrasts with selective striatal dopaminergic neurotoxins such as 6-

hydroxydopamine and MPTP. 

In addition to the non-specificity of the atrazine-induced neuronal loss, another 

characteristic not seen after atrazine exposure is the suite of neurobehavioral and 
Page 43 of 263 

histological features associated with Parkinsons’s disease. Histologically, Parkinson’s 

disease is characterized by the presence of intracytoplasmic inclusions, Lewy bodies, 

formed mainly by α-synuclein and ubiquitin. None of the available studies have 

demonstrated any aggregation of proteins that form Lewy bodies after atrazine 

treatment. Behavioral abnormalities noted in Parkinson’s disease include tremor, 

bradykinesia, hypokinesia, balance and gait disturbances. No overt behavioral signs 

were reported in the available atrazine studies. This contrasts with rotenone, which 

causes a Parkinson-like syndrome, and results in reduced mobility, flexed posture, 

rigidity and even catalepsy in the rat. Rodriguez (2005) provided some evidence for 

increased locomotor activity following d-amphetamine sulfate injection of rats treated 

with atrazine. However, the authors’ assertion that the increased locomotor activity is 

associated with striatal dopamine deficiency from atrazine treatment should be further 

explored and supported with a study design that includes L-dopa and dopamine agonist 

and antagonist administration. 

Several in vitro studies addressed the putative mechanism of dopaminergic 

toxicity of atrazine, primarily in striatal slices and striatal synaptosomes and vesicles 

(Hossain and Filipov 2008; Filipov et al. 2007). The results revealed that atrazine, in 

vitro, alters striatal dopamine levels possibly by interfering with the vesicular storage 

and/or cellular uptake of dopamine. Tyrosine hydroxylase per se is not a target of 

atrazine. The relevance of these in vitro data to dopaminergic mechanisms in vivo is 

not clear given the high concentrations of atrazine examined in vitro and the complex 

interactions between various neurotransmitter and endocrine systems in the intact brain. 

Furthermore, as mentioned above, the available data indicate that the neurotoxicity of 

atrazine is not specific to dopaminergic systems. The effects of atrazine on aromatic 

amino acid decarboxylase, monoamine oxidase and neuronal mitochondrial function are 

unknown. 

The somatostatinegic system in mouse brain was used as a model by Giusi et al.

(2006) to study the impact of atrazine exposure on this system. The rationale for this 

study was that somatostatin plays a role in growth hormone (GH) secretion and the 

gender-based differences in GH secretion in rodents. The authors theorized that the 

differential in GH secretion may be linked to gender-related differences in the 

transduction of somatostatinergic mechanisms in brain and/or pituitary targets. As a 

result, the researchers concluded that the GH- and SST-dependent relationships “might 

provide further insights into the types of neurotoxicological mechanisms involved in the 

delay of the estrous cycle or the alteration of the hypothalamic-hypophyseal-gonadal 

axis in animals treated with atrazine (Wetzel et al. 1994).” Though the authors reported 

sexually dimorphic changes in the hypothalamus of females and changes in the 

regulation of somatostatin receptors in the hypothalamus of both males and females, 

the reliability of this study is uncertain given the numerous deficiencies (including poor 

description of the methods and poor quality of micrographs used to substantiate 

conclusions) identified in the study design and described in the summary review in 

Appendix A. 
Page 44 of 263 

A neurobehavioral study in mice is also available for consideration. In this study 

Belloni and coworkers (2007) report that atrazine exposure from GD14-PND21 at low 

doses (1 or 100 μg/kg/day) led to behavioral effects including delays in righting reflex, 

decreased temperature, changes in pup vocalizations and an acceleration of the 

ontogeny of the forepaw grasp response. It should be noted that this study also had a 

number of deficiencies such as inappropriate statistical analyses and unexplained 

discrepancies in the sampling of pups from litters which are described in the summary 

review in Appendix A that call the validity of the results into question. 

More closely related to the postulated MOA for atrazine is the research 

conducted by Cooper et al., 2007 and Foradori et al. (2009) on the pulsatile release of 

GnRH neuronal activation after atrazine exposure. The research by Foradori and 

coworkers show that a brief (4 day) exposure to atrazine at doses ≥ 50 mg/kg/day 

resulted in a decrease in GnRH activation as indicated by a decrease in cFos activity 

concomitant to a significant reduction in the LH and FSH surges. Thus it appears that 

atrazine can induce changes in these hypothalamic neurons. These data, therefore, 

illustrate the close correlation between effects on the central nervous system (e.g.,

effects on GnRH activation) and effects on the reproductive system. Whether or not this 

downregulation of the GnRH neurons are the result of a direct action of atrazine or 

atrazine metabolites on the GnRH neuron or the result of increased hypothalamicpituitary-adrenal axis are under investigation. Indeed, recent data show that atrazine 

exposure leads to a rapid increase in corticosterone and progesterone (adrenal steroid 

hormone) secretions which decrease GnRH secretion (Fraites et al.,2009; Laws et al., 

2009). 

In summary, there are a number of studies indicating that atrazine and or 

atrazine metabolites may impact different neuronal pathways of the brain. The reliability 

and validity of findings on the brain somatostatinergic system and on neurobehavior in 

the mouse are uncertain due to serious deficiencies of the studies (i.e., Guisi et. al. 

2006 and Belloni et al. 2007). The recent studies examining changes in the rat brain 

dopaminergic systems and associated behavioral changes were also found to have 

significant deficiencies that also limit their utility for risk assessment purposes. In 

addition, results of in vivo animal toxicity tests do not support an effect of atrazine 

exposure on neurological function including Parkinson’s Disease. The observations that 

the chlorotriazines may alter GnRH neuronal activity are consistent with the proposed 

neuroendocrine MOA of atrazine. Previous studies have demonstrated that atrazine 

can alter dopamine in hypothalamic regions that are important in the regulation of GnRH 

secretion, consistent with the neuroendocrine MOA of atrazine. 

3.5 Immunotoxicity

In the Agency’s 2003 evaluation of atrazine, the immune system was identified 

as one of the target systems for atrazine toxicity. Since then, numerous studies both in 

vivo and in vitro have been conducted to further investigate atrazine’s potential to cause 

immunotoxicity. The in vivo studies reported various potential immunological effects of 
Page 45 of 263 

atrazine on cellular and humoral immune systems. These included natural killer (NK) 

cell function, delayed-type hypersensitivity responses to bovine serum albumin (BSA), 

macrophage phagocytic activity, antibody responses to sheep erythrocytes or keyhole 

limpet hemocyanin, T cell proliferation and cytolytic activity, spleen and thymic cell 

phenotypes, humoral response after immunization with heat-killed Streptococcus 

pneumoniae, lymphocyte populations in peripheral blood mononuclear cells, and 

expression of MHC Class II proteins on splenocytes. One study design included a host 

resistance test, which assesses the function of the immune system in toto (Karrow et al.

2005). 

All of the adult in vivo immunotoxicity studies focused primarily on cellular and 

humoral systems. Several studies evaluated limited systemic effects such as spleen 

and thymic weights and body weights. None of the studies provided detailed and 

thorough histological examinations of lymphoid organs(e.g., spleen, thymus, bone 

marrow, lymph nodes) that would be useful in understanding the potential mechanisms 

of immunotoxicity. Consistent effects (e.g., decreased splenic and thymic weights and 

alterations in splenic and thymic cellularity and phenotypes) were noted across the adult 

immune studies that examined these endpoints. In many instances, the changes were 

slight (albeit statistically significant), and given the functional reserve capacity of the 

immune system, it is difficult to extrapolate the rodent findings to human health risk 

assessment. However, it is interesting to note that the results of the host resistance test 

to validate the biological significance of changes in cellular and humoral immune 

function revealed significant decreases in resistance to the B16F10 tumor challenge at 

doses of 250 and 500 mg/kg/day atrazine, but not at 25 mg/kg/day. Host resistance 

assays are often considered to be the most relevant test for validating other methods 

and for extrapolating the potential of environmental agents to alter host susceptibility in 

the human population. 

It is well known that alterations in corticosterone levels may result in impaired 

immune function through the activation of the HPA axis. Pruett et al. (2003; 2009) and 

Schwab et al. (2005) exposed rats intraperitoneally to atrazine at high doses ranging 

from 100-300 mg/kg in an attempt to determine if corticosterone area under the curve 

could be used to predict immunotoxicity. The effect of HPA axis perturbations on 

immunological parameters can be quantified by relating immunosuppression to change 

in corticosterone levels represented by the area under the corticosterone vs. time curve 

(AUC) (Schwab et al. 2005). Pruett et al. (2003, 2009) and Schwab et al. (2005) 

evaluated atrazine in the corticosterone response model including acute and 28-day 

exposures to atrazine. In this model, atrazine treatment resulted in a number of 

immune system effects (e.g., suppressed white blood cell counts, increased neutrophils, 

decreased lymphocytes), consistent with effects on corticosterone concentrations 

(Pruett 2009). However, the atrazine-induced decrease in natural killer cell activity 

was not mediated by changes in the HPA axis. The latter observation suggests other 

mechanisms besides HPA activation in atrazine-induced decreases in natural killer cell 

activity. Pruett et al. (2009) provided some supporting evidence that 28-day atrazine 
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exposure did not cause habituation or tolerance to the HPA axis perturbations, but 

immune function (e.g., antibody production) was not evaluated in this study. 

It is important to note that the corticosterone response was stimulated by 

intraperitoneal injection of atrazine. Pruett et al. (2003) demonstrated that a single high 

oral dose of 500 mg/kg atrazine also increased endogenous corticosterone levels. This 

study was intended to provide insight into the predictive value of corticosterone 

production over time for impairments of the immune system not to assess the 

immunotoxicity of atrazine per se. 

While the available studies suggest a potential effect of atrazine on the immune 

system as noted in studies prior to 2003, conflicting results were reported in the two in 

vivo developmental immunotoxicity studies available. Rooney et al. (2003) reported 

immunosuppression of cellular and humoral immune function in male Sprague-Dawley 

rats, whereas Rowe et al. (2006) reported immunopotentiation of immune function in 

male Balb/c mice. The reasons for the contradictory results are not known but may be 

related to differences in the timing and route of maternal exposure, species differences 

and different methodologies used to assess immune response. Rooney et al. examined 

Sprague-Dawley rats following oral exposure – a relevant route of human exposure – 

from GD 10 until PND 23 to 35 mg/kg/day atrazine. Delayed type hypersensitivity 

response and the IgM antibody response to sheep red blood cell antigen were 

measured. In comparison, Rowe et al. used Balb/c mice which were exposed 

subcutaneously to atrazine for 21 days via time release pellets beginning between GD 

10 and 12 through PND 10. The starting dose was 35 mg/kg/day beginning at GD10 

and then decreased to approximately 23 mg/kg/day when the mice gave birth, due to a 

constant rate of atrazine release from the implant that was not adjustable for increasing 

maternal body weight. T cell function (proliferation and cytolytic activity) after in vitro

allogeneic stimulation was measured. Humoral response was assessed after 

immunization with heat killed streptococcus pneumoniae. Finally, it should be noted 

that the results reported by Rooney et al. have not been reproduced by the same 

laboratory that conducted the first experiments. 

It is not known if the developmental immunological effects of atrazine reported by 

Rowe et al. and Rooney et al. represent HPA axis alterations similar to those seen in 

adults at much higher doses. Rooney et al. (2003) provided some evidence that 

immune changes associated with atrazine during early development are not mediated 

through the suppression of prolactin or thyroid hormones. The precise underlying 

mechanism of an atrazine-mediated sex-specific effect, however, is not fully 

understood. 

In vitro studies intended to provide mechanistic data that would further clarify 

atrazine’s effect on the immune system, including intracellular signal transduction, have 

also been conducted. The underlying mechanisms of atrazine-induced inflammatory 

effects such as nociception and plasma extravasation, may be mediated through mast 

cell degranulation and activation of the Gq/11-protein coupled neurosteroid receptor, 
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phospholipase C and intracellular Ca2+ (Mizota and Ueda 2006). However, the 

inflammatory responses were examined following intraplantar administration of atrazine, 

a route of exposure that is not likely to occur in humans. Pinchuk et al. (2007) provided 

in vitro evidence suggesting that atrazine directly targets dendritic cell maturation and 

decreases major histocompatibility complex 1 (MHC-1) molecule expression on the 

dendritic cell surface. 

Atrazine-induced inhibition of in vitro human peripheral blood lymphocyte NK cellspecific lysis of K562 human leukemia cells may be the result of inhibition of lytic 

granule release, without affecting the ability of the natural killer cell to form stable 

conjugates with target cells (Rowe et al. 2007). Using human peripheral blood 

mononuclear cells, the in vitro study of Devos et al. (2003) suggests that atrazineinduced inhibition of human peripheral blood mononuclear cell proliferation and cytokine 

production is most likely not mediated through nuclear receptors such as the 

glucocorticoid receptor, androgen receptor, members of the peroxisome proliferatoractivated receptor family, and the retinoid-related orphan receptor α. 

Although in vitro studies provided some insight into potential mechanisms of 

atrazine-mediated immunotoxicity, the extrapolation of these mechanisms to the 

interpretation of immunotoxicity observed in vivo is difficult. Unlike the in vitro situation, 

in vivo the immune system’s response to atrazine exposure involves complicated 

feedback communication pathways with the central nervous system operative (for 

example, potential modulation of immune cell function by endocrine hormones such as 

corticosterone). 

In summary, the recent studies suggest a potential for atrazine to affect the 

immune system. However, the underlying modes of action of atrazine-mediated 

immunotoxicity and its relevance to potential adverse health effects in humans are still 

not thoroughly understood. In adult rodents, the indications of immunotoxicity reported 

in the atrazine database may be due to direct interactions between atrazine and/or its 

metabolites and immune system cells. Alternatively, the immunotoxicity response could 

be related to endocrine hormones acting on immune cells. Consequently, no 

conclusions may be drawn at this time on the relationship between the immunotoxic 

effects observed after atrazine exposure and the activation of the HPA axis with the 

subsequent disruption of the HPG axis. Furthermore, data regarding the developmental 

immunotoxicity potential of atrazine is inconclusive since the two available 

developmental immunotoxicity studies yielded conflicting results. Nonetheless, the 

available data do not indicate atrazine-induced immunotoxicity is a more sensitive 

endpoint than the atrazine-induced effects on neuroendocrine function, e.g., attenuation 

of LH surge in female Sprague -Dawley rats which is used for the basis of the points of 

departure for the intermediate and chronic exposure scenarios. 
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3.6 Genotoxicity and Carcinogenesis

During the initial review of atrazine in 1986, the Agency designated this pesticide 

as a Group C carcinogen (i.e., possible human carcinogen) due to the increased 

incidence of mammary tumors seen in Sprague-Dawley rats after chronic exposure and 

the lack of mechanistic data suggesting a MOA that could be evaluated for human 

relevance. It should be noted that no other tumor sites were found in rats and there 

were no tumors induced in mice. 

Since the 1986 assessment, an extensive mechanistic database has been 

generated by laboratories across the world. The Agency presented its assessment of 

the available mode of action information to the FIFRA SAP in 2000 (FIFRA SAP, 2000). 

At that time it was concluded, that the data show that the operative MOA for mammary 

gland tumorigenesis involves the perturbation of the hormonal milieu through the HPG 

axis and not a genotoxic or mutagenic MOA. While the disruption of the LH surge that 

is central to atrazine’s MOA is a relevant endpoint to assess potential adverse 

reproductive effects, it is not relevant for mammary tumor development in humans. In 

rats, the mammary tumors arise as a result of constant stimulation of the mammary 

gland by elevated levels of circulating estrogen and prolactin during the early 

reproductive senescence caused by the disruption of the LH surge. In contrast, 

humans’ reproductive senescence (menopause) is not the consequence of disruptions 

at the hypothalamic/pituitary level, but rather a depletion of follicles and a decrease in 

estrogen. That is to say, that while the hallmark of atrazine-induced reproductive 

senescence in rats is elevated estrogen, in humans menopause is marked by a 

decrease in both estrogen and prolactin. Consequently, in the absence of constantly 

elevated estrogen and prolactin levels mammary gland tumors would not develop in 

humans as a result of atrazine exposure. 

Several genotoxicity and carcinogenicity studies using transgenic and 

chemically-induced rodent carcinogenesis models have been published since the 2000 

SAP review and the 2003 IRED. Researchers have studied atrazine’s potential effect 

on tumor progression in a number of glandular tissues (pituitary, thyroid, ovaries, and 

mammary gland). It should be noted that none of these experiments study the tumorinitating capabilities of atrazine per se but rather its ability to accelerate the progression 

of already existing tumors. In general, these data show no evidence that atrazine 

exposure contributes to tumor progression or that it makes the tumors already present 

in the system more aggressive. In vitro studies – for the most part – corroborate the 

findings in the in vivo studies and show that atrazine is cytotoxic for most of the celllines tested.

Work by Fujimoto and coworkers in 2003 using transplanted MtT/E-2 pituitary rat 

cells (a cell line highly-sensitive to estrogen-induced proliferation), showed that in 

ovariectomized F344 rats exposed through the diet to atrazine at dose levels ranging 

from 5-500 mg/kg/day atrazine exposure did not accelerate tumor progression. In 

contrast, tumors were observed within 9 days in animals treated with 0.5 mg 
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subcutaneous pellet of estradiol. In this test system, serum prolactin levels, cell 

proliferation, and estrogen gene activation were also unaffected by exposure to up to 

500 mg/kg/day of atrazine. Similarly, work by Son et al. (2003) using a DHPN-induced 

thyroid carcinogenesis model demonstrated that atrazine exposure did not enhance 

thyroid tumor progression nor did it affect thyroid hormone levels (T4, T3, and TSH). 

DMBA-induced ovarian carcinogenesis was yet another model used to study atrazine’s 

potential to affect tumor progression. Using this model, Tanaka et al. hypothesized that 

the operative mode of action leading to ovarian adenocarcinomas involves hormonal 

disruption (particularly estrogen). Therefore, they postulate that exposure to atrazine 

(which has been associated with hormone disruption) may also affect ovarian 

carcinogenesis. As expected, a single exposure to 0.5% DMBA induced ovarian tumor 

formation. Subsequent atrazine exposure through the diet at doses ranging between 5-

500 ppm led to a slight, non-statistically significant decrease in the incidence of ovarian 

tumors seen after DMBA exposure alone. When considered collectively, the data 

reported by Fujimoto, Son, Tanaka and co-workers demonstrate that atrazine exposure 

did not accelerate tumor progression. 

Two in vivo studies are available. Fukamachi et al. in 2004 reported that in 

transgenic rats carrying a human c-Ha-ras proto-oncogene atrazine exposure enhanced 

DMBA-induced mammary tumor development. However, a dose-response could not be 

established for this finding. Likewise, the incidence of mammary adenocarcinomas 

appeared to be increased but a dose-response relationship was not observed since the 

incidence at the low- and mid-dose was higher than in the high dose. Non-transgenic 

rats were also used in this study, however, the data for these animals was not included 

in the report. Furthermore, atrazine exposure in vitro did not cause MCF-7 cell 

proliferation – an estrogen receptor-positive human mammary cancer cell line. 

Consequently, it is difficult to ascertain if the changes seen after atrazine exposure are 

truly related to an inherent carcinogenic property of the compound or if it is due to the 

genetic background resulting from the presence of a human proto-oncogene in the cells. 

Ueda et al. conducted a similar set of experiments in 2005 but instead of using a 

transgenic rat model they used a DMBA-induced mammary carcinogenesis model. In 

this study the effect of atrazine exposure on the progression of DMBA-induced 

mammary tumors in ovariectomized Sprague Dawley rats was investigated. When 

DMBA-induced rats were examined, no clearly discernible correlation between atrazine 

exposure and the number of tumor-bearing rats at the end of the study (i.e., atrazine 

exposure did not increase the incidence of rats bearing tumors) was observed nor did 

atrazine exposure affect the regression of palpable tumors observed after ovariectomy. 

Some statistically significant changes were reported by the authors but that is mainly 

due to the statistical analysis used. Exposure to 500 ppm atrazine by itself did not 

induce any mammary tumors. 

Agency scientists identified a number of deficiencies in the conduct, 

interpretation, and reporting in both the Fukamachi and Ueda studies which are 

described in Appendix A. Nonetheless, these two sets of data suggest that atrazine 
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does not induce mammary tumors in transgenic rats or ovariectomized rats treated with 

a mammary tumor inducer thus highlighting the importance of the ovarian hormones in 

the development of tumors in the mammary gland. 

In vitro data evaluating the cytotoxicity and cell proliferative properties in a variety 

of cell lines indicate that atrazine is cytotoxic or causes decreases in cell proliferation. 

In general, these data – like the in vivo data – suggest that atrazine is not genotoxic or 

mutagenic. 

Chinese Hamster ovary (CHO) and human fibroblast cell proliferation was 

decreased at relatively low levels of atrazine exposure (Kmetic et al. 2008 and Manske 

et al. 2004). However, data from Yi et al. (2010) suggests that atrazine and its 

metabolites are not cytotoxic to two steroidogenic cell lines (H295R and JEG-3) as well 

as two non-steroidogenic cell lines (HT-22 and MCF-7). 

Comet assay – a sensitive and rapid method for DNA strand break detection in 

individual cells – was used to study atrazine’s capability of inducing genotoxicity. Using 

this assay, Garaj-Vrhovac et al. and Zeljezic (2004) concluded that Gesaprim (an 

atrazine formulation) induced genome damage. The limitation of these studies is that a 

formulation of atrazine was used and no information is provided to determine the 

percentage of atrazine present in the test material. Thus, it is entirely possible that the 

DNA breaks reported after Gesaprim exposure may be related to other chemicals in the 

formulation rather than atrazine per se. Sister chromatid exchange (SCE) analysis – a 

sensitive method used to study DNA instability or a deficiency in DNA repair – has also 

been used to study the genotoxic potential of atrazine in human peripheral lymphocytes 

arrested at the G2 phase of the cell cycle. Using this method, Malik et al. demonstrated 

that over a concentration range of 5- 200 μg/L atrazine did not increase the frequency of 

SCE induction in G2-prematurely condensed chromosomes. 

Finally, two studies intended to evaluate if vitamin E treatment following atrazine 

exposure would ameliorate atrazine-induced effects are available. After atrazine 

exposure at a high dose of 300 mg/kg/day, Singh et al. (2008) report a marked increase 

in lipid peroxidation and decrease in acetylcholinesterase activity and cell membrane 

lipid content suggesting an increase in oxidative stress. Concurrent exposure to 

atrazine and vitamin E dampened all of these effects. A subsequent study by the same 

research group showed that at 300 mg/kg/day of atrazine induced DNA instability as 

measured by the Comet and micronucleus assays. Again, vitamin E exposure at 100 

mg/kg/day decreased micronuclei formation and DNA breaks. The results of this study 

are questionable given that the atrazine doses used to induce these genotoxic effects 

are orders of magnitude higher than what is currently used as the point of departure for 

human health risk assessment. 
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3.7 Insulin Resistance and Mitochondrial Function Impairment 

In a recent publication in the electronic journal PLoS ONE, Lim et al. (2009) 

suggest that atrazine exposure leads to insulin resistance, fat accumulation, and 

increased weight gain by increasing blood glucose levels and lowering energy 

expenditure. The authors postulate that atrazine disrupts mitochondrial function by 

inhibiting mitochondrial complexes I, II and III, which interact with ubiquinone for 

electron transport. This hypothesis is based on atrazine’s known pesticidal mode of 

action by disrupting electron transport via plastoquinone which is similar in structure to 

ubiquinone in vertebrates. Mitochondria are involved in fat oxidation and insulin 

secretion pathways, so their disruption could cause steatosis or insulin pathologies. 

However, mitochondrial inhibition should cause decreased insulin secretion, not 

increased as the authors propose. In fact, a recent publication in the Proceedings of the 

Academy of Sciences (PNAS) by Hoehn et al. (2009) demonstrated that – contrary to 

the Lim et al. hypothesis – mitochondrial inhibition reverses insulin resistance (i.e.

excess mitochondrial electron flow signals the over-fed state to produce insulin 

resistance). 

The authors state that atrazine exposure led to an increase in body weight and 

fat deposition regardless of the caloric intake. However, neither the body weight nor the 

fat deposition increases (↑5-10%) reported in the study show a dose-response. 

Moreover, the blood glucose levels reported by the authors after atrazine exposure 

though elevated relative to control are well within the normal range. Numerous 

deficiencies have been identified in this study and are described in detail in Appendix A. 

Amongst the most noteworthy deficiencies is the lack of several pieces of critical 

information in the material and methods, as well as inappropriate statistical analysis. 

The authors concluded that exposure to atrazine at dose levels as low as 30 

μg/kg/day resulted in significant mitochondrial dysfunction. Considering that NOAELs 

have been established in guideline in vivo toxicology studies at doses that are ≈ 60 to 

300-fold higher, this seems to be unlikely. Overall, the quality of this study was poor 

with numerous inconsistencies and deficiencies in the reporting thus rendering it of 

limited utility in understanding the toxicological profile of atrazine. 

In summary, Lim et al. are the only researchers that have proposed a relationship 

between atrazine exposure and mitochondrial dysfunction and obesity. The study used 

to support this hypothesis is critically flawed. Moreover, the preponderance of the 

evidence indicates that atrazine exposure leads to decreases – not increases – in body 

weight. Consequently, the validity of these data is uncertain and renders it of little 

relevance for risk assessment purposes. 

4. Summary of Mammalian Toxicity 

Atrazine exposure has been reported to lead to a number of toxic effects 

including effects on the reproductive health of the animals, immunotoxicity and 
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neurotoxicity. Rather than considering these toxicities as unrelated entities, it is 

important to examine them in the context of what is known about the PK and the MOA 

of this pesticide. Currently, the MOA for atrazine’s effect on the reproductive system 

and rat mammary carcinogenesis has been described as a perturbation of the HPG axis 

resulting in attenuation of the LH surge which in turn initiates a cascade of events 

leading to early reproductive senescence in the rat and to effects on reproduction and 

development. Recent data, however, suggest that an even earlier event in this process 

is the perturbation of the HPA axis manifested as increases in corticosterone levels. 

Changes in corticosterone levels are postulated to be a point of commonality for most – 

if not all the toxic effects – elicited by atrazine. Corticosterone levels can change 

significantly within 15 minutes of atrazine exposure but quickly returns to background 

level after a few hours. Although, it is well-understood that a continuous 3-4 day 

elevation of corticosterone leads to perturbations of the HPG axis, the toxicological 

relevance of this rapid increase is currently unclear (i.e., at what duration and at what 

doses does this perturbation lead to an adverse outcome). Time-to-effect relationship 

and the correlation between changes in corticosterone and attenuation of the LH surge 

suggest that HPA axis perturbation is the initial step in the MOA driving the most 

sensitive and biologically plausible toxic effect seen after atrazine exposure (i.e., 

suppression of LH). 

According to Pruett and coworkers, at high doses (≥ 100 mg/kg/day), atrazine 

and its metabolites DIA and DEA (but not DACT) have a clear effect on the secretion of 

pituitary adrenocorticotropin (ACTH) and adrenal steroid hormone secretion (i.e.,

corticosterone and progesterone) (Pruett et al., 2003). In the rat, this response is rapid 

(i.e., blood concentrations are significantly increased within 15 minutes after oral 

gavage). Furthermore, this group of researchers has correlated atrazine-induced 

corticosterone changes with a number of immune effects including suppressed white 

blood cell counts, increased neutrophils, and decreased lymphocytes. These data, 

however, must be interpreted cautiously since in this series of experiments atrazine 

exposure was through intraperitoneal injection – a route not relevant to human exposure 

and used high doses. 

Increases in corticosterone have also been shown to affect the activity of the 

neurotransmitters and neuropeptides of GnRH controlling neurons (Kirby et al., 2009), 

including increases in gonadotropin inhibiting factor, CRH and norepinephrine all of 

which are known to decrease GnRH pulses. Besides the neuroendocrine component, 

there is evidence that atrazine may affect the dopaminergic system. Given that the 

dopamine transporter (DAT) present in most – but not all dopaminergic neurons – has 

some affinity for norepinephrine, it is not unreasonable to consider that changes in 

corticosterone levels resulting in norepinephrine increases may affect the dopaminergic 

system. In fact, in humans, a persistent increase in cortisol levels has been associated 

with changes in dopamine neuronal activity (Molcrani et al., 1997). However, no data 

are currently available directly linking the atrazine-induced changes in corticosterone to 

effects in the dopaminergic system. 
Page 53 of 263 

 Interestingly, unlike other dopaminergic neurons, pharmacological data suggest 

that a functional dopamine transporter is not present in tuberoinfundibular (TIDA) 

neurons. Thus, the increased incidence in prostatitis resulting from the dampening of 

the suckling-induced prolactin surge in atrazine-treated dams is likely not related to toxic 

effects characteristic of the dopaminergic system. Nonetheless, the prostate effects 

elicited by atrazine exposure occur at higher dose levels than those suppressing the LH 

surge. 

In summary, the toxic effects seen after atrazine exposure are the result of 

multilevel interactions of a variety of systems, particularly the neuroendocrine, 

reproductive, nervous, and immune systems. Activation of the HPA axis and the 

subsequent disruption of the HPG axis appear to be the cornerstone for the most 

sensitive effects attributed to atrazine exposure – estrous cyclicity disruption. The 

extent of HPA activation (measured as increases in corticosterone) needed to elicit the 

decrease in GnRH and subsequent disruption of estrous cyclicity is not clear at this 

time. Neither the duration of exposure nor the dose that would lead to this adverse 

health outcome has been clearly described. It has been demonstrated by Fraites et al.

that a 4 day exposure to atrazine at 12.5 mg/kg/day leads to an increase in both ACTH 

and corticosterone. In this same time frame, exposures to 25 and 6.25 mg/kg/day of 

atrazine lead to decreases in GnRH and LH, respectively. With the exception of the LH 

attenuation, a no observed effect level (NOEL) has not been identified for any of these 

effects. As part of the WOE evaluation to be conducted for the SAP in the Fall, the 

Agency is planning to conduct a benchmark dose (BMD) analysis to better characterize 

the dose-response curve for these effects. This analysis along with additional ongoing 

research investigating the putative HPA-HPG axes interaction will help inform the 

Agency’s determination on the temporal and dose-response concordance of these 

events and how they reflect the relationship between the HPA and HPG axes. 

5. Approaches to Evaluating Water Sampling Strategies and Frequency of 

Monitoring 

5.1. Introduction 

As a condition of re-registration, the atrazine registrants were required to develop 

a program to monitor levels of atrazine and its chlorinated degradates in both raw 

(untreated) and finished (treated) drinking water in areas of potential vulnerability 

throughout the U.S. where atrazine is used. The Atrazine Monitoring Program (AMP) 

conducted by the registrant, Syngenta, began during 2003 with the collection of 

monitoring data from public utility Community Water Systems (CWS) located primarily in 

the corn and sorghum growing use areas of the Midwestern US. The current reevaluation of atrazine entails a review of the most recent toxicological data available. In 

conjunction with the toxicological review, the Agency has initiated a re-evaluation of the 

sampling frequency that is necessary for determining, with confidence, concentrations 

of the pesticide in water that sources drinking water. 
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Based on the best available information at the time of the 2003 IRED, the Agency 

determined that the most sensitive toxicological endpoint was associated with exposure 

to atrazine over a prolonged period (90-day average time frame). Syngenta employed a 

monitoring strategy – weekly sampling during the use/high runoff season and bi-weekly 

sampling during other parts of the year – intended to characterize exposure over a 90-

day time frame. In implementing a monitoring program, the frequency of sampling is 

closely linked to the health effects of concern. If the health effects of concern relate to 

long-term chronic exposures, less frequent sampling may provide sufficient data for 

EPA to be reasonably confident that the results are representative of a longer duration 

average concentration. However, for effects that can occur after shorter exposure 

durations, more frequent sampling may be needed in order to be confident that the 

sampling has not missed a high-end or peak exposure that could significantly affect the 

estimate of short term exposure. OPP is evaluating the sampling frequency and 

number of samples that may be needed to parallel water monitoring durations with the 

durations of concern for different toxic effects. These durations may vary from a single 

day peak concentration to a 3- or 7-day average concentration or even longer (e.g., 90-

day rolling average). Durations evaluated in this issue paper were selected as 

examples. The Agency has not yet made any decisions with respect to revising the 

duration of exposure concern for risk assessment and for drinking water monitoring 

purposes. 

While considering the question “How many water monitoring samples are 

necessary to adequately characterize varying exposure duration periods?”, the Agency 

is also interested in determining how to make the best use of existing monitoring data 

sets with known sampling intervals. To what extent can pesticide concentrations be 

estimated between known sampling events and/or how can the uncertainty of estimated 

concentrations of different averaging periods be quantified? 

This section provides an overview of the nature of pesticide occurrence in 

surface waters and the implications both in terms of monitoring pesticides in water and 

interpreting monitoring studies of varying sampling frequencies. The Agency discussed 

an approach for monitoring surface water streams with the FIFRA SAP in December, 

2007 (USEPA, 2007c). In this issue paper, the Agency presents results from two 

possible approaches which are similar in concept to the 2007 SAP analysis. Following 

that background, an approach is presented that models underlying distributions of data 

to examine the performance of different sampling schemes for estimating durations of 

interest. 

5.2 The Nature of Pesticide Occurrence in Surface Water 

A unique pattern of occurrence in surface water can be identified for each 

pesticide (and, in some instances, its degradates) resulting from a combination of 

pesticide properties, use patterns, application methods and timing, weather, watershed 

characteristics (e.g., soil characteristics, slope, land cover type), and hydrology (Gilliom 
Page 55 of 263 

et al., 2006). While the interactions of these factors result in complex occurrence 

patterns that are difficult to adequately characterize both geographically and temporally 

with monitoring (USEPA, 2000; Stone and Gilliom, 2009), an understanding of the 

factors affecting pesticide distributions in water can be used to anticipate pesticide 

occurrence in place and time. Although such patterns also occur in differing degrees in 

ground water, the focus of this paper is on pesticide occurrence in surface waters of the 

United States. 

On a broad regional or national scale, pesticide occurrence in surface water can 

be largely anticipated based on the geographic distribution of pesticide use (Gilliom et 

al., 2006; Stone and Gilliom, 2009). Within areas of similar pesticide use, watershed 

characteristics such as soil susceptibility to runoff and/or erosion, weather patterns, land 

management practices, and hydrology can be important factors driving the level of 

pesticide concentrations in surface waters (USEPA, 2009a and 2009b; FIFRA SAP, 

2009). Complex geographic patterns of pesticide concentrations in water can be 

characterized from the dominant factors affecting the spatial variability (see, for 

example, the U.S. Geological Survey’s Watershed Regression on Pesticides, or WARP 

model, developed by Larson et al., 2004, and updated by Stone and Gilliom, 2009). 

Areas of the country that are particularly vulnerable to pesticide exposures in water 

bodies can be identified based on a combination of pesticide use, weather, and 

watershed characteristics (see, for example, the US EPA’s evaluation of the results of a 

monitoring program to assess the effects of atrazine on aquatic communities, described 

in USEPA, 2009a and 2009b). 

While the USEPA (2009a and 2009b) watershed-scale vulnerability assessment 

for atrazine focused on small streams and aquatic ecological community impacts, it may 

have potential applications for drinking water exposure assessments. The Agency is 

currently evaluating the recommendations of the FIFRA SAP (2009) to improve the 

watershed-scale vulnerability assessments. Broader, regional-scale vulnerability 

approaches were also used to identify subpopulations who receive their drinking water 

from vulnerable surface water sources for the cumulative assessments for both the 

organophosphate and the N-methyl carbamate pesticides (USEPA, 2002, 2007b). For 

the cumulative risk assessments, the vulnerability of drinking water sources depended 

on both spatial (use, watershed characteristics, location of drinking water sources) and 

temporal (timing of applications for multiple pesticides) factors. This spatial variability in 

pesticide concentrations in water is being addressed in other efforts; this paper will 

focus on addressing the temporal patterns of pesticide occurrence in surface water 

bodies. 

Pesticide concentrations in surface water bodies vary throughout the year, 

generally occurring at low to no detectable levels for most of the year, with short-term 

seasonal pulses of higher concentrations that are related to the timing of pesticide use 

and rainfall pattern (Gilliom et al., 2006). Such short-term pulses, or spikes, in pesticide 

concentrations may range from less than a day to weeks or months, depending on the 

fate and transport properties of the pesticide and its use, as well as the interaction of 
Page 56 of 263 

other driving factors (e.g., use, watershed characteristics, weather, land use practices) 

contributing to the pesticide occurrence in surface waters. 

Some pesticides such as atrazine, with relatively widespread use and properties 

favorable to pesticide transport (mobility and persistence), are often detected yearround with periods of high concentrations ranging from days to weeks. Other pesticides 

with more localized use patterns or properties less prone to transport (less mobile 

and/or less persistent) may occur infrequently in water. Figure 4, taken from Gilliom et 

al. (2006), contrasts the seasonal patterns of atrazine and chlorpyrifos in the White 

River in Indiana over multiple years using the same sampling frequency. A monitoring 

strategy that may be adequate for characterizing the regular, periodic occurrence of 

atrazine may not be sufficient for a less frequently occurring pesticide such as 

chlorpyrifos. 

Figure 4: Concentrations of atrazine and chlorpyrifos over time in the White 

River, Indiana. Source: Gilliom et al, 2006. 

In any given location, the magnitude and duration of pesticide concentrations in 

water may vary from year to year, depending on such factors as the magnitude, timing, 

and frequency of pesticide application, the timing and intensity of rainfall events postapplication, soil moisture conditions at the time of application and rainfall, and the type, 

timing, and extent of land management practices in place (Gilliom et al., 2006; also 

illustrated in Figure 4). Atrazine occurrence in most bodies of water follows a seasonal 

pattern that corresponds to seasonal usage and weather patterns, with larger ‘spikes’ in 

concentration related to pre-emergent spring applications, particularly when followed by 

periods of runoff-producing rainfall. 
Page 57 of 263 

The magnitude, duration, timing, and frequency of seasonal spikes in pesticide 

concentrations will also vary with the nature of the surface water body (flowing 

waters/streams vs. impounded waters such as reservoirs) and the size of the drainage 

basin. All other factors being equal, smaller streams may have higher, more frequent 

spikes than larger streams with a larger area contributing to drainage to the water body. 

A different temporal exposure profile would be expected from reservoirs, which integrate 

pesticide loading from their watersheds and have slower flow-through, resulting in a 

greater residence time. These impounded waters may be expected to show smaller 

temporal variations than flowing water bodies (Blomquist et al., 2001). 

In additional to seasonal and year-to-year patterns, pesticide concentrations in 

water show high levels of autocorrelation that are not accounted for with traditional 

statistical methods (Crawford, 2004). Pesticides such as atrazine show a serial 

correlation in which the probability of detecting the pesticide in water on a particular day 

is greater when the pesticide was detected on the previous day. Sampling designs and 

methods of interpreting monitoring data need to account for the temporal codependence of pesticide concentrations in water: the exposures measured on one day 

are related to the exposures measured on preceding and subsequent days. 

5.3 Sampling Frequency in Monitoring: Implications for Pesticide Exposure 

Assessments 

Depending on its quality (including location, timing, and frequency of sampling) 

and the particular exposure durations of concern, surface water monitoring data can be 

used to approximate dietary exposure to humans from drinking water sources (see, for 

example, the drinking water assessment for Atrazine and the cumulative assessment for 

the Triazines4). An important consideration in evaluating the suitability of monitoring 

data for use in a dietary exposure assessment is how well the data represent the 

pesticide use both temporally and spatially. Generally, for monitoring data to be 

considered suitable for exposure assessments it must be targeted to the use pattern 

being assessed. Targeted monitoring data should have a study design that focuses on 

both where and when the pesticide is used, and should have a sample frequency 

designed to capture the exposure period of concern (e.g., one-day peak vs. annual 

average concentrations). 

5.3.1 General Monitoring Strategies 

A “monitoring strategy” is a combination of (a) a plan for obtaining new 

contaminant occurrence data and (b) a decision rule, in which the occurrence data are 

used to make a binary decision, such as to decide whether exposure levels are above 

or below some health- or ecological-based level of concern. 

 

4

 Links to both assessments can be found on the USEPA Office of Pesticide Programs atrazine web site 

at http://www.epa.gov/oppsrrd1/reregistration/atrazine/
Page 58 of 263 

Crafting a suitable water monitoring strategy involves many considerations. In the case 

of human health concerns, these include: 

• The cost of obtaining and testing samples of water (source or drinking water) 

• The spatial and temporal variability of the contaminant, particularly when 

occurring at or near levels of concern. 

• The concentrations and durations that are associated with different health 

endpoints 

• The severity of the adverse health outcomes 

• The utility of monitoring data for informing treatment decisions 

• Consequences of failing to detect and address high occurrence (false 

negative) 

• Consequences of false alarm (false positive) 

When the above considerations lead to quantitative performance criteria, those 

criteria become the benchmarks for evaluating different monitoring strategies. When 

available strategies fail to satisfy the criteria, for example, because they too often raise 

false alarm or too often fail to detect high occurrence, planners may need to reconsider 

the performance criteria. 

5.3.2 Data Quality Objectives 

Executive order 5360.1 requires the use of “a systematic planning process to 

develop acceptance or performance criteria” for environmental monitoring projects.5 

Over the past 25 years, EPA’s Quality Assurance Staff has developed and promoted a 

systematic planning process for just this purpose, called “Data Quality Objectives” or 

DQOs.6 

The DQO process applies systematic planning and statistical hypothesis testing 

methodology to facilitate the design and selection of environmental monitoring 

strategies. The seven steps of the process are: 

1. State the Problem 

2. Identify the goal of the study 

3. Identify information inputs 

4. Define the boundaries of the study 

5. Develop the analytic approach 

6. Specify performance or acceptance criteria 

7. Develop the plan for obtaining data 

 

5

 USEPA Executive Order 5360.1, Policy and Program Requirements for the Mandatory Agency-Wide 

Quality System, Chg 1, 7/16/1998. http://www.dpnr.gov.vi/dep/5360-1c1.pdf 6

 USEPA, 2006, Guidance on Systematic Planning Using the Data Quality Objectives Process (EPA 

QA/G4). EPA/240/B-06/001. http://www.epa.gov/quality/qs-docs/g4-final.pdf
Page 59 of 263 

The process becomes quantitative in Step 6, where two kinds of errors and their 

consequences are expressed and considered. The outputs of Step 6 are quantitative 

limits for the probabilities of false positives and false negatives. A statistician can then 

evaluate how well selected monitoring strategies satisfy these criteria, given different 

occurrence scenarios or patterns. In general, waters with high variability are the most 

challenging. Water having a low occurrence level, but high variability, can experience a 

false positive whenever a sample is taken during a short-lived occurrence spike. 

Similarly, water with a high occurrence level with high variability may experience a false 

negative and show lower levels because infrequent monitoring failed to catch a large 

occurrence spike. Several example profiles are presented below. 

5.3.3 Monitoring Strategies Related to Pesticides 

The Agency and other researchers have studied the issue of sampling frequency 

to characterize pesticide exposure for drinking water (see, for example, ILSI, 1999; 

USEPA, 2000; and Crawford, 2004). Generally, longer durations of concern (e.g. 

annual average concentration for a long-term chronic effect) require less frequent 

sampling to approximate longer term exposures. However, as the duration of the 

exposure of concern shortens, the frequency and timing of sampling become more 

important in determining the confidence in how well the sample data capture these 

short-duration exposures. This is most critical when the Agency is concerned about 

acute effects resulting from peak single day exposures or from short-duration 

exposures. For such short-term exposures of concern, the likelihood of adequately 

characterizing the high end of exposure for decreases as the time between sampling 

events increases. 

While the time frame of interest in relation to the health effect(s) of concern is a 

key consideration in determining the sampling frequency, logistics and cost also remain 

a major factor in the design of any sampling program (ILSI, 1999; USEPA, 2000). Often 

the Agency is left to determine how best to evaluate monitoring studies with samples 

that are taken less frequently than desirable for an effect’s period of interest. 

Few pesticide monitoring studies have consistently sampled pesticides in water 

at daily time intervals. An exception is the intensive pesticide sampling efforts 

conducted by Heidelberg University’s National Center for Water Quality Research 

(NCWQR; formerly known as the Heidelberg College Water Quality Laboratory) on 

selected streams draining into Lake Erie7

. Since the 1980s, the NCWQR has intensively 

sampled for a number of pesticides in selected Ohio streams of various sizes. This 

dataset has proven valuable in evaluating varying sampling frequencies (see Crawford, 

2004). The USGS National Water Quality Assessment (NAWQA), one of the more 

extensive national water monitoring programs that includes pesticides, generally 

 

7

 More information on the NCWQR program, its publications, and water quality data retrieval can be found 

at http://www.heidelberg.edu/WQL . 
Page 60 of 263 

sampled weekly to twice monthly during the time of anticipated highest pesticide use 

and runoff (Gilliom et al, 2006). On the other end of the sampling frequency spectrum, 

USEPA’s compliance monitoring regulations under the Safe Drinking Water Act 

generally rely on quarterly sampling from state water programs to determine 

concentrations of contaminants in water. A number of studies of varying sampling 

frequencies have been conducted by pesticide registrants, such as the Acetochlor 

Registration Partnership, ARP (monitoring program description and water quality data 

are available through USEPA, 2007) and Syngenta’s Atrazine Monitoring Program 

(AMP) for Community Water Systems (CWS) and Atrazine Ecological Exposure 

Monitoring Program (AEEMP) to assess impacts to aquatic communities (more 

information on these programs is available through USEPA’s atrazine web site at 

http://www.epa.gov/pesticides/reregistration/atrazine/index.htm). 

After the passage of the Food Quality Protection Act (FQPA) in 1996, the 

International Life Sciences Institute (ILSI) convened a panel whose charges included 

providing guidance on monitoring and modeling needs for generating probability 

distributions of pesticide concentrations in drinking water exposure assessments. 

Based on their best professional judgment (defined by ILSI, 1999, as a “statistical 

probability sampling... modified at times to reflect the real cost or practical and logistical 

constraints”), the ILSI panel recommended a minimum of 100 samples per year, 

targeting the likely pesticide use seasons, for a high level of prediction accuracy for 

maximum peak exposures at a single water supply (ILSI, 1999). For regional and 

national exposures, ILSI (1999) recommended fewer samples at individual supply 

facilities as the number of monitored water supplies increased, reflecting the “practical 

cost” of sampling. 

How well monitoring data capture pesticide concentrations over time depends on 

both the frequency and timing of sampling events relative to the “true” exposure profile. 

Crawford (2004) found that, for sampling programs with a fixed number of samples, 

seasonally weighted sampling strategies provided better estimates of time-weighted 

mean and percentile concentrations of pesticides (in terms of precision and accuracy) 

compared to fixed interval sampling frequencies spread throughout the year. More 

frequent sampling is needed to achieve the same level of precision and accuracy for 

small streams compared to larger streams which integrate pesticide loadings over a 

larger watershed (Crawford, 2004). 

The number and frequency of sampling events will also depend on the relative 

time frame of concern as it relates to the effect endpoint and the duration of effects. 

The shorter the time averaging period required for a short-term effect, the more 

frequently the samples need to be taken to achieve the same level of precision and 

accuracy as seen for a longer averaging period (Crawford, 2004). Similarly, for a 

distribution of concentrations in a year, the level of precision for a given sampling 

frequency decreases as the concentration percentile in the distribution increases 

(Crawford, 2004). 
Page 61 of 263 

5.4 Approaches to Analyzing and Interpreting Monitoring Data Collected at 

Different Sampling Frequencies 

In most cases, the Agency must determine how to interpret monitoring data 

collected at different sampling frequencies. This involves determining how well the 

monitoring data capture the actual pesticide concentrations in water over time for the 

particular toxicity endpoint duration of concern and providing confidence bounds on the 

exposure estimate from the monitoring data. The less frequent the sampling interval, 

the less information is available to characterize the “true” exposure time series of 

pesticide concentrations in surface waters. The Agency has evaluated or will be 

evaluating various methods to interpret available monitoring data in the absence of a full 

time series profile for the pesticide concentrations. The applicability of the methods 

considered depends on both the quality of the monitoring data and the time frame of 

interest for the health effect (acute, short- or intermediate-term, chronic effects). 

Approaches to provide a confidence bound on exposure estimates follow a brief 

discussion of those methods below. 

5.4.1 Characterizing Exposure Time Series From Less Frequent 

Monitoring Data 

At the most basic end of the spectrum, for risk assessment purposes the Agency 

could use only the measured pesticide concentrations as the exposure 

distribution for a drinking water assessment. This approach does not explicitly 

address what exposures occur on non-sampled days, but assumes that mean, standard 

deviation, and distribution of measured samples are representative of the “true” 

exposure time series in the water body. This approach also assumes that the maximum 

exposures of the true distribution are represented in the sample. The fewer the 

samples taken and the greater the interval between sampling events, the less likely the 

sampling dataset is to represent either maximum exposures or the actual distribution of 

pesticide concentrations in the water body. 

Another commonly used approach to interpret monitoring data is to linearly 

interpolate between the sampling points. This approach assumes a linear 

distribution between sampling dates (illustrated with the red lines in Figure 5), which is 

less likely to hold the farther apart the samples occur, and assumes no concentrations 

greater than what was captured in samples. As shown in Figure 5, the timing of the 14- 

and 30-day grab samples8

 captured exposures on either side of the actual 

concentration peak in late April but missed the “true” maximum concentration. The 

extent to which a linear interpolation between sampling points adequately characterizes 

the “true” exposure time series depends not only on the timing of sampling and 

sampling interval, but on the shape of the actual concentration time series. Such an 

 

8

 The term “grab sample” can refer both to samples drawn from the water that do not integrate across the 

water body itself and to samples taken at a particular point in time that do not integrate across any time 

frame. In this document, the term “grab sample” refers solely to the temporal aspects. 
Page 62 of 263 

approach will likely underestimate short-term or peak exposures but may be useful to 

characterize pesticide concentration profiles that have less pronounced temporal 

variations, such as those that may occur in reservoirs or large rivers. 

0

10

20

30

40

50

60

3/1 3/15 3/29 4/12 4/26 5/10 5/24 6/7 6/21 7/5 7/19 8/2 8/16 8/30 9/13 9/27

Date

Atrazine (TCT), ug/L

Daily Time Series

14-day Grab (linear)

30-day Grab (linear)

14-day Grab (stairstep)

30-day Grab (stairstep)

Figure 5: Comparison of daily time series for pesticide concentrations (dark blue 

line) to linear (red lines) and stair-step (light blue lines) extrapolations for 

samples taken at 14- or 30-day intervals. 

An alternative to the linear approach is a stair-step imputation between 

sample points. In this method, the pesticide concentration measured on a particular 

sampling date is assumed to apply to subsequent days until the next sampling date 

(illustrated with the light blue lines in Figure 5). As with the other methods described so 

far, the stair-step imputation assumes no concentrations greater than what was 

captured in samples. The probability of missing maximum concentrations increases as 

the interval between samples increases. The stair-step approach has a greater 

likelihood of overestimating longer-term, time-averaged concentrations than does the 

linear interpolation approach. As illustrated in Figure 5, the longer the time interval 

between samples, the less likely the stair-step imputation will resemble the “true” 

exposure time series. 

These approaches, and similar variations, make simplified assumptions about 

the nature of pesticide concentrations in the water body and how well the sample points 
Page 63 of 263 

reflect the distribution of the entire time series. These assumptions are less likely to 

hold as the sampling interval increases. In addition, the approaches fail to account for 

the temporal autocorrelation that characterizes pesticide concentrations in surface 

waters. Unless the monitoring dataset spans multiple years, it is also unlikely to 

account for the year-to-year variability that results from changes in land use, pesticide 

use patterns, and weather. 

More rigorous methods of interpreting monitoring data may include statistical 

methods such as bootstrapping, neural networks, kriging, random function models, 

regression-based models that predict pesticide concentrations from measured 

variables, and deterministic models based on known relationships between pesticide 

concentrations and physical processes in the environment. The Agency is in the 

process of evaluating the utility of such methods and only makes brief mention of a few 

selected approaches here. In the section that follows, the Agency presents preliminary 

evaluations of the simulation approach taken by Crawford (2004) as well as an alternate 

method that examines simulations producing distributions of maximum running 

averages. USEPA anticipates feedback and recommendations from the FIFRA SAP on 

these preliminary approaches, as well as other methods including those mentioned here 

and others not considered. 

USEPA’s Office of Water (OW) has explored a modeling approach using the 

application of neural networks that will be presented in the following section, as well. 

While artificial neural networks are statistical modeling tools that can be used to model 

complex relationships or to find patterns in data, as with any of the above approaches, 

results are only as good as the sampling data available. This approach is illustrated in 

more detail in Section 5.6 and Appendix C. 

While kriging and random function model approaches have generally been 

applied to geostatistical analyses (Isaaks and Srivastava, 1989; Deutsch and Journel, 

1998), their assumptions of co-linearity can be applied to the temporal autocorrelation 

inherent to pesticide concentration time series in surface waters. A nearest neighbor 

approach accounts for temporal autocorrelation by measuring the variance at different 

lag times and then linearly interpolating between points with an appropriate weighting 

from nearest neighbors (Figure 6). Based on the nature of occurrence patterns 

represented by a sequence of observations, the approach estimates missing values 

with non-subjective linear interpolation techniques. A stochastic simulation adds an 

uncertainty analysis and provides a probabilistic assessment of daily concentrations. 

Kriging may not be viable, however, for pesticide distributions that lack significant 

correlation (such as the chlorpyrifos distributions shown in Figure 4). The data 

smoothing techniques illustrated here will underestimate high occurrence events. 
Page 64 of 263 

Figure 6: Conceptual illustration of the nearest neighbor approach for estimating 

daily pesticide concentrations at less frequent sampling intervals. 

Multiple regression models may be useful for estimating pesticide 

concentrations, provided the relationships are known and the parameters are available 

to populate the model. Larson et al (2004) developed the Watershed Regression on 

Pesticides (WARP) model for atrazine based on nationally-available geospatial data 

and NAWQA monitoring data for atrazine. The intent of the model was to provide 

predictions of pesticide concentrations in unmonitored or inadequately monitored 

streams. Because of the sampling frequency of the atrazine monitoring data used to 

develop the model (weekly to bi-weekly during the pesticide use and likely runoff 

season), WARP originally did not provide pesticide exposure estimates greater than the 

95th percentile of yearly distributions. At given locations, pesticide concentrations 

estimated by WARP were within an order of magnitude of measured concentrations in 

water. While predictions of percentile atrazine concentrations tended to be low in 

comparison to actual measurements for most validation sites with the original model, 

predictions with the updated model were “not substantially biased” (Stone and Gilliom, 

2009). However, because the sampling frequencies of the NAWQA model-development 

sites were not sufficient to reliably characterize the highest concentrations during a 

year, estimates of the annual maximum concentration from the updated WARP model 

are expected to underpredict the actual annual maximums (Stone and GIlliom, 2009). 

The authors noted that while WARP exposure estimates “cannot replace direct 

measurements when reliability requirements are high,” they provide screening estimates 

that can be used to target more intensive monitoring (Stone and GIlliom, 2009). 

The 2009 FIFRA SAP reviewing the Agency’s assessment of the ecological 

impacts of atrazine concentrations in streams in corn- and sorghum-growing areas 

recommended that the Agency consider a Cornbelt WARP model that utilized the data 

and information gleaned from that monitoring effort (FIFRA SAP, 2009). USEPA is 

continuing to analyze the results of that intensive watershed monitoring effort conducted 

by Syngenta Crop Sciences and will be looking into ways the WARP model could 

provide improved spatial and temporal estimates of atrazine exposure in streams. 

The Agency has used deterministic models such as PRZM (Pesticide Root 

Zone Model) and EXAMS (Exposure Analysis Modeling System) to estimate multi-year 

daily pesticide exposure series for use in probabilistic drinking water exposure 
Page 65 of 263 

assessments9. These deterministic models could be used to estimate exposures 

between monitoring samples provided that local soil, crop, and weather data are 

available. Estimated exposures generated by PRZM-EXAMS could be calibrated to the 

measured concentrations and provide a complete time series between sampling dates. 

USEPA (2007) reviewed Syngenta Crop Science’s use of PRZM with site-specific soil, 

cropping, and weather data to estimate atrazine concentrations between 4-day 

monitoring samples as a part of the ecological exposure monitoring program. Even with 

the relatively frequent sampling intervals, time-averaged exposures estimated with the 

PRZM augmentations increased for the majority of the monitoring site years (66 out of 

80) in comparison to stair-step imputations of the 4-day samples (USEPA, 2007). 

5.4.2 Determining Confidence Bounds on Exposure Estimates From 

Monitoring Data 

At a given location, the degree to which a monitoring dataset characterizes the 

“true” pesticide exposure profile and the level of uncertainty in the exposure estimates 

from that data set depend not only on the sampling frequency and the duration of 

sampling but also on the time frame of interest for the health effect (acute, short- or 

intermediate-term, chronic effects). While the capabilities of the methods and models 

for interpreting monitoring data of various sampling frequencies can be evaluated using 

goodness-of-fit and residual error tools (see Stone and Gilliom, 2009, for examples), the 

Agency is also concerned with how accurately the available monitoring data set 

captures the true pesticide concentration exposure of concern, whether it is a maximum 

peak or exposure over a multi-day time period. 

The nature of the temporal patterns of pesticide occurrence in surface waters 

presents challenges in uncertainty analysis. These analyses need to account for the 

temporal relationships in pesticide concentrations, the serial correlations from day to 

day, the periodicity in elevated concentrations within seasons and from year to year, the 

abundance of censored data (non-detections and pesticide concentrations below 

analytical limits of detection), and uncertainty in the shape of the pesticide distributions 

in surface waters. The Agency is soliciting feedback from the FIFRA SAP on statistical 

approaches that may address these issues. 

In the preliminary analyses below, the Agency is evaluating approaches for 

characterizing the level of uncertainty in predicting true pesticide concentrations over 

varying averaging times based on varying sampling frequencies and strategies. The 

resulting uncertainty can be reflected in a couple of basic approaches. In one 

approach, the Agency can determine a prediction interval with specified confidence for 

the predicted new exposures from monitoring data, similar to the approach described by 

Stone and GIlliom (2009). Or, for example, for a particular monitoring data set, the 

USEPA can describe the range in values within which a given percent, e.g. 99 percent, 

 

9

 See USEPA OPP’s Water Models web page at http://www.epa.gov/oppefed1/models/water/ for more 

information. 
Page 66 of 263 

of monitoring samples are expected to occur (tolerance interval). An upper bound of 

this interval can be compared to the toxicity endpoint of concern to determine whether 

the true exposures could exceed the toxicity thresholds of concern. 

Another approach to account for the uncertainty in monitoring data would be to 

place intervals around the threshold concentrations of concern rather than the exposure 

estimate from the monitoring dataset. The lower bound on the threshold would be 

constructed for a given confidence based on the timing and frequency of sampling 

events for the monitoring dataset. For example, suppose the exposure threshold of 

concern for a particular health effect is a 3-day average concentration of 15 ug/L. A 

lower threshold value of 10 ug/L might be set for monitoring data with weekly sampling 

intervals during the pesticide use season. In this example, the lower threshold value 

reflects the maximum 3-day average concentration from a weekly monitoring dataset 

that would be expected to exceed the actual threshold concentration of concern with, for 

example, 95 percent confidence. ILSI (1999) provided guidance on estimating 

confidence and tolerance intervals and calculating prediction intervals to determine the 

appropriate sample size for a monitoring study. The same or similar approaches might 

be adapted to evaluate the results of monitoring data against health effects thresholds 

of concern. 

5.5 Examining the Performance of Various Sampling Strategies with Data 

from the Atrazine Monitoring Program (AMP) 

5.5.1 Profiles of Community Water Systems in the AMP 

The AMP Monitoring of Community Water Systems (CWS) for surface water 

serving 10,000 or more residents began during 2003. The program focused on systems 

with higher expected concentrations, based on compliance monitoring, that was carried 

out on a weekly basis during the growing season (April through July or August in corn 

areas) and biweekly during the remainder of the year. Any CWS that exceeds an 

annual mean screening level concentration of 1.6 ppb atrazine from quarterly Safe 

Drinking Water Act (SDWA) data is included in the AMP. In the seven years of 

monitoring, the program has grown from an original 130 CWS to a little over 150 CWS 

per year in a given year. Under the above monitoring strategy, between 30 and 35 

samples each of raw and finished water are typically collected at each system annually. 

While both raw and treated water samples have been collected, the present paper looks 

exclusively at raw water for summarizing information on results before any treatment 

has occurred. 

The numbers of raw water samples each year have ranged from just under 4,000 

to over 4,800 samples for the 5 full years 2004 through 2008. Chemograph profiles of 

peak results and concentrations exceeding several arbitrary comparison concentrations 

are presented in Table 5 below. 
Page 67 of 263 

Table 5: Summary of Atrazine Monitoring Program (AMP) Data for Atrazine in 

Raw Water* 

Year Total 

samples 

Percentage 

measurements. 

<1.0 ppb 

Percentage

meas. 

< 3.0ppb 

#Peaks>

12.0ppb

Percentage 

peaks 

>12.0ppb 

99th

percentile 

Atz.Conc. 

(ppb) 

99.9th

percentile 

Atz. 

Conc. 

(ppb) 

Maximum 

Atrazine 

Conc. in 

Year 

(ppb) 

2004 4429 54.4 95.6 19 0.4% 7.9 24.8 47.5 

2005 4779 64.2 91.9 71 1.5% 15.4 46.0 84.8 

2006 4817 77.6 93.7 30 0.6% 9.3 28.4 227 

2007 4521 77.7 94.5 10 0.2% 7.1 15.9 25.8 

2008 3927 72.8 92.2 49 1.3% 13.3 42.9 73.0 

* Source: Raw data submitted by Syngenta annually to EPA

In general, the number of individual samples that are below the concentration of 

3 ppb is high, ranging from approximately 92- 96% of the 4,000+ samples each year. 

The number of individual samples below 1.0 ppb ranges from about 54% in 2004 to 

about 78% in 2007. 

Maximum concentrations are given for each year, and range from 25.8 ppb in 

2007 to 227 ppb in 2006. Maximum peaks for the other years vary each year as well, 

going from 47.5 ppb in 2004 to 84.8 ppb in 2005, to 73.0 ppb in 2008. The table also 

lists the 99th%ile and the 99.9th%ile values for all samples each year, with the former 

ranging from about 7 ppb to just over 15ppb, and the latter ranging from about 16 ppb to 

46 ppb. 

Since there is interest in capturing individual peak concentrations in the 

monitoring, the number of individual peaks exceeding several arbitrary concentration 

levels is also presented in Table 5 above as well as in Table 6 below. It is important to 

reiterate that these “peaks” are based on sampling that was carried out once a week 

during the season of use and biweekly during the remainder of the year. As such, it is 

likely to underestimate the “true” peak concentrations at these CWS. In the 

methodology outlined below, however, the significance of the relative shapes of the 

chemographs will become clear when they are used to create reference profiles for 

comparison of sampling strategies. 

Looking at individual samples that equal or exceed 12 ppb in the monitoring, the 

number of peaks varies each year and ranges from 10 samples in 2007 to 71 (1.5%) in 

the year 2005. When 20 ppb is used as the cut-off, the number of peaks exceeding that 

level falls to 1 sample in 2007 up to 22 samples in the year 2005. At 30 ppb the 
Page 68 of 263 

numbers decline even further, ranging from none of the 4,521 samples reaching that 

level in 2007 up to 10 samples (0.3%) exceeding 30 ppb in 2008.10 

Table 6: Atrazine Monitoring Program Data for Atrazine in Raw Water* 

Year Total 

samples 

#peaks> 

20ppb 

# peaks> 

30ppb 

#CWS w. a 

peak 

>12ppb 

#CWS w. a 

peak > 

20 ppb 

#CWS w. a 

peak 

>30ppb 

2004 4429 6 2 15 / 141 5 2 

2005 4779 22 7 27 / 142 12 6 

2006 4817 11 2 20 / 151 10 1 

2007 4521 1 0 7 / 137 1 0 

2008 3927 19 10 23 / 134 14 9 

* Source: Raw data submitted by Syngenta annually to EPA

Generally over the course of the 5 years of monitoring presented, the peaks 

discussed above occurred in a fairly consistent set of CWS each year. Peaks 

exceeding 12 ppb occurred in up to 20-30 CWS over the years, while peaks exceeding 

20 ppb occurred in a subset of 5-15 of those systems. The few higher peaks exceeding 

30 ppb occurred in 9 or fewer [per year] of the 130-150 CWS. 

 

Clearly, both the number and magnitude of individual atrazine peaks has varied 

each year within the AMP data. Across the years, however, a fairly consistent set of 

CWS appears to show the highest levels. 

5.5.2. Approaches from the 2007 and 2009 SAP Meetings on 

Monitoring in Surface Water Streams in the Corn and Sorghum 

Growing Region of the US 

In December 2007, the Agency summarized its preliminary review and 

interpretation of the initial results of the Atrazine Ecological Exposure Monitoring 

Program (AEEMP) before the FIFRA SAP. The Panel provided feedback related to the 

interpretation of the results and the extent to which the methods used by the Agency 

could be implemented or adapted in any future aquatic assessments or monitoring 

efforts to determine the extent to which water bodies exceed atrazine thresholds of 

concern. 

One aspect of that SAP Meeting looked at adapting Crawford’s 2004 “Sampling 

strategies for estimating acute and chronic exposures of pesticides in streams” to 

 

10 The numbers presented refer to individual peak samples and do not represent averages of any 

duration. For the current level of concern there were no 90-day average concentrations equal to or 

exceeding the 37.5 ppb concentration 
Page 69 of 263 

evaluate sampling frequencies. Crawford (2004) used data from 10 years of monitoring 

by the Heidelberg College Water Quality Laboratory from four rivers and streams in 

northwestern Ohio. The sampling data were augmented, where necessary, using 

interpolation between samples to create 365-day profiles which served as the “true” 

chemographs for the exercise. Alternative sampling strategies, ranging from quarterly 

sampling to sampling 10 times per month, were tested by sampling from the daily 

profiles 1,000 times at each site for each year. The performance of the various 

sampling strategies relative to the “true” profiles was evaluated by examining 

differences from the daily profile for the mean and upper percentiles of each alternative 

strategy. 

A similar approach was first recommended by Crawford and coauthors in the 

International Life Sciences Institute (ILSI) 1999 report, “A Framework for Estimating 

Pesticide Concentrations in Drinking Water for Aggregate Exposure Assessments.” The 

current SAP paper looks at methods similar to these approaches to present preliminary 

results for example chemographs from a group of ten different CWS in the Atrazine 

Monitoring Program. 

5.5.3 Current Methods 

5.5.3.1 Comparing Upper Percentile Values from Different 

Sampling Strategies with those of the “True” Profile 

The first method employed in the current paper generally follows the Crawford 

(2004) and ILSI (1999) methods. The examples below used the AMP monitoring with 

sampling weekly during the months of April through July or August, and biweekly before 

and after this season. For each chemograph consisting of 30-35 samples, a 365-day 

profile was created by linear interpolation between any successive values that were not 

taken daily. For purposes of this preliminary exercise, these profiles served as the 

“true” chemographs for each site, against which those deriving from alternative 

sampling strategies were compared.11 For each of the “true” chemographs, the mean 

and upper percentiles (90th, 95th, 99th, 99.7th, and 99.9th) were recorded. 

From the true chemographs a number of different sampling strategies were set 

up to sample from the augmented data sets on the following schedules: 

Seasonal daily (D1s)—daily from April through August; biweekly before and after 

Every other day (2d) 

Every third day (3d) 

Every 4th day (4d) 

Weekly seasonal (W1s)—weekly from April through August; biweekly before and after 

 

11 The Agency notes that using derived chemographs that smooth out the day-to-day variations is less 

desirable than chemographs such as some of the Heidelberg dataset which have more frequent sampling 

that better reflects actual day-to-day variations in exposure. 
Page 70 of 263 

Weekly annual (W1a) 

Every ten days (10d) 

Biweekly (M2a) 

Monthly (M) 

Every 45 and 60 days 

Quarterly (Q) 

Chemographs were resampled with replacement on the above schedules 

following a random start, with over 4,500 simulations run for each schedule. Each 

resample was augmented to 365 days by linear interpolation and the mean and upper 

percentile values were recorded for each. The simulations were aggregated for each 

CWS and mean values for each percentile concentration were presented by sampling 

strategy and compared with those for the “true.” Results for the daily peaks are 

presented below for several example chemographs and a subset of the sampling 

strategies. 

Table 7 shows that for yearly profiles with 365 daily values it was possible to 

obtain estimates up to the 99.7th %ile for each sampling strategy. For CWS #22, 

sampling every 4 days returned estimates of the 99.7th %ile single day values that 

averaged around -12% of true, while those for the 99th %ile underestimated the true by 

about 7%. It was possible to estimate the 95th %ile of the single day peaks with good 

accuracy (+1.08%), as well as the 90th and 50th percentiles and the mean (0.31%). 

Estimates for the weekly and biweekly sampling followed a similar pattern, but with 

accuracy for the given percentiles that ranged from -21% to +8% for weekly and -42% to 

+35% for biweekly sampling. Similar to the ILSI findings, the accuracy of the percentile 

estimates fluctuated somewhat within each sampling set. The precision of the 

estimates followed an expected pattern, however, with good precision at the mean and 

wider intervals for the highest estimates. 

Table 7 presents estimates for two other CWS whose results show increasing 

accuracy that is likely related to their shape, as discussed in the next section below. 

Results for CWS #8 ranged from -5-6% to +8% for the given percentiles for sampling 

every 4 days, and estimated both mean and median with virtually no error for both 4-day 

and weekly sampling. For CWS #24, accuracy was good at both the upper percentiles 

and the mean. Figures 7 (a-c) show the chemograph profiles. 

Crawford (2004) reported disparity in comparisons between true values and 

estimates derived from sampling at the 99th%ile, although for larger rivers he could 

achieve estimates within approximately 50% of the “true.” Performance for the smaller 

streams was not good at that level, but was generally acceptable for the 90th and 95th 

percentiles. 
Page 71 of 263 

Table 7: Upper Percentile Values Derived from Different Sampling Strategies for 3 

Example CWS 

Mean median 90th %ile 95th %ile 99th %ile

99.7th

%ile

Peak/

maximum

CWS #22

True Chemograph (daily)

Concentration, ppb 2.718 0.306 8.293 12.368 46.806 57.34 57.98

Sampling every 4 days  

(mean) Estimate 2.73 0.32 8.51 12.50 43.64 50.47   

(% error) 0.31 3.03 2.67 1.08  ‐6.77  ‐11.97   

(95%CI)

(2.61‐

2.83)

(0.316‐

0.316)

(8.20‐

8.90)

(11.56‐

13.43)

(37.81‐

46.85)

(41.91‐

57.35)

Sampling every 7 days

(mean) Estimate 2.72 0.32 8.95 12.48 38.95 45.05   

(% error) 0.21 3.92 7.98 0.92  ‐16.78  ‐21.42   

(95%CI)

(2.49‐

2.93)

(0.31‐

0.33)

(8.06‐

9.92)

(11.07‐

14.12)

(29.85‐

47.73)

(32.38‐

57.42)

Sampling every 2 weeks

(mean) Estimate 2.72 0.34 9.00 16.71 30.52 33.35   

(% error) 0.19 10.29 8.49 35.10  ‐34.79  ‐41.84   

(95%CI)

(1.96‐

3.51)

(0.31‐

0.37)

(6.67‐

11.92)

(11.60‐

24.21)

(12.70‐

51.90)

(12.79‐

57.63)

CWS #8

True Chemograph (daily)

Concentration, ppb 3.315 0.660 6.622 25.541 40.755 44.76 44.92

Sampling every 4 days  

(mean) Estimate 3.31 0.66 7.14 25.45 39.37 42.27   

(% error)  ‐0.01 0.00 7.79  ‐0.36  ‐3.40  ‐5.57   

(95%CI)

(3.245‐

3.38)

(0.66‐

0.66)

(6.595‐

8.458)

(24.77‐

25.54)

(37.35‐

40.75)

(38.57‐

44.76)

Sampling every 7 days

(mean) Estimate 3.31 0.66 7.94 25.15 37.74 40.41   

(% error)  ‐0.02 0.00 19.83  ‐1.51  ‐7.39  ‐9.72   

(95%CI)

(3.18‐

3.44)

(0.66‐

0.66)

(6.25‐

9.81)

(23.66‐

25.96)

(33.71‐

40.91)

(35.45‐

44.77)

Sampling every 2 weeks

(mean) Estimate 3.31 0.69 9.60 23.99 34.25 36.33   

(% error)  ‐0.08 3.98 44.96  ‐6.06  ‐15.97  ‐18.83   

(95%CI)

(2.79‐

3.83)

(0.66‐

0.74)

(5.05‐

13.05)

(19.56‐

28.47)

(28.04‐

41.91)

(28.53‐

44.79)
Page 72 of 263 

Mean median 90th %ile 95th %ile 99th %ile

99.7th

%ile

Peak/

maximum

CWS #24

True Chemograph (daily)

Concentration, ppb 1.613 0.864 3.769 5.279 6.169 6.34 6.35

Sampling every 4 days  

(mean) Estimate 1.62 0.93 3.77 5.05 6.11 6.22   

(% error) 0.28 7.20 0.08  ‐4.28  ‐1.01  ‐1.84   

(95%CI)

(1.60‐

1.63)

(0.88‐

1.04)

(3.58‐

3.95) (4.71‐5.29)

(6.00‐

6.17)

(6.06‐

6.34)

Sampling every 7 days

(mean) Estimate 1.62 0.99 3.80 4.88 6.00 6.13   

(% error): 0.26 14.21 0.88  ‐7.61  ‐2.73  ‐3.29   

(95%CI)

(1.59‐

1.65)

(0.85‐

1.08)

(3.37‐

4.13) (4.57‐5.29)

(5.84‐

6.17)

(5.88‐

6.34)

Sampling every 2 weeks

(mean) Estimate 1.62 1.04 3.80 4.70 5.70 5.93   

(% error): 0.29 20.19 0.94  ‐10.92  ‐7.54  ‐6.54   

(95%CI)

(1.45‐

1.79)

(0.88‐

1.13)

(2.92‐

4.81) (4.16‐5.37)

(5.33‐

5.99)

(5.36‐

6.33)
Page 73 of 263 

Figure 7: (a-c) Profiles for Chemographs #22, #8, and #24 

(a) Chemograph for CWS #22 

CWS #22 Illinois, 2005

0

10

20

30

40

50

60

70

1/1 1/31 3/2 4/1 5/1 5/31 6/30 7/30 8/29 9/28 10/28 11/27 12/27

Date

Atrazine (TCT), ug/L

(b) Chemograph for CWS #8 

CWS #8 Illinois, 2008

0

5

10

15

20

25

30

35

40

45

50

1/1 1/31 3/1 3/31 4/30 5/30 6/29 7/29 8/28 9/27 10/27 11/26 12/26

Date

Atrazine (TCT), ug/L
Page 74 of 263 

(c) Chemograph for CWS #24 

CWS #24 Illinois, 2005

0

1

2

3

4

5

6

7

1/1 1/31 3/2 4/1 5/1 5/31 6/30 7/30 8/29 9/28 10/28 11/27 12/27

Date

Atrazine (TCT), ug/L

5.5.3.2. Examining the Ranges of Maximum Running Averages 

of Different Durations for Various Sampling Strategies 

In the process of determining exposure estimates from drinking water for the 

purpose of assessing risk to human populations, USEPA derives the maximum 

measured concentration from monitored data to estimate potential “maximum” exposure 

for different durations of interest (e.g., single day peak, maximum 3-day average, 

maximum 7-day average, maximum 90-day average) for a given system by year. With 

the above method, it was not possible to estimate the very highest percentile values in 

the year of a given system with great accuracy and precision, if at all. Data presented 

above for the AMP program show a large difference among values in the upper 

percentile range for systems with the highest peaks, even between 99.5th %ile and 

maximum values. Because of these limitations in estimating highest percentile values 

and because the sample maximum value is the concentration typically derived for each 

duration of interest and used in OPP risk assessments, an alternative method was 

employed to assess the performance of different sampling schemes in capturing the 

“true” chemograph maximum. . 

The alternative method that follows begins similarly to the method discussed 

above. In the examples below, for each chemograph consisting of roughly 30-35 

samples, a 365-day profile again was created by linear interpolation between any 

successive values that were not taken daily. These profiles served as the “true” 

chemographs for each site, against which those deriving from alternative sampling 
Page 75 of 263 

strategies were compared. For each of the “true” chemographs, the following ‘running’ 

averages were derived, and the maximum of each of those averages was recorded: 

Single day peak 

2-day average 

3-day average 

4-day average 

7-day average 

14-day average 

21-day average 

28-day, 60-day, 90-day, 180-day, and 

Annual average 

At the same time a number of different sampling strategies described below were 

simulated from the raw data sets on the following schedules: 

Seasonal daily (D1s—daily from April through August; biweekly before and after) 

Every other day (2d) 

Every third day (3d) 

Every 4th day (4d) 

Weekly seasonal (W1s)—weekly from April through August; biweekly before and after 

Weekly annual (W1a) 

Every ten days (10d) 

Biweekly (M2a) 

Monthly (M) 

Every 45 and 60 days 

Quarterly (Q) 

 

Sampling according to the above schedules was carried out with replacement 

after a random start, and each resample was augmented to 365 daily values by linear 

interpolation. A total of over 4,500 simulations were run for each sampling scheme, and 

the maximum single day peak, maximum 2-day average, maximum 3-day average, etc. 

were recorded for each run. 

For every sampling strategy the range and summary percentiles of the 

distributions of maximum averages for each duration period were compiled. For 

example, for sampling every 4 days, the distribution of maximum 3-day averages, the 

distribution of maximum 7-day averages, and the distribution of maximum 14-day, etc., 

averages were compiled. In addition, the percentile of the “true” maximum average for 

each sampling scheme and duration was recorded within these results. The Tables 

below illustrate. 
Page 76 of 263 

5.5.3.3 Results

As illustrated in the tables that follow, sampling according to a schedule that is 

less than daily makes it possible both to overestimate as well as to underestimate the 

true average of interest that is derived from daily sampling. As would be expected, with 

more frequent sampling and linear interpolation between sampling points, both the 

percentage of simulations underestimating the “true” average of interest as well as the 

magnitude of the underestimation is less than for strategies employing less frequent 

sampling. Additionally, for averages of longer duration, the amount of underestimation 

is generally less than for those of shorter duration, so that, for example, the maximum 7-

day average concentration is underestimated less often and by a lower amount than the 

maximum 3-day average or the maximum single day peak. 

For longer term averages, in fact, the amount by which the maximum average of 

interest may be overestimated increased as the average and the sampling interval 

began to increase. Since the overestimation was not great, however, in this exercise 

attention was directed to the lower range of the realizations to characterize how often a 

given maximum average might be underestimated and by how much. 

For the CWS that were run using this methodology and the 10 CWS profiles 

presented in this paper, some general patterns began to emerge, where performance in 

capturing peaks of interest appeared to correspond to the general shapes of the 

chemographs assessed. 

Chemograph examples: Single narrow peaks 

CWS #4 in 2008 is typical of a group of chemographs that show one high and 

narrow peak that is detected in a given week and appears to decline substantially by the 

following week. The maximum daily peak of 72.99 is preceded by a concentration of 

0.38 ppb measured the week before, and followed by a concentration of 10.70 ppb 

measured 7 days later. 
Page 77 of 263 

CWS #4 Ohio, 2008

0

10

20

30

40

50

60

70

80

1/15 2/15 3/15 4/15 5/15 6/15 7/15 8/15 9/15 10/15 11/15

Date

Atrazine (TCT), ug/L

Figure 8: Illustration of a CWS chemograph with a single, relatively short 

duration (narrow) peak 

Single Daily Peaks

When the chemograph shown in Figure 8 was sampled every 4 days, the 

maximum daily value of 72.99 ppb was captured about 26% of the time. The mean of 

the simulations gave a maximum value of 63.21, which underestimated the “true” 

maximum by a little over 13%. The lowest 1% of the resamples was 37% lower than 

the true maximum concentration (Table 8). 

Weekly sampling was less accurate, capturing the true maximum over 14% of 

the time, and underestimating it by about 23% on average and over 56% at the low end 

of the range. Biweekly sampling captured the true max about 7% of the time and 

underestimated the daily peak by about 46% on average and about 86% on the low 

end. 
Page 78 of 263 

Table 8: Percentiles of Maximum Concentrations for CWS #4 Sampled at 4-, 7-, or 

14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th% 

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

4 72.99 63.21 46.33 52.24 52.24 62.62 72.99 72.99 25.58 

% error -13.40 -36.52 -28.42 -28.42 -14.21 0.00 0.00 

Sampling every 7 Days 

4 72.99 56.04 31.50 37.45 41.87 55.22 72.99 72.99 14.50 

% error -23.22 -56.85 -48.70 -42.63 -24.35 0.00 0.00 

Sampling every 2 Weeks 

4 72.99 39.63 10.38 10.75 10.79 37.45 64.10 72.99 7.19 

% error -45.70 -85.79 -85.27 -85.22 -48.70 -12.17 0.00 

As may be apparent, the right hand column representing the percentage of time 

that the sample max is captured is close to expected for the three different sampling 

schemes, which would be about 25% of the time for sampling every 4 days, 14% for 

sampling every 7 days, and 7% for sampling every 14 days. For average durations of 

greater than 1 day, however, the numeric solution is more complicated. Presenting the 

range of outcomes from the simulations in this manner provides a straightforward 

illustration of results as obtained from a large number of sampling realizations 

performed according to the specified strategies for the different durations of interest. In 

general, for averages approximating acute exposures, the sampling results were more 

accurate (with less underestimation) as the average duration of interest increased. For 

durations of longer term, however, it was increasingly possible to overestimate the true 

maximum when less than daily sampling was employed. 

3-Day Averages

For 4-day sampling intervals, the maximum 3-day average was captured (or 

exceeded) about 26% of the time. The true maximum was underestimated by about 

11% half the time, and about 32% for the lowest realizations. With weekly sampling the 

3-day maximum average was captured or exceeded over 14% of the time and 

underestimated by about 22%, on average, and over 53% for the lowest runs. 

Sampling every 2 weeks captured or exceeded the maximum average about 7% of the 

time, underestimating it by about 46% in half the runs and about 86% for the lowest 

runs (Table 9). 
Page 79 of 263 

Table 9: Percentiles of Maximum 3-Day Average Concentrations for CWS #4 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

4 66.57 59.12 45.59 51.06 51.06 58.97 66.57 66.57 25.58 

% error -11.19 -31.52 -23.30 -23.30 -11.42 0.0 0.0 

Sampling every 7 Days 

4 66.57 52.32 31.17 36.70 40.21 51.44 66.57 67.36 14.50 

% error -21.41 -53.17 -44.87 -39.60 -22.73 0.0 1.18 

Sampling every 2 Weeks 

4 66.57 37.96 10.08 10.48 10.70 35.96 61.26 69.93 7.19 

% error -42.98 -84.85 -84.26 -83.93 -45.99 -7.98 5.05 
Page 80 of 263 

7-Day Averages

For 7-day averages, sampling every 4 days returned a maximum average that 

captured or exceeded the true max nearly 10% of the time (Table 10). The true 

maximum was underestimated by about 7% in half the runs, while the lowest maximum 

7-day averages underestimated the true by about 22%. Sampling every 7 days and 

every 14 days returned maximum 7-day averages that were about 18% lower than the 

true and 38% lower than the true, on average, respectively, and underestimated in the 

lowest runs by 83% for biweekly sampling. The highest runs overestimated the true 7-

day maximum by small amounts for sampling every 4 days and every 7 days, but by 

over 15% for sampling every 2 weeks. 

Table 10: Percentiles of Maximum 7-Day Average Concentrations for CWS #4 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value Mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

4 56.48 52.33 44.10 45.76 48.23 52.36 56.48 56.73 9.53 

% error -7.35 -21.92 -18.98 -14.61 -7.31 0.0 0.44 

Sampling every 7 Days 

4 56.48 46.61 30.52 35.28 37.46 46.15 56.48 58.54 11.03 

% error -17.47 -45.97 -37.55 -33.67 -18.29 0.0 3.64 

Sampling every 2 Weeks 

4 56.48 35.37 9.67 10.05 10.59 33.61 56.78 65.13 12.79 

% error -37.38 -82.87 -82.21 -81.24 -40.49 0.52 15.31 

In sum, for this chemograph with short-duration peaks, sample runs could 

underestimate true values by as much as 80-90% in the lowest runs for sampling every 

2 weeks, but could be just 7-14% lower than true, on average, for sampling every 4 

days, depending on the duration of interest. 
Page 81 of 263 

Moderate width peaks 

Results for a peak of slightly wider shape showed accuracy in the estimates that 

was higher and an amount of underestimation that was less than that for the narrower 

peak above, regardless of peak height. CWS #21 is a system that is typical of a class 

with one slightly wide peak that builds up and then declines over the course of several 

weeks (Figure 9). 

CWS #21 Ohio, 2005

0

5

10

15

20

25

30

35

1/5 2/5 3/5 4/5 5/5 6/5 7/5 8/5 9/5 10/5 11/5 12/5

Date

Atrazine (TCT), ug/L

Figure 9: Illustration of a CWS chemograph with a moderate duration peak and 

extended tail 
Page 82 of 263 

Single Day Peaks

For single daily peaks, 4-day sampling intervals returned a maximum value for 

CWS #21 that was just over 4% less than the true, on average, while the lowest runs 

underestimated by just over 11% (Table 11). For weekly sampling the maximum was 

underestimated by about 8% on average, and just over 17% for the lowest runs. 

Sampling every 2 weeks returned single day maximums that were less than the true by 

about 14-15%, for the average and median of the runs, and 27%, at the low end. 

Table 11: Percentiles of Maximum Daily Concentrations for CWS #21 Sampled at 

4-, 7-, or 14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

21 31.25 29.88 27.68 28.54 28.54 29.46 31.25 31.25 25.43 

% error -4.40 -11.43 -8.68 -8.68 -5.71 0.00 0.00 

Sampling every 7 Days 

21 31.25 28.89 25.82 25.89 26.79 28.57 31.25 31.25 14.09 

% error -7.56 -17.37 -17.14 -14.29 -8.57 0.00 0.00 

Sampling every 2 Weeks 

21 31.25 26.70 22.69 23.11 23.26 26.79 30.36 31.25 7.49 

% error -14.55 -27.41 -26.05 -25.55 -14.29 -2.86 0.00 
Page 83 of 263 

3-Day Averages

Looking at the range of maximum 3-day averages from all resamples for CWS 

#21, the maximum average returned by the mean and the median of the runs is 3-4% 

less than the true maximum for sampling every 4 days, while the lowest 1% of the 

simulations underestimate the “true” maximum by just under 10% (Table 12). 

For weekly sampling, the true 3-day maximum average was underestimated by 

6-7%, on average, and about 14% for biweekly sampling. The maximum 3-day average 

was captured (or exceeded) at least 25% of the time with sampling every 4 days, about 

14% of the time with weekly sampling, and nearly 7% for sampling every 2 weeks. The 

amount by which the true was overestimated in all of these runs is less than 1%. 

Table 12: Percentiles of Maximum 3-Day Average Concentrations for CWS #21 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value Mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

21 30.36 29.24 27.37 28.09 28.24 29.15 30.36 30.36 25.43 

% error -3.67 -9.84 -7.47 -6.96 -3.96 0.0 0.0 

Sampling every 7 Days 

21 30.36 28.29 25.58 25.58 26.41 28.16 30.36 30.43 14.09 

% error -6.80 -15.72 -14.73 -12.99 -7.24 0.0 0.23 

Sampling every 2 Weeks 

21 30.36 26.05 22.37 22.89 23.06 25.84 29.50 30.51 6.87 

% error -14.18 -26.30 -24.59 -24.04 -14.87 -2.82 0.52 

7-Day Averages

For 7-day averages, sampling every 4 days returned maximum averages that 

approximated the true maximum fairly closely a large percentage of the time (Table 13). 

That value was equaled or exceeded over 15% of the time, with runs that ranged from 

about 7% less than true to less than 1% higher in the highest runs. 

Weekly and biweekly sampling underestimated the true maximum by about 5% 

and 13-14%, respectively, on average, and ranged from -13% and -25% to about 1.5% 

higher for both. 
Page 84 of 263 

Table 13: Percentiles of Maximum 7-Day Average Concentrations for CWS #21 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value Mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

21 28.95 28.24 26.89 27.40 27.54 28.23 28.95 28.99 15.50 

% error -2.43 -7.12 -5.43 -4.86 -2.48 0.0 0.16 

Sampling every 7 Days 

21 28.95 27.38 25.18 25.84 25.87 27.40 28.95 29.10 11.44 

% error -5.41 -13.01 -10.75 -10.65 -5.34 0.0 0.52 

Sampling every 2 Weeks 

21 28.95 25.06 21.79 22.24 22.65 24.91 28.30 29.40 6.87 

% error -13.42 -24.74 -23.19 -21.76 -13.96 -2.25 1.57 

In sum, for this profile, accuracy for sampling every 4 days ranged from -7% to -11% for 

the lowest runs (-2.4% to -4.4% on average) and approximated the max almost perfectly 

for the highest runs. Sampling every 7 days ranged from -13% to -17% at the low end 

to +0.52% at the high end. Biweekly sampling gave estimates of the “true” that ranged 

from -27% among the lowest to +1.6%, with middle runs underestimating the true by 

about 13-15%. 
Page 85 of 263 

Broad or extended peaks 

A third category of chemographs containing one broad or several continuing 

peaks is represented by CWS #30 (Figure 10). 

CWS #30 Missouri, 2005

0

5

10

15

20

25

1/20 2/20 3/20 4/20 5/20 6/20 7/20 8/20 9/20 10/20 11/20 12/20

Date

Atrazine (TCT), ug/L

Figure 10: Illustration of a Chemograph with a Broad or Extended Series of Peaks 

Results for this CWS showed the most accuracy of the groups for estimating 

maximum averages, starting with values for single daily peaks that averaged from just 

under 3% below true for sampling every 4 days to just over 8% less than true for 

sampling every 2 weeks. At the lowest range the true sample max was underestimated 

by 7-8% for sampling every 4 days to just over 16% for sampling every 2 weeks. The 

highest runs captured the true max with no error and did so 25% of the time. 
Page 86 of 263 

Single Day Peaks

Table 14: Percentiles of Maximum Daily Concentrations for CWS #30 Sampled at 

4-, 7-, or 14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

30 23.01 22.39 21.25 21.64 21.72 22.36 23.01 23.01 25.23 

% error -2.71 -7.65 -5.95 -5.62 -2.81 0.00 0.00 

Sampling every 7 Days 

30 23.01 21.93 20.47 20.86 21.07 22.03 23.01 23.01 14.59 

% error -4.71 -11.04 -9.34 -8.43 -4.26 0.00 0.00 

Sampling every 2 Weeks 

30 23.01 21.12 19.22 19.69 19.78 21.07 22.42 23.01 6.96 

% error -8.22 -16.46 -14.43 -14.05 -8.43 -2.56 0.00 

3-Day Averages

3-day averages showed a tighter range, with % differences from true values 

ranging from -2% to 0% error for 3-day averages sampled every 4 days. Weekly 

sampling gave returns that, on the low end, underestimated the max 3-day average by a 

little over 9%, and biweekly sampling by just under 15%, but averaged -4% to -6.5%. 

The highest runs exceeded the max by just over 2% for sampling every 2 weeks. 
Page 87 of 263 

Table 15: Percentiles of Maximum 3-Day Average Concentrations for CWS #30 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

30 22.49 22.02 21.17 21.45 21.59 22.02 22.49 22.49 25.23 

% error -2.09 -5.89 -4.64 -4.03 -2.11 0.0 0.0 

Sampling every 7 Days 

30 22.49 21.57 20.40 20.73 20.84 21.60 22.47 22.62 6.94 

% error -4.10 -9.28 -7.83 -7.32 -3.96 -0.11 0.57 

Sampling every 2 Weeks 

30 22.49 21.04 19.14 19.61 19.73 20.92 22.40 22.97 6.96 

% error -6.47 -14.90 -12.80 -12.26 -6.99 -0.43 2.12 

7-Day Averages

For 7-day averages the maximum was underestimated less often and by even 

smaller amounts, but overestimated more frequently and by a slightly higher amount. 

The lowest runs were less than the true 7-day max by 3% for sampling every 4 days to 

nearly 12% for sampling every 2 weeks. On average the simulations ran from -1% to -

3.7% for the different sampling periods, while the highest runs overestimated the true 

max average by up to 5.5%. 
Page 88 of 263 

Table 16: Percentiles of Maximum 7-Day Average Concentrations for CWS #30 

Sampled at 4-, 7-, or 14-day Intervals

CWS True 

Value mean 1st% 5th% 10th% 50th% 90th% 99.9th%

% of 

sample 

max 

avgs >

true 

Sampling every 4 Days

30 21.7 21.44 21.01 21.16 21.22 21.47 21.70 21.72 10.53 

% error -1.17 -3.16 -2.46 -2.18 -1.03 0.0 0.10 

Sampling every 7 Days 

30 21.7 21.06 20.27 20.42 20.54 21.07 21.61 22.01 8.19 

% error -2.93 -6.56 -5.88 -5.34 -2.89 -0.39 1.43 

Sampling every 2 Weeks 

30 21.7 20.89 19.13 19.49 19.64 20.73 22.35 22.88 24.14 

% error -3.70 -11.84 -10.18 -9.46 -4.45 3.00 5.47 

Summary Tables 

 

Results for the above systems were run with those from others that fell into a 

similar chemograph grouping that included 10 CWS in total and three categories of 

chemograph shape. The selection of chemographs was made from among those that 

included many with the highest peaks, in addition to several that appeared to represent 

typical chemographs containing consistently lower values for the year. Summaries 

were made of the % differences from true values and are presented in the tables that 

follow. 

The results show some consistencies among the groups in this small set of 

CWS. For more defined results a much larger number of chemographs would need to 

be run, and results for that group might still be better characterized as being descriptive 

of that set rather than definitively predictive of monitoring profiles to come. In general, 

however, some broad patterns seen over seven years of monitoring may be helpful in 

deciding on ways to proceed for groups of systems that have shown some consistency 

in monitoring values over years in the program. 

Table 17 below shows summary values and average % differences from “true” 

values for maximum 3-day averages derived from sampling every 4 days for the 10 

CWS. The CWS are summarized into three groups corresponding to the chemograph 

shapes described above. 

 
Page 89 of 263 

Table 17: Maximum 3-Day Average Concentrations for All CWS Sampled at 4-day 

Intervals 

CWS True Value mean 1st% 5th% 10th% 50th% 90th% 99.9th% 

% of sample 

maximum 

running 

averages >

true value 

4 66.57 59.12 45.59 51.06 51.06 58.97 66.57 66.57 25.58 

% error -11.19 -31.52 -23.30 -23.30 -11.42 0.00 0.00 

14 5.28 4.93 4.33 4.44 4.44 4.95 5.28 5.28 26.40 

% error -6.75 -18.02 -16.03 -16.03 -6.32 0.00 0.00 

17 209.50 190.50 159.60 165.60 165.60 192.20 209.50 209.50 0.00* 

% error -9.05 -23.81 -20.93 -20.93 -8.24 0.00* 0.00* 

22 53.20 47.75 38.05 41.42 41.42 47.78 53.20 53.20 9.03 

% error -10.25 -28.48 -22.14 -22.14 -10.20 0.00 0.00 

average % error -9.31 -25.46 -20.60 -20.60 -9.04 0.00 0.00 

8 43.36 41.13 37.79 38.65 38.65 40.91 43.36 43.36 18.65 

% error -5.15 -12.84 -10.87 -10.87 -5.64 0.00 0.00 

20 28.69 27.98 26.75 27.16 27.16 27.99 28.69 28.69 18.25 

% error -2.45 -6.75 -5.31 -5.31 -2.41 0.00 0.00 

21 30.36 29.24 27.37 28.09 28.24 29.15 30.36 30.36 25.43 

% error -3.67 -9.84 -7.47 -6.96 -3.96 0.00 0.00 

average % error -3.76 -9.81 -7.88 -7.71 -4.00 0.00 0.00 

13 5.36 5.32 5.25 5.28 5.28 5.32 5.36 5.36 24.88 

% error -0.72 -2.14 -1.59 -1.59 -0.74 0.00 0.00 

24 6.26 6.18 6.01 6.06 6.06 6.18 6.26 6.26 26.03 

% error -1.41 -4.00 -3.29 -3.29 -1.28 0.00 0.00 

30 22.49 22.02 21.17 21.45 21.59 22.02 22.49 22.49 25.23 

% error -2.09 -5.89 -4.64 -4.03 -2.11 0.00 0.00 

average % error -1.40 -4.01 -3.17 -2.97 -1.37 0.00 0.00 

* Realizations fail to equal true max by <0.001%; disparities due to rounding 

The table shows that best results were achieved for the third group containing 

broad peak(s) so that, on average, sample runs for the CWS in this group approximated 

their true [max.] 3-day averages to within a 1-2% difference. Lowest runs averaged a 

little over 4% less than the true and highest runs all captured the maximum average 

with no error. 

The first group of CWS was characterized by single narrow peaks and included 

CWS #17, which had the highest peak concentration (227 ppb) across systems and 

years of the program. This group also contained CWS #14, whose maximum 

concentration was 5.6 ppb, which rapidly declined by the following week. Accuracy for 
Page 90 of 263 

every CWS in this group of similarly shaped chemographs appeared to be comparable 

to that of the others in the group, regardless of peak height. The means of the 

resamples in this group gave 3-day maximums that averaged approximately 9% lower 

than their true values. Lowest runs underestimated true values by an average of about 

25%, while highest runs captured the true with essentially no error. 

Summary results are also presented below for single day peak concentrations 

derived from sampling every 7 days. 

Table 18: Single Day Concentrations for All CWS Sampled at 7-day Intervals 

CWS True Value mean 1st% 5th% 10th% 50th% 90th% 99.9th% 

% of sample 

maximum 

[peaks] > true 

value 

4 72.99 56.04 31.50 37.45 41.87 55.22 72.99 72.99 14.50 

% error -23.22 -56.85 -48.70 -42.63 -24.35 0.00 0.00 

14 5.62 4.78 3.67 3.77 4.06 4.84 5.62 5.62 14.50 

% error -14.99 -34.70 -32.92 -27.76 -13.88 0.00 0.00 

17 227 183.10 126.10 129.90 146.30 186.60 227.00 227.00 14.46 

% error -19.32 -44.44 -42.77 -35.55 -17.78 0.00 0.00 

22 57.98 45.48 26.16 32.46 34.11 45.22 57.98 57.98 14.46 

% error -21.56 -54.89 -44.02 -41.16 -22.01 0.00 0.00 

average % error -19.77 -47.72 -42.10 -36.78 -19.50 0.00 0.00 

8 44.92 40.54 34.00 35.56 37.12 40.24 44.92 44.92 14.49 

% error -9.75 -24.31 -20.84 -17.36 -10.42 0.00 0.00 

20 29.3 27.71 26.04 26.04 26.21 27.67 29.30 29.30 14.70 

% error -5.43 -11.13 -11.13 -10.55 -5.56 0.00 0.00 

21 31.25 28.89 25.82 25.89 26.79 28.57 31.25 31.25 14.09 

% error -7.56 -17.37 -17.14 -14.29 -8.57 0.00 0.00 

average % error -7.58 -17.60 -16.37 -14.07 -8.18 0.00 0.00 

13 5.4 5.31 5.18 5.21 5.24 5.32 5.40 5.40 14.03 

% error -1.68 -4.17 -3.47 -3.02 -1.51 0.00 0.00 

24 6.35 6.14 5.86 5.88 5.97 6.16 6.35 6.35 14.09 

% error -3.34 -7.76 -7.42 -5.94 -2.97 0.00 0.00 

30 23.01 21.93 20.47 20.86 21.07 22.03 23.01 23.01 14.59 

% error -4.71 -11.04 -9.34 -8.43 -4.26 0.00 0.00 

average % error -3.24 -7.66 -6.75 -5.80 -2.91 0.00 0.00 

 

Results for single day maximum concentrations again show a consistency among 

groups of similarly shaped chemographs, with most accuracy once again being 

demonstrated for the group of broad, extended peak(s). In mean runs this group 

returned sample maximums that averaged just over 3% less than true values and were 
Page 91 of 263 

7-8% less for the lowest runs. The true chemograph max was captured with no error 

and in over 14% of the simulations. 

Group 1 showed less accuracy for capturing single day maximum values with 

weekly sampling. Once again, the chemograph max was captured in over 14% of 

resamples, with the lowest runs averaging 48% less than the true max and the mean 

and median runs averaging about 20% less. 

Demonstrating the efficiencies gained by targeted sampling (in time), Table 19 

shows results for maximum 3-day averages derived from sampling taken every day 

during the season of use and biweekly for the remainder of the year. 

 

Table 19: Maximum 3-Day Averages for All CWS Sampling Every Day (April thru 

August); Every 14 Days (balance of year) 

CWS True Value mean 1st% 5th% 10th% 50th% 90th% 99.9th% 

% of sample 

maximum 

running 

averages >

true value 

4 66.57 64.81 60.15 60.15 60.15 66.57 66.57 66.57 60.30 

% error -2.64 -9.64 -9.64 -9.64 0.00 0.00 0.00 

14 5.28 5.20 4.95 4.95 5.01 5.28 5.28 5.28 60.31 

% error -1.65 -6.35 -6.35 -5.26 0.00 0.00 0.00 

17 209.50 204.90 192.00 192.00 195.10 209.50 209.50 209.50 32.06 

% error -2.17 -8.36 -8.36 -6.84 0.00 0.00 0.00 

22 53.20 51.90 48.42 48.42 48.42 53.20 53.20 53.20 60.25 

% error -2.45 -8.98 -8.98 -8.98 0.00 0.00 0.00 

average % error -2.23 -8.33 -8.33 -7.68 0.00 0.00 0.00 

8 43.36 42.74 40.91 40.91 41.80 43.36 43.36 43.36 61.40 

% error -1.42 -5.64 -5.64 -3.60 0.00 0.00 0.00 

20 28.69 28.51 28.07 28.07 28.08 28.69 28.69 28.69 59.09 

% error -0.60 -2.14 -2.14 -2.13 0.00 0.00 0.00 

21 30.36 30.06 29.15 29.15 29.56 30.36 30.36 30.36 44.05 

% error -0.97 -3.96 -3.96 -2.64 0.00 0.00 0.00 

average % error -1.00 -3.92 -3.92 -2.79 0.00 0.00 0.00 

13 5.36 5.35 5.32 5.32 5.34 5.36 5.36 5.36 62.01 

% error -0.18 -0.74 -0.74 -0.49 0.00 0.00 0.00 

24 6.26 6.24 6.18 6.18 6.20 6.26 6.26 6.26 60.31 

% error -0.35 -1.38 -1.38 -1.05 0.00 0.00 0.00 

30 22.49 22.35 21.97 22.02 22.03 22.49 22.49 22.49 60.13 

% error -0.61 -2.31 -2.11 -2.05 0.00 0.00 0.00 

average % error -0.38 -1.47 -1.41 -1.20 0.00 0.00 0.00 
Page 92 of 263 

As might be expected, results for this sampling design show the most accuracy 

across all groups, with mean runs ranging from -2% of true to less than 1% below true. 

Lowest runs are only a little over 8% below true values in the group of narrow peaks 

and only 1.5% below true for the “broad” group. At least 50% of the simulations showed 

no error for these CWS. 

Finally, summary results are presented for the group of systems for 90-day 

averages derived from sampling that was taken weekly during the ‘season’ of use and 

biweekly during the remainder of the year, a strategy that is similar to the one currently 

employed by the AMP. 

Table 20: 90-Day Averages for All CWS Sampling Every 7 Days (April thru 

August); Every 14 Days (balance of year) 

CWS True Value mean 1st% 5th% 10th% 50th% 90th% 99.9th% 

% of sample 

maximum 

running 

averages >

true value 

4 9.35 9.34 7.89 8.20 8.56 9.35 10.12 10.84 50.30 

% error -0.10 -15.67 -12.37 -8.47 0.02 8.26 15.90 

14 1.49 1.49 1.41 1.43 1.44 1.49 1.53 1.58 41.39 

% error -0.53 -5.86 -4.34 -3.51 -0.48 2.32 5.75 

17 25.99 25.98 22.28 23.03 23.87 26.05 28.06 29.77 52.33 

% error -0.05 -14.28 -11.39 -8.14 0.24 7.97 14.53 

22 9.93 9.90 8.85 9.08 9.29 9.92 10.50 11.06 49.39 

% error -0.25 -10.90 -8.52 -6.39 -0.08 5.78 11.35 

average % error -0.23 -11.68 -9.16 -6.63 -0.07 6.08 11.88 

8 11.53 11.45 10.86 10.99 11.11 11.45 11.79 12.09 39.22 

% error -0.71 -5.76 -4.63 -3.64 -0.72 2.24 4.86 

20 12.66 12.65 12.39 12.46 12.50 12.65 12.80 12.99 47.33 

% error -0.07 -2.14 -1.56 -1.24 -0.06 1.09 2.59 

21 7.93 7.92 7.62 7.70 7.75 7.92 8.08 8.26 44.74 

% error -0.24 -4.01 -2.96 -2.38 -0.20 1.80 4.13 

average % error -0.34 -3.97 -3.05 -2.42 -0.33 1.71 3.86 

13 2.55 2.53 2.46 2.48 2.49 2.53 2.56 2.61 18.77 

% error -1.00 -3.53 -2.84 -2.46 -0.98 0.43 2.19 

24 3.72 3.69 3.55 3.59 3.62 3.70 3.77 3.87 37.29 

% error -0.56 -4.31 -3.24 -2.64 -0.52 1.49 4.22 

30 17.41 17.37 17.08 17.16 17.20 17.37 17.54 17.75 38.84 

% error -0.21 -1.88 -1.42 -1.17 -0.21 0.76 1.97 

average % error -0.59 -3.24 -2.50 -2.09 -0.57 0.89 2.79 
Page 93 of 263 

Results for the 10 CWS summarized show estimates whose averages ranged 

from roughly -12% to +12% of “true” for the group with the most narrow peaks, and from 

-3-4% to +3-4% for the other two groups. An examination of the 5th %ile summaries for 

all groups indicates that 95% of the resamples by group gave estimates that were no 

more than 10% lower than true values (with better performance for most CWS), while 

50% were no more than 1% lower. 

Finally, there appeared to be more overestimation of true values among 

resamples for these longer term 90-day averages. In addition, preliminary simulations 

using a stair-step type of imputation procedure (not presented here) gave indications 

that that method may provide slightly higher estimates (more overestimation and less 

underestimation) than the linear interpolation method for these and for all averages. 

Summary tables are available for other sampling schemes and average durations 

of interest, but those above demonstrate patterns for several common sampling 

strategies as well as for durations that may be typical approximations of both acute and 

chronic exposure. 

5.5.4. Summary of Initial Analyses 

The above methods examined raw water by CWS annually, and give ranges and 

summaries that are applicable to the systems used in the exercise. Among this small 

set, however, some general patterns do emerge. Results of this exercise demonstrate 

that chemographs can be categorized according to shape and that sampling strategies 

perform differently according to those shape categories. Moreover, the exercise 

indicates that, to the extent that they can be predicted in advance, the width of the 

chemograph peaks, representing the period of their duration, may be more important 

than their height in finding a sampling scheme to capture maximum values. 

Results for this subset of 10 CWS also indicate that the current sampling strategy 

of weekly intervals during the period of highest use and anticipated runoff appears to be 

adequate for capturing maximum 90-day average concentrations with reasonable to 

good accuracy. More frequent sampling may be necessary, however, for averages of 

shorter duration and for single day concentrations, particularly for chemical profiles 

characterized by narrow, fast moving (i.e., short duration) peaks. 

The methods used above employed systematic sampling (as is often done in the 

field) from random start dates. The Agency did not combine years to create larger 

sample sizes, as OPP risk assessments create exposure profiles on a year-to-year 

basis. As a result, the dataset is necessarily more limited in range and in the inferences 

that can be made. Additionally, as mentioned before, the “true” profiles for each 

chemograph were created with interpolation procedures employed on samples that 

were originally collected on a weekly or biweekly basis, so that the actual pattern of 

intervening peaks is not known. It is likely that these interpolation procedures, which 
Page 94 of 263 

are used in common practice, may not always adequately mirror genuine variability in a 

true concentration profile that exists throughout the year. 

An additional outcome that may become apparent in a larger sample is that the 

amount of underestimation can sometimes be greater for a missed peak in the range of, 

say, 5 ppb, than for one at higher concentrations because the 5 ppb peak may drop to a 

level that is 5-fold lower in the week that follows. This disparity generally is less 

common for peaks in the higher concentrations, and/or for those that extend over the 

course of several weeks. 

General information from the AMP presented above showed that measurements 

for 92-96% of the samples each year were less than 3 ppb. No large scale analysis has 

been performed to examine chemograph shapes among the CWS represented by this 

large majority of program samples. Because the consequences of sampling that could 

miss peaks are greater when yearly profiles consist of samples in the higher 

concentration range, however, an examination of shape patterns in the CWS that have 

demonstrated higher concentrations in past monitoring may be beneficial. The subset 

of CWS showing peak concentration values >30 ppb, >20 ppb, and >12 ppb was 9, 14, 

and 27 CWS, respectively, in the highest years, with nearly complete nesting of the 

same CWS within these categories. The above analysis shows that it may be possible 

to arrange for more rigorous sampling schemes that can be applied to these subsets of 

CWS, if that is determined necessary. 

While the analysis above has merit for presenting some general patterns that 

appear to hold as sampling intervals and concentration durations increase or decrease, 

there is uncertainty associated both with the estimates and with generalizing from the 

particular set(s) of chemographs analyzed to those that might be expected in future 

years for the same and for other systems. In the first method above, nonparametric 

confidence intervals were calculated for the percentile estimates to show some measure 

of their precision. Because the samples were not taken strictly at random and because 

of the obvious serial correlation in the samples, however, there is likely to be some 

amount of bias in these estimates. 

In the second method the Agency presented ranges of the lower, middle, and 

upper simulations which, in many cases, gave a fairly narrow interval surrounding true 

values. These may also serve as the basis for discussing uncertainty bounds for future 

datasets. EPA seeks the Panel’s feedback regarding recommended approaches, 

feasibility and the utility of constructing intervals for future observations in combination 

with larger datasets and methods similar to those above. In addition, guidance is 

sought in general on characterizing uncertainty as well as on the utility of these 

approaches for designing future sampling plans for other potential endpoints of interest. 

In the following section of the paper, USEPA presents a modeling approach for 

characterizing atrazine occurrence and for examining the issue of sampling frequency. 
Page 95 of 263 

5.6. Artificial Neural Network (ANN) Modeling of Atrazine 

Occurrence Patterns 

This section of the paper describes one potential approach for occurrence modeling 

that USEPA’s Office of Water used to simulate the pattern of short-lived, high 

concentration peaks or “spikes,” and shows how these models can be used to assess 

how well candidate monitoring strategies satisfy quantitative performance criteria. This 

section illustrates one alternative approach for how the Agency might estimate exposure 

concentrations from monitoring data of varying sampling intervals As discussed in 

Section 5.7.1, USEPA plans a systematic evaluation of this and other methods 

described in Section 5.4.1. 

5.6.1 Time Series Plots Using Frequent Monitoring Data 

The Agency used monitoring data from the Heidelberg University’s National 

Center for Water Quality Research (NCWQR) file for large rivers for a preliminary 

evaluation of ANN modeling. 
Page 96 of 263 

Figure 11, displaying 2001 data from the Maumee River, illustrates that the ANN 

approach may not work well where concentrations change rapidly between events or 

where short-lived peaks occur outside of anticipated patterns. 

Figure 11: Data for Maumee River 2001 
Page 97 of 263 

Figure 12 is a plot of Maumee 1998 (one of the data sets used for ANN 

modeling) data, showing larger short-term day-to-day variability or “noise” (in log units). 

Based on this and other plots, it appears reasonable to treat 0.25 μg/L as a censoring 

limit. The natural log of 0.25 is about -1.4. This figure clearly shows two occurrence 

peaks. 

Figure 12: Data for Maumee River 1998 
Page 98 of 263 

5.6.2 Artificial Neural Network Modeling 

Artificial Neural Networks (ANNs) are often seen as magical “black boxes” that 

learn from data, and end up predicting how one or more “dependent variables” change 

in response to “independent variables.” Lee (2004) opens up the ANN black box, 

providing mathematical forms of ANN models and some real-world interpretations of the 

model parameters. The book goes on to describe parameter estimation in a Bayesian 

framework for multivariate regression, classification, and other applications. A detailed 

explanation of the ANN approach, including the equations that describe the modeling 

parameters, is beyond the scope of this paper, but more detail can be found in 

Appendix C. 

Figure 13 illustrates an attempt to fit the 1998 Maumee River data, plotted in log 

10 concentrations, using a single node. A second node with a decreasing effect will be 

needed to pull the ANN curve down after day 130 and a third node will be needed to 

explain the occurrence peak around day 166. 

Figure 13: Maumee 1998 and ANN Model with One Node 

0 100 200 300 400 − 5

0

5

10

The “best” ANN model for any one-year data set will be the model with fewest 

hidden nodes that does an adequate job of explaining the occurrence data. “Adequate” 

will be expressed in terms of log-likelihood. 

The ANN model describes the expected log-concentration, but clearly, the 

concentration on any given day will not be exactly that predicted by the model. Some 

amount of noise can be seen in all plots of occurrence data. We assume the difference 

between a day’s measured log-concentration and that given by the underlying model 

will be normal with mean zero and some variance that we can estimate using the model 

and the data. We assume the variance is constant. A day’s log-concentration is 

regarded as a normal random variable with mean equal to the model prediction and, for 
Page 99 of 263 

measured values above a censoring limit, the likelihood is the normal probability 

density. For nondetects and measured values below a censoring limit, the likelihood is 

the value of the cumulative normal distribution function (the probability of a log 

concentration below the censoring limit). 

Rather than a full Bayesian treatment, where prior probabilities and data combine 

to reduce uncertainty about the model parameters, we seek maximum likelihood 

models. This simplifies the evaluation of monitoring strategies, where the true model 

and its parameters are fixed and data are random (simulated) based on the fixed 

occurrence model. 

Once a best-fitting ANN model is identified, the autoregressive (AR) structure can 

be explored and modeled. AR structure explains how the deviation of one day’s logconcentration from the model is related to the deviation of previous days. It turns out 

that days with log-concentration greater (or less) than expected tend also to be followed 

by days with log-concentration greater (or less) than expected. This is explained by 

positive coefficients in the AR model. 

The time-series plot for the Maumee River in 1998 reveals two occurrence 

peaks. Additional ANN model development, detailed in Appendix C, found a three 

hidden node model with AR(2) behavior to provide a preferable fit to the existing time 

series (shown in Figure 14). 
Page 100 of 263 

Figure 14: Maumee 1998 and Max Likelihood Three-Node ANN Model 

5.6.3. Predictive Analytics 

This discussion describes how the ANN occurrence models can be used to evaluate 

source water monitoring strategies, where the concern is for detecting situations like the 

following: 
Page 101 of 263 

a) Distributions of daily concentrations where the Xth percentile exceeds Y ug/L. (In 

this situation we don’t want to have more than a specified number of days per 

year above Y ug/L and the high-occurrence days do not need to be consecutive 

to do harm.) 

b) Distributions with mean concentrations greater than Y ug/L. (Concern is for longterm exposures, such as associated with some cancer risk.) 

c) Distributions with an average of 1 or more times during the year when 

concentrations exceed Y ug/L for Z or more consecutive days. (Concern is for 

sustained exposure over consecutive days.) 

Under these models, a particular day’s concentration will vary from year-to-year as a 

lognormal random variable, so each day’s distribution function is known. The values 

shown in Table 21 were calculated directly. Other percentiles could be derived in the 

same fashion. 

Table 21: 75th Percentiles and Means for the Three Node Model 

Occurrence 

Model 

a) 75th

Percentile

b) 90th

Percentile

c) Mean

Maumee 1998 

Three-Node 

AR(2) 

0.0920 μg/L 3.02 μg/L 1.428 μg/L 

Estimating the expected number of episodes per year having at least Z 

consecutive days’ concentrations above a level of interest is more involved, as it 

requires simulating many years of occurrence and keeping track of episodes 

encountered. Simulations of this sort have not yet been performed, but are entirely 

feasible, should the data be assembled. 

Given maximum likelihood parameter values, the Maumee 1998 occurrence 

levels may be considerably different than situations of interest. For example, neither of 

those occurrence levels is directly relevant if the concern is having a 90th percentile at or 

above 10 μg/L. 

Fortunately, the models can be scaled easily by adjusting the intercept term, b0. 

Having homogeneous variance on the log-scale ensures that relative error (ratio of 

day’s standard deviation to the day’s expected concentration) is constant. 
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5.6.4. Simulating Daily Levels 

Simulation is required to assess the ability of a monitoring strategy to “detect” 

occurrence situations of interest. Simulating a year of daily concentrations requires 

adding some “error” to the ANN-predicted log-concentration for each day of the year. 

These daily “errors” have two components. One component is like “white noise,” in that 

it is independently and identically distributed (i.i.d.) across days. On the log-scale, the 

white noise distribution is normal with a standard deviation of 0.243 for Maumee 1998. 

The other component of error is due to the AR behavior. In the case of Maumee 

1998, the model is AR(2) and the error on day D includes 0.381 times the “white noise 

error” of the previous day (D-1) and 0.195 times the “white noise error” of day D-2. 

For example, to scale Maumee 1998 so that the resulting occurrence pattern has 

10 μg/L as its 90thpercentile, parameter b0 is increased to 0.613. One year of simulated 

data is shown in Figure 15. In this particular simulated year, 10 μg/L (shown in the plot 

as a horizontal red line) is exceeded on 34 days, so 10 falls just above the 90th 

percentile. Over many simulated years, the percentile associated with 10 μg/L will vary. 

This particular simulated year just happened to have 9.3% of the values fall above10 

μg/L. 
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Figure 15: Simulation Based on the Maumee 1998 Model 

5.6.5 Evaluating a Monitoring Strategy

Having a means of simulating daily occurrence levels for an occurrence level and 

pattern of concern, one can select daily observations in accordance with a monitoring 

strategy and then process the selected observations to make the binary decision: to 

decide whether there is a problem or not. For example, if the strategy is to collect one 

sample per month (one sample every 30 days), and determine whether the maximum 

value exceeds Y, one could do the following: 
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1. Select an occurrence pattern and level of concern. This is a source water 

occurrence scenario where there is concern about either a false positive or 

false negative determination. The simulation exercise is crafted to determine 

whether a strategy adequately limits decision error for the selected scenario. 

2. Select a random start day in the first month. StartDay <- sample(1:31,1) 

3. Add 30, 60, ... 330 to mark the other sampling days for the year or, for 

random dates, select one day at random from every calendar month. 

4. Observe the concentrations simulated for those days in a one-year simulation 

5. Identify the maximum concentration and compare to Y, recording the result 

6. Repeat the steps 2 through 5, above until many years of monitoring have 

been simulated 

7. Across all simulated years, determine the fraction of times that the result was 

positive (because the year’s sample maximum exceeded Y) 

Example: Determine the probability that monthly sampling will produce a 

positive result, where a positive is defined as having a maximum greater than 10 

μg/L when the occurrence pattern is Maumee 1998 having a 75th percentile of 10 

μg/L. For this exercise, this level is considered “high” and a positive rate of at 

least 95% is desired. 

• The occurrence pattern is Maumee 1998 and coefficient b0 is adjusted so the 

long-term 75th percentile is 10 μg/L. 

• Steps 2 through 5 are repeated 10,000 times 

Results 

• Under systematic sampling, a random sampling date is selected for January 

and other sampling dates follow at exactly 30-day intervals. Among the 

10,000 simulated sample maxima, only 180 exceeded 10 μg/L. A positive 

result was obtained 98.2% of the time. The goal of at least 95% positives 

has been met. 

• With random sampling during each of 12 30-day “months,” positive results 

were obtained in only 82.1% of the simulations. The high-occurrence peak 

that was almost always detected with systematic sampling was often missed 

with random sampling. The goal of at least 95% positives has not been met. 
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5.6.7. Summary – Advantages and Disadvantages of Using the ANN 

Models 

There are several important advantages and disadvantages to using ANN 

models for the purpose of evaluating monitoring strategies for the Atrazine Monitoring 

Program. First, ANN Models are flexible and can potentially represent realistic 

occurrence patterns. The models account for some autocorrelation, so they can be 

used to understand the distinction between consecutive days above a level of concern 

and percentiles of the occurrence distribution. As with other approaches, the models 

can be used to assess how a monitoring strategy’s performance is related not only to 

the sample size (number of samples collected each monitoring period) but also to the 

sample timing with respect to occurrence peaks. And finally, the models are scalable, 

so that different magnitudes of occurrence are easily simulated using the same basic 

occurrence pattern and relative error. 

On the downside, the mathematical form of an ANN model is complex, so 

individual model parameters are often difficult to interpret. Additionally, we are not yet 

able to produce a hierarchical model that includes year-to-year variability in timings, 

numbers, and magnitudes of spikes. Expanding these models to account for year-toyear variability in parameters is feasible, but would require many years of data for each 

location modeled. Computing and interpreting occurrence endpoints may be 

challenging. 

The illustration here uses robust monitoring data, with near-daily sampling during 

most of the year. The Agency has not yet evaluated the capability of the model to 

accurately simulate true exposure patterns with less frequent monitoring data. 

5.7 Summary of Water Monitoring Frequency Methods 

The methods discussed above illustrate two different approaches to examine the 

issue of monitoring frequency for assessing exposure durations of interest in human 

health risk assessments. The first (section 5.5) exercises use interpolation procedures 

and looks at upper percentiles of single day estimates and maximum running averages 

of several days’ duration. They compare the performance of different sampling 

strategies for deriving estimates of the “true” concentrations for several periods of time. 

The second (section 5.6) offers a modeling approach that can be applied to pesticide 

occurrence data and combined with different sampling strategies to evaluate their 

performance. A variety of data quality objectives are addressed using specific example 

questions and quantitative performance criteria. Additionally, the Agency plans to 

evaluate other options discussed in section 5.4.1 but not presented in detail here. 

The relative merits of each type of approach depend on both the goals and 

specific questions of interest, as well as on the ability to use each approach with both 
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current data and for anticipated monitoring. While the first approaches that use 

example profiles demonstrate the accuracy of different sampling strategies in a fairly 

straightforward manner, there are questions as to how well results from the small 

sample set can be generalized to the larger body of data, in addition to the best way to 

use them for designing programs for evaluating future monitoring results. And although 

peak width may be more important than peak height for evaluating the performance of a 

given sampling strategy, it may be no less difficult to determine with less than daily 

sampling. It may also be somewhat more variable among the same CWS from year to 

year, while relative peak height has demonstrated some consistency in certain systems 

across the years of monitoring. 

5.7.1. Planned Approach to Evaluate the Methods and Models for 

Estimating Pesticide Concentrations From Less Frequent Monitoring 

Data 

For existing monitoring data with varying sampling frequencies, the Agency is 

interested in both (1) putting confidence bounds on the exposure estimates similar to 

those presented in section 5.5 and (2) using models to estimate exposures between 

measurements, as described in section 5.4.1. Such interpolation methods would also 

have uncertainty bounds associated with their estimates. The Agency anticipates that 

some methods may be better suited for exposures of longer durations (e.g., 90-day 

averaging periods) than for exposures of short duration. 

The Agency plans to use the following approach to evaluate the different 

interpolation methods referenced in section 5.4.1: 

• Use the robust Heidelberg NCWQR monitoring data sets and, as applicable, 

more frequently-sampled headwater streams from the Atrazine Ecological 

Exposure Monitoring Program data to represent the three general exposure 

shapes mentioned in section 5.5, as well as capturing multiple peaks. 

• Sample these data sets at different intervals (e.g., 7-, 14, 30- day sampling 

intervals). 

• Use the various approaches described in Section 5.4.1 (linear, stair step, 

kriging/nearest neighbor, ANN, etc) to estimate the exposures between 

sampling points for each of the sampled intervals. 

• Generate estimated exposures for varying rolling average periods (1, 3, 7, 14, 

30, 60, 90 days) and compare those estimates against the actual values. 
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6. Implications of MOA & Mammalian Toxicity Findings on Sampling 

Frequency 

The Agency has conducted an extensive review of the toxicological and in vitro 

data published since the atrazine IRED was finalized in 2003. In addition, it has initiated 

a re-evaluation of the sampling frequency needed to determine pesticide concentrations 

in water. The objectives of this effort are: (i) to describe the evolution of the state-of-the 

science and how these developments may be incorporated into the atrazine human 

health risk assessment; and (ii) evaluate the water sampling frequency that most closely 

corresponds to the temporal relationship between atrazine exposure and toxicological 

effects of concern. 

The toxicological and in vitro data generated in the last seven years support the 

neuroendocrine MOA described in the 2003 IRED. Moreover, these data enhance our 

understanding of the MOA by identifying another disrupted pathway in the MOA: 

activation of the HPA axis manifested as increases in corticosterone. Atrazine-induced 

HPA activation leads to an increase in pituitary ACTH release, resulting in increases in 

corticosterone and progesterone release from the adrenal gland. In turn, corticosterone 

increases lead to a decrease in the release of GnRH from the hypothalamus. The 

toxicological significance of the rapid HPA axis activation (15 minutes after atrazine 

exposure) remains unclear (i.e., at what doses and after what duration of exposure do 

these changes lead to an adverse health outcome). Data from Cooper et al. (2007) 

indicate that after 4 days of atrazine exposure GnRH levels are decreased at 25 

mg/kg/day (lowest dose tested) while in a separate set of experiments the LH surge is 

attenuated at 6.25 mg/kg/day. Considered in its totality the data reported by Cooper et 

al., Laws et al., Fraites, et al., and Pruett et al., suggest a relationship between 

corticosterone increases and GnRH decreases. At this time, it is unknown what level of 

corticosterone increase and for what duration would suffice to induce the reported 

decrease in GnRH. Research is currently underway to further characterize and 

describe this putative dose-response and temporal concordance between the HPA axis 

activation and HPG disruption. 

The neurotoxic effects reported in the recent data do not support a relationship 

between atrazine exposure and Parkinson’s disease. Moreover, the results of the 

neurotoxic studies (Rodriguez et al., 2005) have some limitations which reduce their 

utility. The dopaminergic responses appear to be, generally, consistent among studies. 

However, these studies lack a consistent hypothesis for the MOA that may be operative 

on the dopaminergic system. Moreover, the increases in corticosterone may be 

associated with these changes. The relationship between corticosterone increases and 

dopamine changes, however, have not been investigated. Nonetheless, the Agency 

believes that points of departure based on neuroendocrine effects will be protective of 

the changes in the dopaminergic system. 

The new data indicate that atrazine-induced immunotoxic effects occur at higher 

doses than those used to establish the NOAELs used in the risk assessment. The 
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potential impact of atrazine on developmental immunotoxicity (DIT) remains unclear 

since the available DIT studies offer conflicting results or could not be replicated. 

In the case of aromatase, the data continue to show that although aromatase 

activity is increased in vitro the same is not seen after in vivo exposure. Multiple studies 

have demonstrated that in the intact animals aromatase changes are not seen. While 

informative for mechanistic studies, cellular systems do not represent the full scope of 

pharmacodynamic and pharmacokinetic responses that are expressed in the intact 

animal. Consequently, with respect to the aromatase studies, the Agency puts more 

weight on the outcomes of in vivo mammalian studies to predict potential risks to human 

health. 

One of the main objectives of the re-evaluation is to evaluate the drinking water 

sampling frequency that most closely corresponds to the temporal profile of the 

toxicological effects of concern. For instance, if the health effects of concern relate to 

long-term chronic exposures less frequent sampling may be sufficient. For effects seen 

after shorter exposures, however, the frequency and timing of sampling may need to 

increase in order to capture these short-duration exposures. This is most critical when 

the Agency is concerned about acute effects resulting from peak, or single day, 

exposures. Depending on the aquatic resource being sampled, the likelihood increases 

that a peak exposure may be missed by less frequent sampling. 

In the 2003 IRED, a six month LH endpoint was identified and a 90-day period 

was chosen as the corresponding exposure duration of concern. It was this 90-day 

average that guided the selection of the current sampling frequency. In preparation for 

the September 2010 SAP, the Agency plans to perform a more complete MOA analysis; 

this analysis will include a thorough evaluation of the temporal pattern of toxicity along 

with consideration of temporal concordance of the key events in the MOA. It does 

appear that new toxicity data available since 2003 suggests that toxicologically relevant 

effects may occur after durations shorter than six months. For example, Table 3 

provides data on several hormonal changes which occur at durations ranging from 15 

minutes to four days. The degree to which these rapid hormonal changes can be linked 

to adverse health outcomes is unclear at this time. The Agency is aware of on-going 

studies to consider such linkage which are expected to become available in 2010. In 

anticipation of the availability of these data, the Agency is considering methods for 

evaluating the performance of different sampling strategies that may be necessary to 

assess drinking water exposures of shorter duration. Several methods have been 

proposed and two are discussed in greater detail in this issue paper. The Agency is 

soliciting comments from the Panel on these proposed approaches. While no 

conclusions have been drawn at this time, preliminary indications suggest that if a 

shorter duration of toxicological concern is selected then a strategy of more frequent 

sampling may be considered in the future. 

Finally, the science that informs atrazine’s risk assessment is complex and multifaceted. The 2003 risk assessment represented the state of the science at the time and 

was one of the most extensively peer-reviewed assessments done by the Agency. 
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Since that time, a vast amount of data have been generated which enhances our 

understanding. At the present time, the Agency is in the midst of its analysis to evaluate 

all these new data. It’s important to note that additional data on a variety of topics such 

as mammary gland development, HPA-HPG axes interaction, and epidemiological data 

from the AHS are expected to become available within the next few months. No firm 

conclusions may be drawn at this time pending analysis of these data. The Agency is 

looking forward to the Panel’s feedback and the public’s comments on this issue paper 

in preparation for the draft WOE issue paper that will presented in the fall SAP.
Page 110 of 263 

Appendix A 

EVALUATION OF ARTICLES ON ATRAZINE AND 

ATRAZINE METABOLITES RELATED TO MAMMALIAN 

TOXICITY STUDIES SUGGESTING POTENTIAL 

ADVERSE HUMAN HEALTH OUTCOMES 
Page 111 of 263 

A.1 Content of this Appendix 

An evaluation of peer-reviewed articles related to atrazine and/or its metabolites 

published since 2003 was conducted. The scope of this evaluation was restricted to 

articles reporting on mammalian toxicity studies or in vitro studies that provided data on 

atrazine and atrazine metabolites mode of action (MOA). The purpose of this 

evaluation was to determine the scientific quality of the research conducted since the 

atrazine Re-registration Eligibility Decision (RED) was finalized in 2003. Ultimately, the 

objective of this evaluation is to ascertain if these new data impact the Agency’s 

conclusions regarding points of departure, MOA and overall impact of atrazine exposure 

on human health. To the extent that these data provide additional information on these 

areas they will be used to update the atrazine human health risk assessment. 
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A.2 Effects on Females 

A.2.1 Dooley, G.P., Reardon, K.F., Prenni, J.E., Tjalkens, R.B., 

Legare, M.E., Foradori, C.D., Tessari, J.E., Hanneman, W.H. (2008). 

Proteomic analysis of diaminochlorotriazine adducts in Wistar rat 

pituitary glands and LβT2 rat pituitary cells. Chem Res Toxicol 

21:844-851. 

In a protein adduct study using immunohistochemistry and Western blot techniques, 

ovariectomized Wistar female rats (4/group) were administered oral gavage doses of 0 

or 200 mg/kg atrazine (97.9%) in carboxymethylcellulose and sacrificed on 

postexposure day 5. Pituitary glands were harvested, and either frozen in liquid nitrogen 

or fixed with formalin. Formalin-fixed tissues were embedded in paraffin, sectioned, 

processed for immunohistochemistry and incubated with a 1:100, 000 dilution of 

commercial DACT adduct antibody overnight at 4° C. Prepared slides were visualized 

with a Vectastain Universal ABC kit, counterstained with hematoxylin and examined for 

DACT-protein adducts. For the two-dimensional electrophoresis, pituitary glands were 

frozen until use. 

A similar approach was taken to prepare the LβT2 gonadotrope cells for DACT-protein 

adducts analysis and for the two-dimensional electrophoretic analysis. Cell cultures of 

LβT2, grown in culture medium to 80% confluency were plated at a density of 400,000 

cells on to cover slides and allowed a 48-hour attachment period. Attached cells were 

exposed to 300 μM DACT, culture medium or the solvent (dimethyl sulfoxide, DMSO) 

for 24 hours. Treated cells on slides were rinsed, fixed in methanol, mixed with Triton 

X, blocked with phosphate buffer, incubated with the DACT adduct antibody, washed 

and reincubated with commercial goat antirabbit antibody labeled with the fluorescent 

dye, Alexa Fluor 488, and examined for DACT-protein adducts. Under similar culture 

conditions, LβT2 cells were grown to 80% confluency, exposed to 300 μM DACT, 

culture medium or DMSO for 24 hours and frozen in liquid nitrogen until use. 

For the two-dimensional electrophoresis, either the frozen pituitary glands or LβT2 cells 

were thawed, pooled, sonicated, and centrifuged. Supernatants were removed; 

proteins were precipitated with a commercial kit, and dissolved by sonication in 400 μL 

of a rehydration buffer. Samples of the tissue or cellular proteins were plated onto trays 

containing gel and subjected to electrophoresis. At the end of the procedure, the two 

dimensional gels were either stained with Sypro Ruby (for protein detection) or 

subjected to Western blotting for detection of the DACT-adducted proteins. Protein 

spots on the Western blots were matched to spots on the Sypro Ruby-stained gels. 

Matched spots from pituitary tissue samples were excised from the Sypro Ruby-stained 

gels, digested, rinsed and proteins were identified through MALDI-TOF/TOF MS. 

Matched spots from the cell cultures were also excised from the Sypro Ruby-stained 

gels, digested, rinsed and processed for MS. Proteins detected in DACT-exposed LβT2 

cells were identified using Sequest search of the MS/MS data. For both sample types, 
Page 113 of 263 

MS spectra-identified proteins were searched against the National Center for 

Bioinformation (NCBInr) protein databases using the taxonomy filter Rattus. 

 

DACT formed 19 spots and covalent adducts with 8 unique proteins in the rat pituitary 

and 21 spots and covalent adducts with 19 unique proteins in the LβT2 cells. The 

investigators reported that the proteins found in both sample types were: proteosome 

activator complex subunit 1 (involved in proteosomal degradation but effect on protein 

stability or function is not known); ubiquitin carboxyl-terminal hydrolase isozyme L1 

(involved in ubiquitin-tagged protein proteosomal system degradation which is critical to 

cell growth, differentiation, development and transcription); tropomyosin (this protein 

binds to actin, one of the major components of the cytoskeleton, and acts as a mediator

of internal cell motility); and ERp57 (an oxidoreductase found in the endoplasmic 

reticulum of cells; exact function is not completely understood). In addition, RNAbinding proteins containing active-site or solvent-exposed cysteine residues were also 

detected in both sample types. 

Based on the results of this study in combination of the other Dooley studies (in PK 

section below) along with other studies, the authors speculate that “Because DACT is 

capable of forming covalent protein adducts and brain tissue is exposed to large 

quantities of DACT following atrazine exposure, specific modifications of proteins within 

the pituitary could cause aberrant function, leading to the observed suppression of the 

LH surge.” 

Reviewer’s Comments: Adduct formation may be important in the regulation of pituitary 

function since adduct formation can be seen in the pituitary glands of rats exposed to 

either atrazine or DACT as well as in LβT2 Rat Pituitary Cells. In vivo exposure to 200 

mg/kg atrazine resulted in 8 DACT-protein adducts. Similarly, LβT2 rat pituitary cells 

exposed in vitro to 300 μM DACT led to adduct formation between DACT and 19 

proteins. This study was not designed to study a potential dose-response in terms of 

adduct formation nor does it provide any data pertaining to the functional outcomes of 

these adducts. Nevertheless, it is noteworthy that these data entail exposure to 

extremely high levels of atrazine and/or metabolites that far exceed the potential 

environmental exposures. 

A.2.2 Fraites, M.J.P., Cooper, R.L., Buckalew, A., Jayaraman, S., 

Mills, L., and Laws, S.C. (2009). Characterization of the 

Hypothalamic-Pituitary-Adrenal Axis Response to Atrazine and 

Metabolites in the Female Rat. Tox. Sci. 112(1):88-99. 

In this article the authors reported the results of 3 studies. The objective was to 

investigate if atrazine and/or two of its metabolites – desethylatrazine (DEA) and 

diamino-s-chlorotriazine (DACT) – affected the hypothalamic-pituitary adrenal (HPA) 

axis in females by monitoring the levels of circulating adrenocorticotropic hormone 

(ACTH), corticosterone, and progesterone. Previously, it had been demonstrated that 

these hormones were affected in males after a single exposure to atrazine at a dose 
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level of 100 mg/kg/day. In addition, studies were also conducted to determine if the 

effects seen in these hormones were similar to those elicited by restraint stress or if 

they were secondary to gastrointestinal discomfort. 

Study 1: Oral Chloroatrazine Exposure and Restraint Stress 

Single exposure 

Four to nine regularly cycling Long-Evans female rats were treated by gavage with a 

single dose of either1% methyl cellulose (vehicle), 75 mg/kg atrazine (purity 97%), 60.2 

mg/kg DIA, or 50.6 mg/kg DACT (atrazine equimolar doses) on the morning of 

proestrus. Precisely 15 minutes after treatment, the animals were sacrificed and their 

trunk blood collected to assay for ACTH, corticosterone, and progesterone. At 

necropsy, the pituitary and uteri were collected and weighed. In addition to examining 

the impact of chloroatrazine exposure on hormone levels, the investigators also 

evaluated the impact of restraining non-treated animals for 5 minutes on stress 

hormone levels as well as the pituitary and uterine weights. 

With the exception of a statistically significant 33% uterine weight decrease after DACT 

exposure, neither the 5 minute restraint nor treatment with a single dose of atrazine or 

DIA affected body weight, pituitary or uterine weights. In contrast, a single dose of 

atrazine or DIA resulted in a statistically significant increase in ACTH, corticosterone, 

and progesterone within 15 minutes of exposure. Interestingly, DACT though the most 

prevalent of the metabolites present in the plasma after atrazine exposure, had little or 

no impact on any of the stress hormone levels. 

Restraining the animals for 5 minutes and sacrificing them precisely 15 minutes after 

resulted in a statistically significant increase in ACTH, progesterone, and corticosterone 

levels. While the magnitude of the progesterone and corticosterone response was 

similar to that elicited by atrazine or DIA treatment, ACTH increases after restraint 

stress were markedly lower than the responses following compound exposure. 

Repeated exposure 

Nine to 14 regularly cycling females were treated by gavage with vehicle, 12.5 or 75 

mg/kg/day atrazine, 10 or 60.2 mg/kg/day DIA, or 8.4 or 50.6 mg/kg/day DACT {atrazine 

equimolar doses] for 4 consecutive days starting on the morning of vaginal estrous and 

ending on the morning of proestrous. As was done during the single exposure study, 

animals were sacrificed precisely 15 minutes after the last administration of the 

compound and their trunk blood collected to assay for ACTH, corticosterone, and 

progesterone. At necropsy, the pituitary gland and the uteri were collected and 

weighed. In addition to examining the impact of chloroatrazine exposure on hormone 

levels, the investigators also evaluated the impact of restraining non-treated animals for 

5 minutes on four consecutive days. 
Page 115 of 263 

Body weight and uterine and pituitary weights were unaffected by compound 

administration though a statistically significant 20% increase in both absolute and 

relative uterine weights were observed after the animals were restrained for 5 minutes. 

Consistent with what was observed after a single exposure, repeated atrazine and DIA 

exposures led to increases in ACTH, corticosterone, and progesterone. All of these 

increases were statistically significant except for the ACTH increase seen after 

treatment with 12.5 mg/kg/day of atrazine. Again, DACT appeared to have little or no 

impact on stress hormone levels. Interestingly, though statistically significant, the ACTH 

response after repeated exposure was markedly attenuated from the response after an 

acute exposure while the magnitude of the response for both corticosterone and 

progesterone were similar after acute or repeated exposures. 

Atrazine, DEA, DIA, and DACT plasma concentrations were obtained 15 minutes after 

the last treatment under both exposure paradigms. After 15 minutes, the plasma 

concentrations were ranked such that atrazine<DEA<<DIA<DACT. After 4 consecutive 

exposures to 75 mg/kg/day atrazine, DACT plasma concentrations were ≈400-fold 

higher than the parent compound and 7-fold higher than DIA. 

 

Study 2: Vagotomized

The objective of this study was to determine if the increase in stress hormones 

observed after atrazine, atrazine-metabolites treatment were related to irritation of the 

gastrointestinal tract rather than a direct effect on the HPA axis. 

Ten vagotomized rats and 10 intact rats were used in this experiment. Four to 5 of the 

vagotomized or intact rats received either 100 mg/kg atrazine or vehicle (1% 

methylcellulose) by gavage. The animals were sacrificed precisely 15 minutes after 

treatment and the trunk blood collected for hormone analysis. Atrazine treatment 

resulted in an increase in ACTH, corticosterone, and progesterone levels in both 

vagotomized and intact animals. For ACTH and progesterone, the response in 

vagotomized animals was substantially more robust than in intact animals. 

Corticosterone levels in both intact and vagotomized animals were also increased after 

atrazine treatment but the difference was not as marked. Nonetheless, these findings 

suggest that the stress hormone release noted after atrazine or atrazine-metabolite 

administration is not the outcome of GI discomfort. 

Study 3: Intravenous DIA Exposure

This study was also conducted to evaluate if the stress hormone release observed 

shortly after atrazine or atrazine-metabolites treatment was due to GI discomfort. In this 

study, rats with an indwelling jugular vein catheter were treated with either vehicle or 1 

ml of 7.8 mM DIA (thus bypassing the GI tract). Blood was drawn 15 minutes after 

treatment and assayed for ACTH and corticosterone levels. Both ACTH and 

corticosterone levels were statistically significantly increased 15 minutes after DIA 

administration relative to animals exposed to vehicle; suggesting that the release of 
Page 116 of 263 

stress hormones was not due to GI discomfort but rather a direct effect of atrazine or its 

metabolites on the HPA axis. 

The authors of these studies concluded that, in addition to the hypothalamic-pituitarygonadal (HPG) axis, atrazine treatment also affects the HPA axis as evidenced by the 

increase in levels of circulating ACTH, corticosterone, and progesterone. Given that 

activation of the HPA axis has been shown to impact reproductive outcomes (likely 

through interactions of corticotropin-releasing factors (CRF) and gonadotropin release 

hormone (GnRH) neurons), atrazine’s effect on the HPA axis may represent a precursor 

event to the attenuation of the LH surge observed after atrazine exposure. 

Reviewer’s Comment: The findings in these series of studies is consistent with 

observations in female mice where atrazine exposure to 500 mg/kd led to an increase in 

corticosterone levels. Similar to what was reported in this study, male rats exposed to a 

single oral dose to atrazine, DIA, or DEA experienced an increase in ACTH, 

corticosterone and progesterone. Interestingly, DACT appeared to have little or no 

impact on the HPA axis although it is the most prevalent of the chloroatrazine 

metabolites. Thus, it appears that atrazine and/or the intermediate metabolites (DEA or 

DIA) are critical in the activation of the HPA axis. ACTH release, however, is attenuated 

after repeated exposures to atrazine or DIA yet corticosterone levels remained markedly 

elevated and were comparable after a single or multiple exposures. 

This study is relevant for the risk assessment and supports the MOA for atrazine. These 

observations strongly suggest that the atrazine-induced endocrine response is a direct, 

chemical-induced change in the hypothalamic-pituitary-adrenal tissue and not the result 

of a non-specific stress response. 

A.2.3 Gojmerac, T., Pleadin, J., Zuric, M., Rajkovic-Janje, R., and 

Korsic, M., 2004. Serum Luteinizing Hormone Response to 

Administration of Gonadotropin-Releasing Hormone to AtrazineTreated Gilts. Vet Human Toxicol. 46(5): 245-247. 

This study looked at porcine serum luteinizing hormone levels in response to 

administration of gonadotropin-releasing hormone to atrazine-treated pigs. 

From the beginning of estrous (days 0 and 21), 10 female pigs (ages 7-8 months) were 

given 1 mg atrazine/kg bw (99% purity) in the feed daily for 20 days of the estrous cycle. 

There were 5 female control pigs. One hour following the last treatment on day 20 

(when the first signs of estrous were observed), blood samples were collected (min 0) 

from control and atrazine-treated groups. Five atrazine-treated pigs were immediately 

given an i.v. dose of 100 μg GnRH. Blood sample for porcine LH (pLH) determination 

were collected from the atrazine-exposed and the GnRH-injected atrazine-treated 

groups at 20, 30, 40 and 90 minutes. Serum concentrations of pLH were determined by 

radioimmunoassay. 
Page 117 of 263 

The experiment was preceded by another which measured pLH concentration in 

peripheral blood samples from 3 intact pigs during the estrous cycle. Serum 

concentrations of pLH were determined in samples collected from the onset of estrous 

(days 0 and 21) between 8 and 9 am, and then twice daily at 3-hour intervals, and on 

days 1,2, 4, 6, 8,10, 12, 14,16,18,19. and 20 of the estrous cycle. 

The pLH concentration from 3 normally cycling (intact) mature female pigs measured at 

3 daily 3-hr intervals during the estrous cycle was increased from 2.6 to 3.9 ng/ml on 

days 0 and 21, which indicated the onset of estrous. The mean serum pLH 

concentration in control animals on day 20 of the estrous cycle correlated with the levels 

in the 3 normally cycling animal on the same day. Repeated exposure of female pigs to 

atrazine resulted in significant reduction (p<0.001) of serum pLH on day 20 of the 

estrous cycle (0.57 ±0.05 ng/ml) compared to control animals (2.24±0.20 ng/ml), which 

is consistent with other studies showing significantly reduced estrogen-induced LH 

response following atrazine administration in female rats. The single iv GnRH 

administration to atrazine-treated female pigs resulted in significant increase in pLH 20 

and 30 minutes after GnRH administration, indicating that attenuation of GnRH release 

in atrazine-treated animals was responsible for the suppression of serum pLH secretion. 

Reviewer’s Comments: This study is relevant to risk assessment in that it supports the 

neuroendocrine MOA identified for atrazine. By demonstrating that suppression of the 

LH secretion can be abrogated by providing an exogenous source of GnRH, the study 

authors have clearly demonstrated the relationship between disruption of GnRH's 

pulsatile release and attenuation of the LH surge. 

A.2.4 Juliani, C., Silva-Zacarin, E., Santos, D. and Boer, P. 2008. 

Effects of Atrazine on Female Wistar Rats: Morphological Alterations 

in Ovarian Follicles and Immunocytochemical Labeling of 90 kDa 

Heat Shock Protein. Micron. 39:607-616. 

The purpose of this study was to characterize morphologically the effect of low and 

sublethal doses of atrazine on ovaries of adult female Wistar rats to determine the 

possible intrafollicular target site through which atrazine acts. In addition, they analyzed 

the expression of the 90 kDa heat shock protein in both ovarian follicular cells and 

ooctye by immunochemical labeling, to evaluate the role played by this protein on the 

ovary under stressed conditions, induced by atrazine exposure. 

Female Wistar rats (n=5/dose group) were dosed via oral gavage with atrazine (97.1% 

purity) at doses of 0 (vehicle), 0.75 and 400 mg/kg/day. The sublethal dose of 400 

mg/kg/day was chosen since it is two-fold the atrazine dose responsible for disruption of 

the estrous cyclicity in female rats (Laws et al 2000). The dose of 0.75 mg/kg/day was 

chosen since it was the lowest dose of atrazine that had been tested on female rats 

which had not induced estrous cyclicity alterations (Cooper et al. 1996; Laws et al. 

2000). The study was conducted in two blocks. In the subacute treatment block, 

females received 0 or 400 mg/kg/day atrazine for 14 days. In the subchronic treatment 
Page 118 of 263 

block, the females received 0 or 0.75 mg/kg/day atrazine for 30 days. Body weights 

were recorded daily. At the end of the treatments, the animals were euthanized and 

ovaries were removed and prepared for histology and immunohistochemical analysis. 

Primary, preantral, and antral follicles per ovary were analyzed. 

In the subacute group, there was a decrease in food consumption and animals lost 

~19% of their initial body weight after 14 days, while the control group had a 17.2% 

increase in body weight. Clinical signs included fatigue and weakness in the treated 

animals, slight trembling in hind legs and presence of strong odor in urine. It should be 

noted that none of these data were provided in the article. In the subchronic group, 

there was no significant decrease in food consumption in the 0.75 mg/kg/day dose 

group. There was an increased body weight (8.5%) in the dosed animals after 30 days. 

This was lower than the weight gain in the control group (18%). Clinical signs included 

fatigue and weakness. 

In the subchronic treatment group (0.75 mg/kg/day for 30 days, rare multioocytic 

follicles were observed in the treated group. In the subacute treatment group (400 

mg/kg/day for 14 days), atrazine induced oocyte toxicity as evidenced by the presence 

of preantral follicles with disorganized granulosa cells and/or a degenerating oocyte with 

discontinuous zona pellucida, which were not observed in the control group. Ovotoxicity 

was also observed in antral follicles in varied degrees. In some atretic antral follicles, 

where high intensity of apoptosis was observed in the granulosa cells, the oocyte 

showed nucleolus fragmentation and irregularities of the Zona Pellucida. 

Low doses of atrazine induced an increased expression of HSP90 in follicular granulosa 

cells in comparison to the control group. However, the positive reaction product, 

indicative of the HSP90 expression, was not found in follicular granulosa cells of ovaries 

collected from rats exposed to subacute treatments. 

Reviewer’s Comments: It should be noted that in this study no quantification of findings 

was attempted. Most results were presented in the form of photomicrographs, thus it is 

difficult to assess the relevance of the findings since most of the assessments were 

subjective (e.g. visual inspection of color change in cells.) This study, therefore, is not 

very useful for risk assessment. 
Page 119 of 263 

A.2.5 Laws, S., Farrell, J., Stoker, T. and Cooper, R. (2003) Pubertal 

Development in Female Wistar Rats following Exposure to Propazine 

and Atrazine Biotransformation By-Products, Diamino-SChlorotriazine and Hydroxyatrazine. Toxicological Sciences 76:190-

200. 

 

The purpose of this study was to evaluate the effects of two atrazine by-products, 

diamino-s-chlorotriazine (DACT) and hydroxyatrazine (OH-ATR), and a structurally 

similar chlorotriazine, propazine (PRO) on female pubertal development. Previous 

studies by Laws et al. have shown that atrazine delays the onset of pubertal 

development in female rats. 

Female Wistar rats (n=15/treatment group) were gavaged from postnatal days (PNDs) 

22 through PND 41 with DACT (96.8% purity) (16.7, 33.8, 67.5, 135 mg/kg), OH-ATR 

(97.1% purity) (22.8, 45.7, 91.5, 183 mg/kg) or PRO (99.8% purity) (13, 26.7, 53, 106.7, 

213 mg/kg). The dose range for each chemical was selected as the molar equivalent of 

atrazine (12.5, 25, 50, 100, 200 mg/kg). The females were monitored daily for vaginal 

opening (VO) and killed on PND 41. The age at complete vaginal opening was 

recorded. Body weights were recorded daily. Tissue weights for each animal were 

recorded for liver, kidney, adrenals, ovaries, uterus, and pituitary. Histological 

evaluations were performed on the thyroid, uterus, and ovaries. [Note: The Protocol for 

the Assessment of Pubertal Development and Thyroid Function in the Female Rat 

(Goldman et al. 200) was used for these studies. Since this protocol is undergoing 

validation by US EPA, thyroid hormones were evaluated in these studies even though 

no previous data suggested that chlorotriazines would affect thyroid function.] 

DACT (33.8, 67.5, and 135 mg/kg) significantly (p<0.05) delayed the age at vaginal 

opening by 3.2, 4.8, and 7.6 days, respectively, compared to controls (33.1± 0.4 (SE) 

days of age). Four of 15 animals in the highest DACT dose group did not attain vaginal 

opening by necropsy at PNDs 41-42. Body weight at the age of VO was also 

significantly increased in the three highest dose groups of DACT (13-19%). At 

necropsy the body weight in the high dose DACT animals remained significantly lower 

(10.4%) than controls. PRO (106.7 and 213 mg/kg) also significantly delayed the age of 

VO by 3.6-4 days. A significant increase in body weight at VO was seen in females 

receiving the highest dose of PRO. Doses of OH-ATR (up to 200 mg/kg) did not cause 

a significant delay in the age of VO. 

Significant reductions in kidney, pituitary, and adrenal weights were observed following 

exposure to the highest dose of DACT. No significant differences in tissue weights were 

seen in any of the OH-ATR animals. Pituitary weights in the two highest dose groups of 

PRO (106.7 and 213 mg/kg) were significantly decreased compared to controls. 

No significant dose related effects were seen for serum T3 or TSH following exposure to 

any of the test chemicals. An absence of corpora lutea was noted in 4 animals in the 
Page 120 of 263 

highest DACT treatment group that did not attain VO prior to necropsy. No treatmentrelated microscopic changes were seen in any animals in the PRO or OH-ATR groups. 

This study concluded that oral exposure to DACT and PRO from PNDs 22-41 delays 

the age of vaginal opening in Wistar rats in a dose-dependent manner. The no effect 

level (NOEL) for DACT (16.7 mg/kg) was identical to the equimolar NOEL for atrazine 

(25 mg/kg). The LOEL for delay in vaginal opening for DACT (33.8 mg/kg) was 

equimolar to that reported for atrazine (50 mg/kg). The LOEL for PRO was 2-fold higher 

that that for atrazine (100 mg/kg vs 50 mg/kg). OH-ATR appeared to be less potent and 

did not alter the onset of puberty at doses equimolar to 200 mg/kg ATR. 

Reviewer’s Comments: It appears that post-natal exposure to DACT results in a delay in 

sexual maturation. These delays do not appear to be secondary to low body weight 

since body weight at time of VO was significantly higher for the delayed pups. Given 

that atrazine is quickly metabolized in the body, it appears that DACT is driving the 

delays in puberty onset. The DACT NOAEL for sexual maturation reported by Laws et 

al. (25 mg/kg/day in atrazine molar equivalents) was higher than the NOAEL (1.8 

mg/kg/day) for attenuation of the LH surge currently used as the point of departure in 

the Agency’s risk assessment. 

A.2.6 McMullin, T.S., Andersen, M.E., Nagahara, A. Lund, T.D., Pak, 

T., Handa, R.J., Hanneman, W.H. (2004). Evidence that atrazine and 

diaminochlorotriazine inhibit the estrogen/progesterone induced 

surge of luteinizing hormone in female Sprague Dawley rats without 

changing estrogen receptor action. Tox. Sci. 79:278-286. 

High oral doses of atrazine (ATRA) suppress the estrogen-primed luteinizing hormone 

(LH) surge in ovariectomized female rats. The mechanism by which ATRA mediates this 

action is unknown, but may be related to its anti-estrogenic activity since LH release 

from the pituitary gland is largely regulated by estrogen binding to its receptor in the 

hypothalamus. Since atrazine is rapidly metabolized to diaminochlorotriazine (DACT) 

(i.e., AUC for DACT is 166-fold greater than that of ATRA at 24 hours after dosing rats 

with 300 mg/kg bw atrazine), it could also be the actions of this metabolite on the 

estrogen receptor (ER). The current study addresses this issue by dosing 

ovariectomized Sprague Dawley rats by oral gavage with ATRA or DACT to investigate 

if the effects of atrazine and/or its major metabolite diaminochlorotriazine (DACT) on the 

estradiol benzoate (EB)/progesterone-induced LH surge are due to impaired ER 

function. As expected, ATRA suppressed the EB and progesterone-induced LH surge in 

a dose dependent manner. A daily dose of 300 mg ATRA/kg bw for 5 days nearly 

abolished the LH surge. In contrast, a dose of 77 mg DACT/kg bw (which produces the 

same AUC for DACT as dosing with 300 mg/kg bw ATRA) only partially attenuated the 

LH surge (~ 60%). The effect of DACT on pituitary function was also examined in 

response to exogenously added gonadotropin-releasing hormone (GNRH). DACT 

attenuated the LH surge by 47% as compared to controls, indicating a decrease in 

pituitary function. 
Page 121 of 263 

Binding studies with uterine cytosolic containing ER and in vitro-transcribed ER indicate 

that ATRA, but not DACT at the same molar equivalent concentration, decreases 

estradiol binding regardless of incubation time. Based on the dose dependent inhibition 

of estradiol-binding, an inhibition binding constant (Ki) of 0.02 mM was estimated for 

ATRA while DACT exhibited a 10-fold greater value. 

In an effort to investigate whether ATRA alters estrogen binding to hypothalamic ER, 

unoccupied ER levels were evaluated in two estrogen-responsive hypothalamic nuclei. 

Treatment with ATRA along with estradiol benzoate did not alter the levels of 

unoccupied ER levels as compared to estradiol benzoate treatment alone. Moreover, 

ATRA failed to block estrogen-induced progesterone mRNA expression as compared to 

estrogen treatment alone. 

Reviewer’s Comments: In summary, the results of this study indicate that (1) although 

ATRA binds ER in vitro, the suppression of the LH surge in vivo may not be due to 

alteration of ER function in the hypothalamus by ATRA itself. This finding is not 

consistent with the findings of several other researchers that show that atrazine does 

not bind directly to the ER (Cooper et al. 2007, Albanito et al. 2008, Judson et al. 

(2010); (2) the difference in potency between ATRA and DACT in suppressing the LH 

surge may be due to pharmacokinetic differences, that is, a greater internal exposure to 

DACT may result from dosing with ATRA than DACT itself due faster 

metabolism/excretion of this species; (3) the effects of DACT in suppressing the LH 

surge involves at least in part decreased pituitary function. 

A.2.7 Shibayama, H. Kotera, T., Shinoda, Y., Hanada, T. Kajihara, T., 

Ueda, M., Tamura, H., Ishibashi, S., Ymashita, Y., and Ochi, S. 2009. 

Collaborative Work on Evaluation of Ovarian Toxicity Two- or Fourweek Repeated Dose Studies and Fertility Study of Atrazine in 

Female Rats. 

Atrazine was administered via oral gavage to female (n=10/group) Sprague-Dawley rats 

(>97% purity) for two or four weeks at doses of 0, 3, 30, or 300 mg/kg/day for the 

repeated dose toxicity study and at doses of 0, 3, 30, or 100 mg/kg/day for the female 

fertility study from two weeks before mating to Day 7 of gestation. 

Repeated Dose Toxicity Studies: Dose levels of 0, 3, 30 or 300 mg/kg/day were 

selected for these studies based on results of previous studies that showed that 

treatment of female SD rats with atrazine for 21 days induced disruption of the estrous 

cycle at 75 mg/kg/day and inhibited follicle and corpus luteum development at 300 

mg/kg/day (Cooper et al. 1996). Treatment of ovariectomized female rats with atrazine 

for five days suppressed the peak level of the LH surge at 30 mg/kg/day (McMullin et al. 

2004). 
Page 122 of 263 

Five week old female SD rats were treated for either two or four weeks. Clinical signs 

and mortality were observed twice daily. Body weight/gain and food consumption were 

measured twice a week. Vaginal smears were taken every day and the mean estrous 

cycle was calculated during the dosing period. Animals were sacrificed after 2 or 4 

weeks, blood samples were taken for hematology and blood chemistry. The ovaries, 

uterus, and pituitary gland were weighed. These organs, as well as the vagina and 

mammary gland, were examined histopathologically. 

Female Fertility Study: Dose levels of 3, 30 or 100 mg/kg/day were selected as 

described above. Ten week old male and female SD rats were used for the fertility 

study. Females were treated for two weeks as the premating period. Males were not 

treated and were only used for mating purposes. After the premating period, females 

were caged with untreated males on a 1:1 basis overnight for up to two weeks. Daily 

administration of atrazine or vehicle was continued throughout the mating period and 

until Day 7 of gestation, or until the last day of the mating period if the animal did not 

copulate. Clinical signs and mortality were observed twice daily during the 

administration period and once daily during the other periods. Body weights were 

measured twice a week during the pre-mating and mating periods and on Days 0-8, Day 

11 and Day 14 of gestation period. Food consumption was measured twice a week 

during the premating period and on Days 1, 4, 8, 10, and 13 of gestation. The mean 

estrous cycle length during the pre-mating period was calculated. Vaginal smears and 

vaginal plugs were checked for the presence of sperm during the mating period. On Day 

14, animals were exsanguinated and the presence or absence of implantations was 

determined after macroscopic examination of the main organs. The number of corpora 

lutea, implantations, live embryos, and dead embryos were counted and the copulation 

rate, and pregnancy rate were calculated. Animals that did not copulate were 

necropsied 14 days after the mating period and the thoracic and intraperitoneal organs 

were examined macroscopically. 

Results for Repeated Dose Toxicity Studies: No mortality occurred in the 2- or 4-week 

study. In the two week study, clinical signs included lacrimation seen at 30 and 300 

mg/kg/day and salivation and soiled perineal region at 300 mg/kg/day. However, no 

incidence for these findings was provided. In the four week study, clinical signs 

included lacrimation, salivation, and soiled perineal region at 30 and 300 mg/kg/day and 

decreased stool observed at 300 mg/kg/day. Decreased body weight/body weight gain 

was observed in the 300 mg/kd/ay dose groups in both the two week (11%, 

p<0.05/39%, p<0.01) and four week (17%/ 42%, both at p<0.01) studies. 

Prolonged mean estrous cycle was observed at the high dose in the two week study 

(9.3 days vs 4.2 days, control, p<0.01) and in the 4-week study at 300 mg/kg/day (8.9 

days vs 4.2 days control, p<0.01). The number of animals with irregular estrous cycles 

was increased (p<0.01) at 300 mg/kg/day in both the 2-week and 4-week studies (100% 

and 80% incidence vs 0-20% incidence in control). 
Page 123 of 263 

Decreased absolute ovarian weights were observed at 300 mg/kg/day in the 2-week 

study (19%, p<0.01) and the 4-week study (17%, p<0.05). The uterus weight was 

decreased at 300 mg/kg/day (25%) in the 4-week study. In the two week study at the 

high dose, histopathological findings occurred in the ovary (loss of currently formed 

corpora lutea, decrease in numbers of previously formed corpora lutea, increased in 

large-sized atretic follicles, swelling of previously formed luteal cells), the uterus 

(atrophy), vagina (mucification and increased single cell necrosis in the vaginal 

epithelium) and mammary gland (lobular hyperplasia). No weight or histological 

changes were observed in the pituitary gland. In the 4-week study at the high dose, 

histopathological findings occurred in the ovary (increase in large-sized atretic follicles 

(slight), swelling of previously formed luteal cells (slight)), uterus (atrophy), and 

mammary gland (lobular hyperplasia and increased lactation). The four week treatment 

group showed lower incidences of abnormal ovarian and vaginal histopathological 

findings then the two week treatment group. The authors noted that these results may 

be explained by spontaneous recovery of some animals from a disturbed to a normal 

estrous cycle. 

Results for Female Fertility Study: No mortality occurred. Clinical signs included 

salivation at 30 and 100 mg/kg/day and lacrimation and decreased stools at 100 

mg/kg/day. However, no incidence of these findings was provided. Atrazine did not 

show significant effects on the fertility study in rats. The copulation index, fertility index, 

number of corpora lutea, number of implantation sites, numbers of live and dead 

embryos, and percentage of preimplantation and postimplantation loss were not 

affected by atrazine treatment. It should be noted that the high standard deviations for 

these observations call into question the quality of the data. Copulation failure caused 

by prolongation of diestrus was seen in 1 animal in the 100 mg/kg/day group, which 

could be due to the anovulatory effect of atrazine. No histopathological findings were 

seen in the ovaries. 

The authors concluded that the effect of atrazine on female fertility in rats could be 

assessed by detailed histopathological examination of the ovaries in a two-week 

repeated dose toxicity study. 

Reviewer’s Comments: In summary, atrazine caused irregular estrous cycles 

accompanied by adverse changes in ovarian histopathology at doses of 300 mg/kg. 

Extended dosing for 4-weeks did not further exacerbate the effects. In contrast, no 

effect on fertility was observed at a dose of 100 mg/kg. While one of the objectives of 

this study was to compare ovarian histology with fertility, the lack of identical doses in 

the repeated dose toxicity studies and the fertility studies prevented this comparison. It 

is noteworthy that the NOAEL for the effects reported by Shibayama et al., (30 

mg/kg/day in atrazine molar equivalents) were higher than the NOAEL (1.8 mg/kg/day) 

for attenuation of the LH surge currently used as the point of departure in the Agency’s 

risk assessment. 
Page 124 of 263 

A.3 Reproductive Effects in Males 

A.3.1 Betancourt, M., Reséndiz, A., Casas, E. and Fierro, R. (2006) 

Effect of two insecticides and two herbicides on the porcine sperm 

motility patterns using computer-assisted semen analysis (CASA) in 

vitro. Repro. Tox. 22:508-512. 

In this study the authors investigated the effects of four pesticides – malathion, diazinon, 

fenoxaprop ethyl, and atrazine – sperm viability, morphology, and motility pattern in 

porcine semen. An in vitro viability staining method was used to assess viability while a 

computer-assisted-analyzer (CASA) was used to study sperm mobility. 12

Semen samples were collected from 3 Duroc boars of proven fertility and the sperm 

checked for anomalies in motility or morphology. Only samples with sperm motility ≥

85% and sperm abnormalities < 15% were used in the experiment. Sperm at a 

concentration of 25 x 106

 sperm/ml, were placed in 4 well plate samples at a final 

concentration of 0, 50, 100, or 500 μM in a volume of 500 μl tris-buffered medium 

[approximately 0, 5.4, 11, or 54 μg] and incubated for 1 hour at 37°C. For the viability 

analysis, 10 μl of the semen sample were placed on a slide and stained with 10 μl 

eosin-nigrosin staining. Sperm that were viable did not incorporate the stain while dead 

spem were stained purple. For the motility evaluations, 8 μl of sperm sample were 

placed on a slide and observed using a CASA analyzer. Parameters measured by this 

device include mean velocity, linear velocity, curvilinear velocity, mean lateral head 

displacement, and frequency of head displacement. 

Exposure to 11 or 54 μg of atrazine resulted in an 8% and 21% statistically significant 

(p<0.05) decrease in sperm viability, respectively. With respect to sperm motility, 

atrazine exposure at 11 or 54 μg led to a statistically significant decrease in progressive 

motility of 23 and 75%, respectively. Atrazine exposure appeared to affect the mean 

velocity and linear velocity of sperm. These parameters are indicators of sperm 

progression. In contrast, other parameters examined by the CASA that were not 

affected by atrazine (e.g., mean lateral head displacement and frequency of head 

displacement) are indicators of sperm vigor. 

The authors of this study conclude that atrazine has an effect on sperm motility and, 

therefore, affect fertility. It should be noted, however, that no data are available from 

this study to corroborate this hypothesis. Interestingly, other researchers have reported 

that the outcomes of in vitro fertilization (IVF) using sperm treated with up to 10 μM 

atrazine were not affected. The authors also speculate that the effects in sperm motility 

may be a sequela of mitochondrial function disruption – cellular respiration, in particular. 

Reviewer’s Comments: Overall, the data suggests an effect of atrazine on sperm 

motility but not morphology or viability. The study, however, entails direct exposure of 

 

12 In this evaluation only the results for atrazine will be discussed 
Page 125 of 263 

germ cells to atrazine without taking into account physiological conditions that may 

preclude the pesticide from eliciting this effect in vivo. Given that atrazine is rapidly 

metabolized, it is likely that the metabolites and not the parent compound are the 

moieties reaching the sperm and testis. This consideration, however, was not 

accounted for by the study authors. Moreover, no attempt was made by the 

researchers to investigate the consequences of these changes in sperm motility on 

reproductive health (e.g., decrease in fertility). In the absence of these considerations, 

the data presented have little relevance to human health risk assessment 

A.3.2 Friedmann, AS. 2002. Atrazine inhibition of testosterone 

production in rat males following peripubertal exposure. 

Reproductive Toxicology 16: 275-279. 

Juvenile Sprague-Dawley male rats (n=4-6/dose group) were administered 0 or 50 

mg/kg/day atrazine (purity not stated) via gavage for either a 3-day exposure (PND 46-

48) or a 27-day exposure (PND 22-48). For both exposure scenarios, animals were 

killed on PND 49 between 9 and 11 in the morning by decapitation. Testosterone (T) 

levels in trunk blood, interstitial fluid of testes and cell culture media were measured. 

[Note: The 50 mg/kg/day dose was based on a pilot study in which rats were dosed with 

50 and 200 mg/kg for PND 22-48 and killed on PND 49. Both doses lowered body 

weight, reduced serum T and interstitial fluid T.] For the in vitro treatment looking at 

testosterone production, Leydig cells isolated from rats on PND 49 were co-cultured 

with 50 μg/ml or 232 μM atrazine in the presence of a maximally stimulating 

concentration of luteinizing hormone. 

In the 27-day in vivo exposure to 50 mg/kg/day, mean testosterone concentrations were 

significantly reduced by 38% in serum and 53% in intratesticular testosterone. 

Decreased body weight (7%) was seen in the 50 mg/kg/day group (215 g) compared 

to controls (230 g). In the 3-day exposure to 50 mg/kg/day atrazine reduced both serum 

(57%) and intratesticular (58%) levels of testosterone. There was no significant 

decrease in body weight of the atrazine group compared to control in the 3-day 

exposure treatment. 

In vitro treatment of Leydig cells for 3 hours with atrazine culture medium resulted in 

significantly reduced testosterone production (35%) compared to controls. Atrazine also 

reduced testosterone levels in Leydig cells stimulated with db-cAMP by 34%. However, 

atrazine did not reduce testosterone production when cells were stimulated with 

hydroxycholesterol. 

The author concluded that atrazine inhibits steroidogenesis in vitro and in vivo. The 

mode of action is via inhibition at the testicular level. 

Friedmann argued against the earlier paper by Trentacoste (he was a co-author) that 

concluded the decrease in T was only the result of underfeeding. He did this by citing 

the drastic reductions in food intake needed to lower serum T. This argument was 
Page 126 of 263 

supported in the Stoker et al., paper mentioned above in which she measured serum T 

and interstitial T and found no difference in the males underfed to the 200 mg/kg group. 

Finally, the fact that the short-term treated rats also had lower T values and these 

animals had not different BWs also argues against the suggestion that all the hormone 

changes observed in these studies is a function of decreased weight. 

In discussing his in vitro study Friedmann concluded that T production by the Leydig cell 

was decreased when exposed to atrazine. The mechanism for this, if repeatable, is 

unclear. Friedman did suggest that as the synthesis of testosterone in the presence of 

hydroxycholesterol was not impaired, the herbicide interferes with cAMP’s role in 

stimulating Leydig cells Furthermore, it should be noted that unpublished data from the 

EDSP validation studies conducted at NHEERL, used much lower doses of atrazine in 

culture and measured T production in H295R cells and compared the results with 

similar treatment to primary Leydig cells. In both cases, T production was increased 

(see Higley et al., paper for data on H295R cells using doses ranging from 1-100 μM). 

Reviewer’s Comments: In summary, a limited number or no measures of key androgen 

dependent tissues were examined in the in vivo study presented in this paper, 

especially in the long-term dosed rats. The in vitro data needs repeating with a range of 

doses. 

A.3.3 Hase Y, Tatsuno M, Nishi T, Kataoka K, Kabe Y, Yamaguchi Y, 

Ozawa N, Natori M, Handa H and Watanabe H. (2008) Atrazine binds 

to F1F0-ATP synthase and inhibits microchondrial function in sperm. 

Biochem Biophy Research Comm 366: 66-72. 

This paper demonstrates the ability of ATR to alter human sperm motility in vitro, and 

tests hypotheses on the mechanism through which this might occur, specifically by 

decreasing ATP availability for sperm flagellar motion. In a series of biochemical tests, 

the authors present evidence that ATR can bind to F1F0-ATP synthase and thereby 

inhibit mitochondrial function (decreasing ATP available for sperm motion). 

Note: The title is misleading because the authors did not actually determine effects on 

sperm mitochondria – rather they used liver mitochondria. Sperm energetics are quite 

different from somatic cell energetics and sperm mitochondria differ from somatic 

mitochondria in specific ways that should be discussed. 

Approach: Ejaculated human semen samples were washed to recover motile sperm 

and the sperm were then cultured with atrazine (ATZ) and ATZ-NH2, a modified version 

of ARZ needed for subsequent biochemical studies). Oligomycin, a sperm metabolic 

poison which uncouples ATP production in mitrochondria, was used as a positive 

control. Oligomycin inhibited % progressive sperm at 0.05 mM; ATZ inhibited at 0.3 

and 1.0 mM but not 0.1 (i.e. was less effective than the positive control). Sperm ATP 

levels were also measured and shown to be significantly decreased at the same 

concentrations of test compounds that inhibited % progressive motility. Motility 
Page 127 of 263 

assessments were made using established computer aided sperm analysis (CASA) 

methods. 

Data rule out several early steps in ATP synthesis and make a solid case for ATR ability 

to bind the ATPase. 

The authors conclude that this likely explains earlier reports that ATR decreases porcine 

sperm motility in vitro (as discussed in the preceding two papers). Importantly, they 

also conclude that “This study was motivated by the idea that ATZ applied to fields may 

cause a reduction of sperm count and motility to humans and other animals. However, 

the effect of ATZ on sperm motility was seen at >100 μM, exposure levels that probably 

do not result from normal use of the herbicide. It is, therefore, uncertain whether the 

observed phenomena are ecologically relevant.” 

Reviewer’s Comments: The relevance of these findings to risk assessment is 

questionable given that the concentration levels required to affect sperm motility were 

high and exceed likely exposure levels resulting from atrazine use in the environment. 

Moreover, the relevance of these ex vivo findings to the in vivo physiologically relevant 

conditions is also uncertain. 

A.3.4 Kandori, H, Suzuki S, Asamoto M, et al. 2005. Influence of 

atrazine administration and reduction of calorie intake on prostate 

carcinogenesis in probasin/SV40 T antigen transgenic rats. Cancer 

Sci: 96: 221 – 226. 

The effects of a 13- week dietary administration of 500 and 1000 ppm atrazine on the 

development of androgen-dependent prostate cancer were investigated using male 

probasin/SV40 T antigen transgenic (TG) rats (Sprague-Dawley genetic background, 6 

weeks of age). Based on food consumption data, the corresponding doses in 

mg/kg/day were 33.0 mg/kg/day for the 500 ppm group and 61.6 mg/kg/day for the 1000 

ppm group. Each treatment group contained 10 animals. A control group was included. 

The rationale for using TG rats was based on previous findings that atrazine inhibited 

testosterone production in the Leydig cells directly of male rats. This would allow for an 

examination of atrazine treatment on the development of androgen dependent prostate 

carcinomas. The authors noted that the TG rats have been established in their 

laboratory, and have developed well-differentiated adenocarcinomas in the prostate at 

100% incidence before 15 weeks of age. Since the tumors are considered to be 

completely androgen dependent, the hypothesis was that exposure of atrazine to the 

TG rats would cause inhibition of testosterone production, resulting in reduced 

carcinoma development. Since atrazine has been reported to decrease body weights, a 

dietary-restricted TG rat group was also included to assess the influence of reduction of 

calorie intake on the development of prostate cancer. 
Page 128 of 263 

The authors reported that mean food consumption in the dietary-restricted group was 

about 70% of that in the control group. At the end of 13 week treatment period, the 

following organs were subjected to histological examination: testes and accessory sex 

organs, ventral prostate, the dorsolateral prostate including the urethra, and the anterior 

prostate/seminal vesicle complex. Serum testosterone levels were measured for every 

animal in each group using radioimmunoassay. Serum levels of atrazine and atrazine 

metabolites were measured for 3 animals per group using gas chromatography-mass 

spectrometry. Immunohistochemistry for SV40 T antigens and androgen receptors 

were performed using avidin-biotin-peroxidase complex method. The ratios of prostate 

epithelial areas were evaluated morphometrically. 

The authors reported that no deaths were observed. Body weights in the atrazine 

treated groups were significantly lower than in the control group. Bodyweights of the 

dietary-restricted and 1000 ppm atrazine groups were similar, and significantly lower 

than control values throughout the treatment period. Food consumption was lower in 

the atrazine treatment groups compared with control group. In the dietary-restricted 

group, mean relative ventral prostate weight was significantly decreased (25%) relative 

to controls. No other treatment-related changes in relative organ weights in any 

treatment group were reported. Serum testosterone levels were not significantly 

different between the atrazine and dietary restricted groups compared with control 

group. Atrazine and its metabolites diaminochlorotriazine, desethylatrazine, and 

desisopropylatrazine were detected in the serum of the atrazine treated animals, but not 

in the control or dietary restricted groups. 

Histopathological examination of the ventral, lateral, and anterior lobes of the prostate 

revealed lesions in all groups including controls. The authors described the lesions as 

marked epithelial proliferation with formation of irregular glands and luminal bridging to 

give a cribriform pattern in focal populations. The nuclei demonstrated enlargement and 

severe atypia. According to the authors, the lesions appeared compatible with welldifferentiated adenocarcinomas in human cases and were therefore diagnosed as 

adenocarcinomas. These were observed in the ventral, lateral, and anterior lobes of the 

prostate in almost all rats. In the dorsal lobe, adenocarcinomas were observed in two of 

three rats of each group. The incidences of adenocarcinomas in any treatment group 

were not different from those of the control group. Foci within glands with less 

proliferation were also observed. These exhibited crowding of stratified epithelial cells 

with irregular spacing and occasional luminal bridging. Nuclear atypia were described 

as severe, however, basic structures of the prostate glands were mostly maintained, 

comparable with prostatic intraepithelial neoplasias (PIN) of human cases. 

Because almost the entire lobes of the prostate were occupied with tumor lesions at 

week 13, morphometric assessment ratios of the prostate epithelial area to the whole 

prostate tissue area were evaluated. Morphometric examination of the prostate 

epithelium revealed significant decreases in the ratios of the epithelial areas to whole 

prostate tissue areas in the ventral, dorsal, and lateral lobes in the dietary-restricted 

group, and in the lateral lobe of the 1000 ppm atrazine group. The values in the dorsal 
Page 129 of 263 

lobe in the atrazine groups showed a tendency to decrease (not statistically significant) 

in a dose-dependent manner. No significant effect was observed in the anterior lobe in 

any treatment groups. 

SV40 Tag and androgen receptor expression were detected immunohistochemically in 

almost all cells of the prostate adenocarcinomas and PIN. No treatment-related 

changes in the testes, epididymides, and seminal vesicles were observed. 

The authors concluded that dietary administration of atrazine for 13 weeks showed 

slight suppressive effects on the development of prostate cancer in the probasin-SV40 

T antigen transgenic rats, even though atrazine treatment did not affect serum 

testosterone levels. Based on the observation that there was equal or greater 

suppression of prostate neoplastic lesion development in the dietary-restricted group, 

the authors also concluded that the observed atrazine-related suppression of prostate 

cancer was probably caused by the decrease in calorie intake, rather than endocrine 

effects. 

Revewer’s Comments: While this study suggests the possibility that prostate 

carcinogenesis may be a secondary effect to a reduction in caloric intake, a test system 

in which testosterone levels are altered would provide a more definitive confirmation. 

A.3.5 Laws, S.C., Hotchkiss, M., Ferrell, J., Jayaraman, S., Mills, L., 

Modic, W., Tinfo, N., Fraites, M., Stoker, T., and Cooper, R. (2009). 

Chlorotriazine Herbicides and Metabolites Activate an ACTHdependent Release of Corticosterone in Male Wistar Rats. Tox. Sci. 

112(1):78-87 

This study is a follow-up to a previous set of experiments study in which these 

researchers demonstrated that atrazine exposure results in an increase in 

steroidogenesis leading to increases in corticosterone, progesterone, and estrogens. In 

this study the investigators sought to characterize the temporal changes in 

adrenocorticosteroid (ACTH), progesterone, and corticosterone in males receiving a 

single dose of atrazine, simazine, propazine or the chlorinated metabolites of these 

triazines (DIA, DEA,and DACT).13 

Male Wistar rats (≈ 50-60 days old) received 0, 5, 50, 100, or 200 mg/kg atrazine while 

animals exposed to DIA received 4, 10, 40, 80, or 160 mg/kg and DEA-exposed animals 

received 173 mg/kg. DACT-exposed animals received 3.37, 33.7, 67.5, or 135 mg/kg. 

The authors state that the maximum dose for each metabolite was the molar equivalent 

of atrazine at 200 mg/kg. Animals were sacrificed precisely 5, 15, 30, 60 or 180 

minutes after exposure. ACTH, corticosterone, progesterone, and prolactin plasma 

levels were measured using commercially available radioimmmmunoassay kits. 

Furthermore atrazine, DIA, DEA, and DACT plasma levels were also measured. 

Statistically significant increases in ACTH levels were first detected 5 minutes after 

atrazine exposure at doses ≥ 100 mg/kg. Maximal increases in this hormone (↑5.6-fold) 

 

13 This review will only discuss data for atrazine, DIA, DEA, and DACT 
Page 130 of 263 

were observed 15 minutes after exposure to 200 mg/kg atrazine. The time-to-effect 

profile for corticosterone and progesterone increases were slightly slower with first 

statistical significant changes noted15 minutes after exposure at 50 mg/kg and above. 

For both of these hormones, maximum plasma levels were seen 30 minutes after 

exposure (↑7.3- and 4.5 fold for corticosterone and progesterone, respectively). 

Exposure to DIA at doses ≥ 40 mg/kg led to increases in ACTH, corticosterone, and 

progesterone within 15 minutes of exposure (↑6.2, 6.3, 12.6-fold, respectively at 161 

mg/kg DIA). Similarly, DEA exposures at 173 mg/kg led to a marked increase in ACTH 

(↑11.8-fold), corticosterone (↑6.4-fold), and progesterone (13.6-fold) within 15 minutes 

of exposure. In contrast, exposure to DACT at doses as high as 137 mg/kg led to a 

minimal increase in these hormones (≤1.3-fold). 

Plasma levels of atrazine, DIA, DEA, and DACT were detected within 5 minutes of 

exposure. The levels of the metabolites increased with time. Five minutes after 

exposure to atrazine DIA was the most prevalent metabolite but by 180 minutes DACT 

was the predominant metabolite seen in plasma. 

The authors conclude that the rapid increase in ACTH after exposure to atrazine or its 

chlorinated metabolites induces adrenal steroidogenesis indicative of initial effects at 

the hypothalamus and/or pituitary level. 

Reviewers comments: This is a well-conducted study that carefully evaluates not only 

the dose-response but also the temporal-response relationship between atrazine, DIA, 

or DEA exposure and changes in hormones in the HPA axis. Elevated ACTH, 

corticosterone, and progesterone levels can be seen 15 minutes after a single exposure 

to atrazine at doses ≥ 50 mg/kg. Although the authors did not establish a NOEL for this 

study, the no effect level may be established at 5 mg/kg – the lowest atrazine dose 

tested. Interestingly, though DACT is the final and most prevalent atrazine metabolite, 

it has little impact on corticosterone, progesterone, or ACTH levels. The relationship 

between these hormonal changes and the adverse reproductive health outcomes 

observed after atrazine exposure, however, remains unclear. To what extent or for how 

long do these hormones must remain elevated before adverse effects are seen is not 

known at this time and cannot be determined from these data. 

A.3.6 Laws, SC, Stoker, TE, Ferrell, JM, Hotchkiss, MG, and Cooper 

RL. 2007. Effects of Altered Food Intake During Pubertal 

Development in Male and Female Wistar Rats. Toxicol. Sci. 100(1): 

194-202. 

Wistar rats (n=13) were underfed 10%, 20%, 30%, or 40% less than the ad libitum food 

consumed by controls from postnatal days (PND) 22-42 (females) or PND 23-53 

(males). This time period encompasses the age of the onset of puberty in both sexes. 

For any given food restriction (FR) treatment group, each animal within that group was 

paired with a control rat of similar initial body weight. Body weight was recorded daily. 

The day of preputial separation (PPS) in males and vaginal opening (VO) in females 
Page 131 of 263 

was recorded. Females were killed by decapitation on PND 41-42 and liver, kidney, 

adrenal ovary, uterus and pituitary weights were recorded. Males were killed by 

decapitation on PND 53-54, and liver, kidney, adrenal, pituitary, left testis, ventral 

prostate, left epididymis, seminal vesicles with coagulating gland (with fluid) were 

removed and weights recorded. Thyroid and reproductive tissues were examined 

histologically. Serum T3, T4 and TSH, glucose, leptin and pituitary (males only) 

prolactin and LH were measured. 

The terminal body weights of FR females (PND 42) and males (PND 53) were 2, 4, 12, 

19% and 2, 6, 9, 19% lower than controls for the 10, 20, 30 or 40% FR groups, 

respectively, being statistically significant at the top two doses. For both females and 

males, the age of pubertal onset was not significantly different from controls for all FR 

groups. 

In females, the thyroid hormone endpoints were not affected by any FR group 

associated with 2-19% reduction in body weight. In males, there was a significant 

decrease in T3 and T4 at the 30% and 40% FR groups associated with 9% and 19% 

body weight decrease, respectively. TSH was significantly decreased in the 40% 

restricted group. No differences in serum testosterone, LH or prolactin were noted in 

any of the males. Serum glucose concentrations in males were not different from 

controls. Female rats in the 30% and 40% FR groups had significantly decreased serum 

glucose when compared to controls. Mean serum leptin concentrations were decreased 

in the 30% and 40% FR males, but were only reduced in the 40% FR females. 

The absolute weights, but not the relative weights, for pituitary, adrenals, liver and 

kidney were significantly lower in the females with a 12% reduction in body weight (30% 

FR) and significantly lower in males with a 6 or 9% reduction in body weight (20% and 

30% FR, respectively). The exception was a significant change in relative liver weight in 

the animals with a 6, 9, and19% body weight reduction. No histopathological changes 

were observed in any organs. 

In females, the absolute weights, but not the relative weights, for ovaries were 

decreased in the 30% and 40% FR groups. The mean uterine weights were not different 

from control for any FR group. In males, the absolute, but not relative weights, for 

ventral prostate and seminal vesicles were significantly lower than the controls in the 

40% FR. 

Reviewer’s Comments: This study clarifies the relationship between altered growth and 

reproductive development in the male and female rat and can be useful in interpreting 

effects of reproductive toxicants and endocrine disrupting chemicals. Previous studies 

used must greater weight loss paradigms during the postnatal period which usually 

resulted in over 50% weight loss. This study uses milder food restriction limits which 

show that a 2 to 19% difference in weight do not interfere with the endpoints measured 

in the male and pubertal protocols. These observations support the concept that a 10% 

reduction in body weight is a reasonable basis for setting the maximum dose for the 
Page 132 of 263 

female pubertal protocol in conjunction with any other information concerning the 

toxicity of the test compound (e.g., clinical signs, other toxicity). 

A.3.7 Maravilla-Galvan, R., Fierro, R., Gonzáles-Marquez, H. GómezArroyo, S., Jiménez, Ir and Betancourt, M. 2009. Effects of Atrazine 

and Fenoxaprop-Ethyl on Capacitation and the Acrosomal Reaction 

in Boar Sperm. International Journal of Toxicology. Volume 2, 

Number 1. pp. 24-32. 

The purpose of this study was to evaluate the in vitro effects of atrazine and 

fenoxaprop-ethyl on capacitation, spontaneous acrosome reaction (SAR) and 

progesterone-induced acrosome reaction (PIAR) in boar sperm.14 

Sperm samples were obtained from the sperm-rich ejaculated fraction of 3 healthy 

fertile boars. Sperm viability was evaluated by eosin-nigrosin staining. Only ejaculates 

showing more than 85% progressive motility, at least 90% viability, and less than 10% 

abnormality were used. Sperm capacitation was done in TALP-HEPES media for 4 

hours. Capacitation and SAR were evaluated immediately; PIAR was evaluated 30 

minutes later. The acrosome reaction (AR) was induced by adding progesterone at a 

final concentration of 10 μg/mL and incubating for 30 minutes. The spontaneous 

acrosomal reaction without progesterone induction is called SAR. Sperm membrane 

status was assessed by chlortetracycline staining and analyzed with a UV 

epifluorescence microscope. Sperm with a uniformly distributed fluorescence over the 

whole head and an intact acrosome were considered noncapacitated; sperm showing 

bright fluorescence in the acrosomal region beside a fluorescence-free band in the 

postacrosomal region with an intact acrosome were considered capacitated; sperm with 

a dull fluorescence over the whole head except for a thin, bright ban in the equatorial 

segment were considered acrosome-reacted. At least 200 sperm were analyzed per 

slide. 

Cytotoxicity was determined by incubating sperm using concentrations of atrazine 

(technical grade, purity not reported) of 0 (control), 20, 40, 60 and 100 μM. Treatment 

with atrazine resulted in a dose-related decrease in sperm viability. For 0, 20, 40, 60 

and 100 μM atrazine the percent viability was 80, 60, 37, 27, and 6, respectively. The 

median lethal concentrations of atrazine were calculated. Final concentrations of 8, 20, 

and 40 μM atrazine were used in the experiments. These concentrations corresponded 

to the LC50/5, LC50/2, and LC50, respectively. The concentrations used were sublethal for 

sperm in vitro, using the LC50 as a maximum. For the capacitation and PIAR studies, 

the herbicide was added at the beginning of the 4 hour incubation. The control was the 

same solvent with the herbicide (0 μM). 

Sperm Capacitation: In the presence of atrazine during capacitation and PIAR, the 

viability of capacitated sperm decreased in a linear fashion for the 8, 20 and 40 μM dose 

 

14 In this evaluation, only the results for atrazine will be discussed. 
Page 133 of 263 

groups. Capacitation decreased significantly only at the high dose (40 μM), to 79% of 

controls (p<0.05). SAR increased 1.9 fold for the 8 and 20 μM and 2.2 fold for the 40 

μM dose groups, all at p<0.05. The noncapacitated population was reduced at all 

concentrations, compared to controls (p<0.05). 

PIAR: SAR observed in control sperm immediately after capacitation was 17%. After 30 

minutes of progesterone induction of acrosome reaction, PIAR increased to 30% in 

controls. This increase shows that progesterone acts as an AR inducer. All atrazine 

concentrations produced a significant decrease (p<0.05) in noncapacitated and 

capacitated sperm, compared to controls. PIAR was statistically increased at 8 μM (1.6 

fold), 20 μM (1.8 fold), and 40 μM (1.8 fold), compared to controls. 

Similar to a previous study by this group (Betancourt et al, 2006), the authors review 

literature on atrazine effects and use, but fail to provide a sound rationale for examining 

direct in vitro effects on sperm. There is no literature to imply that atrazine selectively 

targets mature sperm and impairs their fertilizing ability after in vivo exposure. They 

state that “it is necessary to carry out in vitro studies to clarify the mechanisms of action 

of toxic compounds,” but do not provide justification for this statement. Rather they 

state that because atrazine and FE are used in Mexico and other countries, the aim of 

the study is to evaluate in vitro effects....on boar sperm capacitation and the 

progesterone-induced acrosome reaction. These two statements are unrelated and do 

not provide a sound rationale for the study. There is also no evidence that atrazine 

reaches maturing sperm in the testis, epididymis or female tract at concentrations 

resembling those selected for testing in vitro. 

Reviewer’s Comments: In summary, these data do not appear relevant to assessment 

of risk of atrazine after in vivo exposures nor provide biological plausibility for 

suspecting that atrazine may selectively target sperm and thereby impact fertility or 

sperm function. The authors did note that the atrazine concentrations used in this study 

are not in the relevant range to produce in vivo effects. 

A.3.8 Mu, H. , Shang, P. and Xu, J. (2008). Testicular Toxicity and 

Mechanisms of Chlorotoluron Compounds in the Mouse. Toxicology 

Mechanisms and Methods. 18: 399-403. 

This study looked at the effects of chlorotoluron and atrazine ingestion on male mouse 

testes during the peripubertal period. 15

Groups of 20 male mice (Chinese Kunming strain) were given either chlorotoluron alone 

(625, 1250, 2500, 5000 mg/kg), atrazine alone (218.75, 437.5, 875, or 1750 mg/kg), or 

a combination of these chemicals (combination 1: atrazine/chlorotoluron: 218.75/625, 

218.75/1250, 218.75/2500, or 218.75/5000 mg/kg; combination 2: 

atrazine/chlorotoluron: 437.5/625, 437.5/1250, 437.5/2500, 437.5/5000 mg/kg.) There 

 

15 In this evaluation, only the results for atrazine will be discussed. 
Page 134 of 263 

was one vehicle control group. The animals were dosed by daily gavage from day 27 to 

day 52. On day 52, 24 hours after the last gavage, body weights were measured and 

recorded and blood samples were taken. Following sacrifice testis weights were 

measured and recorded. Testes tissue was processed for examination by light 

microscope and transmission electron microscope. Superoxide dismutase (SOD) 

activity was measured. SOD is an antioxidant (removes superoxide radicals). 

There was a dose related decrease in relative testes weights at all dose levels for 

atrazine (4.6-13%) and combined atrazine/chlorotoluene (6.9-14%), although the 

decreases were not statistically significant. The SOD enzyme activities increased in a 

dose-related manner in animals treated with atrazine and combined, with the effects of 

treatment with the combination of herbicides being greater than the single chemical. 

Control values were not reported. 

Histologic changes in the testes that occurred in treated animals included shedding of 

spermatogenic cells, increased intercellular space, appearance of mild interstitial 

edema, and modest congestion of tissue. No tables were provided and it wasn’t 

clear whether these findings were for atrazine or chlortoluron, or both. Findings 

for mice treated with a combination of chlorotoluon and atrazine included seminiferous 

tubules that were shrunken and had indentations and increased shedding of 

spermatogenic cells and Sertoli cells. Other effects seen by electron microscopy 

included decreased smooth endoplasmic reticulum and Golgi (at combined dose of 625 

mg/kg chlorotoluron plus 218.75 mg/kg atrazine) and heterochromatin in the mural cells 

which appeared in a blocked state, decreased nuclear matrix, spermatogenic cells with 

swollen appearance, segmental degeneration of cell membranes and tight junctions 

which were partially damaged (at combined dose of 1250 mg/kg chlorotoluron plus 

437.5 mg/kg atrazine). 

Comments: This study was poorly written such that it was unclear whether the findings 

were for atrazine or chlorotoluron. Consequently, this study was not useful for risk 

assessment. 

A.3.9 Pogrmic K, Fa S, Dakic V, Kaisarevic S, and Kovacevic R. 

2009. Atrazine Oral Exposure of Peripubertal Male Rats 

Downregulates Steroidogenesis Gene Expression in Leydig Cells. 

Toxicological Sciences 111(1):189-197. 

The purpose of this study was to attempt to identify the possible mechanism of inhibition 

of Leydig cell steroiodogenesis in peripubertal male Wistar rats after in vivo exposure to 

atrazine. The study was based on earlier published papers (described above) that 

identified a decreased testosterone following atrazine exposure when dosing began 

shortly after weaning until after sexual maturation (defined as PPS). 

Male Wistar rats were treated by gavage with 0, 50 or 200 mg/kg/day atrazine (98% 

purity) from PND 23-50. Animals were sacrificed 24 hours after last dose of atrazine. 
Page 135 of 263 

They reported that oral administration of atrazine (200 mg/kg/ay) produced significant 

reduction in serum T/DHT(assay they used was sensitive to both). At 200 mg/kg/day, 

body weight was also reduced significantly as were the weights of androgen-dependent 

organs (testes and seminal vesicles at both, dorsal and ventral prostate at high dose 

only). But LH was not altered at 50 and not significantly reduced in the 200 mg group. 

50 mg/kg atrazine did not alter serum hormone levels nor the weight of androgen 

dependent tissues. Adrenal and Testes weights were affected in both dose groups. 

They pointed out that Trentacoste et al. (2001) suggested that testosterone-reducing 

ability of atrazine is secondary to weight loss. 

Their in vitro dosing is of interest as both doses caused significant decrease in basal 

and hCG stimulated testosterone release. There was no dose response and no 

variance presented in all the cell-stimulation. However, the variance was presented for 

the dose of 10 μM hCG in a bar graph for hCG 10 μM. In addition to a decrease in T 

production, there was also a dose dependent decrease in the cAMP concentrations. 

When the cells were incubated in the presence of hydroxycholesterol, pregnolone, 

progesterone and androsteinedione, in every case, the amount of T produced from the 

Leydig cells obtained from the 50 and 200 mg/kg/ atazine-treated animals was reduced 

compared to controls. Importantly, there was no dose response. Finally the authors 

reported reduced levels of transcripts for CYP17A1 and 17bHSD, which seem to 

indicate an effect upstream and downstream of androgen synthesis. LH did appear 

reduced at 200 mg/kg but was not significant. This is in contrast to the observation of 

Friedmann, 2002 who reported that in vitro treatment with atrazine suppressed T from 

Leydig cells of untreated animals, but the suppression could be overcome by coincubating with hydroxycholesterol. If these observations are both correct then there is 

a difference in the ex vivo vs. the in vitro exposed Leydig cell. 

This group also measured the transcription of several genes involved in steroidogenesis 

(including the LH receptor) after p.o. administration. They report a clear dosedependent decrease in gene expression of LHR, SR-B1, StAR, TSPO, SF-1, PDE4B, 

3bHSD, CYP17A1, 17bHSD in Leydig cells. There was no effect on CYP11A1 and ßHSD. They conclude that the inhibition of all these genes following atrazine may be 

related to decreased c-AMP stimulation. However, there are many inconsistencies with 

the literature (i.e., others found SF1 increased after atrazine exposure in vitro) and 

within their own data (i.e., cAMP is lowered, as is PDE4B....the enzyme that degrades 

cAMP). 

Reviewer’s Comments: The quality of this manuscript is hard to judge. There is a lot of 

data, much of which appears solid, however, the lack of a dose response in the Leydig 

cell incubation studies and the decrease in the expression of so many genes in the RTPCR studies demands confirmation. Finally, as to whether or not these data support 

the HPG MOA or indicate a direct action of Atrazine on the Leydig cell can not be 

determined. In addition, it should be noted that the doses used in this study were 
Page 136 of 263 

relatively high compared to the doses eliciting the neuroendocrine effects and used for 

regulatory purposes. 

A.3.10 Rayner J L., Enoch R R, et al. 2007. Atrazine-induced 

reproductive tract alterations after transplacental and/or lactational 

exposure in male Long-Evans rats. Tox Appl Pharmacol: 218: 238 – 

248. 

The authors note that previous studies have shown that early postnatal exposure to 

atrazine delayed preputial separation (PPS) and increased incidence of prostate 

inflammation in adult Wistar rats. The authors stated that a cross-fostering paradigm 

was used in their study to determine if gestational exposure to atrazine would also result 

in altered puberty and reproductive tissue effects in the male rat. Timed-pregnant LongEvans rats were dosed by gavage on gestational days (GD) 15 – 19 with 100 mg/kg/day 

atrazine or 1% methylcellulose (controls). On postnatal day (PND) 1, half litters were 

cross-fostered to create the following four treatment groups: birth dam or gestational 

exposure only (ATR-C); milk source or lactational exposure only (C-ATR), exposure 

both pre-and postnatal (ATR-ATR), or neither (C-C). Beginning on PND 37, male 

offspring (n>18males/group) were evaluated for puberty (i.e., PPS). Necropsy was 

performed on either PND120 (n = 10/group) or 220 (n = 9-10/group); organs included 

pituitary gland, testes, lateral and ventral prostates, and seminal vesicles. Serum 

prolactin, testosterone, androstenedione and estrone levels were measured by 

radioimmunoassay. The left lateral prostates were analyzed for myeloperoxidase 

activity. Histological examination of the right lateral and ventral prostates were 

conducted. The distribution scoring and severity classification were provided in the 

study. Body weights were monitored throughout the study. 

Mean body weight of the ATR dams on GD19 was reduced 13% when compared to 

control dams. The male offspring in the ATR-ATR group were 6.5% smaller when 

compared to offspring in the C-C and C-ATR groups on PND4. A significant 2 1⁄2 day 

pubertal delay was seen only in males in the ATR-ATR group. Body weights at the time 

of PPS were also decreased in the ATR-ATR animals. 

At PND120, the lateral prostates of the ATR-ATR offspring group weighed significantly 

more than those in any other group, even when corrected for body weight. The average 

ATR-ATR lateral prostate weight was 49% higher than control on PND120. At PND220, 

lateral prostate weights were significantly increased (45 – 110%) in animals within all 

ATR exposure groups compared to control animals. When adjusted for body weight, 

animals in ATR-C and ATR-ATR groups had significantly increased lateral prostate 

weights. 

At PND120, necropsy evaluation of offspring indicated macroscopic abnormalities of the 

left and right lateral prostate in the ATR-ATR group; the abnormalities were 

characterized by nodular pale white foci present on the outer surface. At PND 220, all 

atrazine groups had the abnormalities, mostly on the right lateral prostate. 
Page 137 of 263 

Histological examination of lateral and ventral prostates revealed an increased 

incidence and distribution of inflammation in the lateral prostates of C-ATR males at 

PND 120. Only one out of ten ATR-ATR males also exhibited inflammation; there was 

no inflammation in the C-C and ATR-C groups. The C-ATR and ATR-ATR lateral 

prostates had neutrophils as the predominant inflammatory cells. In regard to ventral 

prostates at PND 120, inflammation was evident in all groups (C-C, ATR-C, C-ATR and 

ATR-ATR) indicating no effect of treatment. The authors stated that it is difficult to 

assess inflammation in the ventral prostate because of a high background present. The 

authors also noted that although necropsy revealed macroscopic abnormalities on the 

surface of the lateral prostate of males in the ATR-ATR group, these abnormalities “may 

not have penetrated deep within the gland.” By PND220, lateral prostate weights were 

significantly increased for ATR-C and ATR-ATR groups, but there were no significant 

changes in inflammation in either the lateral or ventral prostate. 

The results of the myeloperoxidase assay demonstrated no significant effects; the 

authors noted the discrepancy between the assay and the pathological findings. The 

authors explained the discrepancy as possibly due to not having both lateral prostates 

for assay (one used for the assay, the other for pathology). No statistically significant 

differences in serum hormone concentrations of total testosterone, androstenedione, 

estrone, and prolactin were observed among the different treatment groups. 

The authors concluded that the results of the study suggest that the developing lateral 

prostate gland in the Long-Evans rat is sensitive to atrazine-induced changes that are 

transplacental or via nursing. In addition, lactational exposure to these atrazine-induced 

changes increases lateral prostate inflammation. 

Reviewer’s Comments: This study only examines one dose, so there are no dose 

response evaluations. The authors do not mention the time of day which they killed the 

males at 120 or 200 days of age or how long the necropsy lasted, as this would be very 

important when evaluating effects on the endocrine system. The increased lateral 

prostate weights are reflective of an increase in lateral prostate inflammation, which has 

been found previously following early postnatal exposure of atrazine to the lactating 

dam (Stoker et al., 1999). There is also a delay of PPS in the ATR-ATR dose group 

only, indicating that it is the combination of gestational exposure to the dam and the 

postnatal milk from those mothers responsible for the effect. Rosenberg et al, 2008 

also observed a delay in PPS at 100 mg/kg with an oral perinatal exposure only, a 

condition that would be similar to the ATR-CON group in whom Rayner found no effect 

on PPS. It should be noted that these effects in the Rayner et al. study occur at doses 

higher than those eliciting disruption of the LH surge. 
Page 138 of 263 

A.3.11 Rosenberg, B.G., Chen, H., Folmer, J., Liu, J., 

Papadopoulos, V., and Zirkin, B.R. (2008). Gestational Exposure to 

Atrazine: Effects on the Postnatal Development of Male Offspring. J. 

Andrology 29(3):304-311. 

In this study, the authors investigated the impact of atrazine exposure during gestation 

on the development of Sprague-Dawley (SD) rats male offspring. Fourteen to 16 

pregnant dams were exposed via gavage from gestation day (GD) 14 - 21 to 0, 1, 10, 

50, 75, or 100 mg/kg/day of atrazine (purity 98.5%). The male offspring of 7-8 dams per 

dose group were sacrificed on post-natal day (PND) 0. The testes from these males 

were collected and used to measure testicular testosterone levels in the newborn pups. 

The litters of the remaining 7-8 dams were culled on PND2 to 8 pups (4/sex/litter). Body 

weights and food consumption of pregnant dams were recorded daily from GD 14-21. 

On PND21 the body weights and anogenital distance (AGD) were measured for each 

pup. The 4 male pups from each litter were also examined for preputial separation 

beginning on PND35. On PND 60 the pups were sacrificed by decapitation and their 

blood (serum), testes, ventral prostate, and seminal vesicles collected. The testes, 

ventral prostate, and seminal vesicles were weighed. Testosterone levels were 

measured in both the serum and intratesticular fluid. 

Maternal body weight was statistically significantly reduced at doses ≥ 75 mg/kg/day 

starting on GD18. This decrease coincided with a 33-47% decrease in food 

consumption for the 50, 75 and 100 mg/kg/day dose groups. Litter size was unaffected 

by atrazine treatment. However, pup death between PND 0 and 2 was increased by 

approximately 10-25% at doses ≥ 10 mg/kg/day, with statistical significance attained at 

the 75 and 100 mg/kg/day doses (~20-25%). Pup weight decreases of 10-17% were 

reported for pups whose dams were exposed to doses 50 mg/kg/day or higher. None of 

these pup weight decrements, however, were statistically significant. 

Intratesticular testosterone levels measured from neonates did not reveal any 

statistically significant effects at any dose level. Although a 60% increase in 

intratesticular testosterone was noted at the 10 mg/kg/day dose level, there was no 

statistical significance or dose response for this effect (i.e., testosterone levels at ≥ 50 

mg/kg/day were comparable to control). It is noteworthy, that at this dose level a nonstatistically significant increase in AGD was observed in males on PND 21. while AGD 

was significantly reduced at 100 mg/kg/dose levels on PND 21. 

A statistically significant delay in PPS ranging from 1-3 days was noted at 50 mg/kg/day 

and above. (Note: Graph and text differ: graph indicates ss only at 100 mg/kg/day 

(p<0.004) while text says ss at ≥50 mg/kg/day (p<0.05, p<0.01)). 

On PND 60, the animals used to assess PPS and AGD were sacrificed and their testes, 

seminal vesicles, and ventral prostate weights measured. In addition, testosterone 

levels in both the serum and intratesticular fluids were measured. No changes in 

terminal body weight or organ weights were noted. Serum testosterone levels, 
Page 139 of 263 

however, were decreased at ≥ 50 mg/kg/day while intratesticular testosterone was 

reduced at doses of 75 and 100 mg/kg/day. [Note: graph and text report of T differ; they 

are reversed.]

The authors of this study concluded that in utero exposure resulted in changes that 

manifested in the neonatal, peripubertal, and adult life stages. The authors, however, 

did point out that these effects were observed at concentrations that “are unlikely to be 

experienced under any but experimental conditions.” 

Reviewer’s Comments: The highest two doses 75 and 100 mg/kg/day resulted in 

significant reductions in the dam’s BW gain. There was a dose-dependent loss of pups 

-- ~20-25% pup death at 75 and 100 mg/kg from PND 0-2. There were no differences in 

neonatal T at PND 0, but there did appear to be effects on androgen dependent 

measures later in life, including reduced AGD at PND 21, a delay in PPS in the 100 

mg/kg group and a decrease in serum T at 60 days of age in the 50, 75 and 100 mg/kg 

group. Oddly, none of the androgen-dependent tissue weights, including the seminal 

vesicles or ventral prostate were affected even at the highest dose. It should be noted 

that the effects on maturation and altered androgen status occurred in this study at dose 

levels substantially higher than those leading to LH surge disruption, which serves as 

the basis of the Agency’s current risk assessment. 

A.3.12 Stoker TE, Guidici DL, Laws SC, Cooper RL. 2002. The 

Effects of Atrazine Metabolites on Puberty and Thyroid Function in 

the Male Wistar Rat. Toxicological Sciences 67: 198-206. 

Male Wistar rats were gavaged (between 8 and 9 am) from PND 23 –PND 53 with 

atrazine metabolites (97-98% purity), deethylatrazine (DEA), deisopropylatrazine (DIA), 

and diaminochlorotriazine (DACT) at doses equivalent to the atrazine equimolar doses 

(AED) of 0, 6.25, 12.5, 25, 50, 100, or 200 mg/kg/day.. The day of preputial separation 

(PPS) was measured. Males were killed by decapitation 2 hours following the last dose 

on PND 53. The pituitary, adrenal, thyroid, testes, epididymides, seminal vesicles, and 

ventral and lateral prostates were weighed and examined histologically. Blood and 

serum were assayed for hormones (testosterone, estrogen, LH, prolactin, TSH, T4, T3). 

There was a significant decrease in body weight seen with all the metabolites at the two 

highest dose groups. For all metabolites at 200 mg/kg/day, there was a greater than 

10% decrease in body weight at PND 43 and 53. For all metabolites at 100 mg/kg/day, 

body weight decreases ranged from 9-12% at PND 43 to 7-13% at PND 53, with DEA 

being the metabolite exceeding 10% body weight decrease at both time points. 

The day of PPS was delayed by all 3 metabolites. For DIA, PPS was significantly 

delayed at 25, 100, and 200 mg/kg/day AED by 1.2, 1.2 and 3.4 days, respectively, 

resulting in a NOAEL for delayed PPS of 12.5 mg/kg/day. For DEA, PPS was 

significantly delayed at 25, 100, and 200 mg/kg/day AED by 1, 2 and 4 days, 

respectively, with a NOAEL of 12.5 mg/kg/day. For DACT, PPS was significantly 
Page 140 of 263 

delayed at 12.5, 25, 100, and 200 mg/kg/day AED by 1, 2.3, 1, 4, and 4.2 days, 

respectively with a NOAEL of 6.25 mg/kg/day. 

Testicular weights were similar to controls in all treatment groups for all three 

metabolites. When males were killed on PND 53, DEA (100 and 200), DIA (50-200 

AED), and DACT (200 AED) treatments caused significant reduction in ventral prostate 

weight, while the highest doses of DIA and DEA resulted in significant decrease in 

lateral prostate weight. Seminal vesicle weight was reduced at 100 and 200 AED by all 

three metabolites. Epididymal weights were decreased in the DEA (200 AED), DIA (200 

AED), and DACT (100 and 200 AED) treatment groups. 

Serum testosterone was significantly decreased only in DIA exposed males at 100 and 

200 AED. Serum estrone was significantly increased only by DACT at 100 and 200 

AED. 

The mean anterior pituitary weight was significantly decreased on PND 53 at 100 and 

200 AED by DEA and DACT and the highest dose of DIA. On PND 53, serum LH 

showed a significant trend for a dose-dependent decrease from control to high dose in 

the DIA group. Pituitary LH was significantly decreased in the 100 AEd of DIA and the 

200 AED of DEA compared to controls. Pituitary prolactin content was significantly 

decreased at 100 and 200 AEd of DEA and at 200 AED of DACT. 

TSH, T3 and T4 were unaffected by any treatment group. No effects were observed on 

thyroid histology of high dose or controls. 

Minimal hypospermia (defined as rats in which the overall density of spermatozoa within 

the epididymal ducts appeared to be decreased compared to control samples() was 

seen in 25% of the high dose group of DIA, 40% of the high dose group of DACT, and 

12.5% of the high dose group of DEA. The author reported that this observation is 

probably a result of the length of the delay in puberty in the high dose groups of atrazine 

metabolites and the age of sacrifice. 

Reviewer’s Comments: This study shows the effects of the three primary atrazine 

metabolites on pubertal onset and growth of androgen dependent tissues. Interestingly, 

many of the same effects were observed including delayed PPS and decreased 

reproductive tract development. DIA was the only metabolite which resulted in 

decreased serum testosterone and DACT increased serum estrone. The doses appear 

to be similar to those that were effective with atrazine for the same endpoints, including 

PPS. DACT delayed puberty at the same doses (12.5 to 200 AED). It is noteworthy 

that the lowest NOAEL for the effects reported by Stoker et al. 2002 (6.25 mg/kg/day in 

atrazine molar equivalents) was higher than the NOAEL (1.8 mg/kg/day) for attenuation 

of the LH surge currently used as the point of departure in the Agency’s risk 

assessment. 
Page 141 of 263 

A.3.13 Stoker, T.E., Laws, S.C., Guidici, D., and Cooper, R.L. 

2000. The effects of atrazine on puberty in male wistar rats: An 

evaluation of a protocol for the assessment of pubertal development 

and thyroid function. Toxicological Sciences. 58: 50-59. 

Intact male Wistar rats (n=6-20) were treated with atrazine (97.1% purity) via gavage at 

doses of 0, 12.5, 25, 50, 100, 150, or 200 mg/kg/day from postnatal day (PND) 23 to 53. 

An additional pair-fed group was added to compare effects of any decreased food 

consumption in the high dose group. Daily body weight and preputial separation were 

measured. Males were killed by decapitation on either PND 45, 53, (or 54) or 120. The 

pituitary, thyroid, testes, epididymides, seminal vesicles, and ventral and lateral 

prostates were weighed and examined histopathologically. Blood and serum were 

assayed for hormones (testosterone, estrogen, LH, prolactin, TSH, T4, T3). 

There was a significant reduction in body weight in the high dose (200 mg/kg/day) on 

PND 43 (14%) and PND 50 (17%). The pair fed group of 200 mg/kg/day had a 

significant reduction in body weight on PPS day (13%), PND 43 (20%) and PND 53 

(15%). 

Preputial separation was significantly delayed in the 12.5, 50, 100, 150, and 200 

mg/kg/day dose groups by 2.3, 1.8, 1.7, 1.6 and 3 days as compared to controls. PPS 

was also delayed by 2 days in the pair-fed animals compared to controls. The delay in 

PPS observed in the pair-fed animals was not as severe as that observed in the 

atrazine 200 mg/kg/day group. 

This study showed that atrazine suppressed the growth of androgen dependent 

reproductive tissues at 50 mg/kg and up (ventral prostate). Ventral prostate weight was 

also decreased in the pair-fed group. Seminal vesicle and epididymal weights on PND 

53 were decreased in the 200 mg/kg/day atrazine group and pair-fed animals. By PND 

120, all reproductive tract organ weights returned to control levels in all treatment 

groups, except for the ventral prostrate which was still significantly decreased in the 200 

mg/kg/day atrazine group (784.8±46.1, controls vs 638.13±25.3, 250 mg/kg/day). 

Lateral prostate and testicular weights were not different from control in any of the 

atrazine or pair-fed rats killed on PND 53. 

There was no effect on serum testosterone at 53 days of age, but intra-testicular 

testosterone was decreased on PND 45 which might explain the delay in pubertal 

development. There was no significant effect on serum LH on PND 53, but serum 

estrogens were increased at 200 mg/kg/day. These effects did not appear to be due 

solely to decreased growth, as there were effects at doses which did not affect growth 

(both PPS and tissue weights). 

Reviewer’s Comments: Peripubertal exposure to atrazine resulted in delayed puberty 

onset and delayed growth of the reproductive tract of male rats. These data support the 

reported alteration of the hypothalamic control of pubertal progression. 
Page 142 of 263 

A.3.14 Trentacoste, S V.. Friedmann, AS, Youker, RT, 

Breckenridge, CB, and Zirkin, BR. 2001. Atrazine Effects on 

Testosterone Levels and Androgen-Dependent Reproductive Organs 

in Peripubertal Male Rats. Journal of Andrology, Vol. 22, No. 1, 

January/February 2001 ; pp. 142-148. 

Male Sprague-Dawley rats received atrazine (96.1%) from PND 22-47 by gavage in 

methyl cellulose at doses of 0, 1, 2.5, 5, 10, 25, 50, 100 or 200 mg/kg/day (n = 9-12 

rats/dose) and killed by decapitation on PND 48 (24 hours following last dose; doesn’t 

state time of day killed). A food restriction study was conducted with rats pair fed to the 

100 mg/kg/day atrazine treated group. In life measures included daily (?) body weights. 

The day of preputial separation (PPS) was measured in controls and only the 100 and 

200 mg/kg/day dose groups. Testosterone (serum and interstitial fluid) and serum LH 

concentrations were measured. 

Body weight (9%, 100 mg/kg/day/21%, 200 mg/kg/day), seminal vesicle (32%/55%) and 

ventral prostate (26%/48%) weights, serum T (34%/32%) and intratesticular fluid T 

(41%, 45%), LH (17%, not s.s./20%) and PPS (3 days/4 days) were significantly 

reduced in the 100 and 200 mg/kg/day groups. PPS was only evaluated in the 100 and 

200 dose groups. As body weight was affected by the atrazine 100 and 200 mg/kg/day, 

a group of males were pair fed to the 100 mg/kg/day group. The underfed only animals 

had a decrease in T and LH on PND 47 that was similar to the 100 mg/kg/dose group. 

The authors concluded that these results indicate that atrazine exposure, up to 50 

mg/kg/day, had no effect on the hypothalamic-pituitary-testicular axis, and that at levels 

greater than 50 mg/kg per day, the effects observed in response to atrazine could not 

be distinguished from the effects observed after reduced food consumption. The 

author’s emphasized that caution must be exercised before concluding that atrazine (or 

any potentially toxic chemical) has direct, detrimental effects when the toxicant also 

produces significant changes in body weight. They further emphasize that body weight 

must be both monitored and accounted for in the assessment of potential toxic effects. 

Reviewer’s Comments: The study author’s contention that the changes in the male 

reproductive tissue weight and PPS changes observed was the result of decrease body 

weight is not supported by an earlier study by Stoker et al., 2000. In that study, Stoker 

examined similar measures in the male Wistar rat. This group reported that 100 

mg/kg/day reduced BW approximately 7% (vs. approximately 10% in the present study 

with Sprague-Dawley males). However, Stoker also found a decrease in ventral 

prostate weights at 50 mg/kg/day males (which had BW reduction of 3%) and delays in 

preputial separation following 12.5 mg/kg/day and above. Stoker also noted lower 

serum testosterone values in males treated with 25 mg/kg/day and above, which was 

very similar to that observed by Rosenberg et al., 2008, following gestational dosing). 

Stoker et al., also pair fed males during the experimental period base on the food 

consumed by the 200 mg/kg/day animals. The body weight in the pair fed animals was 

84% of control body weights (reduced 16%). Serum T was not reduced in Stoker et al 
Page 143 of 263 

study, however they did have smaller ventral prostates, seminal vesicles and a delay in 

PPS (albeit significantly less than that observed in the 200 mg/kg/day rats). Importantly, 

the Trentacoste et al., paper did not look at the onset of preputial separation in animals 

dosed with less than 100 and 200 mg/kg/day, the very endpoint that set the LOAEL an 

NOAEL in the Stoker paper. No explanation is given for this omission. Freidman 

(2002) reported a significant decrease in both serum testosterone and interstitial 

testosterone in Sprague-Dawley rats treated during the same PND period, and body 

weight was reduced 7% (230 = control 215 = atrazine 50 mg/kg/day from 22-48. 

A.3.15 Victor-Costa, AB, Bandeira SMC, Oliveira AG, Mahecha 

GAB, Oliveira, CA. 2010. Changes in Testicular Morphology and 

Steroidogenesis in Adult Rats Exposed to Atrazine. Reproductive 

Toxicology. oi10.1016/j.reprotox.2009.12.006. 

This study evaluated the effects of atrazine on the steroidogenic pathway in adult male 

rats by analyzing the 3β-HSD expression, plasma and testicular estrogen and 

testosterone levels, expression of androgen receptor, and morphophysiological changes 

in the testes. 

Adult male Wistar rats (4-7/group) (120 days old) were given daily doses of atrazine 

(purity not provided) via gavage for 7 days (300 mg/kg/day), 15 days (50 and 200 

mg/kg/day) or 40 days (200 mg/kg/day). A commercialized mix of atrazine called 

Gesaprim® was used. This formulation consisted of 500 g/l atrazine and 500 g/l of inert 

ingredients. Control animals were treated for similar periods with the vehicle, corn oil. 

After treatment, rats were weighed and sacrificed. Testes and adrenal glands were 

weighed. Testes were examined histopathologically. Changes in the expression of 3βhydroxysteroid dehydrogenase (3β-HSD) enzyme and androgen receptor (AR) in the 

testes were studied by immunohistochemistry. 3β-HSD is the enzyme responsible for 

various stages of the steroidogenic pathway, including synthesis of adrostenedione, the 

testosterone precursor. Adrenal glands were also evaluated for the 3β-HSD by 

immunodetection for comparison between steroidogenic tissues. Immunostaining was 

quantified by computer-assisted image analysis. AR staining was quantified in 30 

interstitial Leydig cells as well as 30 Sertoli cells lining seminiferous epithelium stages 

VII or VIII, per animal, except for those treated with atrazine 200 mg/kg/day/40 days in 

which the testes were atrophic and the stages of the seminiferous epithelium cycle 

could not be identified. In this case, the Sertoli cell positivity was measured in randomly 

observed tubules. Plasma testosterone and estradiol were measured by both 

radioimmunoassay (RIA) and enzyme linked immuno sorbent assay (ELISA). Western 

blot assays were performed to determine the specificity of the antibodies and the 

changes in the expression of 3β-HSD enzyme in testis and adrenal and androgen 

receptor in testes of treated groups. 
Page 144 of 263 

There were significant body weight decreases (p<0.05) in the rats treated with atrazine 

200 mg/kg/day (15 and 40 days) (35%) and 300 mg/kg/day (7 days) (38%). A 

significant increase (p<0.05) in the relative and absolute testes weights were seen in 

rats treated with atrazine 200 mg/kg/day/15 days (80% and 16%) and 300 mg/kg/day/7 

days (83% and 14%). However, exposure to atrazine 200 mg/kg/day/40 days resulted in 

a 41% and 60% reduction in the relative and absolute testis weight, respectively. There 

was a significant increase (p<0.05) in the relative adrenal weight of 64%, 104%, and 

41% for the rats treated with atrazine 200 mg/kg/day/15 days, 200 mg/kg/day/40 days, 

and 300 mg/kg/day/7 days, respectively. There was no effect on body weight, testis or 

adrenal weights in animals treated with atrazine 50 mg/kg/day for 15 days. 

Plasma testosterone levels, as measured in RIA assays, were statistically decreased 

(p<0.05) compared to controls in all treated animals (65% for 50 mg/kg/day/15 days; 

85% for 200 mg/kg/day/15 days; 86% for 200 mg/kg/day/40 days; 87% for 300 

mg/kg/day/7 days). ELISA assay confirmed the reduction in testosterone (data not 

provided). Testicular levels of testosterone were also significantly (p<0.05) reduced 

(32%) after treatment with atrazine 200 mg/kg/day/15 days. However, plasma and 

testicular estradiol levels were significantly increased by 33% and 38%, respectively, 

after treatment with atrazine 200 mg/kg/day/15 days. At all other dose levels, the 

plasma and testicular estradiol levels were similar to controls. 

Atrazine exposure caused changes in testis morphology. Atrazine exposure caused 

dilation of seminipherous tubules at doses of 200 mg/kg/day/15 days and 300 

mg/kg/day/7 days. Pleomorphic Leydig cells with irregular nuclei were observed in all 

atrazine treated animals. Atrazine 200 mg/kg/day/40 days resulted in testis atrophy and 

reduction in the seminiferous tubules lumen. In this group giant multinucleated bodies 

and a large number of apoptotic cells were frequent within the seminiferous tubules. 

Immunopositivity for AR was detected in Leydig cells, Sertoli cells, and Myoid cells of 

both treated (200 mg/kg/day/15 and 40 days; 300 mg/kg/day/7days) and control rats. 

There was no difference in AR protein levels when animals treated with atrazine 200 

mg/kg/day/15 days and controls were compared by Western blotting assay. 

Quantification of the AR immunopositivity in specific cell types after exposure to atrazine 

at the same dose (200 mg/kg/day/15 days) showed equal AR intensity in Sertoli cells 

and Leydig cells compared to controls, which confirmed the Western blotting results. 

Treatment with higher doses of atrazine (300 mg/kg/day/7 days) resulted in decreased 

AR intensity in both Sertoli and Leydig cells. Longer treatment with atrazine (200 

mg/kg/day/40 days) resulted in decreased AR staining in Sertoli cells but increased AR 

staining in Leydig cells. It was noted that the rats treated for 40 days had atrophied 

testis and most of the tubules presented AR-positive Sertoli cells, with reduced staining 

intensity. 

In control animals, 3β-HSD positivity in the testis was found in the Leydig cells 

cytoplasm. After atrazine exposure, there was a great reduction in Leydig cells 3β-HSD 
Page 145 of 263 

immunoreactions (either weakly stained or negative). These data were confirmed by 

Western blotting, in which rats treated with atrazine 200 mg/kg/day/15 days showed 

significant reduction (40%) in the intensity of 3β-HSD positive bands in the testis. The 

expression of 3β-HSD immunoreaction was found in cells of the three zones of the 

adrenal cortex. The pattern of distribution and intensity of the 3β-HSD immunoreaction 

in the adrenal cortex was similar in both control and treated animals. Western blotting 

was in agreement with these results, showing that the 3β-HSD protein was not altered 

in adrenal cortex of treated animals compared to controls. 

Reviewer’s Comments: This study used some unusual treatment regimens. There is no 

dose-response examined, as there is only one dose per treatment period except in the 

15 day exposure. For example, in the 15 day exposure, they include a 50 and 200 

mg/kg dose, but do not show any effects for the 50 mg/kg except for decreased 

testosterone. It is difficult to interpret the results with this experimental design and the 

high doses. They do include some measures that other studies in this area did not 

examine, including the measurement of testicular and adrenal 3B-HSD and testicular 

androgen receptors. 3B-HSD is a key enzyme in the androgen biosynthetic pathway, 

but changes in the expression or protein levels could be a result of the suppression of 

luteinizing hormone. The fact that they found a decrease in B-HSD in the testes is 

different than the Pogrmic paper wherein this was one of only two (of the many 

examined) that did NOT change, but the current paper looks at the protein using 

immunocytochemistry and the Pogrmic paper looked at message. The changes in 

testicular weight are interesting and haven’t been shown before. For example, testis 

increased weight with transient exposures (200 for 15 days or 300 for 7 days), but 

showed atrophy with exposed for 40 days at 200 mg/kg. The larger weights correlated 

with increased lumens of the seminiferous tubules. The increased lumen is likely due to 

increased fluid accumulation (backflow). Over a period of time, this can lead to atrophy, 

which may be why it is observed in the 40 day exposure. The high doses and the fact 

that 50% of this was made from “other-ingredients” in the commercial mixture make the 

results difficult to interpret. This paper adds little to what we know. 

A.4 Aromatase 

A.4.1 Albanito L, Lappano R, Madeo A, Chimento A, Prossnitz ER, 

Cappello AR, Dolce V, Abonante S, Pezzi V, Maggiolini M. (2008). Gprotein-coupled receptor 30 and estrogen receptor-α are involved in 

the proliferative effects induced by atrazine in ovarian cancer cells. 

Environ Health Perspect. 116(12):1648-55. 

This study used in vitro methods to further evaluate the effects of atrazine in multiple 

cell lines. The hypothesis for the study is based upon previously reported endocrine 

disrupting effects of atrazine for androgen- and estrogen-mediated processes following 

in vivo and in vitro exposures. Using a series of molecular approaches, the study 

evaluates a number of potential cellular mechanisms to include potential effects on 
Page 146 of 263 

estrogen receptor expression and other estrogen target genes, extracellular signalrelated kinase (ERK) phosphorylation, and cell proliferation. 

Studies were conducted using human BG-1, MCF-7 (breast cancer), Ishikawa (human 

endometrial), and SkBr3 (breast cancer) cell lines. BG-1, MCF-7, Ishikawa cells were 

(transiently) transfected with ER luciferase reporter plasmids, and SkBr3 was cotransfected with ERα expression plasmid and ER-luc. All transfected cell line were 

maintained for 24 hrs., and then exposed to solvent, estradiol (100 nM), atrazine (1 – 10 

μM)m, ICI ER antagonist (10 μM), or combinations of ICI + E2, ATR + E2 for an 

additional 24 hrs. Figure 2 shows that atrazine did not stimulate luciferase expression 

or block E2 induction in any of the cell lines at concentrations up to 10 μM. A study to 

determine whether or not atrazine regulated ERα expression was conducted using BG1 cells, and results demonstrated that atrazine (1 μM) did not alter mRNA or protein 

concentrations of the receptor (Fig. 3) as compared to the down-regulation of these 

measures in those cells exposed to estradiol. In addition, the study confirms that 

atrazine does not bind directly to the ER as previously reported by Cooper et al. 2007. 

Together, these data demonstrate that atrazine does not bind or activate ERα. 

 

In experiments using the triated-water release assay, atrazine did not alter aromatase 

activity or gene expression in the BG-1 cells following a 40-hr exposure to 1 μM. This 

finding is in contrast to that reported by Sanderson et al. (2000) for the H295R cell line. 

However, the current study reports only aromatase activity as % of controls. Without 

absolute values for aromatase activity of the controls, it is difficult to assess whether or 

not the BG-1 cells exhibit constitutively high aromatase activity as observed in the R2C 

Leydig cell line (Heneweer et al., 2004) that would prevent further amplification by 

exposure to atrazine. In addition, the current study does not provide a positive control 

for either aromatase activity or gene expression. 

To test the hypothesis that atrazine may generate rapid signaling via second messenger 

systems such as Ca2+, cAMP, nitric oxide, and G-proteins, which in turn can lead to 

activation of downstream kinase, an experiment was conducted to evaluate the ability of 

atrazine to produce effects on extracellular signal-related kinase (ERK) phosphorylation 

in the BG-1 cells. Figure 5A-B and 6 show that atrazine (1 μM) stimulated ERK 

phosphorylation within 20 min., albeit a higher concentration and prolonged time was 

required as compared with effects of estradiol. A similar effect was observed in 2008 

ovarian cancer cells. The ER agonist, ICI, prevented the atrazine and E2 mediated 

effects on ERK phosphorylation (Fig. 6). 

 

Given the results on ERK phosphorylation, the authors further evaluated the ability of 

atrazine to up-regulate the expression of c-fos, an early gene that responds to a variety 

of extracellular stimuli, including estrogens. An 1-hr exposure to atrazine (1uM) 

significantly enhanced c-fos and cyclin A mRNA levels (200-269% increase as 

compared with control), and longer exposure (24-hr) resulted with significant elevations 

in progesterone receptor, pS2k and cyclin A. The authors conclude “Atrazine is able to 
Page 147 of 263 

stimulate the expression of diverse estrogen target genes without an apparent activation 

of ERα. Additional experiments demonstrated that the atrazine dependent upregulation of c-fos was abolished after 2-hr incubation with ER antagonist ICI, the 

EGFR inhibitor AG, or the ERK inhibitor, PD. Thus, the authors concluded “in ovarian 

cancer cells, atrazine involves ERα and the EGFR/MAPK pathway to trigger c-fos 

protein increase.” 

The study further evaluated the effects of atrazine on the G-protein-coupled receptor 30 

(GPR30), a seven-transmembrane receptor which is structurally unrelated to the 

nuclear ER, but has recently been shown to mediate rapid actions of estrogens. The 

authors have also recently shown that c-fos stimulation of E2 occurs through GPR30 

and requires ERα and EGFR-mediated signaling in cancer cells (Albanito et al 2007, 

Cancer Res. 67:1859-1866). In the current study, both atrazine-dependent ERK 

phosphorylation and c-fos induction were abolished in BG-1, 2008 ovarian, and SkBr3 

cells after silencing of GPR30 with small interfering RNA (siRNA), Fig. 10. 

Reviewer’s Comments: This study shows no evidence that ATR binds directly or 

activate ER-α in cancer cells. It does offer intriguing evidence that atrazine may bind to 

a membrane receptor that modifies a signaling pathway associated with c-AMP, ERK, 

and P13k activation. The concentrations used to indicate this effect are well within, or 

below the range of concentrations known to modify the steroidogenesis. The fact that 

the authors identify GPR30 as the target site is also interesting in that although there is 

clear evidence that this membrane receptor mediates very rapid (non-genomic) cellular 

responses, the finding that the ligand typically used in these experiments is estradiol. 

This manuscript, in combination with the Suzawa and Ingraham and Higley et al., 

papers argues that atrazine influences signal transduction and provides an alternative to 

phosphodiesterase as the membrane associated target molecule for the herbicide. 

A.4.2 Benachour N, Moslemi S, Sipahutar H, Seralini GE. (2007). 

Cytotoxic effects of aromatase inhibition by xenobiotic endocrine 

disrupters alone and in combination. Toxicology and Applied 

Pharmacology. 222:129-140. 

The purpose of this study was to evaluate the in vitro effects of known endocrine 

disrupting chemicals on aromatase and cytochrome P450 reductase activities, the later 

being the second moiety of the aromatase enzyme complex that serves as the electron 

donor during the conversion of androgens to estrogens. Chemicals (aroclor 1254, 

atrazine, o,p’-DDT, vinclozolin, p,p’DDE, bisphenol A, chlordecone, nonylphenol, 

tributylin oxide, and diethylstilbestrol) were tested in both human placental microsomal 

and purified equine testicular aromatase preparations, as well as in human embryonic 

293 cells (transiently) transfected with human aromatase cDNA. 

Human embryonic 293 cells (50,000/well) were grown in 24-well plates to 80% 

confluency and transfected with human aromatase cDNA 48 hrs prior to exposure to 
Page 148 of 263 

test chemicals. An initial evaluation of cell viability following exposure to each chemical 

(up to 500 μM) was determined using the MMT method. Following exposure to the test 

chemicals, media was removed, cells were washed with serum-free media, and tested 

for aromatase activity using the tritiated-water release assay. Specifically, the cells 

were incubated for 45 min. with 3H-androstenedione, a substrate for aromatase. 3Hwater, released during the conversion of each molecule of androgen to estrogen is a 

direct measure of estrogen production and enzyme activity. Additional assays were 

conducted to determine the inhibitory effects of the test chemicals on aromatase activity 

in human placenta microsomes and equine testicular preparations containing the full 

aromatase (reductase) enzyme complex. Direct effects on the reductase moiety of the 

aromatase complex was tested by measuring the absorbance corresponding to the 

reduced form of cytochrome c in the presence of NADPH+. For this assay, reductase 

(isolated from equine testes) was preincubated with the test chemical for 15 min. prior to 

initiation of the reaction. 

In general, results from the study are difficult to interpret. Initial experiments to detect 

inhibitory effects on aromatase activity in human placental microsomes were conducted 

for each test chemical at a single high dose of 500 uM. Atrazine had no inhibitory 

effect at 500 uM. Chemicals that reduced aromatase activity by 50% were further 

tested at concentrations ranging from 10 – 1000uM. BPA inhibited reductase activity, 

albeit the IC50 was exceptionally high, 1250 uM. The authors report “a slight increase 

in reductase activity in the presence of atrazine” but the actual concentration 

responsible for the effect is unclear. Viability of the embryonic cells was affected after 

24 hrs in culture at chemical concentrations ≥ 50 uM. Thus, maximal concentrations 

used for the aromatase assays in the cultures was 20 uM. Binary mixtures were tested 

for some of the chemicals, but again, data are difficult to interpret. Fig. 7 shows that 

atrazine significantly inhibited aromatase activity in the embryonic cells. 

Reviewer’s Comments: In conclusions, the data reported by Benachour et al. are not 

useful for the current assessment of atrazine due to an incomplete documentation of 

methods, doses, and results. Atrazine is fairly insolubility at concentrations higher than 

50 uM, especially in media. Sections of the discussion are poorly written and cite data 

from other studies incorrectly (e.g., Sanderson, 2000; Crain 1997).

A.4.3 Fan W, Yanase T, Morinaga H, Gonda S, Okabe T, Nomura M, 

Hayes T, Takayanagi R, Nawata H. (2007a). Herbicide atrazine 

activates SF-1 by direct affinity and concomitant co-activators 

recruitments to induce aromatase expression via promoter II. 

Biochemical and Biophysical Research Communications. 355:1012-

1018. 

The authors were interested in confirming previous findings that atrazine induces 

aromatase expression via promoter II (ArPII) in a SF-1 (steroidogenic factor 1) manner. 

They were also interested in studying binding of atrazine to the receptor, and whether 

affinity is independent of the ligand binding domain. The in vitro assays utilized H295R 
Page 149 of 263 

cells (human adrenocortical cancer cells), HIH-3T3 fibroblasts cells, and KGN tumor cell 

line (human ovarian granulose-like tumor cell line). A luciferase gene reporter system 

was examined. Information on the construction of the human CYP19 promoter II 

luciferase reporter and human SF-1 reporter was provided. 

The in vitro experiments with H295R cells and luciferase gene reporter system showed 

that the ArPII reporter responded (dose-dependently) to atrazine (10-7 to 10-5 M) without 

exogenous SF-1 co-expression. To confirm that SF-1 is essential for atrazine 

stimulation, endogenous SF-1 in H295R cells were knocked down by siRNA. The 

results indicated a complete loss of responsiveness of ArPII to either atrazine (10-5 M) 

or simazine (10-5 M). In the presence of exogenous SF-1, atrazine and simazine 

induced ArPII in the normally non-responsive KGN cells. The authors also noted that 

both atrazine and simazine were not cytotoxic and didn’t affect SF-1 gene expression. 

Data were presented to demonstrate that protein kinase a (PKA) and liver cell homolog1 (LRH-1) are not essential for atrazine stimulation. To assess if the affinity between 

SF-1 and atrazine is followed by co-activator recruitment, mammalian two hybrid-assays 

for SF1-TIF2 interaction were performed. Results suggested that atrazine enhanced 

the interaction between SF-1 and its co-activator TIF2. The authors concluded that 

atrazine-SF-1 affinity is coupled with enhanced receptor-co-activator interactions. To 

examine the functional domain of SF-1 in mediating atrazine stimulation over ArPII, 

mutations were introduced to the DNA binding domain (DBD) and the ligand binding 

domain (LBD). Results revealed that mutations in DBD, but not LBD of SF-1 alter 

atrazine stimulation. The authors concluded that atrazine binds to and activates SF-1 

to induce ArPII. 

Reviewer’s Comments: Fan et al 2007a, b showed that atrazine binds directly to SF-1 

and induces aromatase expression in vitro. It should be noted, however, that after 

aromatase activity is not affected after in vivo exposure in mammalian species. 

A.4.4 Fan W, Yanase T, Morinaga H, Gondo S, Okabe T, Nomura M, 

Komatsu T, Morohashi K, Hayes TB, Takayanagi R, Nawata H. 

(2007b). G Atrazine-induced aromatase expression is SF-1 

dependent: implications for endocrine disruption in wildlife and 

reproductive cancers in humans. Environ Health Perspect. 

115(5):720-7. 

This in vitro study focused on the role of steroidogenic factor 1 (SF-1) in atrazineinduced aromatase expression. A luciferase reporter driven by the SF-1 dependent 

aromatase promoter (ArPII) was used to examine activation of this promoter by atrazine 

and simazine. Atrazine-responsive adrenal carcinoma cells (H295R) and atrazine nonresponsive cells, (i.e., HIH-3T3 fibroblasts cells, and KGN tumor cell line (human 

ovarian granulose-like tumor cell line)) were examined. A luciferase gene reporter 

system was used for the transfection assays. 
Page 150 of 263 

Atrazine-responsive H295R cells expressed 54 times more SF-1 than the 

nonresponsive KGN cells. Exogenous SF-1 conferred aromatase responsiveness to 

atrazine and simazine in KGN cells. The results of the chromatin-immunoprecipitation 

(ChIP) assay indicated that atrazine and simazine increased binding of SF-1 to ArPII. 

Reducing the aromatase promoter II to 516 base pairs did not affect atrazine-induced 

aromatase response. However, a mutation in the SF-1 binding site on promoter II 

(AFFTCA to ATTTCA) eliminated the responsiveness to atrazine and simazine 

treatment. 

The authors concluded that atrazine binds directly to SF-1, showing that atrazine is a 

ligand for this “orphan” receptor. The results of this study are supported by another 

study conducted by these investigators (Fan et al. 2007b). 

Reviewer’s Comments: Fan et al 2007a, b showed that atrazine binds directly to SF-1 

and induces aromatase expression in vitro. It should be noted, however, that after 

aromatase activity is not affected after in vivo exposure in mammalian species 

A.4.5 Heneweer M, van den Berg M, Sanderson JT. (2004). A 

comparison of human H295R and rat R2C cell lines as in vitro

screening tolls for effects on aromatase. Toxicol. Lett. 149(2):183-

194. 

The purpose of this study was to compare two cell lines, rat Leydig cell carcinoma 

(R2C) and human adrenocorticocarcinoma (H295R) cells, for their suitability as a 

screening method to detect effects on aromatase expression and catalytic activity 

following exposure to selected xenobiotics. For each cell line, aromatase activity using 

the tritiated-water release assay and promoter-specific mRNA levels were measured 

following exposure to prochloraz, fadrozole, epoxyconazole, atrazine, 8-bromo-cyclic 

adenosine monophosphate (8-Br-cAMP), prostaglandin E2, phorbol 12-myristate 13-

acetate, and dexamethasone. This study is unique in that it is one of the first efforts to 

evaluate changes in aromatase activity of the test chemicals as well as the indentify the 

specific promoter regions of the CYP19 gene that is affected during exposure. 

For all experiments, cells were cultured in 24-well plates, and exposed to each test 

chemical (1 – 10 uM,) for 24 hr prior to assay for aromatase. These cells were used to 

evaluate effects on aromatase activity that required mRNA synthesis of the CYP19 

gene and/or other transcription factors. In contrast, another group of untreated cells 

were exposed to the test chemicals only during the 3 –hr incubation period of the 

aromatase assay to evaluate effects related to direct (rapid) inhibition of the enzyme 

through competitive or non-competitive binding of the test chemicals to the enzyme 

binding sites, binding to allosteric sites of the enzyme causing conformational changes 

and loss of enzymatic activity, or alteration of other posttranslational events that 

generally occur rapidly. Appropriate controls were used to demonstrate the specificity of 

the aromatase assay and measurement of promoter-specific mRNA levels; solvent 

controls, 4-OH-androstenedione (known inhibitor of catalytic activity of aromatase), and 
Page 151 of 263 

8-BR-cAMP (inducer of aromatase activity). Cell viability was evaluated using the MTT 

reduction assay. 

Results from positive and negative controls confirm assay specificity and demonstrate 

the precision of the methods to detect significant differences in aromatase activity and 

gene expression in both cell lines. Atrazine (0.3, 3 and 30 uM) caused a dosedependent increase in aromatase activity (LOEL 10 uM) in the H295R cells only when 

exposed for 24 hrs. (Fig.5) indicating that gene transcription and/or other longer-term 

cellular event was required. While an increase in the amplification response of I.3 and 

pII-containing aromatase transcripts, the change as shown in Fig. 6 was not significantly 

different from control or 8-Br-cAMP (100 uM). The authors suggest that the change in 

these particular promoters may be related to an increase in cAMP, as this transcription 

factor is crucial for stimulation of this particular promoter. In contrast, no effects on 

aromatase activity was observed in the R2C Leydig cells following 3 or 24-hrs of 

exposure to atrazine or 8-Br-cAMP. This cell line, believed to be under the primary 

regulation of promoter pII, is also simulated by cAMP. The authors report that basal 

aromatase activity in the R2C cell line is very high as compared to that of the H295R 

cells, and that it is possible that one or more aromatase regions are fully activated, 

leading to constitutively high aromatase expression in the R2C cells with no further 

room for induction by chemicals. 

Reviewer’s Comments: In conclusion, these data support earlier findings of atrazinedependent increases in aromatase activity in the H295R cell line, and provide some 

insight on the possible cellular regulation of aromatase during the 24-hr exposure 

period. It is clear that atrazine does not alter enzymatic activity through a rapid 

(competitive or non-competitive inhibition, allosteric modification ) alteration of the 

enzyme. However, failure to evaluate other promoters within the H295R cells is a 

limitation of this study, and stops short of providing firm (significant) correlation between 

increased transcripts with I.3 and pII with elevated aromatase activity. In addition, the 

study demonstrates that the R2C Leydig cell line is not suitable for screening chemicals 

for identification of induction of aromatase gene expression. 

Aromatase activity (AA) : H295R cells displayed dose dependant increase in AA 

(0.3 , 10 and 30 uM) with 3-fold induction as compared to control at highest dose. 

 LOEL 10 uM, NOEL 0.3 uM) 

R2C cells = no sign. effect on AA or cell viability (at 30uM), NOEL 30 uM 

(Authors suggest lack of effect was likely due to constitutively high aromatase 

expression as compared with that observed for the H295R cells. 

Promoter-specific mRNA Levels: 

H295R cells – Following 24 hrs exposure, an increase in I.3 and pII transcripts 

was observed in cells treated with 30 uM, but was not sign. different than control 

or 8-Br-cAMP. (Thus, it is still unclear whether or not cAMP and/or activation of 

these promoters are totally responsible for elevated aromatase activity). 

 
Page 152 of 263 

A.4.6 Higley EB, Newsted JL, Zhang X, Giesy JP, Hecker M. (2010). 

Assessment of chemicals effects on aromatase activity using the 

H295R cell line. Environ Sci Pollut Res Int. Jan 20. (Epub ahead of 

print). 

This study compared the effects of seven model chemicals (atrazine, forskolin, 

prometon, ketoconazole, aminoglutethimide, letrozole, and prochloraz) on aromatase 

activity and steroid production (estrogen, testosterone) in H295R human 

adenocarcinoma cells. The suite of chemicals selected for the study were selected 

because they were chemicals known to induce aromatase activity through up-regulation 

of gene expression and/or transcription factors. Using a tritiated-water release 

aromatase assay to quantify the conversion of radiolabeled androstenedione to estrone, 

the authors tested an approach to determine whether or not a given chemical affected 

aromatase directly (e.g., immediate competitive inhibition of enzyme), indirectly (e.g., 

altered activity requiring a longer exposure time), or a combination of both direct and 

indirect effects. Measurement of estrogen and testosterone allowed an evaluation of 

the predictability of these endpoints for effects on aromatase activity in the cultured 

cells. 

For each experiment, H295R cells were cultured in 24-well plates, 300,000 cell/ml, and 

allowed to attach for 24 hrs prior to treatment. Media was changed and cells were 

exposed to test chemicals for an additional 48 hrs. DMSO (≤ 0.1% v/v) was used as 

solvent, and six concentrations of the each chemical (0.01 to 10 uM) along with solvent 

controls were tested in duplicate or triplicate. MMT assay used for detection of 

cytotoxicity. At the end of each experiment, culture media was collected for hormone 

assay (ELISA), and the cells were further subjected to the tritiated-water release 

aromatase assay for 1.5 hrs. To differentiate between direct, indirect or a combination 

of direct and indirect effects on aromatase activity, the exposure of the cells to the test 

chemical was varied in one of 3 ways: (1) indirect effect- no further exposure of the 

cells during the 1.5 hr. incubation, (2) combination of direct and indirect effects- cells 

exposed for 48 hrs in culture and then again during the 1.5 hr assay, and (3) untreated 

cells during the 48 hrs culture were exposed to the test chemical only during the 1.5 hr 

assay period. 

Reviewer’s Comments: Overall, the results of this study indicate that the increase in 

estradiol observed in the H295R cell assay was not due to a direct increase in 

aromatase activity. Atrazine, like forskolin (which activates the enzyme adenylyl 

cyclase and increases the intracellular levels of cAMP) enhanced steroidogenesis as 

evidence by increased T and E. In contrast, when atrazine and forskilin were tested in 

the “direct” tritiated water assay, there was no apparent change in aromatase activity 

(even at concentrations greater than the concentrations that changed estradiol 

production. These observations are important because they demonstrate that atrazine 

does not interact directly with the enzyme aromatase (as indicated earlier by the paper 

of Sanderson using the same cell line) and casts further doubt on the hypotheses that 

any adverse effects of the chemical are mediated through activation of aromatase. 
Page 153 of 263 

In addition, significant elevations of (indirect) aromatase activity were only observed 

following a longer exposure for both of these chemicals. The authors conclude, “The 

hormone and aromatase activity profiles for forskolin and atrazine were comparable, 

and suggest similar mechanisms of activity even though exposure to forskolin resulted 

in greater concentrations of estrogen and testosterone, and greater aromatase activity 

at lower concentrations than observed for atrazine.” In contrast, known inhibitors of 

aromatase (prochloraz, letrozole, aminoglutethimide, ketoconazole) caused decreases 

in estrogen, testosterone and (direct) aromatase activity measured following the 1.5 hrs 

exposure. The novel finding of increased (indirect) aromatase activity following longer 

exposures to these inhibitors suggests that a compensatory feedback regulation of 

aromatase gene expression may also occur in response to the low estrogen 

concentrations. Thus, the authors conclude that multiple measures of aromatase 

activity to evaluate immediate (direct) effects on the enzyme as well as longer term 

(indirect) effects should be measured in using in vitro culture systems such as the 

H295R cell line. 

Figure 16: Effect of Atrazine Exposure on Aromatase Activity 

and Hormone Levels 

(A1, A2) Atrazine: 48-hrs. exposure, 0.01 – 100 uM, 

E2, 7.2X increase (100uM), LOEL (1 uM), NOEL (0.1 uM) 

T, 1.4X increase (100 uM), LOEL (10 uM), NOEL (1.0 uM) 

Direct AA: no effect (100uM) 

Indirect AA: increase LOEL (1 uM), NOEL (0.1 uM) 
Page 154 of 263 

Limitations of study: 

‐ Data for all endpoints reported as fold-change, with no actual values for 

means ± SEM for any observations for steroid concentrations or aromatase 

activity. Without control data, it is difficult to gauge how consistent data are 

among experiments within the study or compare with data reported 

elsewhere. 

‐ The large discrepancy between the fold changes in AA and E2 (ATR (100 

uM) AA was 2.25X versus 7.2X for E2 as compared to respective controls) in 

Fig 17. is believed to be a reflection of different collection times, e.g, AA is 

that change which occurs in tritiated water release over a 1.5 hr period, 

versus E2 production over the 48 hrs in culture. 

‐ Although positive controls used to demonstrate specificity of aromatase 

assay (e.g., radio inert androstenedione and fadrozole), no concentrations for 

androstenedione reported and vague information on that used for fadrozole. 

‐ Solubility of ATR (100uM) is questionable. 

A.4.7 Holloway, A. Anger, D., Crankshaw, D., Wu, M, and Foster, W. 

2008. Atrazine-induced Changes in Aromatase Activity in Estrogen 

Sensitive Target Tissues. Journal of Applied Toxicology. 28:260-270. 

The purpose of this study was to determine the effects of atrazine treatment on 

aromatase activity in cells from estrogen sensitive target tissues in the ovary and 

endometrium. 

The effect of atrazine on aromatase activity was measured in human granulosa-lutein 

cell cultures, cells that abundantly express aromatase, and endometrial stromal cell 

(ESC) cultures, cells that do not express aromatase. Aromatase activity was quantified 

by the tritiated water method and the specificity of the assay was confirmed by coincubation with 4-hydroxyandrostenedione, an irreversible inhibitor of the catalytic 

activity of aromatase, to block the formation of tritiated water. The cells were treated for 

24 hours with increasing concentrations (1 nM to 1μM) of atrazine. Prostaglandin E2

(PGE2, 1 μM) and vomitoxin (a selective cyclooxygenase-II inducer, 250 mg/ml) were 

used as positive controls. 

In the granulosa-lutein cell cultures, atrazine treatment induced a dose-dependent 

increase in aromatase activity (p=0.007). Aromatase activity in atrazine treated (1 nM0.1 mM) granulosa-lutein cells (GC) was increased more than 2-fold compared with 

control cultures, with significant aromatase activities at 0.1 and 1.0 μM. Atrazine 

treatment had no effect on ESC aromatase activity at any concentration tested. 

Atrazine treatment had no effect on GC or ESC protein concentrations, which indicated 
Page 155 of 263 

no change in cell number, suggesting that the atrazine induced changes in aromatase 

activity were not due to cell proliferation. The positive controls PGE2 (1.0 μM) and 

vomitoxin (250 ng/ml) induced a significant increase in aromatase activity (132 ± 10 and 

149± 13% of control, respectively, p<0.05). There was also no effect of atrazine 

treatment on human recombinant aromatase activity in cell free test system. It was 

concluded that μM concentrations of atrazine can increase aromatase activity of human 

granulosa cells but not ESC and this effect is not elicited at the enzyme level. 

Reviewer’s Comments: The authors concluded that atrazine treatment induced an 

increase in aromatase activity in human luteinized granulosa cells, however, the 

concentrations needed to induce the observed change is considered to be outside the 

range likely to be achieved in human tissues and, therefore, is unlikely to pose a health 

threat through this mechanism. 

A.4.8 Laville N, Balaguer P, Brion F, Hinfray N, Casellas C, Porcher 

JM, Ait-Aissa S. (2006). Modulation of aromatase activity and mRNA 

by various selected pesticides in the human choriocarcinoma JEG-3 

cell line. Toxicology. 228:98-108. 

This study evaluates 30 pesticides for their ability to modulate aromatase activity in the 

human choriocarcinoma JEG-3 cell line. Pesticides were selected based upon chemical 

structure and environmental relevance, but also included a number of known aromatase 

inhibitors and inducers. Atrazine was among one of the reference pesticides used in 

this study. By using the tritiated water release assay after both short (2 hr) and long 

(24hr) exposures to each test chemical, the authors were able to identify either inhibition 

or induction (requiring longer term exposure) of aromatase enzymatic activity. 

Pesticides that were newly found to induce aromatase activity were further evaluated for 

their action at the transcriptional level with measurement of CYP19 mRNA and through 

the retinoic acid receptor signaling pathway. 

JEG-3 cells were seeded in 24-well plates, density of 50,000 cells/well, and allowed to 

attach for 24 hrs. before changing media and exposing the cells to the test chemicals (1, 

3, 10 uM) for an additional 24 hrs. Media was collected at the end of the exposure 

period, cells were washed once with media, and further elevated for aromatase activity. 

The tritiated water release assay was used to quantify aromatase activity in cells 

exposed to test chemicals for 24 hrs (to detect possible effects of chemicals on 

aromatase gene expression, or changes at transcription or (post) transcription levels), 

and in untreated cells exposed to the test chemical for only 2 hrs (e.g., direct 

competitive effects on the aromatase enzymatic complex). OH-Androstenedione, an 

irreversible inhibitor of aromatase activity was used to demonstrate time- and 

concentration-dependent inhibition. Forskolin and TTNPB were used as positive 

controls for up-regulation of aromatase expression. Cell viability was determined using 

the methyl-thiazol-tetrazolium (MMT) assay. 
Page 156 of 263 

Reviewer’s Comments: While neither atrazine nor forskolin had any effect on aromatase 

activity following a 2 hr exposure, both of these chemicals increased aromatase activity 

after 24 hrs of exposure. Approximately a 2-fold increase in aromatase activity was 

observed in cells treated with 10 uM atrazine, but no change in CYP19 mRNA was 

observed. 

Atrazine: JEG3 cells, doses 1, 3, and 10 uM (24 hrs) 

 LOEL: 10 uM NOEL: 3 uM 

Strengths of study: Use of positive controls to demonstrate specificity of aromatase 

assay and CYP19 mRNA measurements. This study supports other 

in vitro studies demonstrating that atrazine does not alter aromatase enzyme 

competitive inhibition, but rather requires longer exposure time such that enzyme 

stability, synthesis and/or post-transcriptional events can be altered. 

A.4.9 Rayner, J., Wood, C., and Fenton, S. (2003) Exposure 

Parameters Necessary for Delayed Puberty and Mammary Gland 

Development in Long-Evans Rats Exposed in Utero to Atrazine. 

Toxicology and Applied Pharmacology 195:23-34. 

This study looked at the effects on delayed puberty and mammary gland development 

in rats exposed in utero to atrazine.16 Groups of 20 timed-pregnant Long-Evans rats 

were gavaged on gestational days (GD) 15-19 with atrazine (purity 97.1%) at doses of 

100 mg/kg bw or vehicle control (C). On PND 1, half of each litter was cross-fostered, 

creating four treatment groups: C-C, ATR-C, C-ATR, and ATR-ATR (dam-milk source, 

respectively). Litters were weighed and equalized to 10 pups on PND4. On PND 22 

(weaning), animals were weighed and separated into 2-4 females/cage. Some females 

were sacrificed on PND 4, 22, 33, 40 and 58. The data from a treated-dam’s offspring 

were evaluated with the dam (two pups/dam or litter) as the experimental unit, with the 

exception of vaginal smears. 

 

On PND 29 females (n>29/group) were evaluated for vaginal opening (VO). The PND 

of complete VO and body weight on that day were recorded. Daily vaginal smears were 

collected beginning the day after VO for each animal until PND 58 to determine cyclicity 

patterns. Female pups (n=14-16) were sacrificed on PND58. Blood was collected and 

the pituitary gland, ovaries, and uterus were weighed and prepared for histopathology. 

Serum luteinizing hormone (LH), prolactin (PRL), and thyroid stimulating hormone 

(TSH) were analyzed. 

Pups in the ATR-ATR group were statistically significantly smaller than those in the 

control group on PND4 (p<0.01) (8.2±0.1 g ATR-ATR vs 8.7±0.1g, C-C), however, their 

mean weight was reduced 5.7% from control animals, which was within normal range. 

 

16 This review will concentrate on the assessment of delayed puberty onset. The discussion of the 

mammary gland development will be deferred until the September SAP meeting. 
Page 157 of 263 

There was no difference in body weight among groups at PND 22, 33, 40 or 58. A 

significant delay (p<0.02) in VO was seen only in animals nursing from ATR-treated 

dams (C-ATR 35.4±0.6 days, and ATR-ATR 37.1±0.5 days vs C-C 33±0.4 days). Mean 

body weight on day of VO was significantly (p<0.002) increased in the ATR-ATR group 

(~10%, estimated from graph), but not in the C-ATR group, compared to C-C group. 

There were no significant differences in the number of consecutive normal estrous 

cycles between VO and PND 58 or in the number of animals demonstrating persistent 

estrous (PE) or persistent diestrous (PD). However, while not statistically significant, 

there appeared to be a lower number of animals with irregular cycles in the ATR-ATR 

group (3%), compared to controls (23%) and the number of animals with normal cycles 

(2-5 days) appears to be increased in the ATR-ATR animals, compared to controls. 

No significant treatment-related changes were seen in circulating hormones (serum LH, 

PRL, and TSH) in any treatment group at PND 33, 40 or 58. 

At PND 58, all atrazine exposure groups had increased pituitary glands; however only 

the pituitary glands of the animals in the ATR-ATR group were significantly increased, 

compared to controls. There were no statistically significant differences in reproductive 

organ weights among the groups. 

Reviewer’s Comments: The researchers in this article demonstrate that atrazine in 

utero and perinatal exposure to atrazine can lead to a delay in vaginal opening in 

female rats. These findings are consistent with those reported by Laws et al. in 2000 

and 2003. It should be noted, however, that these effects are seen at substantially 

higher dose levels than those used as points of departure in the Agency’s human health 

risk assessment. 

A.4.10 Suzawa, M and Ingraham, HA. 2008. The herbicide 

atrazine activates endocrine gene networks via non-steroidal NR5A 

nuclear receptors in fish and mammalian cells. PLoS ONE 3(5): 

e2117. doi:10.1371/journal.pone.0002117. 

* In this evaluation, only the results pertaining to mammalian cells are discussed. 

The purpose of this in vitro study was to examine the potential effects of atrazine on 

NR5A receptors (steroidogenic factor 1 or SF-1). The specific interest was on whether 

Cyp19A1 (aromatase), a known target of NR5A receptors would be selectively activated 

by atrazine. The focus on SF-1 was a result of the two papers by Fan et al., who 

argued that this NR5A receptor was the target molecule for atrazine evoking changes in 

aromatase activity and potentially the molecular mechanism for many assumed adverse 

outcomes following exposure to this herbicide in vivo. Cellular reporter assays, utilizing 

JEG3 human placental cells, were performed. JEG3 cells contain modest amounts of 

SF-1. In one experiment, the effects of in vitro atrazine on luciferase activity after 

transfection of human placental JEG3 cells with aromatase-luciferase reporter and the 

parent reporter (pGL3-luciferase) with mSF-1 (mouse SF-1) and hLRH-1 (human liver 

receptor homolog) expression vectors were examined. The data revealed a dose-
Page 158 of 263 

dependent increase in luciferase activity which the authors interpreted as activation of 

aromatase promoters. The effects were significant at atrazine concentrations of ≥ 1 

μM. No activation was reported for the parent reporter or with mutant SF-1 binding 

sites. Atrazine also activated mSF-1 in HepG2 (human liver) cells. The authors also 

provided data demonstrating activation of other SF-1 reporters, such as MIS-Luc, StARLuc, and HSD3B-Luc. The authors concluded that atrazine effects depend on DNA 

binding and receptor occupancy of the promoter. 

In a knock-down experiment, the authors provided results showing knocking-down 

hLRH-1 in human HepG2 liver cells attenuated atrazine-induced activation of the 

aromatase reporter, which the authors interpreted as demonstrating a dependence on 

this NR5A receptor. In addition, they conclude that all NR5A subfamily receptors will be 

responsive to atrazine. 

Atrazine treatment was without effects on the estrogen responsive zcyp19a2 (ERE-Luc 

reporter). No significant activation of NR5A was observed with other estrogenic 

compounds tested. 

Several additional experiments were performed to determine the underlying cellular 

mechanisms of activation of NR5A receptors. These included mitogen-activated protein 

protein kinase (MAPK), phosphatidyl 3-kinase (Pl3K), G proteins, phospholipase C 

(PLC) in JEG3 cells. Pharmacological inhibitors of these systems were examined. The 

results indicated that inhibitors of both the MAPK and Pl3K signaling decreased 

activation by atrazine, whereas the inhibitors did not affect G protein or PLC signaling. 

The finding of phosphorylation of AKT/protein kinase B provided further support for 

effects on MAPK and Pl3K signaling. Atrazine (≥ 1 μM) significantly increased cAMP 

levels in JEG3 cells. 

The authors also assessed whether or not atrazine binds directly to SF-1 to either 

increase DNA binding or act as a ligand. Atrazine had no effect on DNA binding activity 

to a high affinity SF-1 binding site (the mMIS binding site was used). Atrazine also did 

not activate a Gal4-SF-1 ligand binding domain fusion construct. The authors 

concluded that these results suggest that atrazine may not directly interact with NR5A 

receptors, but instead activates three signaling pathways known to activate NR5A 

receptors, including phosphorylation of SF-1, generation of SF-1 ligands, and increased 

production of cAMP. The authors also reported that atrazine can increase a cluster of 

genes involved in endocrine signaling in specific cell types; however, very limited data 

were presented to corroborate these findings. 

Reviewer’s Comments: Overall, this study provides some preliminary research on the 

underlying cellular mechanism of aromatase expression following atrazine in vitro

treatment. The study has limitations including lack of details on methodology of 

luciferase activity and transfection of cells. Only a few poor quality results of PCR 

analyses and western blots were provided to corroborate the findings. The authors 

made several references to “data not shown” to support their conclusions. The 
Page 159 of 263 

activation of important second messenger pathways, and lack of evidence for direct 

binding to SF-1 does not support the reports of Fan et al., who conclude that atrazine 

has a direct SF-1 mediated activation of aromatase and subsequently increase estradiol 

production. The results indicating an indirect activation of aromatase are also in 

agreement with the observations of Higley et al reviewed above. The experiment 

examining the effect of atrazine on zebra fish was previously reviewed by the Agency 

and numerous deficiencies were identified. 

A.4.11 Yi D K, Kim P J, et al. 2010. Dose- and time-dependent 

effect of atrazine or its metabolites on aromatase mRNA in vitro. 

Only a preprint of article available.

The purpose of this study (available only as a preprint) was to examine the potential 

effects of dose and duration of exposure to atrazine and its metabolites 

(diaminochlorotriazine, DACT; deethyl atrazine, DEA; deisopropyl atrazine, DIA) in vitro

on the expression of aromatase mRNA in two steroidogenic lines, i.e., human 

adrenocortical cancer cells (H295R), and human placental carcinoma cells (JEG3). 

There were no details in the methods section of the article pertaining to the 

concentrations used and the duration of treatment. Based on information in the abstract 

and figures, atrazine and metabolites (all were reported to be 97% purity and dissolved 

in DMSO) were administered in vitro at equimolar concentrations of 0, 100 nM, 1 μM or 

10 μM for 15 minutes to 72 hours. There were descriptions of cell cultures, RNA 

extraction and cDNA synthesis, primer design, reverse transcription PCR, and statistical 

analyses. 

Exposure to 10 μM atrazine increased aromatase mRNA expression in H295R cells 

approximately 2.2 fold after 2 hours and approximately 3-fold after 4 to 24 hours. 

Aromatase mRNA expression was increased about 2.5 fold at 48 hours and 2.2 fold 

after 72 hours. At 1 μM atrazine, there was about a 2-fold increase in aromatase mRNA 

expression at 24 hours but not at other time points. No expression was observed at the 

low concentration of atrazine. 

Exposure of H295R cells to 10 μM DEA increased aromatase mRNA approximately 1.5-

fold after 2 to 24 hour time period. Exposure of H295R cells to 10 μM DIA increased 

aromatase mRNA approximately 1.8-fold after 2 to 48 hour time period. There were no 

apparent treatment-related effects with hydroxyatrazine and DACT. 

Reviewer’s Comments: The authors concluded that exposure to 10 μM atrazine in vitro

resulted in an increased expression of aromatase mRNA. This in vitro response is 

dose- and time-dependent with peak expression occurring after 4 to 24 hours of 

exposure. Atrazine metabolites, DACT and hydroxyatrazine, failed to show a 

consistent response. 
Page 160 of 263 

A.4.12 Yi, KD, Perez, EJ, Breckenridge, CB, and Simpkins, JW 

(2010?) Ex vivo effects of atrazines or metabolites on 

phosphodiesterase activity.

This study concentrated on phosphodiesterase (PDE) activity and whether atrazine and 

its metabolites inhibit this process, while also noting effects on aromatase in vivo. It 

provides several theories on the possible MOA regarding the incidence of mammary 

tumors, delayed onset of puberty, and immune suppression. 

The premise that there is an alternative MOA for mammary tumors in female SpragueDawley rats is that mRNA expression and aromatase activity was increased in H295R 

adrenocortical carcinoma cells when exposed to a minimum of 10μM atrazine. 

Increased cyclic AMP (cAMP) levels were correlated with the induction of aromatase 

activity by atrazine; increases in cAMP may be mediated either via increases in adenylyl 

cyclase which catalyzes the conversion of ATP to cAMP, or via the inhibition of PDE 

which catalyzes the breakdown of cAMP to AMP. Therefore, high concentrations of 

atrazine in vitro may be mediated by increases in intracellular cAMP, activating adenylyl 

cyclase, or by inhibiting PDE. 

Atrazine, deethyl atrazine (DEA), deisopropyl atrazine (DIA), diaminochlorotriazine 

(DACT), ammeline (AM), and hydroxyatrazine (hydroxyl-ATZ) used were approximately 

97% pure. IBMX, 3-isobutyl-1-methylxanthine was used as the positive control. The 

IMAP phosphodiesterase assay kit was used along with bovine PDE at varying 

concentrations (0.000025 to 0.5 PDE U/ml in 96-well plates). To determine the effects 

of addition of atrazine after completion of the PDE reaction, an hour long incubation 

period was allowed and then to assess the effects of atrazine and its metabolites on 

PDE activity, the potential inhibitors were added at concentrations ranging from 5pM to 

5 nM in 10 μl of assay buffer enzyme with additional 90 minute substrate/incubation 

period. Competitive inhibition studies were similarly conducted with the addition of 

varying concentrations of DACT with atrazine. Determining IC50 values was done using 

a 4-parameter log curve and creating sigmoidal standard curves. 

The results from the optimized assay for PDE inhibition showed a concentrationdependent increase in the relative fluorescence output of the assay at both 30 minutes 

and 2 hours after the addition of the binding reagent. Maximal output, of 0.025 PDE 

U/ml was used for all subsequent assays. Addition of atrazine after completion of the 

enzymatic reaction didn’t have any effect on the fluorescence output of the assay. 

Regarding the effects of atrazine and to a much lesser extent its metabolites inhibited 

PDE in a cell-free system. The IC50 for atrazine (39.52 μM) while for IBMX it was 1.749 

μM. The IC50 for DIA was 1371 μM and DEA at 7156 μM were 35 and 181-fold less 

potent inhibitors of PDE than was atrazine; all other metabolites were inactive. DACT, 

however dose-dependently caused a rightward shift in the dose-response curve of the 

atrazine mediated inhibition of PDE activity suggesting to the authors that although 

DACT does not inhibit PDE out right, it perhaps modifies the effect of atrazine on PDE. 
Page 161 of 263 

Also at both 5 and 50 μM concentrations of DACT, the IC50 of atrazine was several folds 

higher, suggesting competitive inhibitory effects of DACT. 

The authors concluded that atrazine at all concentrations which exceed its aqueous 

solubility limits, is a weak inhibitor of PDE and that its metabolites have extremely weak, 

or no effect on PDE activity. The primary metabolite of atrazine, DACT was shown to 

act as a competitive inhibitor of atrazine-induced inhibition of PDE activity. Although, 

not supported, the authors elude to the possibility that the inhibition by atrazine of PDE 

in ex vivo condition, a cell-free system with a complex mixture of different PDE 

isozymes and substrate, could be due to a non-specific effect of the precipitate on the 

kinetics of the reaction. The IC50 for atrazine-mediated inhibition of PDE activity in this 

study (40 μM) was vastly different, 22-fold higher, form the concentration reported by 

Roberge et al (2004). No true rationale was given for this discrepancy – however, they 

went on to describe the many similarities in results from the two laboratories. Even at 

high concentrations of atrazine there have been no shown increases in aromatase 

mRNA or enzyme activity in vivo with the exception of a study on juvenile zebrafish. 

Therefore the study concludes that a general or local increase in the expression of this 

enzyme in vivo, would not account for the observed effects of high doses of atrazine on 

estrous cycles, mammary tumors or the age of onset of puberty. 

Reviewer’s Comments: In mammals, atrazine is NOT acutely toxic (oral LD= 3090 

mg/kg) and is only moderately toxic following repeat dosing to rats, mice, rabbits, or 

dogs. Atrazine-mediated inhibition of PDE ex vivo is unlikely to account for the tissue, 

sex, strain and species-specific effects of chronic high-dose exposure to atrazine. The 

bottom-line is that it is unlikely that an atrazine-mediated inhibition PDE activity would 

occur at environmentally relevant concentrations. The potential human exposure to 

atrazine is low and equally unlikely to result in PDE inhibition in humans. The study 

goes on to endorse the NOEL (1.8 mg/kg/day) which is currently used to regulate 

chronic exposure to atrazine and its chlorometabolites and appears to be protective of 

any potential effects in humans. 

A.5. Neurotoxicity 

A.5.1 Belloni V, Alleva E, et al. 2007. Effects of low doses of 

atrazine on the neurobehavioural development of mice. Ethology 

Ecology & Evolution 19: 309 – 322. 

The authors stated that the aim of their work was to study possible neurodevelopmental 

effects of perinatal exposure to low, environmentally relevant doses of atrazine in 

mouse pups. Specifically, the focus was on somatic parameters and a wide range of 

reflexes to assess sensorimotor maturation. 

The authors noted that mice of an outbred Swiss-derive strain (CD-1) were used in the 

study; no details on age or body weights were provided. Breeding pairs were formed, 
Page 162 of 263 

and on GD 12, males were removed and females housed singly. GD 14 females were 

assigned to one of three treatment groups: control (received corn oil); low-dose 

atrazine (1 μg/kg/day) and high-dose atrazine (100 μg/kg/day). Atrazine (98.4% purity) 

was dissolved in corn oil and administered daily to female mice by self administration 

drinking from a modified syringe. The authors stated that the procedure was not 

stressful since the animals were previously trained to drink from the apparatus. The 

treatment period began GD 14 until PND 21. The pups were not treated directly and 

were only exposed by transplacental transfer or via lactation. On PND 2, litters were 

culled to 8 per litter, 4 males and 4 females. 

For behavioral testing, two male and two female pups from 32 different litters were used 

for postnatal assessment of somatic and neurobehavioral development. A total of 128 

mice were subjected to behavioral testing between 2 and 15 days of age. Assessment 

of somatic growth and sensorimotor development included the following parameters: 

righting reflex, cliff aversion, forepaw grasp, and auditory startle. Only brief descriptions 

of these tests were provided. Scoring was as follows: 0, no response; 1, uncertain; 2, 

incomplete; and 3, full. On PND 2, 4, 9, and 12, pups were weighed. 

Evaluation of pup vocalizations (ultrasonic calls) was also performed on PND 4, 9, and 

12. The authors provided adequate details on this evaluation. A spectrographic 

analysis of ultrasonic calls was also performed on PND 9 (which the authors mention is 

the peak day in the ontogenetic profile of ultrasonic vocalization). In addition, body 

temperature was recorded on PND 4, 9, and 12. 

The authors reported that there were no differences in dam body weight gain during 

gestation. A pup body weight decrease of approximately 8% was noted in both atrazine 

treatment groups compared with the control group on PND 2; no effects were noted at 

PND 4, 9 and 12. Righting reflex (expressed as “day of full response”) was delayed in 

the high-dose atrazine group (mean of 6.60 vs. control mean of 4.60). There was an 

acceleration of forepaw grasp (“day of full response”) in the low-dose atrazine group 

(mean of 5.18) and high-dose atrazine group (mean of 5.25) in comparison with the 

control group (mean of 7.50). 

On PND 9, mean body weight temperatures were significantly lower in the males and 

females of the low-dose atrazine group (5% decrease in males; 4% decrease in 

females) when compared with controls. There were no significant changes on PND 4 

and 12 and no significant changes in the high-dose group. 

Reviewer’s Comments: The authors indicated that were was a tendency towards a 

decrease in the mean number of ultrasonic calls in atrazine-treated pups when 

compared to controls on PND 9. However, the data (in contrast to controls) show a 

decrease (not statistically significant) in atrazine-treated females (both low and high 

dose groups) and only the low-dose group for atrazine-treated males. Moreover, the 

decreases in mean number of ultrasonic calls in atrazine-treated females on PND 9 did 

not display a clear dose-response relationship. Based on spectrographic analyses of 
Page 163 of 263 

the ultrasonic calls, the authors claim that there was a tendency towards a longer 

ultrasonic call mean interpulse (seconds) in atrazine-treated animals compared to 

control groups. However, the data indicate that this tendency was only apparent in the 

low-dose atrazine group of females or when data from males and females were 

combined. No differences were noted in the high-dose atrazine groups, whether data 

are presented as sex specific or combined. Peak frequency was slightly (not 

statistically significant) increased in atrazine-treated males (low and high dose groups) 

and in atrazine-treated females (just the high dose group). 

The authors concluded that exposure to low doses of atrazine during the fetal and 

suckling period interferes with some aspects of somatic growth of pups in a reversible 

manner, and more clearly with their neurobehavioral development. However, this study 

has serious deficiencies and flaws. The primary problem entails the inappropriate 

sampling of pups from litters and the statistical evaluation of the data. The authors fail 

to account for the potential effects of litter, and the key results reported by the authors 

rely on only individual pup measurements which inflates sample size. The failure to 

account for litter effects can result in increased type 1 errors and overestimate any 

effects, thus reducing the validity of the findings of the study. 

In addition to inappropriate statistical analyses, there were unexplained discrepancies in 

the sampling of pups from litters. For instance, a lower number of pups were evaluated 

for somatic growth and sensorimotor development, body temperature, and ultrasonic 

call emittance compared to the actual number of pups available. For the spectrographic 

analyses of ultrasonic vocalization, not only were significantly less animals evaluated in 

contrast with the assessment of mean ultrasonic calls, but the reported total numbers of 

pups evaluated did not match the total reported for males and females separately. The 

number of animals evaluated for spectrographic analyses of the ultrasonic calls should 

match the numbers evaluated for the mean number of ultrasonic calls. 

Other deficiencies of the study include a lack of details on the procedures used for 

assessment of somatic growth and sensorimotor development, a lack of inclusion of 

positive controls that would support the reliability of the methodology, the lack of 

objective and validated behavioral tests, lack of neuropathology, and the lack of actual 

spectrograms to corroborate the spectrographic results. The serious deficiencies of 

these studies raise questions about the validity and reliability of the data and its use for 

risk assessment purposes. 

A.5.2 Coban A, and Filipov, N M. 2007. Dopaminergic toxicity 

associated with oral exposure to the herbicide atrazine in juvenile 

male C57BL/6 mice. Journal of Neurochemistry 100: 1177-1187. 

The objectives of this study were to determine the following: (1) the effects of atrazine 

exposure on striatal neurochemistry and striatal expression of tyrosine hydroxylase; (2) 

whether atrazine effects on striatal neurochemistry are associated with dopaminergic 
Page 164 of 263 

neuron loss; and (3) whether the neuronal loss is permanent and specific to the 

substantia nigra pars compacta. 

One-month-old male C57BL/6 mice were administered atrazine (5, 25, 125, and 250 

mg/kg/day) by daily gavage for 14 days. Several indices of neurotoxicity were 

evaluated on days 15, 22 or 64. Dopamine and its metabolites, 3, 4-

hydroxyphenylacetic acid (DOPAC), and homovanillic acid (HVA) were measured by 

high performance liquid chromatography. Striatal tyrosine hydroxylase levels were 

determined by western-blot analysis. Fixed half-brains were used to analyze neurons in 

the substantia nigra pars compacta and ventral tegmental area by 

immunohistochemistry/unbiased stereology. 

No effects of atrazine treatment on body weights were reported (data not shown). 

Atrazine at doses of 125 and 250 mg/kg decreased (dose dependently) striatal 

dopamine (approximately 80 ng/mg protein at 250 mg/kg vs. 100 ng/mg protein in 

controls), DOPAC (approximately 6 ng/mg protein at 250 mg/kg vs. 5 ng/mg protein in 

controls) and HVA (approximately 6 ng/mg protein at 250 mg/kg vs. 8 ng/mg protein in 

controls) levels on day 15. There was no difference between control and atrazinetreated animals in striatal dopamine levels at day 22. Slight decreases in DOPAC and 

HVA were present at day 22. At day 64, there were no statistically significant effects on 

DOPAC and HVA. There were no effects of atrazine treatment on striatal levels of TH 

as determined by western blot analysis. 

On day 15, there was a decrease in the number of TH-positive neurons in both the 

substantia nigra pars compacta and ventral tegmental area. The loss of neurons was 

statistically significant at 250 mg/kg/day (the high dose). At day 22, the loss of neurons 

in the substantia nigra pars compacta was significant at 25 mg/kg/day dose. In regard 

to the ventral tegmental area, there was a significant decrease in the number of THpositive neurons at days 14 and 22. The decrease in the ventral tegmental area was 

reported to be 19% in contrast to a 32% decrease in the substantia nigra pars 

compacta. On day 64, atrazine exposure decreased the number of TH-positive neurons 

in both the substantia nigra pars compacta and ventral tegmental area, with the overall 

effect being significant at all dose levels in the ventral tegmental area. The authors 

reported that at 64 days, the effect on the neurons in the substantia nigra pars 

compacta at the high dose was only marginally greater than the effect in the ventral 

tegmental area (33% cell loss in substantia nigra pars compacta vs. 28% cell loss in the 

ventral tegmental area). 

Reviewer’s Comments: There are several limitations with this study: 

• The reason for a lack of a dose-response relationship with respect to the number 

of TH+ neurons is not clear. The study did not include a positive control such as 

6-hydroxydopamine which produces dose dependent alterations in dopamine 

and dopamine metabolites and loss of tyrosine hydroxylase-immunoreactive cells 

in the substantia nigra. 
Page 165 of 263 

• The results reported for the atrazine-induced TH+ neuronal cell numbers (only 

bar graphs presented) cannot be corroborated since there was no presentation of 

photomicrographs of brain sections to correlate with the findings presented in the 

bar graphs. Also, there was no information on the calibration of the stereological 

test system. The only statement on the precision of the estimate of neuronal 

counts was the calculation of a Gundersen coefficient of error. 

• No histological examination of the substantia nigra and ventral tegmental area 

was performed; this would provide insight into any morphological alterations to 

support their cell number data. 

• The dose-response relationships with regard to dopamine and dopamine 

metabolite levels were flat. Also, the decreases were slight even at the two 

highest doses tested (i.e., 125 and 250 mg/kg/day). A positive control, for 

example, 6-hyroxydopamine (discussed above) was not included in the study. 

• There were no functional assessments of the dopaminergic alterations, for 

example, assessment of behavior and motor activity to correlate with the 

neurochemical findings. 

• Neurochemical analyses were not performed for the ventral tegmental area 

which would have provided some support for the observed findings of the loss of 

dopaminergic neurons in this region. 

• Coban and Filipov also presented data for days 22 and 64 of the experiment 

revealing only slight changes in the dopamine metabolites DOPAC and HVA at 

day 22 (flat dose response) and no alterations in dopamine and its metabolites at 

day 64. However, these data (i.e., Figure 3 on page 1182 of the study) are 

contradicted by the description of the data in which the authors state that the 

“some of the animals received MPTP on day 15” (no further details provided). 

MPTP has been associated with a Parkinsonian-like syndrome, and it is not 

certain if the word MPTP was a typographical error, if MPTP was meant as a 

possible positive control (not discussed in methods or any other section) or if the 

wrong results were presented. If MPTP was included as a positive control it is 

not clear why it was not administered to mice at the same treatment start time as 

atrazine. 

A.5.3 Filipov N M, Stewart M A et al. 2007. Dopaminergic toxicity of 

the herbicide atrazine in rat striatal slices. Toxicology 232: 68 – 78. 

This in vitro study examined the effects of atrazine treatment of various aspects of 

dopamine metabolism in rat striatal slices. Striatal tissues from adult male SpragueDawley rats were incubated with up to 500 μM atrazine for 4 hours. The following were 

evaluated: tyrosine hydroxylase activity using L-DOPA accumulation as an indicator, 

high potassium-stimulated dopamine release, media dopamine levels in the presence of 

the dopamine uptake blocker nomifensine, and striatal dopamine metabolism. In 

addition, the effects of in vitro exposure to atrazine on LDH levels was performed to 

determine if any potential dopaminergic effects are caused by non-specific cytotoxicity. 
Page 166 of 263 

Dopamine and metabolites, 3,4-hydroxyphenylacetic acid (DOPAC) and homovanillic 

acid (HVA) were measured. 

Atrazine treatment at concentrations of 100 μM or greater resulted in a dose-dependent 

decrease in tissue levels of dopamine. At 50 μM or greater concentration of atrazine, 

DOPAC + HVA/DA ratio was dose-dependently increased. Tyrosine hydroxylase 

protein levels and activity were not affected by atrazine treatment. However, atrazine 

decreased high potassium-induced dopamine release; the increase in media dopamine 

in the presence of nomifensine was increased even further by atrazine in a dosedependent manner. These effects were observed at levels that were not toxic to the 

tissue. The authors concluded that their results suggest that atrazine decreases tissue 

dopamine levels not by affecting tyrosine hydroxylase activity, but possibly by interfering 

with the vesicular storage and/or cellular uptake of dopamine. 

Reviewer’s Comments: The results revealed that atrazine, in vitro, alters striatal 

dopamine levels possibly by interfering with the vesicular storage and/or cellular uptake 

of dopamine. Tyrosine hydroxylase per se is not a target of atrazine. The relevance of 

these in vitro data to dopaminergic mechanisms in vivo is not clear given the high 

concentrations of atrazine examined in vitro and the complex interactions between 

various neurotransmitter and endocrine systems in the intact brain. The effects of 

atrazine on aromatic amino acid decarboxylase, monoamine oxidase and neuronal 

mitochondrial function are unknown. 

A.5.4 Foradori, C D, Hinds, L R, et al. 2009. Atrazine inhibits 

pulsatile luteinizing hormone release without altering pituitary 

sensitivity to a gonadotropin-releasing hormone receptor agonist in 

female wistar rats. Biology of Reproduction. 81: 40 – 45. 

The objectives of this study were to examine the effects of atrazine on normal tonic 

release of luteinizing hormone (LH) and to elucidate the site of action of atrazine in the 

hypothalamic-pituitary-gonadal axis. To assess potential effects of atrazine on pulsatile 

LH release, ovariectomized adult female Wistar rats were administered atrazine (50, 

100, or 200 mg/kg/day by gavage) or vehicle (1% carboxymethylcellulose sodium salt) 

control for 4 days. At termination, blood samples were obtained using an indwelling 

right atrial cannula (implanted on second day of treatment). Samples were examined 

for LH levels. There was a significant reduction in LH pulse frequency and a 

concomitant increase in pulse amplitude in the 200 mg/kg/day group. 

The second experiment involved validation of a protocol for GnRH immunoneutralization 

and pituitary response to GnRH agonist. Utilizing the same experimental procedure 

above, animals were administered GnRH antiserum via cannula to block the actions of 

endogenous GnRH. The anti-GnRH serum was prepared against keyhole limpet 

hemocyanin-conjugated GnRH. Following blood sampling, animals were treated with 

one of four doses of GnRH receptor agonist, D-Ala6

-des-Gly-NH2

10-GnRH-ethylamide 

(0.01, 0.1, 1.0, or 10 ng; 4-6 animals per treatment group). LH levels were measured. 
Page 167 of 263 

The results showed that LH levels were at or below the detection level of the assay in 

animals administered the GnRH antiserum, indicating that the effect of endogenous 

GnRH on the pituitary release of LH was suppressed. Administration of GnRH agonist 

resulted in dose-dependent increases in mean plasma LH levels. 

The third experiment entailed an examination of the effects of atrazine on in vivo 

pituitary response to GnRH agonist. The objective was to determine whether atrazine 

reduces pituitary sensitivity to a GnRH agonist. Ovariectomized rats were administered 

atrazine (0, 50, 100, or 200 mg/kg/day by gavage) for 4 days. On the second day of 

treatment, intra-atrial cannulae were implanted, and rats were treated with anti-GnRH 

serum via cannula. On the last day of treatment, sampling of blood was performed and 

D-Ala6-des-Gly-NH2

10-GnRH-ethylamide (0.1 or 1.0 ng) was administered via catheter. 

Sampling was continued for an additional 90 minutes. Atrazine-treated animals that had 

been immunoneutralized with the anti-GnRH serum showed an LH response 

comparable to that observed in the control group. Both doses of D-Ala6-des-Gly-NH2

10-

GnRH-ethylamide caused an increase in the circulating concentration of LH. However, 

there was no significant change in the levels of LH related to atrazine treatment. 

The authors concluded that although LH pulse period and amplitude were increased in 

atrazine-treated animals, the anterior pituitary function does not seem to be altered by 

atrazine, as LH levels were not reduced in atrazine-treated animals in response to a 

GnRH agonist after GnRH immunoneutralization. Additionally, the inhibition of LH 

pulses and the disruption of cyclicity in female rats treated with atrazine are likely to be 

mediated by interference with central mechanisms controlling GnRH release from the 

hypothalamus. The brain appears to be the primary target mediating the effect of 

atrazine on LH release in the rat. 

Reviewer’s Comments: The Foradori study provides added support for the hypothesis 

that atrazine targets the brain to modify the neuronal control of pituitary function. 

Evaluating the secretion of gonadotropin releasing hormone (GnRH) in rats revealed 

that atrazine alters the release of this neuropeptide from the brain. GnRH is essential for 

LH release from the pituitary. 

A.5.5 Foradori, C D, Hinds, L R, et al. 2009. Effects of atrazine on 

GnRH neuroendocrine function after its withdrawal in the adult 

female wistar rat. Biology of Reproduction 81(6): 1099 – 1105. 

The authors previously reported that atrazine treatment decreased LH pulse frequency 

and increased pulse amplitude in ovariectomized rats without changing pituitary 

sensitivity to a GnRH receptor agonist. The authors interpreted these results to 

suggest a neural site of atrazine’s action. In order to explore this possibility, the authors 

examined the effect of atrazine on the estrogen and progesterone-induced LH surge in 

freely moving, ovariectomized rats to determine if atrazine’s inhibition of LH secretion 

coincides with a reduction in GnRH neuronal activation. The immediate early gene 

product FOS (cFos) was colocalized in GnRH neurons as a measure of cellular activity. 
Page 168 of 263 

In addition, withdrawal studies were performed to determine whether LH levels and 

measures of GnRH neuronal activation would return to control levels following the 

termination of atrazine treatment. 

To examine the potential effects of atrazine on GnRH neuronal activation, 

ovariectomized young adult female Wistar rats were treated (by gavage in 1% 

carboxymethylcellulose sodium salt) once daily with atrazine (0, 50, 100, or 200 mg/kg) 

for 4 consecutive days, and were primed with 17beta-estradiol-3-benzoate and 

progesterone (EB + P) to induce LH surge. Near the peak of the predicted LH surge, 

animals (n=4-6) were anesthetized and perfused, and brains were removed. Brains 

were processed for GnRH and cFOS using immunohistochemistry. To determine if 

atrazine alone would have a stimulatory effect on GnRH neuronal activation, a second 

cohort of animals was treated similarly except that no hormones were given to induce 

GnRH and LH surges. For this part of the experiment, rats were treated with 50 mg/kg 

atrazine or vehicle for 4 days. To examine the effects of atrazine withdrawal on 

hormone-induced LH surge and GnRH activation, ovariectomized animals were given a 

4-day regimen of atrazine (200 mg/kg) by gavage. Control animals received vehicle 

only. An LH surge was induced in these animals either during the atrazine treatment 

period or 2 days or 4 days after the cessation of atrazine treatment. 

Atrazine treatment inhibited the EB+P LH surge at all doses. Atrazine also reduced the 

area under the curve (AUC) for the LH surge at all doses examined. Atrazine treatment 

did not affect peak FSH levels; however, atrazine treatment at 200 mg/kg reduced the 

AUC for FSH levels in this group. Treatment with 100 mg/kg and 200 mg/kg atrazine 

reduced the percentage of GnRH neurons immunoreactive for cFOS compared with the 

vehicle-treated and 50 mg/kg atrazine groups. There was no difference between the 

100 and 200 mg/kg atrazine groups. Treatment with 100 mg/kg and 200 mg/kg atrazine 

also reduced the mean number of GnRH neurons immunoreactive for FOS; there was 

no difference between these groups. The results also indicated that atrazine alone 

does not induce FOS immunoreactivity in GnRH neurons. 

Within 4 days (but not 2 days) after cessation of atrazine treatment, the reductions in 

GnRH activation and hormone-induced LH surge returned to control levels. 

The authors concluded that their data indicate that atrazine affects neuroendocrine 

function in the female rat by actions at the level of the GnRH neuron and that the acute 

effects of high doses of atrazine can be reversed within 4 days after withdrawal of 

treatment. The authors acknowledge that “it remains unclear whether atrazine acts 

directly on GnRH neurons or on one of many neurotransmitter containing neurons in the 

brain that are known to have a role in controlling the preovulatory surge of GnRH.” 

Reviewer’s Comments: This study provides further support to their previous findings 

(Foradori et al. 2009). 
Page 169 of 263 

A.5.6 Giusi G, Facciolo RM, et al. 2006. The endocrine disruptor 

atrazine accounts for a dimorphic somatostatinergic neuronal 

expression pattern in mice. Toxicological Sciences 89(1): 257 – 264. 

The intent of this study was to examine the potential effects of atrazine on various 

somatostatin receptor subtypes (in particular, SST2, 3, 5) including possible regional 

specificity in some hypothalamic and extra-hypothalamic estrogen-enriched brain 

regions. The authors provided a rationale for the selection of the somatostatin receptor 

subtypes. The authors noted that the widely distributed SST2, 3, 5 appear relatively early 

during development but also remain stable during adult life and exert a key role in the 

organization of the central nervous system. The authors also noted the role of 

somatostatin in the control of the secretion of growth hormone (GH) and the striking 

differences in GH release between male and female rodents. The authors stated that 

differentiated GH secretion may be due to gender-related differences in the transduction 

of somatostatinergic mechanisms in brain and/or pituitary targets. Finally, the authors 

concluded that the GH- and SST-dependent relationships “might provide further insights 

into the types of neurotoxicological mechanisms involved in the delay of the estrous 

cycle or the alteration of the hypothalamic-hypophyseal-gonadal axis in animals treated 

with atrazine (Wetzel et al. 1994).” The interest in regional specificity was based on the 

observations that altered SST levels have been reported for hypothalamic nuclei. 

Outbred Swiss-derived strain (CD-1) mice were used in the study. Gestation day (GD) 

14 females were divided into 2 groups: one group (low-dose) received 1ug/kg day 

atrazine via drinking water from a syringe, while the second group (high-dose) received 

100 ug/kg day atrazine. The authors noted that the procedure was monitored to make 

sure that pups did not attempt to drink the solution from the syringe. Treatment period 

was from GD14 to postnatal day (PND) 21. On PND 21, mothers were removed and F1 

mice of both sexes (n = 6 for both sexes) continued with the treatment protocol (control 

group was included). At PND 60 – 65, the animals were sacrificed and brains removed. 

Brain sections were prepared. Amino cupric silver staining was used for examining 

potential degenerative changes. Reverse transcription polymerase chain reaction was 

applied for the detection of SST2,3,5. In situ hybridization was utilized for mRNA. 

The authors reported a high-dose atrazine-dependent dimorphic neurodegeneration 

pattern based on the amino cupric silver staining results. The authors described the 

neurodegeneration as “a consistently evident argyrophilic reaction of axonal processes 

and perikarya in some extra-hypothalamic areas, specifically the external pyramidal 

neuron layer of the female hippocampal area, but not those of the male.” The authors 

also indicated that examination of another hippocampal field (i.e., the dentate gyrus), 

the neurons showed a rather significant overall reduction in the total number of neuronal 

cells accompanied by significant perikaryal swelling plus well-developed astrocytic 

formations in the female. The dimorphic pattern was also evident in the hypothalamus, 

as demonstrated by significantly darker axonal processes in the female arcuate 

hypothalamic nucleus. The dimorphic pattern was not observed in extra-hypothalamic 

areas such as the cortex or striatum. 
Page 170 of 263 

In the high-dose female group, the authors reported a very strong (p < 0.001) 

upregulation of sst2 expressing neurons in the female hypothalamic areas, specifically 

the suprachiasmatic nucleus (+110%) and ventromedial hypothalamic nucleus (+65%), 

whereas a similar downregulatory trend was noted in the some extrahypothalamic areas 

such as the striatum (- 96%) and central amygdaloid nucleus (-45%). In the high-dose 

male group, the authors reported very strong upregulatory and downregulatory actions 

for sst3 expressing neurons, with upregulation in the arcuate hypothalamic nucleus 

(+120%) and basolateral amygdaloid nucleus (+78%), and downregulation in the 

cortical areas ( - 88%) and dendate gyrus (- 105%). 

The authors concluded that the observed neurotoxicological effects of atrazine are “very 

likely linked to dimorphic expression patterns of specific somatostain subtypes in 

discrete but key hypothalamic and extrahypothalamic areas” of the mouse. 

Reviewer’s Comments: 

• There was a lack of details on the age at which mice were bred, the source and 

purity of atrazine, and the body weights of the animals, and systemic toxicity 

measurements were not performed. It is not clear if atrazine was dissolved in 

corn oil which was administered to the controls. It is also not clear if the treated 

animals received the same amount of solution (i.e., 0.1 ml) as was administered 

during a pretreatment period to train the mice to drink from a syringe. 

• Dams were treated with atrazine during gestational and lactational phases, 

however, there was no mention of standardizing litter sizes. Standardization of 

litter size would reduce between-litter variability. 

• Also, several of the reference citations did not match or support statements 

presented elsewhere in the study. For example, the reference to Surrales (1995) 

pertains to alachlor, mitocyn, and vinblastine. Gould et al. (1997) refers to 

research on polychlorinated biphenyl mixtures, not atrazine. 

• The few photomicrographs of the amino cupric silver staining results utilized to 

demonstrate critical neuronal degeneration were of very poor quality and not 

presented in color to portray the reactive staining, and were based on a small 

sample size, and only representative sections were provided. A “blind” 

evaluation was not performed. There was no presentation of count data (all 

stained reactive cells within an area) with statistical analyses to quantify the 

results of the reactive staining. Furthermore, no cell number data (with 

appropriate statistical analyses) were provided to support the claim that there 

was “a rather significant overall reduction in the total number of neuronal cells...”. 

Their claim cannot be confirmed without these data. 

• Only one representative photo on reverse-transcriptase polymerase chain 

amplification results was provided, and there was no mention if there was a 

control for possible genomic contamination in RNA preparations. 
Page 171 of 263 

• No rational basis to explain the purported differential neuronal expression and 

dimorphic sex effects was offered. For example, striatal neuronal degeneration 

was reported in both males and females (although the photomicrographs were 

too poor in quality to verify these findings), yet downregulation of 

somatostatinergic receptor subtype 2 (sst2) was noted only in the females. In 

other brain areas of the female there was upregulation of sst2. There were 

similar difficulties in correlating neuronal degeneration with differential expression 

of sst subtypes and dimorphic sex distribution in other brain regions, and no 

plausible biological mechanism to explain the pattern of effects was discussed. 

Moreover, the relevancy of these findings is not clear. 

• The study did not address the potential confounding by corticosterone. 

Based on the number of serious limitations and no other corroborative support in the 

literature, the preliminary results of this study are inconclusive. 

A.5.7 Hossain M M and Filipov N M. 2008. Alteration of dopamine 

uptake into rat striatal vesicles and synaptosomes caused by an in 

vitro exposure to atrazine and some of its metabolites. Toxicology 

248: 52 – 58. 

To better clarify the potential mechanisms of atrazine-mediated effects on striatal 

dopamine, this study examined the effects of atrazine on the vesicular and 

synaptosomal uptake of striatal dopamine, which may result in disrupted vesicular 

storage and/or cellular uptake of dopamine. The study design involved in vitro atrazine 

exposure using isolated rat striatal synaptosomes and synaptic vesicles. Besides 

atrazine, effects of atrazine metabolites, i.e., didealkly atrazine (DACT), desethyl 

atrazine (DE) and desiopropyl atrazine (DIP) were also investigated. Limited details 

were provided on the various methods such as preparation of synaptic vesicles and 

striatal synaptosomes, vesicular uptake of dopamine, and synaptosomal uptake of 

dopamine. 

 

Atrazine (1 – 250 μM) inhibited dopamine uptake into synaptic vesicles, and the 

inhibition was dose dependent. DACT did not affect vesicular dopamine uptake, while 

DE and DIP significantly decreased vesicular dopamine uptake. Kinetic analysis 

(nonlinear isotherm regression) of the vesicular dopamine uptake showed that atrazine 

decreased the Vmax parameter but not Km. 

Atrazine and DE increased (6 – 13%) synaptosomal dopamine uptake; DACT and DIP 

were without effect. Atrazine, DE and DIP increased the ratio of synaptosomal/vesicular 

uptake of dopamine. The authors concluded that atrazine and two of its metabolites 

(DE and DIP) decrease striatal dopamine levels, at least in part, by increasing cytosolic 

dopamine, which is prone to oxidative breakdown. The authors note that the effects of 

atrazine on aromatic amino acid decarboxylase, monoamine oxidase and neuronal 

mitochondrial function remain unknown. Previously, the authors (Filipov et al. 2007) 

showed that atrazine does not alter the function of tyrosine hydroxylase substantially. 
Page 172 of 263 

Reviewer’s Comments: The results revealed that atrazine, in vitro, alters striatal 

dopamine levels possibly by interfering with the vesicular storage and/or cellular uptake 

of dopamine. Tyrosine hydroxylase per se is not a target of atrazine. The relevance of 

these in vitro data to dopaminergic mechanisms in vivo is not clear given the high 

concentrations of atrazine examined in vitro and the complex interactions between 

various neurotransmitter and endocrine systems in the intact brain. The effects of 

atrazine on aromatic amino acid decarboxylase, monoamine oxidase and neuronal 

mitochondrial function are unknown. 

A.5.8 Rodriguez V M, Thiruchelvam M, Cory-Slechta D A. 2005. 

Sustained Exposure to the widely used herbicide atrazine: altered 

function and loss of neurons in brain monoamine systems. 

Environmental Health Perspectives. 113(6): 708-715. 

The purpose of this study was to examine the hypothesis that atrazine adversely affects 

brain dopamine systems, in particular, the nigrostriatal and mesocorticolimbic pathways. 

In addition, the underlying mechanisms of any potential changes in dopamine function 

in these pathways were explored by examining the acute effects of atrazine on striatal 

dopamine release. 

In the chronic phase of the study, 30 male Long-Evans rats (9 months of age) were 

exposed via the diet to 0, 5 or 10 mg/kg/day atrazine for 6 months. Body weights and 

food consumption were monitored throughout the study. Locomotor activity was 

recorded at 2, 3, and 6 months of atrazine treatment and 2 weeks after cessation of 

treatment. At the 2-month time point, locomotor activity was measured on 3 

consecutive days, in which the rats were injected saline intraperitoneally 5 minutes 

before the session during the first 2 days, and an injection of 1 mg/kg d-amphetamine 

sulfate on day 3. Only a single locomotor activity session was performed at the 3- and 

6-month time points and at 2 weeks after termination of treatment. Locomotor activity 

was recorded during the light phase for 7 hours. The hypothalamus, prefrontal cortex, 

nucleus accumbens, and the striatum were removed from sacrificed animals 2 weeks 

after termination of the treatment. Monoamine and monoamine metabolites were 

measured by HPLC with electrochemical detection. Immunohistochemical and 

unbiased stereologic analyses of tyrosine hydroxylase from the substantia nigra pars 

compacta and ventral tegmental area were performed. Microdialysis was used to 

evaluate changes in striatal dopamine release after acute i.p. exposures to 100 or 200 

mg/kg atrazine in sessions lasting 7 hours. Animals were subjected to stereotaxic 

surgery and cannulation. Brain histology was performed on the rats at the completion of 

micordialysis sampling. 

No treatment-related changes in body weights or food consumption were reported (data 

were not shown). Rats treated for 2 months with 10 mg/kg atrazine exhibited an 

enhanced horizontal locomotor activity response (70% relative to the 0 and 5 mg/kg 

groups) to d-amphetamine. The increased locomotor activity persisted at the 3- and 6-
Page 173 of 263 

month time periods, as well as 2 weeks after treatment, time periods carried out in the 

absence of d-amphetamine administration. At 2 weeks after treatment with atrazine, 

locomotor activity was 40% above control values. A statistically significant decrease 

(approximately 20%) in striatal dopamine levels at 10 mg/kg/day was noted. Dopamine 

levels were increased in the prefrontal cortex in an inverse U-shaped fashion; the 

increase at 5 mg/kg/day was 30 – 40%, while levels declined towards control levels at 

10 mg/kg/day dose. Significant decreases (10 – 15%) in hypothalamic serotonin level 

were observed at the 5- and 10-mg/kg/day doses. The 10 mg/kg/day dose was 

associated with a significant decrease (15 – 20%) in norephineprine levels in the 

prefrontal cortex. The authors reported no changes in the metabolites of serotonin or 

dopamine or dopamine turnover in any region. 

At 2 weeks after the 6-month treatment period, the number of tyrosine hydroxylase 

positive (TH+) and tyrosine hydroxylase negative (TH-) cells were reduced in the 

substantia nigra pars compacta and ventral tegmental areas. This effect was primarily 

due to the 10 mg/kg/day dose level. Mean reductions in cell numbers ranged from 9 to 

13% in the 10 mg/kg/day group, whereas those in the 5 mg/kg/day group ranged from 0 

to 3%. 

Following an acute i.p. administration of 100 or 200 mg/kg atrazine, a significant 

decrease in basal dopamine release was noted as measured at 90, 120, 150, and 180 

minutes postadminstration. By 150 minutes, the decreases averaged approximately 

40% and were seen in both dose groups. The authors also noted a dose-dependent 

decrease in potassium-stimulated dopamine release. No changes in the dopamine 

metabolites (DOPAC or HVA) were observed in the microdialysis component of the 

study. 

The authors concluded that there findings “demonstrate that atrazine may have broad 

effects on brain monoamine systems and thereby influence a wide range of behavioral 

functions.” The authors acknowledge that “additional studies are needed to unravel the 

targets of atrazine and the mechanisms of its effects, as well as the ultimate human 

health consequences of such exposures for behavioral and/or neurological 

dysfunctions.” 

Reviewer’s Comments: This study has a number of limitations, including: 

 

• No photomicrographs were provided to support and corroborate the findings of 

stereological examination of TH+ and TH- cell loss (only cell number data were 

provided), and no histological examination to describe actual morphological 

changes was discussed. There was no information on the calibration of the 

stereological test system and no information on control for potential sources of 

variability in the stereological estimations of cell numbers. There was no 

assessment of the precision of the estimations of neuronal counts. 
Page 174 of 263 

• Behavioral assessment was limited to d-amphetamine-induced locomotor 

activity; inclusion of dopamine agonists and antagonists and L-Dopa in the 

experimental design would help support the findings. 

 

• The study did not include a positive control such as 6-hydroxydopamine which 

produces dose dependent alterations in dopamine and dopamine metabolites 

and loss of tyrosine hydroxylase-immunoreactive cells in the substantia nigra. 

A.6 Immunotoxicity 

A.6.1 Cimino-Reale, G., Ferrario, D., Casati, B., Brustio, R. 

Diodovich, C., Collotta, A., Vahter, M., Gribaldo, L. (2008). Combined 

in utero and juvenile exposure of mice and atrazine in drinking water 

modulates gene expression and clonogenicity of myeloid 

progenitors. Toxicol. Letters 180:59-66. 

In this study, groups of four adult female CD-1 mice were exposed to 1mg/L sodium 

arsenate (NaHAsO4) in drinking water for 10 days before mating and during gestation. 

Other groups of NaHAsO4-exposed male and female (4/sex/group) offspring were 

treated for 4 months with 1 mg/L atrazine (unreported purity), an additional dose of 

1mg/L NaHAsO4, or a combination of atrazine + NaHAsO4 in drinking water. At the end 

of treatment, animals were sacrificed and bone marrow cells were collected from one 

femur, frozen and used for the colony forming unit-granulocyte/macrophage (CFU-GM) 

assay. Cells from the second femur were harvested, flushed with 1 mL of commercial 

RNA-Later to stabilize the RNA for later isolation, and held frozen until use in the gene 

expression phase of testing. 

For the CFU-GM assay, bone marrow cells were thawed, centrifuged, and resuspended 

in culture medium specific for murine hematopoietic cells containing 30% fetal bovine 

serum, bovine pancreatic insulin, human transferrin iron-saturated, 2-mercaptoethanol, 

interleukin-3 and-6, and stem cell growth factor. Cell viability was determined; cells 

were adjusted to 6.0 x 105 viable cells/mL, seeded to yield a final density of 4.0 x 

104

viable cells/plate and incubated. Triplicate plates were prepared per group and five 

replicated experiments were conducted. After 7 days, colonies were counted to 

determine cytotoxicity. 

For the gene expression phase of testing, total RNA was extracted from bone marrow 

cells, and [33P]-labeled cDNA was obtained by converting 1 μg of total RNA into cDNA 

using reverse transcriptase in the presence of Mouse Cancer CDS primer mix. The 

cDNA was purified, hybridized for 16 hours on microarray membranes, washed, and 

exposed on a phosphor-image screen for 21-24 hours. Transcripts were considered to 

be differentially expressed if the p value was ≤0.05. 
Page 175 of 263 

Bone marrow cells were also investigated for modulation of gene expression of 

estrogen receptors alpha and beta using real-time PCR. For this approach, 500 ng of 

total RNA, extracted from the bone marrow of treated males and females, was 

converted to cDNA through reverse transcription using random hexamer primers HighCapacity cDNA Archive Kit and Moloney murine leukemia virus reverse transcriptase. 

No gross pathological changes were seen in the treated mice. A significant (p<0.05) 

~19% (males) and ~23% (females) decrease in the percentage of CFU-GM was see 

after exposure to 1 mg/L atrazine alone. NaHAsO4 had no cytotoxic effect on the bone 

marrow. However, cell growth increased significantly (p<0.05) by 12% (138 vs. 123 

colonies) after the combined atrazine/ NaHAsO4 treatment of females, compared to 

control. Results from the microarray analysis showed that there was no significant 

change in gene expression in bone marrow cells following exposure to either atrazine 

alone or NaHAsO4. However, the combined exposure to atrazine/NaHAsO4 

demonstrated the overexpression of 20 differentially expressed genes (DEGs). For the 

analysis of changes in gene expression of estrogen receptors alpha and beta For the 

analysis of changes in gene expression of estrogen receptors alpha and beta (ERα and 

β), quantitative RT-PCR of exposed bone marrow cells revealed that the ERα was not 

modified in either sex after dosing with the three treatment groups. However, ERβ gene 

expression was significantly increased in both sexes and all treatment groups. 

Nevertheless, the high variability among individual females in expression of either ERα

or β genes limits the interpretation of these data. CFU-GM assay, quantitative RT-PCR 

of exposed bone marrow cells revealed that the ERα was not modified in either sex after 

dosing with the three treatment groups. However, ERβ gene expression was 

significantly increased in both sexes and all treatment groups. 

Reviewer’s Comments: With the exception of the CFU-GM assay results showing 

inhibition of myeloid cells, suggestive of an adverse effect on the immune system, no 

definitive conclusion can be reached that would shed light on the mechanism(s) 

responsible for the bone marrow immunotoxicity. This is because of the lack of an 

effect on gene expression in the treated bone marrow and the wide variation in the gene 

expression of ERβ among individual females. 

A.6.2 Devos S, Bosscher K De, et al. 2003. Inhibition of cytokine 

production by the herbicide atrazine – Search for nuclear receptor 

targets. Biochemical Pharmacology 65: 303 – 308. 

The purpose of this study was to test the hypothesis that atrazine affects leukocyte 

function via nuclear receptors such as the glucocorticoid receptor (GR), the androgen 

receptor (AR), members of the peroxisome proliferator-activated receptor (PPAR) 

family, and the retinoid-related orphan receptor (ROR) α. The authors noted previous 

work that showed weak binding of atrazine to the AR. The GR was investigated 

because of the similarity of effects induced by atrazine and the synthetic glucocorticoid 

DEX. Glucocorticoids have anti-inflammatory and immunosuppressive properties and 

interfere with nuclear factor – κB (NF- κB) and AP-1, and in this way repress the 
Page 176 of 263 

expression of inflammation-related genes such as interleukin (IL)-6, IL-8, ICAM, and Eselectin, that contain NF- κB and AP-1 response elements. Activation of PPARs has 

been reported to have effects on leukocytes. RORα can also affect leukocytes function. 

In this study, adult (2- or 7-month-old) CF1 mice were injected i.p. on days 1 and 4 with 

atrazine (100 mg/kg). Control mice received the vehicle only (carboxymethylcellulose 

containing 0.5% Tween 80). Mice were sacrificed on day 7. Liver and kidneys were 

removed. Brief descriptions of cells (murine fibrosacrcoma L929sA and rabbit kidney 

RK13) and culture procedures, plasmids (p1168hu.IL6P-luc+, p98.IL8p-luc+, p133.IL8pluc+, pELAmP-luc+), transfection and reporter gene analysis, ELISA, AR assay, and 

peroxisome analysis were provided. 

Inhibition of human peripheral blood mononuclear cell (PBMC) proliferation and 

cytotokine production was observed in cultures with atrazine (3 x 10-7 M to 1.5 X 10-5 

M). This effect was not prevented by the glucocorticoid inhibitor RU486. In contrast to 

DEX, atrazine did not reduce IL-8 production. The authors concluded that these data 

suggest that the effects of atrazine on PBMC are not mediated through the GR. 

Atrazine did not affect TNF-induced IL-8 promoter activity, in contrast to DEX. This was 

demonstrated in stable cell pools transfected with an IL-8 promoter-driven reporter gene 

construct, p98.IL8p-luc+, and then induced with TNF and treated with DEX and atrazine 

(3, 0.3, and 0.03 μM) alone or in combination. TNF is an inflammatory stimulus 

activating the reporter genes. Testing a longer variant of the IL-8 promoter, p133.IL8pluc+, yielded the same overall results (data were not shown). To test whether the 

results with the IL-8 promoter were promoter-specific, the authors also tested the effect 

of atrazine on other proinflammatory gene construct, containing the E-selectin promoter 

(with NF- κB elements) or the IL-6 promoter (with NF- κB and AP-1 elements), that are 

both inducible by TNF. The authors indicated that there were no substantial effects with 

atrazine. They concluded that atrazine does not exhibit glucocorticoid-like properties 

and does not interact with the GR. 

No peroxisome proliferation was observed in the liver or kidneys of mice treated with 

atrazine. Moreover, no PPAR-mediated induction of promoter activity was seen on 

targets of PPARα, PPARγ, or PPARδ. No binding of atrazine to the AR was observed. 

The authors concluded that their study shows that AR, GR, PPARs, or RORα are not 

likely targets of atrazine. 

Reviewer’s Comments: Using human peripheral blood mononuclear cells, the in vitro

study of Devos et al. (2003) suggests that atrazine-induced inhibition of human 

peripheral blood mononuclear cell proliferation and cytokine production is most likely not 

mediated through nuclear receptors such as the glucocorticoid receptor, androgen 

receptor, members of the peroxisome proliferator-activated receptor family, and the 

retinoid-related orphan receptor α. The relevance of this study to human health risk 

assessment is limited since it entails intraperitoneal injection of atrazine to the animals 

prior to in vitro experiments.
Page 177 of 263 

A.6.3 Devos S, Van Den Heuvel R, et al. 2004. Limited effect of 

selected organic pollutants on cytokine production by peripheral 

blood leukocytes. Eur. Cytokine Netw: 15: 145 – 151. 

This study examined the potential effects of in vitro atrazine treatment on cytokine 

production by peripheral blood mononuclear cells (PBMC) from control and allergic 

donors. Cells were cultured for six days in the presence of atrazine (3 μM) or vehicle 

with phytohemagglutinin (PHA) or Dermatophagoides pteronyssinus (Dpt) extract, then 

for one day in the presence of PHA + phorbol 12-myristate 13-acetate. Information on 

the donors (selection, ethical approval, allergic disease description) and methods 

(PBMC cultures, cytokine assays, IgE plasma level determination, radioallergosorbent 

or RAST test to confirm Dpt allergy) was provided. 

Atrazine treatment significantly reduced cytokine production IL-5 and IFN-γ in the 

donors. This effect was apparent in PHA-stimulated cultures, but not Dpt stimulation. 

Reviewer’s Comments: The authors concluded that since the effects on cells from 

allergic and non-allergic donors were similar, and the effects on cytokines were limited, 

the impact of atrazine on allergic responses is unlikely. 

A.6.4 Filipov, N M, Pinchuk, L M, et. al. 2005. Immunotoxic effects 

of short-term atrazine exposure in young male C57BL/6 mice. 

Toxicological Sciences: 86(2): 324-332. 

The objective of this study was to assess the effects of atrazine exposure on selected 

immune parameters in young mice. Parameters included: thymus and spleen weights, 

cellularity, lymphocyte subpopulations in the spleen, thymus, and peripheral blood 

mononuclear cells. To assess short- vs. long-term effects, the parameters were 

measured at one day, one week, and seven weeks after administration of the last 

atrazine dose. Atrazine was administered to one-month-old male C57BL/6 mice for 14 

days by oral gavage at doses of 5, 25, 125, and 250 mg/kg bw. 

Spleen weight was decreased at the 250 mg/kg dose level on day 1, while thymus 

weights were decreased at the 125 and 250 mg/kg/day dose levels. Decreased 

thymus weights persisted one week after the last dose of atrazine, but resolved by 

seven weeks. Spleen and thymus cellularity was dose-dependently decreased by 

atrazine treatment (statistically significant at 125 and 250 mg/kg doses) at day 1. The 

decreased cellularity persisted one week after cessation of atrazine treatment. 

However, decreased thymic cellularity was resolved by seven weeks, whereas 

decreased splenic cellularity was significantly decreased at all doses levels of atrazine. 

Thymic T-cell populations were significantly and dose-dependently decreased at day 1. 

The authors reported that one week after cessation of atrazine treatment, the decreases 

in most T-cell populations were still present at the higher doses of atrazine, whereas at 

the lower doses a non-significant rebounding effect was observed (data not shown). 

The authors also reported that by seven weeks after the last atrazine dose, the 
Page 178 of 263 

decreases in the thymic subpopulations were numerically present, but were no longer 

significant (data not shown). 

In regard to splenic cell phenotypes, both MHC II+ and CD19+ cells were dosedependently decreased, whereas only the high dose of atrazine increased the 

percentage of CD3+ cells. In addition, atrazine treatment decreased the number of 

splenic naïve T helper and T cytotoxic cells, whereas it increased the percentage of 

highly activated cytotoxic/memory T cells. The proportion of mature splenic dendritic 

cells (DC; CDIIchigh) was also decreased, which persisted for at least one week. No 

effects on splenic cell phenotypes were seen at seven weeks post treatment time point. 

With respect to peripheral blood mononuclear cells, a dose-dependent decrease in 

circulating CD4+ cells was observed one day after the last atrazine dose. The decrease 

in CD4+ cells was still present at the 250 mg/kg dose (high dose) at seven days after 

the last dose. In addition, at seven days, the MHC-II+ cells were also decreased at the 

high dose. The authors stated that most of the changes in peripheral blood 

mononuclear cells were no longer apparent at seven weeks after the last atrazine dose, 

although data were not shown. The authors concluded that “atrazine exposure appears 

to be detrimental to the immune system of juvenile mice by decreasing cellularity and 

affecting lymphocyte distribution, with certain effects persisting long after exposure has 

been terminated.” 

Reviewer’s Comments: Although T cell subpopulations were decreased at all dose 

levels on Day 1 the fact that they quickly recover diminishes the toxicological 

significance of this finding (i.e., its ability to predict impaired function). A similar 

conclusion was reached by The Joint FAO/WHO Meeting on Pesticides Monograph on 

Atrazine (JMPR 2007). 

A.6.5 Karrow, N A, McCay, J A, et. al. 2005. Oral exposure to 

atrazine modulates cell-mediated immune function and decreases 

host resistance to the B16F10 tumor model in female B6C3F1 mice. 

Toxicology: 15-28. 

The purpose of this study was to examine the potential immunomodulatory properties of 

atrazine and was designed to assess changes in cellular and antibody immune function 

in the female B6C3F1 mouse model. This model also included pathogenic B16F10 

tumor and Listeria monocytogenes challenge models to assess potential biological 

significance of any observed changes in immune function. In this study, female 

B6C3F1 were administered atrazine by gavage (0, 25, 250, and 500 mg/kg/day) for 14 

days then evaluated for immune responsiveness. Immune assays and toxicity 

parameters included: body weights, organ weights (including spleen), hematology, 

differential cell counts, serum IgM titers, splenic natural killer (NK) cell activity, splenic 

mixed lymphocyte response (MLR), splenic IgM antibody-forming cell (AFC) response, 

reticulocyte counts, splenic lymphocyte proliferation, splenic B and T cell enumeration, 

splenic cytotoxic T lymphocyte response (CTLR) to P815 mastocytoma cells, 
Page 179 of 263 

mononuclear phagocytic system (MPS) evaluation, L. monocytogenes challenge and 

B16F10 tumor challenge. 

A decrease in body weights was observed in the atrazine treated groups. A significant 

dose-dependent decrease in spleen and thymus weights was also observed. Kidney 

weights were slightly but significantly reduced at the high dose. Hematological 

alterations included reductions in erythrocyte counts (all dose levels), decreased 

hematocrit (high dose), and increased mean corpuscular hemoglobin (all doses). At 

the high dose, the percentage of CD3+

 and CD4-CD8+ T cells was significantly 

increased by 10 and 18%, respectively. Atrazine treatment did not significantly alter the 

spleen cell proliferative response to mitogens Con A or LPS. There was no effect of 

treatment on splenic primary AFC response and serum IgM titers to sRBCs. The spleen 

cell MLR to DBA/2 murine spleen cells was stimulated (30%) in the high-dose mice. 

The splenic CTLR was significantly stimulated in mice that were treated with both 25 

and 250 mg/kg atrazine. The NK cell activity in the spleen was only inhibited in the 250 

mg/kg/day group and the authors did not consider this effect to be of biological 

significance. A dose-related decreasing trend in MPS function across the treatment 

groups was noted. 

Host resistance to B16F10 tumor challenge was reduced in atrazine treated mice at 

both challenge levels. At the 3 x 105

 cells/mouse challenge level, a significant dosedependent increase in the number of B16F10 nodules was observed in the lungs of 

treated mice. The greatest increase in the number of nodules (122%) was observed at 

the 500 mg/kg treatment level. Although there were no statistically significant changes 

in host resistance to L. monocytogenes, the authors stated that the data suggest that 

atrazine may alter host resistance to this pathogen. The percent mortalities for the 

various treatment groups at the challenge level of 6.3 x 104

 CFU/mouse were 67, 92, 

58, and 33 for the control, 25, 250, and 500 mg/kg atrazine treatment groups. 

Reviewer’s Comments: This study design included a host resistance test, which 

assessed the function of the immune system in toto. 

A.6.6 Mizota K and Ueda H. 2006. Endocrine disrupting chemical 

atrazine causes degranulation through Gq/11 protein-coupled 

neurosteroid receptor in mast cells. Toxicological Sciences 90(2): 

362 – 368. 

The authors examined the in vitro effects of several putative endocrine disrupting 

chemicals including atrazine on β-hexosaminidase release from mast cells and their 

putative neurosteroid receptor involvement. Drawing from their previous research, the 

authors proposed that NS2-type neurosteroid receptors exist on mast cells and mediate 

histamine release, which, in turn, stimulates nociceptor endings. They previously 

demonstrated that neurosteroids cause extravasation as well as hyperalgesia, which 

were abolished by diphenhydramine, a representative H1 receptor antagonist. 

Neurosteroid-induced extravasation has been attributed to degranulation of mast cells. 
Page 180 of 263 

Degranulation of mast cells was determined by measuring the release of granuleassociated β-hexosaminidase from RBL-2H3 cells. Degranulation was also evaluated 

by Alexa 488-annexin V binding to the phosphatidylserine, which is externalized during 

degranulation. Antagonism of atrazine-induced Alexa 488-annexin V binding in RBL2H3 cells by BSA-conjugated progesterone (PROG-BSA) was examined. βHexosaminidase release was characterized by various inhibitors including antisenseoligodeoxynucleotide for Gαq/11, pertussis toxin, phospholipase C inhibitor U-73122, 

inositol 1,4,5-triphosphte receptor inhibitor xestospongin C and Ca2+ channel blocker 

lanthanum chloride. 

Based on the authors previous findings that intraplantarly administered neurosteroids 

cause pain-like responses, such as biting and licking behaviors in a diphenhydraminereversible manner, these responses were also evaluated in male ddY mice. Atrazine 

(10 fmol) was administered intraplantarly (i. pl.) into the hind paw. The total amount of 

time showing pain responses, such as biting and licking, was measured for 10 min. after 

i.pl. injection. 

Atrazine (10 nM – 1 μM) caused a concentration-dependent degranulation in RBL-2H3 

cells and peritoneal mast cells as measured by β-hexosaminidase release. This release 

was blocked by PROG-BSA, a membrane impermeable neurosteroid receptor 

antagonist. PROG-BSA also blocked atrazine-mediated increase in Alexa 488-annexin 

V binding (which labels phosphatidylserine externalization in the plasma membrane 

representing degranulation) in RBL-2H3 cells. The authors indicated that the 

observation of atrazine-induced increase in Alexa 488-annexin V binding shows that the 

atrazine-induced degranulation is unlikely due to cell damage. 

Antisense-oligodeoxynucleotide pre-treatment reduced atrazine-induced βhexosaminidase release. Atrazine-induced degranulation was abolished by 

phospholipase C inhibitor U-73122. Lanthanum chloride, which inhibits Ca2+ influx in 

cells, had no effect. The authors interpreted the findings to reveal that the signal 

transduction involved in the degranulation is mediated though Gq/11, PLC and 

mobilization of intracellular Ca2+, characteristics of neurosteroids. 

The results also demonstrated atrazine-induced pain response that occurred 

immediately and ceased within 5 minutes after i.pl. administration. The responses were 

dose-dependent between 1 and 10 fmol (i.pl.). The effects were abolished by PROG –

BSA and DPH, which is a histamine receptor antagonist. This was interpreted by the 

authors to indicate that the responses were caused by neurosteroid receptor-mediated 

histamine release from mast cells, which was supported by atrazine-induced plasma 

extravasation assay using Evans blue. Overall, the authors concluded that atrazine 

induces some inflammatory effects, including nociception and plasma extravasation, 

and the underlying mechanisms are mediated through mast cell degranulation and 

activation of the Gq/11-protein coupled neurosteroid receptor, phospholipase C and 

intracellular Ca2+ mobilization. 
Page 181 of 263 

Reviewer’s Comments: This study concluded that the underlying mechanisms of 

atrazine-induced inflammatory effects such as nociception and plasma extravasation, 

may be mediated through mast cell degranulation and activation of the Gq/11-protein 

coupled neurosteroid receptor, phospholipase C and intracellular Ca2+ . However, the 

inflammatory responses were examined following intraplantar administration of atrazine, 

a route of exposure that is not likely to occur in humans. 

A.6.7 Pinchuk L M, Lee S-R, and Filipov N M. 2007. In vitro atrazine 

exposure affects the phenotypic and functional maturation of 

dendritic cells. Toxicology and Applied Pharmacology 223: 206 – 

217. 

Based on prior results revealing that atrazine may affect dendritic cell (DC) function 

(Rowe et al. 2006; Filipov et al. 2005), the objectives of this study was to investigate the 

effects of in vitro atrazine exposure on the phenotypic and functional maturation of a 

growth factor-dependent, bone-marrow-derived immature murine DC cell line JAWSII. 

For comparative studies, limited studies were performed with primary thymic DC. 

Details were provided on the following materials and methods used for the analyses: 

dendritic cell line, primary thymic DC preparation, antibodies and flow cytometry, 

endocytosis assay, apoptosis assay, PCR analysis, and real-time PCR analysis. 

JAWSII cells were induced to mature in the presence of growth factors and selected 

maturational stimuli in vitro. The DC line was exposed to atrazine (1 – 300 μM) and the 

effects on phenotypic and functional maturation of DC were examined. Phenotypic 

changes caused by atrazine included a dose-dependent removal of surface MHC-1 with 

a significant decrease at 1 μM concentration. In addition, atrazine treatment decreased 

the expression of the costimulatory molecule CD86 and it downregulated the expression 

of the CD11b and CD11c accessory molecules and the myeloid developmental marker 

CD14. The phenotypic changes in JAWSII DC maturation were associated with 

functional inhibition of maturation at higher concentrations of atrazine where receptormediated antigen uptake was increased. The authors stated that their data suggest that 

atrazine directly targets DC maturation and removes MHC-1 molecules from the DC 

surface. 

Reviewer’s Comments: Pinchuk et al. (2007) provided in vitro evidence suggesting that 

atrazine directly targets dendritic cell maturation and decreases major histocompatibility 

complex 1 (MHC-1) molecule expression on the dendritic cell surface. 
Page 182 of 263 

A.6.8 Pruett, S B, Fan, R, et al. 2003. Modeling and predicting 

immunological effects of chemical stressors: characterization of a 

quantitative biomarker for immunological changes caused by 

atrazine and ethanol. Toxicological Sciences: 75: 343-354. 

The authors stated that the study was conducted to determine if the “stress-induced 

immunological effects of atrazine and ethanol could be predicted, and if it is feasible to 

use one immunological parameter as a biomarker of stress to predict the quantity of 

changes expected in other immunological parameters.” Consequently, doses were 

selected in order to elicit an increase in corticosterone levels as a predictor of immune 

function; this study was not intended as a hazard identification study of atrazine. 

Female C57BL/6 X C3H F1 (B6C3F1) mice (8 – 12 weeks of age following a two-week 

accommodation period) were used in the study. Atrazine was administered 

intraperitoneally (only once) at dose levels of 100-, 200-, or 300-mg/kg bw in corn oil 

(group size was 5 mice). A naïve control group was included. The authors selected 

corticosterone as a mediator that might predict the quantity of immunosuppression 

caused by stress responses. Therefore, the corticosterone area under the curve (AUC) 

values for atrazine-treated mice were determined. Immunological parameters included: 

thymus and spleen cellularity, lymphocyte subpopulations in the thymus and spleen, 

expression of MHC class II protein on splenocytes, antibody responses to keyhole 

limpet hemocyanin, and natural killer cell activity. Models were derived describing the 

relationship between corticosterone AUC and potential immunological changes. 

The peak corticosterone response (approximately 1200 ng/ml) to atrazine occurred at 6 

hours, and was dose-dependent. In order to assess if the observed corticosterone 

response was unique to the intraperitoneal route of exposure, the authors included an 

additional experiment in which five mice were treated by oral gavage (corn oil) to 500 

mg/kg atrazine, while five mice were administered the vehicle. The 500 mg/kg dose 

was selected in order to match the high dose used in the National Toxicology Program’s 

study on atrazine. Three hours after dosing, serum corticosterone levels were 

measured. The authors reported the following corticosterone values: controls: 164 ± 

88; atrazine-treatment: 676 ± 79. 

Linear regression models of corticosterone AUC vs. thymus- and spleen-cell numbers 

and subpopulations revealed that atrazine treatment was associated with decreased 

thymus cell number and percentage of thymic CD4+CD8+, and decreased spleen total 

cell number and splenic B220+ cells. Linear regression models of corticosterone AUC 

vs. expression of MHC Class II protein on splenocytes indicated a dose-dependent 

decrease in the expression of MHC Class II protein on splenocytes in atrazine-treated 

animals. The results of linear models also indicated dose-dependent decreases in 

splenic NK cell activity and IgG1 and IgG2a responses to KLH. 

The authors also assessed the potential correlations between observed effects of 

atrazine and effects predicted using models derived from mice treated with exogenous 
Page 183 of 263 

corticosterone or restraint stress with linear modeling. The authors stated that the 

modeling results indicated that the atrazine effects were similar to results obtained from 

mice subjected to restraint stress; however, some of the atrazine effects were greater 

than predicted on the basis of the stress response alone. 

Reviewer’s Comments: Pruett et al. (2003) demonstrated that a single high oral dose of 

500 mg/kg atrazine also increased endogenous corticosterone levels. This study was 

intended to provide insight into the predictive value of corticosterone production over 

time for impairments of the immune system not to assess the immunotoxicity of atrazine 

per se. 

A.6.9 Pruett, S B, Fan, R, et al. 2009. Patterns of immunotoxicity 

associated with chronic as compared with acute exposure to 

chemical or physical stressors and their relevance with regard to the 

role of stress and with regard to immunotoxicity testing. 

Toxicological Sciences: 109(2): 265-275. 

This study is an extension of an earlier study (Pruett et al. 2003) that entailed single 

dose exposure to atrazine. The purpose was to determine if mice can become tolerant 

or habituated with regard to the stress response and accompanying immunological 

effects.” Female C57BL/6 X C3H F1 (B6C3F1) mice (8 – 12 weeks of age following a 

two-week accommodation period) were used in the study. Mice were dosed daily 

(intraperitoneally in corn oil) for 28 days with atrazine (up to 150 mg/kg/day) or were 

subjected to restraint, which can also induce neuroendocrine stress responses and alter 

immunological parameters. The exact doses of atrazine were not specified except for 

the high dose of 150 mg/kg/day. At the end of the study, the following parameters were 

measured: white blood cell count and differential blood count, lymphocyte phenotypes 

in the blood and spleen, natural killer (NK) cell activity in splenocytes, and 

corticosterone concentrations (at various times after dosing or restraint). The results 

were compared with those from the acute study (Pruett et al. 2003). 

The authors provided results for the corticosterone response in mice treated with 150 

mg/kg/day atrazine with that observed in the acute study (at 200 mg/kg dose level). 

The corticosterone response was very similar after the 28-day treatment as observed 

after a single treatment. The authors concluded that the 28-day atrazine treatment did 

not cause tolerance or habituation. 

Restraint had little effect on white blood cell counts following one treatment or after a 28 

day treatment period. Atrazine suppressed white blood cell counts; the suppression 

was greater after 28 day treatment compared with the single dose treatment. Atrazine 

caused essentially the same increase in neutrophils and decrease in lymphocytes after 

28 days of treatment as it did after 1 dose administration. Changes in the percentage 

of MHC class II expression by B lymphocytes and MHC class II expression on B 

lymphocytes in the spleen were comparable between the single dose and 28-day daily 

dose regimens. Atrazine caused a similar decrease in B cell percentage in the blood 
Page 184 of 263 

and spleen in the 28-day and single day studies. Restraint did not affect the percentage 

of B lymphocytes following acute or 28-day treatment. A dose-dependent decrease in 

CD4+ and CD8+ T lymphocytes in the blood was noted after single dose administration 

of atrazine; however, 28-day treatment increased this parameter. Restraint for 28-days 

decreased the T cell percentage in the blood, whereas acute restraint caused a smaller 

decrease. Decreases in NK cell activity of splenic lymphocytes were noted with both 

acute and 28-day atrazine treatments; however, decreases were greater with the latter 

treatment. 

Reviewer’s Comments: Pruett et al. (2009) provided some supporting evidence that 28-

day atrazine exposure did not cause habituation or tolerance to the HPA axis 

perturbations, but immune function (e.g., antibody production) was not evaluated in this 

study. 

A.6.10 Rooney, A A, Matulka R, and Luebke, R. 2003. 

Developmental atrazine exposure suppresses immune function in 

male, but not female Sprague-Dawley rats. Toxicological Sciences 

76: 366-375. 

This study was designed to test the hypothesis that atrazine may cause developmental 

immunotoxicity through its disruption of prolactin (PRL) or thyroid hormones during a 

critical early period of development. Pregnant Sprague-Dawley (SD) rats were exposed 

via oral gavage to 35-mg atrazine/kg/day from gestational days (GD) 10 (to avoid the 

possible interference of atrazine with embryo implantation) through postnatal day (PND) 

23. The authors indicated that the dose of 35 mg/kg/day was set “just above the NOEL 

for atrazine-induced developmental endocrine dysfunction to examine the potential for 

atrazine to indirectly induce immunotoxicity.” The authors stated that this dose is likely 

to induce endocrine effects in both sexes. Separate groups were exposed to 

bromocryptine (BCR) at 0.2 mg/kg/2x/day to induce hypoprolactinemia or to 

propylthiouracil (PTU) at 2 mg/kg/day to induce hypothyroidism. At 7 weeks old, the 

following immune functions in the offspring were evaluated: natural killer (NK) cell 

function, delayed-type hypersensitivity (DTH) responses to bovine serum albumin 

(BSA), phagocytic activity of peritoneal macrophages, and antibody response to sheep 

erythrocytes (SRBC). 

There was an increase in offspring mortality in atrazine treated animals during PND 2 – 

14. The average % offspring mortality/litter in atrazine-treated dams was 13.2 

compared to 2.3% for control dams. The authors noted that increased mortality was 

“unexpected, as this has not been reported for this dose of atrazine.” They further state 

that “it is not known whether the weight loss or death of pups was due to an effect on 

the physiology or behavior of the dams or the pups themselves.” The authors stated 

that male offspring body weight of the atrazine group was decreased relative to controls 

(mean control body weight was 20.1 g compared to a mean atrazine group body weight 

of 19.0 g). 
Page 185 of 263 

The primary (IgM) antibody response to SRBC was suppressed in atrazine-treated 

males (p = 0.0149), but not female, offspring at 8 weeks of age. There was no 

difference among treatment groups in the IgG antibody response to SRBC. There was 

no difference between the offspring of ATR-exposed dams and the control offspring in 

the IgM antibody response to SRBC in 6-month-old-animals (data were not shown). 

The latter results indicate that that immune function returned to normal by 6 months. 

The DTH response of male, but not female, offspring of atrazine treated dams was 

reduced relative to the control animals (p = 0.0308) when the animals were sensitized to 

BSA at 8 weeks of age and measured at 9 weeks of age. The decrease in DTH 

response of male offspring of the atrazine treatment group persisted until at least 12 

weeks of age. There was no difference in the DTH response between the offspring of 

atrazine-treated dams and the control offspring in 6-month-old animals (data were not 

shown). There was no effect of atrazine treatment on NK cell activity. There was no 

effect of atrazine treatment on phagocytosis by peritoneal macrophages. 

The authors concluded that atrazine treatment causes gender-dependent 

immunosuppression of cellular and humoral immune function, specifically suppression 

of primary antibody production and DTH responses. The authors also concluded that 

the immune changes associated with atrazine are not mediated through the 

suppression of PRL or THs. In addition, the authors concluded that “the current data do 

not support nor completely refute a relationship between atrazine’s immunotoxic 

potential and its endocrine disrupting properties.” 

Reviewer’s Comments: Rooney et al. (2003) provided some evidence that immune 

changes associated with atrazine during early development are not mediated through 

the suppression of prolactin or thyroid hormones. The precise underlying mechanism of 

an atrazine-mediated sex-specific effect, however, is not fully understood. 

A.6.11 Rowe, A M, Brundage, K M, Schafer, R, and Barnett J B. 

2006. Immunomodulatory effects of maternal atrazine exposure on 

male Balb/c mice. Toxicology and applied Pharmacology 21: 69 – 

77. 

The aim of this study was to test the hypothesis that prenatal/lactational exposure to 

atrazine would affect the development of the immune system and alter immune function 

in the adult offspring in the Balb/c mouse model. Pregnant Balb/c dams were exposed 

subcutaneously for 21 days via time release pellets to 700 ug atrazine/day beginning 

between days 10 and 12 of pregnancy. The implanted pellet was designed to release 

the same amount of atrazine every minute of every hour of every day until the end of 

the treatment period. The rate of exposure at the beginning of treatment was reported 

to be approximately 35 mg/kg/day, however, the daily dose dropped to approximately 

23 mg/kg/day by the time the mice gave birth. The authors reported that the 

prenatal/lactational exposure “caused no overt physical malformations in the offspring 

and had no effect on the number of litters carried to term or the litter size.” 
Page 186 of 263 

Immune status was evaluated at approximately 3 months of age. Body weight and 

spleen weights (absolute and relative) were monitored. T cell function was assessed 

by measuring proliferation and cytolytic activity after in vitro allogeneic stimulation. 

Allogeneic stimulation was assessed using two different assays. In one assay, 

splenocytes were isolated from unimmunized prenatally/lactationally exposed Balb/c 

mice and stimulated using irradiated splenocytes from female C57B1/6 mice. 

Proliferation of alloreactively stimulated lymphocytes was assessed by measuring the 

incorporation of 3H-thymidine into newly synthesized DNA following co-culture with 

alloreactive stimulator cells and incubation with 3H-thymidine. In another assay, the 

ability of the T cells to lyse alloreactive target cells (i.e., cytotoxic T lymphocyte 

response), was assessed following alloreactive stimulation. EL-4 lymphoma cells were 

used as targets. The humoral immune response was assessed after immunization with 

heat killed Streptococcus pneumoniae (HKSP). The number of HKSP-specific B cells 

was quantified by the ELISpot assay. Spleen cell phenotype (specifically, CD4+, CD8+ , 

and B220+

), was determined by flow cytometry. 

There were no changes in body weights or spleen weights. No changes were observed 

in the number of CD4+ T cell, CD8+ T cell, and B220+ B cell subpopulations in the 

spleen. Male mice (3-month old) exhibited an increase in both T cell proliferation 

(atrazine offspring: 67 ± 5 x 103 cpm; control offspring: 46 ± 4 x 103 cpm) and cytolytic 

activity (approximately 66% increase). A significant increase in the number of HKSPspecific IgM secreting B cells in the spleen of treated male mice was noted. Male 

atrazine-exposed offspring had 78.7 ± 4.5 HKSP-specific IgM antibody secreting cells 

(ASC) per 106 B220+ cells compared to 58.6 ± 3.0 ASC per 106 B220+ cells for male 

control offspring. Three-month-old female offspring showed no significant difference in 

immune response from controls. The authors concluded that the results indicate “a 

male-specific immunopotentiation of the immune response following prenatal/lactational 

atrazine exposure.” 

In a review article (Rowe et al. 2008; Basic & Clinical Pharmacology & Toxicology, 102, 

139-145), the study authors reported on the results of similar assays performed on 

available littermates at 6 months of age (defined as “long-term”). Limited data were 

presented. The authors noted that too few male offspring were available to perform 

replicate assessments. However, they stated that a single iteration of the mixed 

lymphocyte response assay in the males showed a significant decrease (this contrasts 

with observations at 3 months of age). Female offspring were immunized with the 

HKSP vaccine at 6 months and sera collected at 7 and 14 days after immunization. The 

authors reported that six-month-old atrazine-treated females had a significant and 

reproducible reduction in the number of phosphorylcholine (PC)-specific responding 

splenocytes following HKSP vaccination (PC-specific IgM-producing B cells in the 

spleen of HKSP-vaccinated atrazine-treated females were 69% of control). In addition, 

spleens from the atrazine-treated groups produced a mean of 72% of control IgG PCspecific B cells per million splenocytes. The MLR response was also assessed in 

female offspring. Results indicated that atrazine-treated females had a significant 
Page 187 of 263 

decrease in the MLR (spleen cell proliferation level was 72% of control and was 

statistically significant). 

The authors also stated that in the 6-month-old females, the total number of splenocytes 

and the lymphocyte subpopulation phenotypes were also unaffected. The mean spleen 

weight and total spleen cell number were slightly higher in the treated groups. The 

percentage of spleen cell subtypes (CD4, CD8, and B220) was not significantly different 

between the two groups. Based on the findings of the 3- and 6-month evaluations, the 

study authors concluded that the findings “demonstrate a sex- and age-dependent 

effect of prenatal exposure to atrazine on the immune system of the adult offspring.” 

Reviewer’s Comments: Rowe et al. (2006) reported immunopotentiation of immune 

function in male Balb/c mice. However, these results conflicted with the results by 

Rooney et al. (2003) who reported immunosuppression of cellular and humoral immune 

function in male Sprague-Dawley rats. The reasons for the contradictory results are not 

known but may be related to differences in the timing and route of maternal exposure, 

species differences and different methodologies used to assess immune response. 

A.6.12. Rowe A M, Brundage K M and Barnett J B. 2007. In 

vitro atrazine-exposure inhibits human natural killer cell lytic granule 

release. Toxicology and Applied Pharmacology 221: 179 – 188. 

Earlier studies have revealed effects of atrazine on natural killer (NK) cells. In the 

current in vitro study, Rowe et al. were interested in testing the hypothesis that atrazine 

exposure would decrease target cell adhesion and subsequent granule release in order 

to clarify precise changes in NK cell lytic function. Peripheral blood lymphocytes were 

isolated from healthy human male donors and exposed to atrazine (0, 10 or 30 μM) for 

24 hours. The ability of NK cells to bind target cells (K562 human leukemia cells that 

are sensitive to lysis by human NK cells) as well as the ability of the NK cells to 

subsequently release lytic granule was assessed. Details on the methods used were 

provided in the study including: cell culture, peripheral blood lymphocyte harvest, 

cytotoxic lymphocyte assay, enrichment of NK cells, flow cytometry, NK cell adhesion, 

perforin ELISA and western blots. 

Results showed that atrazine decreased NK cell function of PBLs under the in vitro

experimental conditions, confirming observations by other investigators, e.g., Whalen et 

al. 2003. The authors also reported that atrazine did not affect viability or NK cell 

subpopulation distributions (data were not shown). For this experiment, PBLs were 

assessed for viability and subpopulation distribution via flow cytometry. Subpopulation 

distribution was determined using four lymphocyte markers (CD56, CD16, CD3 and 

CD8), and viability was determined using 7-ADD exclusion. 

The basal level of lytic proteins (i.e., perforin, granzyme A and B levels) was not 

changed following a 24-hour exposure to atrazine. Atrazine also did not affect the posttranslational modification of perforin. In addition, atrazine treatment did not affect the 
Page 188 of 263 

ability of NK cells to bind target cells. However, atrazine treatment decreased the ability 

of NK cells to release granule proteins. 

Reviewer’s Comments: Rowe et al. 2007 showed that atrazine-induced inhibition of in 

vitro human peripheral blood lymphocyte NK cell-specific lysis of K562 human leukemia 

cells may be the result of inhibition of lytic granule release, without affecting the ability of 

the natural killer cell to form stable conjugates with target cells. 

A.6.13 Schwab, C L, Fan R, et al. 2005. Modeling and 

predicting stress-induced immunosuppression in mice using blood 

parameters. Toxicological Sciences 83: 101 – 113. 

This study is an extension of the Pruett et al. (2003) study described above except that 

the blood rather than the spleen was of interest. Utilizing the same approach as Pruett 

et al. (2003), Schwab et al. (2005) showed that the atrazine-induced decreases in CD4+ 

and CD8+ T cells in blood were similar to exogenous corticosterone. 

Reviewer’s Comments: This study provides further support for the predictive value of 

corticosterone for immune markers. 

A.6.14 Whalen M M, Loganathan B G, et al. 2003. 

Immunomodulation of human natural killer cell cytotoxic function by 

triazine and carbamate pesticides. Chemico-Biological Interactions 

145: 311 – 319. 

The effects of in vitro atrazine treatment on the ability of human natural killer (NK) cells 

to lyse tumor cells were investigated. Atrazine was tested in both purified NK cells as 

well as a cell preparation that contained both T and NK lymphocytes (T/NK cells). 

Lymphocytes were exposed to atrazine (10 μM) for periods of time ranging from 1 hour 

to 6 days. Information on the methods used (isolation of NK cells, cell treatments and 

cell viability, and chromium release assay for NK cytotoxicity) was presented in the 

study. 

Exposure of highly purified NK cells to atrazine inhibited K562 tumor cell lysis by 63 ± 

25 % after 24-hour exposure, and by 83 ± 21 % after a 6-day exposure. Atrazine also 

caused significant decreases in lytic function when T/NK cells were exposed for 24-

hours (61 ± 13%) and after 6-days (54 ± 12%). 

Reviewer’s Comments: This in vitro study provides some evidence that atrazine may 

affect NK cell cytotoxic function; however, the relevancy of these findings to in vivo 

exposure remains unclear. 
Page 189 of 263 

A.7 Carcinogenesis/Genotoxicity 

A.7.1 Fujimoto, N and Honda, H. (2003). Effects of Environmental 

Estrogenic Compounds on Growth of a Transplanted Estrogen 

Responsive Pituitary Tumor Cell Line in Rats. Food Chem. Toxicol. 

41:1711-1717. 

The objective of this study was to evaluate the role genistein, p-nonylphenol, or atrazine 

as tumorigenic promoters for estrogen-sensitive tumors. A rat pituitary cell-line – MtT/E2 – that is responsive to estrogen exposure was transplanted into ovariectomized rats. 

The rats were subsequently exposed to estradiol, genistein, p-nonylphenol, or atrazine 

and examined twice a week for the development of tumors.17 In addition, MtT/E-2 cell 

cultures were transfected with an estrogen-response-element-luciferase reporter gene 

and evaluated for activation of the reporter gene. These cells were also grown in vitro

and evaluated for cell proliferation after exposure to the chemicals under evaluation. 

Finally serum collected at the time of sacrifice was used to evaluate prolactin levels. 

Six week old ovariectomized F344 rats (sample size not reported) were inoculated with 

MtT/E-2 tumors cells and subsequently exposed through the diet to 0, 5, 50, or 500 

mg/kg atrazine (purity not reported) for 33 days. Animals were examined for tumor 

development twice per week and sacrificed when the tumor size reached 1-2 cm in 

diameter. At necropsy, the pituitary gland and uterus were collected and weighed and 

blood serum obtained to measure for prolactin levels. For cell proliferation 

assessments, MtT/E-2 cell cultures were exposed to 0 or10-7-10-4 M atrazine for 7 days 

and cell proliferation measured using the WST-1 assay (reduction WST-1 into formazan 

dye by viable cells). Activation of the ERE-luc reporter gene was evaluated by 

measuring luciferase activity in MtT/E-2 cells transfected with the ERE-luc reporter gene 

and subsequently exposed to 0 or 10-7-10-4 M atrazine for 24 hours. 

Atrazine exposure did not result in MtT/E-2 cell proliferation according to the WST-1 

assay nor did it have an estrogenic response as evidenced by a lack of response in the 

ERE reporter gene assay. After 33 days of exposure, atrazine did not cause any 

changes in body, uterine, or pituitary weights. Serum prolactin levels were also 

unaffected by exposure to up to 500 mg/kg atrazine. In contrast, exposure to a 0.5 mg 

subcutaneous pellet of estradiol resulted in a marked decrease in body weight, and an 

increase in uterine and pituitary weights along with a marked increase in serum 

prolactin (↑7-fold, p<0.01). Tumor development was also unaffected by treatment with 

atrazine with evidence of tumor development first appearing on day 24 of the 

experiment for animals in the control or atrazine treated groups as opposed to 9 days 

for animals treated with estradiol. 

Reviewer’s Comments: The current study had a number of deficiencies including the 

lack of data on the purity of the atrazine used in the study or the sample size. 

Nonetheless, some general conclusions may be drawn from this study. In particular, 

 

17 In this evaluation only the results for atrazine will be discussed 
Page 190 of 263 

that atrazine exposure up to 500 mg/kg did not enhance the appearance of estrogendependent pituitary tumors nor does it result in increased cell proliferation. When 

considered collectively, the data reported by Fujimoto, Son, Tanaka and co-workers 

demonstrate that atrazine exposure did not accelerate tumor progression. 

A.7.2 Fukamachi, K., Han, B.S., Kim, C.K., Takasuka, N., Matsuoka, 

Y., Matsuda, E., Yamasaki, T., and Tsuda, H. (2004). Possible 

enhancing effects of atrazine and nonylphenol on 7,2-

dimethylbenz[a]anthracene-induced mammary tumor development in 

human c-Ha-ras proto-oncogene transgenic rats. Cancer Sci. 

95(5):404-410. 

This study evaluates the potential of atrazine or nonylphenol to promote growth of 

mammary tumors induced by 7,2-dimethylbenz[a]anthracene (DMBA) in transgenic (Tg) 

rats carrying the human c-HA-ras proto-oncogene. These rats are exquisitely sensitive 

to DMBA-induced mammary tumors.18 Two-hundred seventy six female and male Tg 

and non-Tg rats were administered a single 25 mg/kg dose of DMBA via gavage at an 

age of 50 days. Beginning on the following day, animals were exposed in the diet to 0, 

5, 50, or 500 ppm atrazine (purity unknown) [≈ 0, 0.55, 6.2, or 36.4 mg/kg/day (♀) and 

0, 0.26, 2.75, or 24.23 mg/kg/day (♂)]. The Tg females were exposed to atrazine for 8 

weeks while the non-Tg females and all males were exposed to atrazine for 20 weeks. 

At the end of the exposure period, animals were sacrificed by exsanguination, the 

numbers of grossly observed tumors were recorded and subsequently measured and 

subjected to histopathological examination. In addition, body, liver, kidney, ovarian, 

uterine, and testis weights were recorded. Levels of serum atrazine were measured 

after necropsy by liquid chromatography and mass spectrometry (LC/MS). The 

potential impact of atrazine on cell proliferation was also measured by exposing the 

human mammary cancer cell line MCF-7 to atrazine for 3 days. Cell proliferation was 

then measured using the WST-1 assay (measures viable cells capability to reduce 

WST-1 into formazan dye). 

Tg females exposed to 500 ppm atrazine exhibited a statistically significant decrease in 

body weight (↓14%, p<0.01) with a concomitant decrease in food consumption (↓10%, 

p< 0.05). A statistically significant increase in the incidence of mammary adenomas 

(↑67%, p<0.01 vs 17% control) was noted following exposure of Tg female rats to 5 ppm 

atrazine. However, no increase was observed after exposure to 50 or 500 ppm 

atrazine. The incidence of mammary adenocarcinomas at 5 and 50 ppm atrazine was 

100% (control: 50%) although the incidence at 500 ppm was lower (≈86%). In contrast 

to the apparent increase in mammary tumors in Tg females, Tg males exposed to 500 

ppm atrazine had a decrease in the incidence of skin tumors (40% vs. 67% control) 

although a non-statistically significant increase in the incidence of mammary 

adenocarcinomas (100% vs 56% control) was also reported at this dose level. No data 

were provided on non-Tg rats (males or females). 

 

18 In this evaluation only the results for atrazine will be discussed 
Page 191 of 263 

The study authors concluded that atrazine appeared to enhance mammary tumors in 

female Tg rats but without any dose relationship while decreasing the incidence of skin 

tumors in Tg males. Furthermore, the authors concluded that atrazine did not increase 

cell proliferation of MCF-7 cells. Several limitations were identified in this study that 

hinders a meaningful interpretation of the results. As an example, Tg female rats 

received atrazine for 8 weeks, the remainder of the animals in the study received 

atrazine for a considerably longer period (20 weeks). In addition, the purity of the 

atrazine used in the study was not reported, no exposure concentrations were provided 

for the MCF-7 experiment, and no data were presented for the non-Tg rats or for the 

MCF-7 cell proliferation assay. 

Reviewer’s Comments: The lack of data on non-Tg rats is a critical deficiency in this 

study. In experiments conducted by Ueda et al. using non-Tg rats treated with DMBA to 

induce mammary tumors, a relationship between atrazine exposure and increases in 

the incidence of tumor-bearing rats cannot be drawn. Thus, in the current study the 

different treatment and lack of data on the non-Tg rats precludes reviewers from 

drawing a conclusion on whether the increases seen in mammary adenocarcinomas 

were related to atrazine exposure. The lack of dose-response on the incidence of 

mammary adenomas and adenocarcinomas further confounds the interpretation of 

these data. 

A.7.3 Garaj-Vrhovac, V. and Zeijezic, D. (2004) Genotoxicity 

evaluation of pesticide formulations containing alachlor and atrazine 

in multiple mouse tissues (blood, kidney, liver, bone marrow, spleen) 

by comet assay. Neoplasma 51.3:198-203. 

In this study the authors evaluated possible genome damage caused by two pesticide 

formulations (Bravo® and Gesaprim®) containing alachlor and atrazine as active 

ingredients by applying the comet assay on mouse cells from blood, kidney, liver, bone 

marrow, and spleen. 1 

The focus was intended to uncover the possible genotoxicity of pesticide formulations 

and not only their active ingredients. Workers who handle these products during their 

production and application stages are exposed to the complex mixture contained in the 

formulation versus just the isolated active ingredients – which in turn could give results 

that don’t correspond to the actual conditions. 

Gesaprim®, containing 500 mg/ml of atrazine as the active ingredient were given at the 

doses of 1.08 ml/kg (540 mg/kg a.i.) and 0.07 μl/kg (3.5 X 10-2 mg/kg a.i.) to five male 

CBA mice assigned to 4 treatment groups and a control group injected intraperitoneally 

once. The lower dose represents the oral chronic RfD and the higher dose 

administered is compatible with that dose which shows survival in mice in vivo. Methyl 

methanesulfonate (MMS) at 70 mg/kg was used as a positive control. The mice were 

sacrificed 24 hours after treatment; blood (taken into heparinized vacutainers) and 
Page 192 of 263 

selected organs were weighed, minced, and suspended in a chilled homogenization 

buffer. 

The alkaline comet assay of blood samples was performed according to standard 

protocol, while organ samples were subjected to a modified assay (Sasaki, YF, 1997). 

Each organ and pesticide concentration, 100 cells were analyzed by the Comet assay II 

automatic digital analysis system to determine tail length and tail moment. Any 

differences of assay endpoints between control blood and organs and those from 

treated mice were evaluated using the Mann-Whitney U-test. 

Results showed no death, morbidity, or distinctive clinical signs observed after any 

treatment (including during necropsy). Mean values of the comet assay endpoints were 

found to be statistically significant (p<0.01) regarding an increase of tail length for all 5 

tissues examined in mice in low (0.07 μl/kg) and high (1.08 ml/kg) treatment groups 

compared to control. The DNA of the kidney and liver, for both concentrations given, 

showed the largest migration. There was also a significant increase for all tissues in the 

higher concentration treated group when compared to the lower concentration group. 

For mice given the lower concentration, the tail length values of the kidney and liver 

were significantly higher than those of blood, bone marrow, and spleen from the same 

group but non significant difference was found between the liver and kidney; while in the 

higher dose group the kidney and liver tail lengths were significantly higher but no 

statistical difference was found. Tail lengths in the kidney DNA from mice treated with 

1.08 ml/kg Gesaprim® were up to 99 μm versus 84 μm for mice in the 0.07 μl/kg group 

(data not shown). For the liver, the tail lengths at the higher dose were 97 μm whereas 

at the lower dose it was 39 μm, much lower when compared to the kidney. 

The authors have concluded that regardless of the dose, genome damage in all tissues 

examined was detectable with the comet assay. The most affected organs were the 

kidney and liver. This paper also cites several studies which show contradictory results 

both in vitro and in vivo. This study also gave descriptions of studies on human 

lymphocytes showing no appearance of genotoxicity and provided a rationale as to why 

the toxic activity maybe slightly increased at higher doses when compared to the RfD, 

could be due to the removal of apoptotic cells (data not shown). Other apoptotic 

detection methods should be employed before presenting those results. 

Reviewer’s Comments: Significant (p<0.01) increases in the tail length and tail moment 

were recorded for all tissues at both doses of atrazine. However, there are 

uncertainties regarding the atrazine findings. For example, the authors stated, “genome 

damage for both pesticides was found to be higher for the higher dose given”. It was 

noted, however, that the “dose response” is very flat considering that more than two 

orders of magnitude separate the atrazine doses that were tested. Nevertheless, the 

relevance of the DNA damage data for atrazine is uncertain because neither the 

species (rat) nor the target tissue for tumors (mammary tumors) were examined. 

Overall, the use of the alkaline comet assay on different tissue samples could provide 

evidence of genotoxic effects of pesticides in vivo. Garaj-Vrhovac et al. and Zeljezic 
Page 193 of 263 

and Garaj-Vrhovac (2004) concluded that Gesaprim (an atrazine formulation) induced 

genome damage. The limitation of these studies is that a formulation of atrazine was 

used and no information is provided to determine the percentage of atrazine present in 

the test material. Thus, it is entirely possible that the DNA breaks reported after 

Gesaprim exposure may be related to other chemicals in the formulation rather than 

atrazine per se. 

A.7.4 Kmetic, I., Srcek, G., Slivac, I., Simic, B., Knlewald, Z., 

Kniewald, J. 2008. Atrazine Exposure Decreases Cell Proliferation in 

Chinese Hamster Ovary (CHO-K1) Cell Line. Bull Environ Contam 

Toxicol. 81: 205-209. 

The purpose of this study was to determine the toxic effect of atrazine at the ovarian 

cellular level. The Chinese Hamster Ovary (CHO-K1) cell line was used as the test 

system for evaluation of in vitro atrazine cytotoxicity and the morphological changes 

were followed during cell death. 

CHO-K1 cells were treated with atrazine at concentrations ranging from 10-160 μg 

atrazine/mL of cell suspension (46-742 μM) for 24, 48 or 72 hours. The cell viability was 

determined by four different bioassays: Trypan blue exclusion method, Kenacid Blue, 

Neutral red and MTT assays. Trypan blue exclusion method was used to estimate the 

proportion of viable cells. The Kenacid blue assay determines the total cell protein 

content. The Neutral red uptake assay determines the accumulation of the neutral red 

dye in the lysosomes of viable uninjured cells. The MTT assay determines the viability 

of cells. 

All four methods showed clear dose-dependent cytotoxic effects. Concentrations of 

atrazine 20-80 ug/mL followed by Trypan blue method showed significantly decreased 

proliferation of cells in CHO-K1 cells line at all dose levels, with the toxicity 

progressively increased with high atrazine concentrations. After 72 hours incubation 

period, the 20 ug/mL atrazine concentration significantly decreased cell proliferation by 

19% in CHO-K1. Cell viability was decreased 49% at 60 ug atrazine/mL and 55% at 80 

ug atrazine/mL, both at p<0.001. 

IC20 and IC50 values were determined after 24, 48 and 72 hours for the four methods. A 

comparison of the IC20 values after 48 hours or IC20 and IC50 after 72 hours of 

incubation showed that Neutral red, Kenacid blue and MTT assays showed a similar 

rate of toxicity. The Trypan blue assay was more sensitive. The IC50 value for trypan 

blue after 72 hours was two times lower than the IC50s for the other 3 assays. 

Morphologically, the level of apoptosis in atrazine treated cells was low. 

Reviewer’s Comments: Cell proliferation was decreased in Chinese Hamster ovary 

(CHO) cell lines at relatively low levels of atrazine exposure. 
Page 194 of 263 

A.7.5 Malik, S. I., Terzoudi, G.I., and Pantelias, G.E. (2004). SCE 

analysis in G2 lymphocytes prematurely condensed chromosomes 

after exposure to atrazine: the non-dose-dependent increase in 

homologous recombinational events does not support its genotoxic 

mode of action. Cytogenet Genome Res 104: 315-319. 

Human peripheral lymphocytes, collected from seven healthy volunteers, were grown, 

stimulated with phytohemagglutinin and exposed to atrazine (unreported purity) 

concentrations ranging from 5 to 220 μg/mL atrazine, the solvent (dimethyl sulfoxide ) or 

the positive control (mitomycin C) for 24 hours. Three separate experiments were 

conducted. Prior to the end of treatment, calyculin-A was added to the appropriate 

cultures for the last 1 hour of incubation (to arrest cells at G2) or colcemid for the last 3 

hours [to arrest cells at metaphase (M-phase)]. The rationale for using cell arrest at G2 

rather than the conventional approach of colcemid treatment to collect cells at 

metaphase was to determine whether atrazine would increase the frequency of 

homologous recombination, a DNA repair process associated with SCE induction. Cells 

were collected, stained by the fluorescent-plus-Giemsa technique and 30-50 cells were 

scored for each culture; triplicate cultures were prepared per treatment group. 

Results from the first experiment showed that concentrations ≥220 μg/mL atrazine could 

be scored for SCE induction in G2-phase cells while no metaphases were found at 120 

and 220 μg/mL in the colcemid-treated cultures. Thus, SCEs could be scored even at 

levels that were lethal in the conventional assay and there was no significant increase in 

SCE induction at 60-220 μg/mL. Results for the second experiment were in good 

agreement with the first trial and indicated that atrazine over a concentration range of 5 

to 200 μg/mL did not increase the frequency of SCE induction in G2-prematurely 

condensed chromosomes (PCCs). Using cells treated with 20 μg/mL and arrested with 

either colcemid or calyculin-A, trial three results indicated that the variation in SCE 

frequencies in lymphocyte cultures is significantly lower in G2-PCCs than in SCEs 

scored in the metaphase cells. 

Reviewer’s Comment: The assay was well-conducted and indicates that there was 

convincing evidence that atrazine is not genotoxic in this test system. 

A.7.6 Manske, M., Beltz, L, and Dhanwada, K. 2004. Low-Level 

Atrazine Exposure Decreases Cell Proliferation in Human 

Fibroblasts. Arch. Environ. Contam. Toxicol. 46:438-444. 

This purpose of this study was to examine the effect of low-level, short-term atrazine 

exposures on human fibroblast cells in culture by assessing cell proliferation and 

apoptosis. 

Normal human fibroblasts, DET 551, were used in the saturation density analysis to 

measure cell proliferation. In this assay, DET 551 cells were plated at 2x105

 cells/100 

mm dish in MEM with 0.5% FBS (low serum medium). Cells were incubated at 37oC 
Page 195 of 263 

with 5% CO2 for 48 hours in the low serum medium to synchronize cells. After 48 hour 

the medium was removed and replaced with complete medium with 10% FBS 

containing increasing concentrations of atrazine or DMSO (0, 3, 10, 50, 100, 200, and 

300 μg/L). Atrazine dilutions were made from an atrazine stock concentration of 32 

mg/L dissolved in DMSO. Cells were grown for 5 days at 37oC and 5% CO2. After 

harvesting, individual cells were counted by the trypan blue exclusion method. Viability 

of cells in all treatment groups and controls was over 99%. The actual number of cells 

treated with increasing concentrations of atrazine or solvent control was compared to 

the number of control cells. Cells were counted using a hemocytometer. All experiments 

were run in triplicate. 

An MTT assay was run to confirm the results for cell proliferation. This method does not 

rely on individual cells being counted. It is a calorimetric assay. DET 551 cells were 

plated in flat-bottom 96-well tissue culture treated plates at 2000 cells/well in low serum 

medium and incubated for 48 hours. After 48 hours, the medium was removed and 

replaced with complete medium with 10% FBS and increasing concentrations of 

atrazine or DMSO (0, 3, 10, 50, 100 and 200 μg/L) for an additional 48 or 72 hours. The 

atrazine stock concentration was the same as before, 32 mg/L in DMSO. For MTT 

analysis, 20 μl of 5 mg/ml MTT in PBS was added to cells and plates were incubated for 

4 hours at 37oC. HCl in isopropanol was added to each well, and optical density was 

read on a UV/VIS spectrophotometer. A similar procedure as followed for human 

peripheral blood mononuclear cells (PBMCs), composed of lymphocytes and 

monocytes. One million PBMCs were plated in 24 well tissue culture plates in PRMI 

with 5% FMS containing increasing concentrations of atrazine or DMSO (40, 100 or 200 

μg/ml). Cells were incubated for 96 hours at 37oC and 5% CO2. Then 150 μl of MTT 

solution was added and cells were incubated for an additional 4 hours at 37oC. HCl in 

isopropanol was added to each well, and optical density was read at 570 nm. The 

increase in OD had a positive correlation with viable cell number and indicated 

enhanced cell growth compared to control cells. All experiments were run in triplicate. 

To determine if the decrease in cell number was due to apoptosis of the treated cells, 

two assays were done—a qualitative immunohistochemical analysis and a quantitative 

enzymatic analysis (caspase assay). In the qualitative immunohistochemical analysis, 

apoptotic cells are detected with a biotin-streptavidin system complexed with 

horseradish peroxidase and a diaminobenzidine-based stain. DET 551 cells were 

exposed to atrazine or DMSO at concentrations of 0, 3, 50 or 200 μg/L for 48 hours 

before the assay was performed. Cells treated with TACS nuclease was the positive 

control. The Caspase assay was used to measure apoptosis enzymatically. Caspase-3 

activity in cell extracts was measured using the CaspASE colorimetric assay system 

protocol. The CaspASE assay is a colorimetric assay that measure activity of caspase3. Cytosolic thiol proteases called caspases are key enzymes involved in apoptosis. 

DET 551 cells were exposed to increasing concentrations of atrazine or DMSO (0, 3, 

100, 200, and 500 μg/L) for 48 hours before analysis. 
Page 196 of 263 

Cell Proliferation Results: The saturation density analysis showed that DET 551 

fibroblasts exposed to increasing concentrations of atrazine showed a decrease in cell 

growth compared to control cells. Cells exposed to 50, 200 and 300 μg/L atrazine had a 

statistically significant decrease (1.2-1.5 fold) in cell number compared to control cells 

(p<0.05). The authors also noted a decrease (not statistically significant) in cell growth 

in the highest concentration of DMSO (300 μg/L) compared to the other DMSO control 

values. This could indicate that this concentration of DMSO may be slightly toxic by 

itself since the percentage of DMSO in these cells is higher than in the other samples 

and these cells were exposed to the chemical for 5 days, 2 days longer than in the MTT 

analysis. 

In the MTT analysis, a 48 hour exposure to atrazine showed a statistically significant 

decrease (p<0.05) in DET 551 cell proliferation. Cells exposed to 10-200 μg/L had a 

dose related significantly decreased absorbance (1.1-1.7 fold) compared to controls, 

indicating a decrease in cell proliferation. There was no statistically significant decrease 

in proliferation in solvent-control-treated cells. There was no effect on cell proliferation 

by MTT analysis when human PBMCs were treated with increasing concentrations of 

atrazine for 96 hours. 

Apoptosis Results: In the immunohistochemical analysis, DET 551 cells were exposed 

to 0, 3, 50, or 200 μg/L atrazine or DMSO for 48 hours before the assay was performed. 

The atrazine and DMSO-treated samples were compared qualitatively to a TACs 

nuclease-positive control. When the cells treated with 200 μg/L atrazine or DMSO were 

compared to control cells, there was only a sight increase in nuclear staining of 

atrazine-treated cells, however, the level of apoptosis in treated–treated cells was low 

compared to the positive control. The caspase assay was then done to determine if the 

small increase in the apoptotic cells was significant. The results showed that all 

atrazine-treated samples (3-500 μg/L) had caspase activity (7.31-9.53 pmol/μl) similar 

to the negative control (7.31 pmol/μl). No significant differences were detected between 

the control treatments (DMSO) and atrazine-treated cells. 

Conclusion: In vitro exposure to low levels of atrazine (as low as10 μg/L) for a short 

exposure (48 hours) causes a decrease in cell proliferation in human fibroblasts but not 

in PBMCs. This study showed that the decrease in cell proliferation of human fibroblasts 

was not attributed to an increase in apoptosis. 

Reviewer’s Comments: In vitro data evaluating the cell proliferative properties in a 

variety of cell lines suggest indicate that atrazine causes decreases in cell proliferation. 

In general, these data suggest that atrazine is not genotoxic or mutagenic. Manske et 

al. 2004 showed that human fibroblast cell proliferation was decreased at relatively low 

levels of atrazine exposure. 
Page 197 of 263 

A.7.7 Mastrangelo, S., Tomassetti, M, Carratu, M.R., Evandri, M.G., 

and Bolle, P. (2006). Quercetin reduces chromosome aberrations 

induced by atrazine in the Allium cepa test. Environ and Mol 

Mutagen 47:254-259. 

In this study, groups of six peeled, white commercial bulbs of Allium cepa, also known 

as the “garden onion”, were placed in glass tubes containing mineral water and the 

flavonoid, quercetin (Q), which is thought to have antioxidant properties, was tested at 

0.1 to 20 μg/mL Q. Bulbs were also exposed to atrazine (unreported purity) at 0, 2.5, 

5.0 or 7.5 μg/ml and varying combinations of Q and atrazine (0.5 or 5 μg/mL Q with 2.5, 

5.0 or 7.5 μg/mL atrazine), and incubated in the dark for 5 days. Test solutions were 

renewed daily and “topped-up” on days 3, 4, and 5. Ten replicate bulbs per each 

treatment group were prepared. Bulbs were observed daily throughout the 5-day 

exposure period for root length and form and the presence of “crochet hooks” and 

tumors. At the end of treatment, the meristematic cell (analogous to stem cells in 

mammalian tissue) region from the root tips was harvested and processed for 

cytogenetic evaluation. One thousand cells were counted to determine the mitotic index 

(MI) and a total of 400 metaphases and 400 ana-/telophases (40 metaphases /slide and 

40 ana-/telophases/slide) were scored for each treatment group. 

No effects were observed on root morphology after exposure to Q or atrazine. Similarly, 

Q alone did not affect the MI at any concentration. By contrast, atrazine alone caused 

an 18% reduction in the MIs at the highest level tested (7.5 μg/mL); no cytotoxic effects 

were noted at lower doses. Combined with either 0.5 or 5 μg/mL Q, 7.5 μg/mL atrazine 

affected a slightly lower reduction in the MI (~23% ↓ for both Q concentrations) then 

when the pesticide was tested alone. Neither Q nor 2.5 or 5.0 μg/mL atrazine were 

clastogenic; however, 7.5 μg/mL atrazine induced a significant (p<0.001) increase in 

structural chromosome aberration. The most prominent type of aberration was 

fragments. When the plant cells were assayed with 0.5 μg/mL Q in combination with 

7.5 μg/mL atrazine, the frequency of chromosome aberrations was listed as significantly 

(p<0.05) lower (~43% ↓) compared to 7.5 μg/mL atrazine alone. However, no increased 

protection was afforded by the higher concentration of Q. 

Reviewer’s Comments: The study was well-conducted and these data provide evidence 

of a clastogenic response induced by atrazine at 7.5 μg/mL atrazine, a concentration 

resulting in adequate cytotoxicity (~ 20% ↓in the MI). The data also suggest that the 

clastogenic activity is likely to be confined to a narrow range of doses because 

concentrations >7.5 μg/mL atrazine would likely exceed the recommended level of 

cytotoxic and no cytotoxicity or clastogenicity was noted at ≤ 5.0 μg/mL. 
Page 198 of 263 

A.7.8 Singh, M., Sandhir, R., and Kiran, R. 2008. Atrazine-Induced 

Alterations in Rat Erythrocyte Membranes: Ameliorating Effect of 

Vitamin E. J. Biochem. Molecular Toxicology. Vol 22, No. 5: pgs. 363-

369. 

This study evaluated the possible beneficial effects of vitamin E against atrazineinduced oxidative stress in erythrocytes. Erythrocytes are susceptible to oxidative 

damage and a good model to understand oxidative damage induced by xenobiotics. 

Vitamin E is an antioxidant. 

Male Wistar rats (n=18 animals/group) were administered atrazine (300 mg/kg/day, 

97.83% purity), Vitamin E (100 mg/kg/day), and combined atrazine (300 

mg/kg/day)/Vitamin E (100 mg/kg/day) for a period of 7, 14, and 21 days. A vehicle 

control group was similarly treated. Blood samples were collected at the end of the 

treatment periods. Erythrocyte membranes were prepared and analyzed for 

acetylcholinesterase (AChE) activity, lipid peroxidation (LPO), and lipid composition 

(total lipid content, phospholipid phosphorus, cholesterol). Protein content was also 

determined. Scanning electron microscopy (SEM) was used to examine morphological 

alterations of erythrocytes. 

Atrazine treatment resulted in significant (p<0.05) decreases in AChE activity in 

erythrocytes at 7 days (22.32%), 14 days (25.58%), and 21 days (26.96%), compared to 

controls. Atrazine/Vitamin E treatment resulted in significant increases (12-14%) in 

AChE activity at 7, 14, and 21 days compared to atrazine alone treated animals. 

Atrazine treatment resulted in a significant increase (p<0.05) in lipid peroxidation (nmol 

MDA/mg protein) compared to controls, with the effects being more pronounced with 

increasing duration. After 21 days treatment there was a 218.29% increase in MDA 

levels. The increase in LPO suggests that oxidative stress is induced by atrazine. 

Vitamin E treatment alone significantly (p<0.05) decreased MDA levels compared to 

controls. Atrazine/Vitamin E treatment significantly (p<0.05) decreased lipid peroxidation 

when compared to animals treated with atrazine alone. 

Atrazine treatment resulted in a significant (p<0.05) decrease (24%) in the total lipid 

content of erythrocyte membranes only after 21 days, compared to controls. Vitamin E 

along with atrazine treatment significantly increased total lipid content to normal levels 

after 21 days, as compared to the atrazine treated group. Atrazine treatment 

significantly (p<0.05) decreased cholesterol content after 14 days (20.12%) and 21 days 

(32.94%). Atrazine/Vitamin E treatment significantly increased cholesterol content after 

14 days (33.86%) and 21 days (57.02%), compared to the atrazine treated group. 

Atrazine treatment resulted in a significant decrease in phospholipid content after 14 

days (16.76%) and 21 days (37.20%), compared to controls. Atrazine/Vitamin E 

treatment significantly increased phospholipid content after 14 days (22.86%) and 21 

days (57.92%), compared to atrazine treated group. 
Page 199 of 263 

Erythrocytes of rats treated with atrazine showed significant morphological changes as 

compared to the control group. These changes included mild to moderate distortion in 

shape, significant ruptured membranes, and echinocyte formation, central or peripheral 

protuberances. SEM of erythrocytes of atrazine/vitamin E group shows improved 

erythrocyte topography as compared to atrazine-treated group. Extent of protuberance 

significantly decreased as compared to the control group. 

Reviewer’s Comments: The results of this study are questionable given that the atrazine 

doses used to induce these genotoxic effects are orders of magnitude higher than what 

is currently used as the point of departure for human health risk assessment. 

A.7.9 Singh, M., Kaur, P., Sandhir, R., Kiran, R. (2008). Protective 

effect of vitamin E against atrazine-induced genotoxicity in rats. 

Mutat Res 654:145-149. 

The protective effect of an antioxidant, vitamin E, against atrazine-induced genotoxicity 

was investigated in young (~4 -5 weeks old, based on the weight range of 100-120 g)19a

Wistar male rats dosed with vitamin E alone, atrazine (97.83%) alone or a combination 

of atrazine and vitamin E in the comet and micronucleus assays. Accordingly, groups of 

six male rats were administered oral gavage doses of corn oil, 100 mg/kg/day vitamin E, 

300 mg/kg/day atrazine or a combination of comparable doses of vitamin E and atrazine 

for 7, 14 or 21 days. At the end of treatment, peripheral blood and liver were collected 

simultaneously from each test animal, processed and assayed for micronucleus 

induction and/or DNA damage (gel electrophoresis and Comet assay). 

Results from the gel electrophoresis on DNA isolated from the liver show that atrazine 

alone induced DNA damage as indicated by “shearing of the DNA” at 7, 14 and 21 

days; the maximum effect was observed at 14 days. The investigators stated that 

atrazine did not induce the classic DNA ladder pattern, which is associated with 

apoptosis but shearing of DNA suggested DNA damage to the atrazine-treated livers. 

Similarly, significant (p<0.001) increases in the DNA tail length and tail moment were 

obtained from the comet assay performed on both blood and liver sampled at all harvest 

times. The response was generally time-related and in good agreement with the 

electrophoresis data showing a marked increase in DNA damage at 14 and 21 days. 

By contrast, vitamin E alone was not genotoxic in either tissue. However, significantly 

(p<0.001) reduced (23-56%↓) DNA tail lengths liver and blood samples were obtained 

for the tissues treated with atrazine plus vitamin E, compared to atrazine treatment 

alone. In agreement with these data, the results of the liver cell micronucleus assay 

demonstrated that atrazine alone increased (p<0.001) the frequency of micronuclei at all 

sample times and the response was time-related with the largest increase occurring at 

21 days. The treatment of the rats with atrazine (300 mg/kg/day) plus vitamin E (100 

 

19 According to personal communications with Charles Parady, Senior Specialist, Charles River, male 

Wistar rats in the weight range of 100-120 gm would be approximately 4-5 weeks old. 
Page 200 of 263 

mg/kg) caused significant (p<0.001) reductions in the frequency of micronuclei at 7 

(23%↓) and 21 (14%↓) days as compared to atrazine-treated rats. 

Reviewer’s Comments: The results of this study are questionable given that the atrazine 

doses used to induce these genotoxic effects are orders of magnitude higher than what 

is currently used as the point of departure for human health risk assessment. 

A.7.10 Son, H-Y., Nishikawa, A., Okazaki, K., Lee, K-Y., 

Imazawa, T., and Hirose, M. (2003). Lack of Modifying Effects of 

Atrazine and/or Tamoxifen on Thyroid Carcinogenesis in Rats 

Pretreated with N-bis(2-hydroxypropyl)nitrosamine (DHNP). Food 

Chem. Toxicol. 41:1811-1816. 

In this study the researchers investigated the effect of atrazine and/or tamoxifen on the 

progression of DHPN-induced thyroid carcinogenesis.20 The goal of the study was to 

assess the impact of atrazine (with or without concomitant tamoxifen exposure) on 

thyroid hormone changes and thyroid lesions induced by DHPN. 

Twenty male F344 rats per group received a subcutaneous injection of 2800 mg/kg 

DHPN or saline. Starting one week later, the animals were exposed to 0, 5, 50, or 500 

ppm atrazine (purity unknown) through the diet for 24 weeks. Rats receiving the saline 

injections were exposed to 0 or 500 ppm atrazine. At the end of the exposure, animals 

were sacrificed and the thyroid, pituitary, liver, lungs, kidney, pancreas, testis, 

epididymis, and brain were collected, weighed and subjected to histopathological 

examination. In addition, serum from 5 rats/group (except the 5 and 50 ppm atrazine 

groups) was collected and used to measure thyroid hormones (T3, T4, and TSH). 

Exposure to 500 ppm atrazine resulted in a decrease in body weight (↓12-14%, p<0.05) 

regardless of DHPN exposure. The relative brain, liver, testicular, and epididymal 

weights from rats receiving both DHPN and 500 ppm atrazine were increased by ≈9-

13% (p<0.05) when compared to animals receiving DHPN only. Moreover, when these 

rats were compared to the control group (no DHPN or atrazine exposure), the changes 

in body weight and relative organ weights were similar. Comparison of rats exposed to 

500 ppm only (no DHPN injection) revealed that these animals experienced a 14% 

decrease in body weight (p<0.05) along with an 11-12% increase in relative brain, 

testicular, an epididymal weight. However, unlike pre-exposure to DHPN followed by 

500 ppm atrazine, exposure to 500 ppm atrazine alone did not elicit an increase in the 

relative liver weight. Histopathology assessments did not reveal any compound-related 

changes though the data were not provided in the study report. Hormone analysis 

revealed that while there is a statistically significant decrease in T4 levels (↓16%, 

p<0.05) after exposure to DHPN + 500 ppm atrazine relative to exposure to DHPN 

alone and no changes in T3 or TSH. When compared to the control group, the 

decrease in T4 is ≈10% and non-statistically significant. Furthermore, exposure to 500 

 

20 In this evaluation only the results for atrazine will be discussed 
Page 201 of 263 

ppm atrazine alone did not elicit changes in any of the thyroid hormones while exposure 

to DHPN by itself resulted in a 7% increase in T4. This suggests that the apparent 

decrease in the hormone after exposure to DHPN + atrazine may be related to the 

increase above background caused by DHPN and not indicative of an effect of atrazine 

on thyroid hormone homeostasis. 

Reviewer’s Comments: The results of this study indicate that atrazine does not have an 

impact on thyroid carcinogenesis or thyroid hormone homeostasis. With the exception 

of a decrease in body weight, atrazine did not appear to have any effects on the 

parameters evaluated in this study. No histopathological changes were reported after 

exposure to 500 ppm atrazine and the increases in relative organ weights observed are 

most likely related to this decrease in body weight rather than a direct effect on the 

organs. Similarly, thyroid hormone assessments did not suggest a direct effect of 

atrazine on thyroid hormone homeostasis. It should be noted, however, that this report 

does not include information on the purity of the atrazine used in the study and that the 

histopathological data are not provided. 

A.7.11 Tanaka, T., Kohno, H., Suzuki, R., Sugie, S. (2004) Lack 

of modifying effects of an estrogenic compound atrazine on 7,12-

dimethylbenz(a)anthracene-induced ovarian carcinogenesis in rats. 

Cancer Lett. 210:129-137. 

The effect of atrazine on DMBA-induced ovarian carcinogenesis was investigated in this 

study. The authors hypothesis is that the operative mode of action leading to ovarian 

adenocarcinomas involves hormonal disruption (particularly estrogen). Therefore, 

exposure to atrazine (which has been associated with hormone disruption) may affect 

ovarian carcinogenesis. 

In this series of experiments, the researchers exposed 12-20 female Sprague-Dawley 

rats to 0.5% DMBA (7,12-dimethylbenz(a)anthracene) injected directly into the left 

ovaries. One week after exposure to DMBA, animals were fed diets containing 0, 5, 50, 

or 500 ppm atrazine (purity unknown) for 50 weeks. Another group did not receive a 

DMBA injection but were exposed to 0 or 500 ppm atrazine through the diet. On week 

51, the animals were sacrificed, necropsied and tissues with gross lesions, as well as, 

the liver, kidney, mammary gland, lung, and heart subjected to histopathological 

evaluation. In addition, immunohistochemistry evaluations for proliferating cell nuclear 

antigen (PCNA), expression of the androgen or estrogen receptors (α and β) and the 

BRCA-1 gene were conducted. 

Neither DMBA, nor atrazine or DMBA + atrazine exposure led to any changes in 

ovarian, uterine, or body weight. DMBA exposure followed by dietary exposure to 500 

ppm atrazine exposure led to a 10% statistically significant increase in absolute liver 

weight, consistent with what has been reported by other investigators. DMBA exposure 

led to a 45% incidence in ovarian adenocarcinomas vs 0% in control. Atrazine 

appeared to slightly modify the effect of DMBA since exposure to 5, 50, or 500 ppm 
Page 202 of 263 

atrazine subsequent to DMBA exposure resulted in a slight non-statistically significant 

decrease in the incidence of ovarian tumors (22, 28, or 26%, respectively) compared to 

45% incidence after DMBA treatment-alone. There were no compound-related effects 

that could be unequivocally attributed to either DMBA, atrazine, or DMBA + atrazine 

exposure in the other tumor types seen in his study (malignant fibrous histiocytomas, 

hemangiomas, mammary tumors). PCNA-labeling after treatment with DMBA alone 

was markedly increased (↑1644%) over unexposed animals. Atrazine exposure did not 

affect PCNA labeling index. Similarly, immunohistochemistry assessments did not 

reveal an impact of atrazine exposure on the expression of the BRCA-1 protein or the 

estrogen or androgen receptors after DMBA treatment. 

Reviewer’s Comments: The study authors concluded that atrazine did not result in any 

modifying effects on DMBA-induced rat ovarian carcinogenesis. It should be noted, 

however, that though not statistically significant the incidence of ovarian tumors due to 

DMBA exposure was reduced by half when DMBA treatment was followed by atrazine 

exposure at dietary concentrations of 5-500 ppm (0.09-8.5 mg/rat/day). The 

toxicological significance of this finding, however, is unclear given the lack of doseresponse over a two-order of magnitude difference in atrazine exposures. However, 

when considered collectively, the data reported by Fujimoto, Son, and Tanaka and coworkers demonstrate that atrazine exposure did not accelerate tumor progression. 

A.7.12 Ueda, M., Imai, T., Takizawa, T., Onodera, H., Mitsumori, 

K., Mtsui, T. and Hirose, M. (2005) Possible enhancing effects of 

atrazine on growth of 7,12-dimethylbenz(a)anthracene-induced 

mammary tumors in ovariectomized Sprague-Dawley rats. Cancer 

Sci. 96(1):19-25. 

The objective of this study was to evaluate the effect of atrazine exposure on late 

promotion/progression of mammary tumors in ovariectomized rats after treatment with 

7,12-dimethylbenz(a)anthracene (DMBA). 

Two hundred and six female Sprague-Dawley rats were used in the study. One 

hundred eighty six received a single gavage dose of DMBA (50 mg/kg) while 20 control 

rats received vehicle. Nineteen weeks after DMBA treatment (when palpable tumor 

incidence was ≈ 50%), the animals were ovariectomized. The 89 rats bearing tumors at 

this time were designated as DMBA-tumors (+) [Group A] while the 90 rats without 

tumors by week 19 were designated as DMBA-tumors (-) [Group B]. These rats were 

distributed among 4 subgroups (22-23 rats/group) that received 0, 5, 50, or 500 ppm 

atrazine (purity unknown) [approximately 0, 0.25, 2.5, and 25 mg/kg/day] through the 

diet for 34 weeks. A third group (Group C) consisting of animals not exposed to DMBA 

but exposed to atrazine at 0 or 500 ppm (10 rats/dose) for 34 weeks was also 

examined. Body weights, food consumption, the number of rats bearing tumors, 

number of tumors/rat, size of tumors, and location of palpable tumors were recorded 

once per week during atrazine-treatment. At the terminal sacrifice, whole skin with 

mammary glands and tumors were collected. In addition, the liver, kidneys, uterus, 
Page 203 of 263 

pituitary glands, and adrenal glands were removed and weighed. Histopathology 

evaluations were conducted on mammary tumors, as well as, the liver, kidneys, spleen, 

lungs, heart, Zymbal glands, uterus, vagina, pituitary, adrenals, thyroids, mammary 

glands (not having gross indications of tumors), and scars of the ovariectomized 

regions. If indications that traces of ovarian tissue remained after the ovariectomy, the 

animals were removed from the study. Thus the number of Group A animals treated 

with the various concentrations of atrazine was between 18-21/group and Group B 

animals treated with atrazine ranged between12-19 rats/group. Immunohistochemistry 

analysis was used to detect potential increases in proliferating-cell nuclear antigen 

(PCNA), single strand DNA (ssDNA), and estrogen receptor α (ER α) in mammary 

tumors (except for fibromas). Finally, estradiol, progesterone, prolactin, and luteinizing 

hormone levels were measured for Group A animals. 

No effects on body weights or organ weights were reported for any treatment group. 

Mortality was higher in Group A (rats with early tumors) than Group B (rats with late 

tumors) but there was no apparent correlation to atrazine exposure. 

Following ovariectomy, the number of Group A tumor-bearing rats and total number of 

tumors palpated decreased by 6-29% and 50-68%, respectively, regardless of atrazine 

exposure. Similarly, the types of tumors (i.e., benign vs. carcinoma) were not affected 

by atrazine treatment and though there was an apparent dose-related increase in tumor 

size at doses ≥ 50 ppm (↑43 -261%) there was no statistical significance due to the 

large variability in the Group A. Immunohistochemistry evaluations showed that Group 

A rats treated with 500 ppm atrazine showed an increase in the number of ERα-positive 

tumor cells relative to control (3/3 vs. 2/5) as well as in the number of PCNA-positive 

cells (↑92%, p<0.05) in malignant mammary tumors. The authors report that no 

changes in hormone levels that could be attributed to atrazine exposure were observed. 

However, no data were provided to corroborate this latter statement. 

Interestingly, at the end of the study Group B rats (i.e., DMBA-treated rats with late 

tumors) had a statistically significant (p<0.05) increase in the number of tumor-bearing 

rats exposed to 500 ppm atrazine relative to the Group B control animals (58% vs. 26% 

in control) yet a comparison with the Group A control animals revealed a lower 

incidence of tumor-bearing rats in the atrazine-treated animals than in the control. A 

≈1300% increase in the size of tumors was also noted for the Group B rats treated with 

≥ 50 ppm atrazine; again comparison to the Group A control animals revealed tha the 

tumors in the atrazine group were smaller than in the Group A controls. There was no 

evidence of a clear correlation between atrazine exposure and the incidence of 

malignancies for either Group A or Group B rats. 
Page 204 of 263 

Figure 17: Treatment Groups 

The authors concluded that atrazine has the potential to facilitate mammary tumors 

during the promotion/progression stage. These conclusions are based on increases in 

the Group B incidence of tumor-bearing rats, number of carcinomas, tumor size at 

doses ≥ 50 ppm, and in the number of cells proliferating (PCNA-positive cells) and 

expressing ERα after exposure to 500 ppm atrazine. 

The preponderance of the evidence, however, does not support the statement that 

atrazine contributes to mammary tumor development. For example, for Group A rats 

(tumors present at week 19), there was no correlation between atrazine exposure and 

the number of tumor-bearing rats, number of new tumors (appearing after ovariectomy), 

number of tumors/rat or the incidence of carcinomas. Moreover, the regression of 

palpable tumors observed after ovariectomy was similar for rats in the control and 

atrazine-treated Group A rats. Although for Group B a statistically significantly higher 

incidence of tumor-bearing rats is seen after exposure to 500 ppm atrazine relative to 

the Group B control, it should be noted that the incidence in the Group B control is 

substantially lower than in the Group A control (Control B: 26% vs Control A: 72%). 

When the Group B 500 ppm atrazine-treated rats are compared to the Group A controls, 

the incidence of tumor-bearing rats is lower after 500 ppm treatment than in the Group 

A controls. It should be noted that the incidence of tumor-bearing rats in the Group B 

control was substantially lower than in the Group A control. When both control groups 

are combined (Group A + Group B), the incidence of tumor-bearing rats at the Group B500 ppm atrazine dose level is increased by 9% and is not statistically significant.21 In 

fact, if Group B rats treated with 500 ppm atrazine are compared to the Group A control 

rats, the tumor incidence after atrazine exposure is lower than in the Group A controls. 

 

21 Calculated by reviewer and analyzed using Fisher’s Exact test 

A

B

C

Table excerpted from Ueda et al., (2005) p. 22 
Page 205 of 263 

For rats treated with 500 ppm atrazine in Group B (no tumors at week 19), the incidence 

of tumor-bearing rats was lower than the number of tumor-bearing rats in the Group A 

control (58% vs 72%). Similarly, the number of carcinomas present in atrazine-treated 

Group B rats did not show a dose response and at 500 ppm atrazine the carcinoma 

incidence was lower than for the Group A control rats. 

With regards to the immunohistochemical evaluations, a statistically significant increase 

(↑92%, p< 0.05) in the number of PCNA-positive cell carcinomas was noted for Group A 

rats treated with 500 ppm atrazine. This is not unexpected given that carcinomas are 

quickly proliferating lesions. Interestingly, atrazine exposure in and of itself does not 

appear to contribute to the increase in PCNA-positive cells as evidenced by the fact that 

for late developing carcinomas (Group B rats) no statistically significant increase was 

noted at the 500 ppm atrazine dose level. An increase in the incidence of ERα-positive 

carcinomas was reported at the 500 pm atrazine level in Group A rats (100% vs 40% 

control). It should be noted, however, that a 100% incidence of ERα-positive 

carcinomas was also reported for the control and 5 ppm atrazine Group B rats (latedeveloping tumors) while the high dose atrazine rats in Group B had an incidence of 

75%. 

Reviewer’s Comments: Based on the multiple lines of evidence presented in this study, 

a relationship between atrazine exposure and increases in the incidence of tumor rats 

cannot be drawn. In many instances it appears that the incidence reported for the 500 

ppm atrazine Group B rats was comparable or at times lower than the incidence 

reported for the control Group A rats. Since control rats in Groups A and B were treated 

the same (only difference is detection of palpable tumors at week 19), a comparison of 

the treated groups with either control group or a combination of both is valid. While it is 

true that increases are occasionally seen in the 500 ppm atrazine-treated rats that 

developed tumors after week 19 of the study when they were compared to the Group A 

control rats or when the Group A and Group B control rats (pre- and post-week 19 

tumor development) were combined, the increase was no longer evident. 

While there are a number of deficiencies in the conduct, interpretation, and reporting in 

the Ueda study, these data suggest that atrazine in an of itself does not induce 

mammary tumors in ovariectomized rats treated with a mammary tumor inducer thus 

demonstrating the importance of the ovarian hormones in the development of tumors in 

the mammary gland. 
Page 206 of 263 

A.7.13 Yi, Kun Don, Breckenridge, Charles B, and Simpkins, 

James W. 2010. Cytotoxicity of Atrazine and its Metabolites in vitro. 

Unpublished data. Syngenta Crop Protection Inc. 

In this study, the cytotoxicity of atrazine and its metabolites (diaminochlorotrizine 

[DACT], deisopropyl atrazine [DIA], ammeline [AM], hydroxyatrazine [OH-ATR]) was 

evaluated in four cell lines. The purity of the compounds was 97%. The four cell lines 

used were HT-22 cells (immortalized murine hippocampal neurons), MCF-7 cells 

(human breast adenocarcinomas), H295R cells (human adrenocortical carcinoma), and 

JEG03 cells (human placental choriocarcinoma). The cells were cultured in the 

appropriate media and the H295R, JEG-3, and MCF-7 cells were maintained at 100% 

confluency, while HT-22 cells were maintained at 50% confluency. 

For the cell viability assay, cells were seeded 24 hours before initiation at varying 

densities depending on the cell type in 96-well plates: H295R cells – 25,000 cells/well, 

JEG-3 cells – 3500 cells/well, MCF-7 cells – 15,000 cells/well, and HT-22 cells- 3500 

cells/well. Cells were exposed to atrazine or its metabolites at concentrations ranging 

from 0.001 μM to 300 μM in physiologically buffered saline (PBS) or in sterile water with 

dimethyl sulfoxide (DMSO) for up to 72 hours. After exposure, cell viability was 

measured using the membrane-permeant calcein-AM dye. Calcein-AM is a fluorogenic 

esterase substrate that is hydrolyzed to a fluorescent product in cells having esterase 

activity and intact membranes. Fluorescence was determined using an Infinity M120 

microplate reader with an excitation/emission of 485/530 nm. The results, obtained in 

relative fluorescent units (RFU), were expressed as the percentage of untreated or 

vehicle treated control values. For each assay, six independent experiments were run 

with triplicate wells for each treatment per experiment. 

The effects of atrazine on mitochondrial activity was measured in H295R cells. H295R 

cells were seeded in 96-well plates at 25,000 cells/well 24 hours before the initiation of 

the assay. Varying concentrations of atrazine were dissolved in DMSO (0.001-300 μM) 

or PBS (0.0003-300 μM) for 24 hours. Mitochondrial activity was assessed using a MTT 

assay. 

Cytosolic reactive oxygen species (ROS) was estimated by measuring the amount of 

ROS by the fluorescent dye 2 ́,7 ́-dichlorofluorescin diacetate (DCFH-DA), which 

measures hydrogen peroxide (H2O2). Cells were plated in 96-well plates at a density of 

25,000 cells/well 24 hours before the initiation of the assay. Cells were exposed to 

atrazine (10-300 μM) dissolved in DMSO or PBS. ROS production was monitored for 

up to 72 hours. DCF-2,7-dichlorofluorescin fluorescence was determined at an 

excitation of 485 nm and an emission of 538 nm using an Infinity M120 microplatereader. 

The effects of atrazine on the cytotoxic effects of other known toxins was measured 

using H295R cells seeded in 96-well plates at 25,000 cells/well 24 hours before the 
Page 207 of 263 

initiation of the assay. Varying concentrations of atrazine, DACT, DEA, DIA, ammeline, 

and OH-ATR dissolved in DMSO were added. Cell viability was measured 24 hours 

after treatment. H295R cells were co-treated with varying concentrations of atrazine 

and other know toxins (glutamate – 15 mM; 3-NPA – 15 mM; H2O2 – 250 μM) for 24 

hours. 

The results of this study showed that atrazine and its metabolites were not cytotoxic in 

four cell lines, irrespective of being solubilized in DMSO or PBS. Atrazine and its 

metabolites did not produce cytotoxicity as indicated by an absence of any effect on cell 

viability in two steroidogenic (H295R and JEG-3) and two non-steroidogenic (HT-22 and 

MCF-7) cell lines. Atrazine had no effect on mitochondrial activity in H295R cells 

regardless of whether it was dissolved in DMSO or PBS. Atrazine did not induce 

oxidative stress in H295R cells, as measured by cellular production of hydrogen 

peroxide (H2O2). 

The potential of atrazine or its metabolites to exacerbate the effects of other compounds 

known to induce cytotoxicity was evaluated. H295R cells were treated concurrently with 

atrazine and glutamate, or 3-nitropropionic acid (3-NPA), or H2O2 24 hours. Atrazine 

and its metabolites did not affect the cytotoxicity of glutamate, 3-NPA, or H2O2. 

Reviewer’s Comments: The methods section of the paper failed to include the 

evaluation of mitochondrial activity or measuring the effects of atrazine or its 

metabolites on cell viability when treated in conjunction with known cytotoxicants. 

Nevertheless, data from Yi et al. (2010) suggest that atrazine and its metabolites are not 

cytotoxic to two steroidogenic cell lines (H295R and JEG-3) as well as two nonsteroidogenic cell lines (HT-22 and MCF-7). 

A.8 Insulin/Mitochondria Function 

A.8.1 Lim, S., Ahn, S.Y., Song, I.C., Chung, M.H., Jang, H.C., Park, 

K.S., Lee, K-U, Pak, Y.K., Lee, H.K. (2009). Chronic Exposure to the 

Herbicide, Atrazine, Causes Mitochondrial Dysfunction and Insulin 

Resistance. PLoS ONE 4(4): e5186, p.1-11. 

The authors have performed a series of in vivo and in vitro experiments to assess the 

extent to which low levels of atrazine in water effect mitochondrial function and insulin 

resistance. The authors have treated Sprague-Dawley rats with 0, 30 or 300 μg/kg/day 

atrazine in drinking water for 5 months. [These levels of atrazine are significantly lower 

than the dose levels used in most atrazine studies.] Rats were given either a standard 

diet or a high fat diet. The authors stated that there were no differences in water 

consumption during the study. The manuscript does not describe the vehicle or how 

often the water was prepared. In addition, the manuscript does not provide any 

information on the concentration of atrazine in the water or estimates of the water intake 
Page 208 of 263 

during the course of the study. In particular it is important to understand if the 

concentration of atrazine in the water or the vehicle changed the water consumption. 

The following measurements were made as part of the in vivo experiments: body 

weight, visceral fat, motor activity, intramuscular and intrahepatic lipid content, plasma 

glucose, serum insulin, total cholesterol and triglycerides, intravenous glucose tolerance 

test, high insulin challenge (hyperinsulinemic-euglycemic study), energy expenditure, 

electron microscopy of mitochondria, and protein expression levels of mitochondrial 

OXPHOS complex. In vitro experiments were conducted to evaluate endogenous 

cellular oxygen consumption and mitochondrial respiratory chain activities. In general, 

the methods section lacks some important information and references to the methods 

used. For example, the methods state that motor activity was measured 4hrs/month. 

However, it is unclear whether this refers to one 4 hr session or one hr/week. The 

authors performed student’s t-tests and ANOVA. However, a 2-way ANOVA with ATZ 

and diet as the independent variables may be more appropriate. Based on limited reanalysis conducted, further scrutiny of the statistical approaches may be useful in the 

future. 

Generally, the results section of this paper is hard to follow. Figure labels and legends 

are difficult to interpret. 

Body weight and fat determinations. Based on the results section, atrazine at these 

doses increased body weights in both normal and high fat diet, although, there is a flat 

dose response relationship. The lowest dose has an equivalent effect of the highest 

water concentration. Similarly, there is poor dose dependent effect on the fat 

measures, either the low dose is equivalent to the high dose or the low dose is more 

affected than the high dose (see intrahepatic lipid/water graph; Fig 1F). These results 

are in direct conflict with many other atrazine studies which suggest that atrazine results 

in decreased body weight, not increased. 

ATZ and insulin and HOMA-IR: The authors report a dose related increase in insulin 

and HOMA-IR levels. 

ATZ insulin resistance: Fasting plasma glucose levels of atrazine treated rats on the 

regular and high fat diets were higher than those in controls. The atrazine treated rats 

showed a reduced response to insulin loading, although the dose-response curves are 

flat. 

In vitro studies: The authors observe minor effects on mitochondrial function of atrazine 

in their in vitro model at concentrations up to 460 uM. Rats given 150 mg/kg have peak 

blood concentrations of 7.5 uM. There seems to be a real disconnect between the in 

vitro concentrations needed to see effects on the mitochondria and the doses that 

produce effects on mitochondrial function in vivo. In order to achieve similar 

concentrations in vivo compared to the in vitro studies, exposures to atrazine would 

have to be well over 150 mg/kg. 
Page 209 of 263 

Reviewer’s Comments: To believe their data, one would have to believe that atrazine 

has significant and near maximal effects on mitochondrial function at doses of 30 

ug/kg/d (a LOEL) in animals on a normal diet. This seems unlikely given that most 

studies have not observed effects of atrazine until exposures are approximately 100-

1000 times higher. Most notably, the results of this study are based on the statistical 

procedures used (which may be inappropriate). Preliminary analyses by Agency 

scientists do not confirm the results reported in the study. This study is not sufficiently 

robust for use in a regulatory context and should be repeated to confirm the findings. 

A.9 Pharmacokinetics: Internal Dosimetry, Metabolism, & Time Course 

A.9.1 Dooley, G.P, Prenni, J.E., Prentiss, P.L., Cranmer, B.K., 

Anderson, M.E., Tessari, J.D. (2006). Identification of novel 

hemoglobin adduct in Sprague Dawley rats exposed to atrazine. 

Chem Res Toxicol 19:692-700. 

The potential of atrazine to form covalent adducts with hemoglobin was studied in 

groups of two female Sprague Dawley rats receiving oral gavage doses of 0, 10, 30, 

100 or 300 mg/kg atrazine (97.1%) for 3 days. Baseline blood samples were taken the 

morning before treatment and at 24, 48 and 72 hours post-initiation; subsequent 

samples were collected at 10 days and 1 and 2 months after treatment had ceased. 

Samples were centrifuged, and the plasma was withdrawn. Packed erythrocytes were 

rinsed and processed to collect purify globin. Globin samples were spotted on MALDI 

plates and subjected to MALDI-TOF/TOF MS (Matrix-Assisted Laser Desorption 

Ionization- Time of Flight/Time of Flight Mass Spectrometry). Globin samples were also 

analyzed by HPLC; fractions collected via HPLC and peptides were extracted via 

electrophoresis and tryptic digestion, purified and prepared for mass spectrometry 

analysis. Similar procedures were used to prepare samples of rat hemoglobin, 

harvested from unexposed bone marrow cells, which were treated in vitro with 90 ppm 

diaminochlorotriazine (DACT, a reactive electrophilic metabolite of atrazine). 

 

The investigators reported that an additional β globin peak was seen in exposed 

animals during the HPLC and MALDI-TOF/TOF MS analysis with a mass 110 Da 

greater than the normal β subunits. Subsequent tryptic digestion of the β peak revealed 

a peptide of 1449.9 m/z; this corresponds to a modified peptide of amino acids 121-132. 

Sequencing of this peptide yielded a 110 Da addition to Cys-125 of the major β globin 

chain. These findings were confirmed in vitro in bone marrow cells reacted with DACT, 

resulting in a peptide of 1449.9 m/z with a similar sequence of this modified peptide. 

Reviewer’s Comments: Overall, the study was well-conducted and support the 

investigators’ conclusion that atrazine exposure resulted in the formation of a covalent 

adduct with cysteine residues of hemoglobin in Sprague Dawley rat bone marrow cells 

both in vivo and in vitro. Given that, unlike rat hemoglobin, human hemoglobin does 
Page 210 of 263 

not have a reduced cysteine residue at position 125, the relevance of rat hemoglobin 

adduct formation to human risk assessment is limited. 

A.9.2 Dooley, G.P., Hanneman, W.H., Carbone, D.L., Legare, M.E., 

Anderson, M.E., Tessari, J.D., (2007). Development of an 

immunochemistry detection method for atrazine-induced albumin 

adducts. Chem Res Toxicol 20:1061-1066. 

These study authors investigated atrazine interactions with cellular macromolecules 

using rat and human albumins as the targets. For the in vivo phase, ovariectomized 

Wistar female rats (3/group) were administered oral gavage doses of 0, 5, 10 or 20 

mg/kg atrazine (97.1%) and sacrificed on postexposure day 4. A second grouping of 

animals was exposed as describe to higher doses of atrazine (0, 50 or 200 mg/kg). 

Blood was collected and the plasma albumin was purified; proteins were purified by gel 

electrophoresis, isolated and digested with thermolysin. Recovered peptides were 

spotted on a MALDI plate and analyzed by MALDI-TOF/TOF MS. 

For the in vitro phase, commercially prepared rat and human albumins were reacted 

with 90 μg/mL DACT for 5 days. Loaded onto polyacryamide gel and electrophoreses 

for 1 hour. Purified albumin was transferred to a polyvinylidene fluride (PVDF) Western 

blotting membrane, rinsed, and probed with commercially prepared anti-DACT adduct 

antibody. The DACT adduct antibody complex was examined by chemiluminescence 

using Western Blot analysis. DACT adducts were confirmed if a band was detected by 

chemiluminescence. 

The investigators indicated that using mass spectrometry, a covalent bond with a mass 

of 110 DA was located on Cys-34 of the albumin from rats dosed with 20- 200 mg/kg 

atrazine. This same adduct was also detected in rat and human albumin exposed to 90 

μg/mL DACT. Using immunochemical analysis, a dose-related increase in adduct 

formation was detected in the purified albumin samples collected from rats treated with 

a wide range of atrazine doses (5-200 mg/kg). DACT adducts were also detected in rat 

and human albumin preparations exposed to 90 μg/mL. 

 

Reviewer’s Comments: The findings of this well-conduced study provide evidence that 

DACT can form protein adducts. Additionally, the investigators proposed this 

methodology as a potential biomarker screen for the detection of atrazine in exposed 

humans. 
Page 211 of 263 

A.9.3 Kim D. and Breckenridge C. (Syngenta). Derivation of the 

short-term inhalation NOAEL using a physiologically based 

pharmacokinetic model. January 29, 2010. 

Physiologically based pharmacokinetic (PBPK) models can be used for extrapolation of 

internal dose across different species and routes of exposure. In this study, a previously 

published PBPK model (McMullin 2007) for orally-administered atrazine (ATRA) was 

modified to include inhalation exposure for the extrapolation of a rat oral NOAEL to the 

equivalent rat and human inhalation NOAELs. The rationale for using a PBPK model is 

based on a request by US EPA for a 28-day inhalation study aimed at examining the 

effects of ATRA on the estrous cycle and luteinizing hormone (LH) surge. Such 

inhalation studies can be reportedly difficult to carry out experimentally since inhalation 

confinements by themselves without food and water would likely alter the estrous cycle. 

Therefore, a well-parameterized PBPK model offers an alternative approach for 

estimating inhalation exposures of ATRA associated with a given internal dose metric. 

The rat oral NOAEL of 6.25 mg/kg/day used in this study was based on a delay in 

preputial separation from a study aimed at examining the effects of ATRA on puberty in 

male rats. 

The PBPK model for orally-administered ATRA consisting of gut, liver, and body/plasma 

(McMullin 2007) was modified to allow inhalation uptake based on species-specific 

pulmonary ventilation rates and amount of ATRA in air, and assuming that ATRA is not 

absorbed in the respiratory tract nor eliminated by exhalation. The internal dose metric 

selected for predicting the equivalent rat and human inhalation NOAELs was the area 

under the 24-hr plasma concentration-time curve (AUC). Thus, the model was first used 

to estimate the AUC resulting from the orally-administered ATRA at the NOAEL of 6.25 

mg/kg/day. Inhalation pharmacokinetics (6-h exposures, while setting oral dose to zero) 

were then simulated to result in the equivalent AUC for rats and humans (using a body 

weight of 0.3 and 70 kg for rats and humans, respectively). The inhalation exposures 

that resulted in the same AUC (reported as 0.58 mmol/L/day) as the rat oral NOAEL of 

6.25 mg/kg were 4.5 and 5.1 mg/m3 for rats and humans, respectively. 

Since a PBPK model accounts of interspecies differences in pharmacokinetics, the 

uncertainty factor of 10 (i.e., 101⁄2 for pharmacokinetics and 101⁄2 for pharmacodynamics) 

used for interspecies extrapolation can be reduced to 101⁄2 (i.e., 3.2) to account only for 

pharmacodynamic differences. Thus, the composite UF of 100 (i.e., including UF of 10 

for intraspecies extrapolation) can be reduced to 32 with the use of a PBPK model. 

Margin of exposure (MOE) estimates were derived based on the PBPK model-derived 

inhalation NOAELs and reported measurements of ATRA inhalation exposures. The 

reported MOE estimates are greater than the PBPK model-refined level of 32 as well as 

the default benchmark level of 100. 

Reviewer’s Comments: There are two main deficiencies associated with this study. 

First, the PBPK model for orally-administered ATRA (McMullin 2007) does a relatively 
Page 212 of 263 

poor job of simulating ATRA plasma levels following oral dosing (See Figure 7A of 

McMullin 2007). Second, ATRA dealkylated chlorinated metabolites were not included 

in the estimation of AUC following oral dosing at the rat NOAEL of 6.25 mg/kg. This is 

particularly important since chlorinated ATRA metabolites are known to be 

toxicologically-active with respect to the estrous cycle and LH surge, and ATRA is 

rapidly metabolized (particularly following oral administration). Inclusion of chlorinated 

ATRA metabolites would result in a greater AUC for a given oral ATRA dose and 

correspondingly lower estimates for inhalation NOAELs. 

A.9.4 McMullin T.S. (2003) Pharmacokinetic modeling of disposition 

and time-course studies with [14C]-atrazine. J. Toxicol. Environ. 

Health, 66(A):941-964. 

This manuscript describes the development of a physiologically based pharmacokinetic 

model in an attempt to estimate total plasma chlorotriazines (atrazine and its chlorinated 

metabolites: deisopropylatrazine, deethylatrazine, and diaminochlorotriazine) time 

courses. The development of the model is based on two previous studies: a single dose 

(30 mg/kg bw) study whereby individual metabolites (chlorinated and non-chlorinated) 

were identified and quantified; and a repeated dose (1, 3, 7, 10, 50, and 100 mg/kg 

bw/day) study where, in addition to plasma, urine, and feces, reactivity of ATRA with red 

blood cells (RBCs) was examined. The compartments in the model are as follows: liver 

(the primary site of metabolism, brain (postulated site of action), a plasma compartment 

(containing RBCs), and a rest of body compartment. Individual metabolites are not 

tracked in the model. Instead, two pools of compounds are described: chlorinated 

triazines and metabolites derived from glutathione conjugation. In the model, 

chlorotriazines can bind plasma proteins, react with RBCs, conjugate with glutathione, 

or be eliminated in urine. In contrast, glutathione conjugates are considered 

toxicologically-inactive and can be eliminated in the model through feces and urine. 

Parameterization of the model was carried out as follows: (1) since the single oral dose 

study quantified individual metabolites, the rates of glutathione conjugation, chlorinated 

triazine elimination, and glutathione conjugate elimination were fitted to the reported 

urinary percentages of 73% chlorinated triazines and 27% glutathione conjugates. This 

parameterization reasonably described the cumulative urinary elimination of presumed 

radiolabeled equivalents (chlorinated triazine and glutathione conjugates) reported in 

the single dose study as well as at all doses in the repeated dose study. The 

accumulation of ATRA-derived reactivity in RBCs was described in the model by 

assuming a reaction with hemoglobin. A second order rate constant was estimated by 

fitting the radioactivity in RBCs reported at the different administered doses in the 

repeated dosing study. After incorporating RBC reactivity, it was noticed that the model 

consistently underestimated the single dose plasma data at the longer time points. In an 

effort to better describe this dataset, plasma protein binding/reactivity was also included. 

A binding rate constant was estimated based on albumin, the major plasma binding 

protein of known concentration and turnover, by fitting the plasma data for retention of 

radioactivity in the single dose study and then evaluating the ability of the model to 
Page 213 of 263 

describe the repeated-dosing study plasma data. Overall the model reasonably 

predicted plasma levels from the repeated-dosing study at the early (first 50 hours postdose) and late time points (>200 hours), while systematically underpredicting levels at 

the mid-time points. 

The study authors also reported on a time-course study whereby a single dose of 90 mg 

ATRA/kg BW was administered by oral gavage to rats and individual chlorinated 

triazines were monitored in plasma. It is unclear to this reviewer why this new dataset 

was not used to evaluate the performance of the model. Instead, a log-likelihood best fit 

to a one-compartment model is described to presumably show that a slower absorption 

rate constant describes the higher dose plasma data, and that a similar terminal 

elimination phase exist across studies (i.e., consistent with slow absorption of ATRA 

and the rapid metabolism of ATRA to DACT). 

Reviewer’s Comments: The major deficiency of this study is that the model developed 

was not reported as having been evaluated using an independent dataset. 

A.9.5 McMullin, T.S., Hanneman, W.H., Cranmer, B.K., Tessari, J.D., 

and Andersen, M.E. (2007). Oral absorption and oxidative metabolism 

of atrazine in rats evaluated by physiologically modeling 

approaches. Toxicology 240:1-14. 

This study reports on physiologically-based modeling approaches to evaluate the role of 

absorption and oxidative metabolism on the pharmacokinetics of atrazine and its 

chlorinated metabolites. High oral doses of atrazine and its di-dealkylated metabolite 

diaminochlorotriazine (DACT), but not its non-chlorinated metabolites, have been 

associated with alterations in the hypothalamic pituitary axis, leading to neuroendocrine 

responses such as suppression of the steroid-induced luteinizing hormone surge in 

adult ovariectomized female rats. Based on these findings, a net tissue exposure to 

chlorinated triazines may be necessary to conduct human health risk assessment for 

atrazine. 

Atrazine undergoes metabolism by P450 enzymes to the mono-dealkylated chlorinated 

species deisopropylatrazine (ETHYL) and deethylatrazine (ISO). Further P450-

mediated dealkylation yields DACT. Atrazine and all three of its chlorinated metabolites 

can undergo glutathione-S-transferase-mediated dechlorination to yield the respective 

non-chlorinated species. 

A physiologically-based pharmacokinetic (PBPK) model based on in vivo

pharmacokinetic studies with 14C-atrazine was previously developed to estimate total 

chlorinated triazines in plasma after single and multiple oral gavage exposures. 

However, the predictive capability of the model was limited by the lack of specific 

information on the rates of saturable, oxidative metabolic clearance of individual 

chlorinated species. This study addresses this deficiency by developing a set of PBPK 

models based on in vitro-derived metabolic parameters and in vivo pharmacokinetic 
Page 214 of 263 

data of individual chlorinated triazines. The resulting individual model parameters were 

integrated into a final composite model in an attempt to describe the kinetics of all four 

chlorinated triazine species after high dose oral administration of atrazine. 

Individual chlorinated triazine model structures 

The model structures for all chlorinated triazines consisted of a GI 

subcompartment to evaluate the potential for pre-systemic metabolism and 

absorption processes producing multiple peaks in plasma profiles; a liver as the 

primary site of metabolism; and a lumped rest of body compartment to account 

for the remaining tissues. 

In vivo time-course pharmacokinetic data for individual chlorinated 

triazines 

Female Sprague Dawley rats were dosed by oral gavage with 150 mg/kg bw 

atrazine or an equimolar amount of one of its chlorinated metabolites: ETHYL, 

ISO, or DACT. Plasma samples were analyzed for all four chlorinated species. 

Sequential Parameter estimation for individual model structures 

The following model parameters were estimated sequentially by fitting the model 

to the respective time-course pharmacokinetic data: 

(1). DACT: volume of distribution and DACT elimination rate constant 

(2). ETHYL: Vmax for metabolism of ETHYL to DACT and ETHYL elimination 

rate constant 

(3). ISO: Vmax for metabolism of ISO to DACT and ISO elimination rate constant 

Model evaluation for individual chlorinated triazines 

DACT: plasma time-course data was simulated using first order absorption and 

elimination. 

ETHYL and ISO: First order absorption could not describe a double peak 

phenomenon; peak plasma concentrations occurred at 0.5 h, followed by a rapid 

decline over 2 h. A second, smaller peak occurred at 2 h and extended over 24 

h. The model was adjusted so that the multipeak behavior was simulated by 

describing different rates of uptake from the gut; a rapid first order uptake and a 

slower zero order uptake of the remaining dose. Absorption rate constants for the 

different uptake processes were estimated by fitting to the time-course data. 

Composite model evaluation for atrazine 

The uptake of atrazine could not be simulated as a single first order absorption 

process due to a double peak phenomenon. As with ETHYL and ISO, this 

phenomenon was described by a combination of first order and zero order 

descriptions. The authors hypothesized that the double-peak phenomenon 

observed for ETHYL, ISO, and atrazine is reflective of limited compound 

solubility in the gut at the high doses used in the study. The continuing 

absorption of more slowly dissolving compound along the GI tract contributes to 

the complex time-course behavior. Addition of pre-systemic intestinal 
Page 215 of 263 

metabolism of atrazine to mono-alkylated metabolites was also necessary to 

adequately describe the bioavailability of atrazine without adjusting the in vitroderived metabolic parameters. 

Reviewer’s Comments: The current study underscores some of the parameters that 

may contribute to the complex pharmacokinetics of atrazine observed following high 

dose oral administration. The utility of the composite model for atrazine is questionable. 

First, there is no direct evidence cited in support of multiple absorption processes and 

GI intestinal metabolism used to fit the model prediction to the plasma concentrationtime profiles. Second, the final composite model significantly underpredicts plasma 

levels of chlorinated metabolites after 8 hours while underpredicting atrazine levels at all 

time points. 

A.9.6 Ross, M.K., Jones, T.L., and Filipov, M.N. (2009). Disposition of 

the herbicide 2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine 

(atrazine) and its major metabolites in mice: a liquid 

chromatography/mass spectrometry analysis of urine, plasma, and 

tissue levels. Drug Metab. Dispos. 37(4): 776-786. 

Mice are increasing being used to assess the potential adverse effects following 

atrazine (ATRA) exposure. However, disposition studies of ATRA in this particular 

species are lacking. This study was aimed at examining the metabolism and disposition 

of ATRA in mice and assessing how tissue levels may correlate with levels of ATRA and 

its metabolites found in plasma and urine, the most accessible biological fluids. Thus, 

following an overnight fast, mice (5-8/dose/time) were administered a single dose of 0, 

5, 25, 125, and 250 mg/kg bw ATRA in corn oil by oral gavage. Plasma and tissue 

levels were measured as soon as 0.5 hours following dosing while urine and feces were 

collected at 24-h intervals. 

Plasma: Levels of ATRA exhibited a biphasic behavior; maximum levels were seen at 

0.5 hours post dose, followed by a rapid decline before a second peak occurred at 12 h. 

The biphasic phenomenon was attributed to discontinuous absorption from the GI tract. 

ATRA levels were below the limit of detection by 24 hrs. In contrast, levels of the didealkylated metabolite diaminochlorotriazine (DACT), the major metabolite identified (~ 

10-fold higher levels than mono-dealkylated metabolites), concomitantly increased and 

peaked at 2 hrs at all dose levels. The clearance of DACT was dose-dependent and 

relatively slow during the first 24 hours (halflives of 7.5 and 42 hrs for 5 and 250 mg/kg 

bw ATRA, respectively). When plasma area under the curves (AUCs) for DACT were 

plotted versus ATRA dose, a significant linear correlation was observed (r2

 = 0.987). 

Urine: DACT levels were 2 orders of magnitude higher (as high as 5400 μM) than 

ATRA or its mono-dealkylated metabolites in the 0-24 hr time period. 

 

Feces: Analysis of fecal extracts did not reveal significant amounts of metabolites. 

Detected amounts of ATRA most likely reflected unabsorbed compound. 
Page 216 of 263 

Liver and kidney: ATRA and all of its metabolites including glutathione conjugates 

were detectable at 4 hrs. DACT was the most abundant species followed by ATRA. 

Lower levels of each compound were found in the kidneys as compared to the liver. 

Brain: Significant levels of DACT (as much as 50 μM at the highest dose) along with 

low levels of ATRA ( ~1 μM at the highest dose) were found at 4 hrs. ATRA was still 

detectable in the brain at all dose levels at 24 hrs, while DACT levels remained high at 

24 hrs. 

Spleen and thymus: At the low doses of 5 and 25 mg/kg bw, maximum levels of ATRA 

(~2-3 μM) were detected at 1 hr, whereas at the two highest doses (125 and 250 mg/kg 

bw ATRA), maximum ATRA levels were seen at 4 hrs. Peak levels of DACT, the major 

species detected, were seen at 4 hrs at the two highest doses of ATRA. 

Reviewer’s Comments: Much of the information reported in this study for mice seems to 

be strikingly similar to that reported in rats (see McMullin reviews). In particular, the 

biphasic absorption phenomenon of ATRA is consistent across these two rodent 

species. Plasma kinetics (maximum levels, time to reach maximum levels, and 

clearance) of ATRA and DACT are also very similar for a given administered ATRA 

dose. This disposition information reported in this study may be important in the use of 

pharmacokinetic models that can link target tissue dose to toxicological effects of ATRA 

and in vivo metabolites. 
Page 217 of 263 

Appendix B 

Atrazine immunotoxicity data 
Page 218 of 263 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

National Health and Environmental Effects Research Laboratory 

Cardiopulmonary and Immunotoxicology Branch 

Environmental Public Health Division, Research Triangle Park, NC 27711 

OFFICE OF 

 RESEARCH AND DEVELOPMENT

DATE: January 28, 2010 

SUBJECT: Atrazine immunotoxicity data 

 

TO: Tina Levine, Ph.D. 

 Director, Health Effects Division 

 Office of Office of Pesticide Programs 

 US EPA 

THROUGH: MaryJane Selgrade, Ph.D. /s/ 

 Chief, Cardiopulmonary and Immunotoxicology Branch 

 Environmental Public Health Division 

 US EPA 

 

FROM: Robert Luebke, Ph.D. /s/ 

 Cardiopulmonary and Immunotoxicology Branch 

 Environmental Public Health Division 

 US EPA 

Dear Dr. Levine, 

In 2003, my laboratory published a paper reporting the effects of maternal atrazine exposure on 

immune function in male and female offspring (attached). Timed-pregnant Sprague Dawley rats 

were exposed to 35 mg atrazine/kg body weight/d from gestational day (GD)10 through 

postnatal day (PND) 23. The dose of atrazine was chosen to be just above the NOAEL for 

delayed onset of puberty in female offspring (25 mg/kg/d), as reported by (Laws et al., Toxicol. 

Sci. 58, 366–376, 2000). Maternal atrazine exposure has also been reported to disrupt prolactin 

production ( Stoker et al., Reprod. Toxicol. 13, 463–472, 1999) and thyroid hormones 

(Kornilovskaya et al., Biomed. Environ. Sci. 9, 60–66,1996). Alterations in either of these 

hormones has been reported to affect immune function. To test our hypothesis that disruption 

of prolactin or thyroid hormone homeostasis was causally related to defects in immune function, 

separate groups of rats were exposed to bromocryptine (0.2 mg/kg, given twice/d LOAEL for 

prostatitis development; Stoker et al., 1999) or propylthiouracil (2 mg/kg/d, a dose that would 

have minimal overtly toxic effects on the dam or offspring; Kevin Crofton, US EPA, personal 

communication). Only one dose level of atrazine was included in the study so that all members 

of exposure cohorts could be examined on a single day. Both the antibody response to 

immunization and the cell mediated response to a foreign protein were suppressed in male, but 

not in female, offspring of dams exposed to atrazine. Bromocryptine and propylthiouracil 
Page 219 of 263 

exposure did not affect immune function. Pup mortality was greater in the atrazine offspring on 

postnatal day 7 (13% vs. 2% in controls) as was the number of litters in which at least one pup 

died (19 vs 4 in controls). Each experiment was done twice, over approximately 18-24 months. 

Similar results were obtained in both replicates. These studies were completed prior to our 

move to the new EPA facility in RTP. 

 

After moving to a new laboratory facility, additional studies were done to derive a dose 

response for atrazine developmental immunotoxicity. Two replicate studies were conducted in 

timed-pregnant Sprague Dawley rats from the same supplier at doses of 0, 3.5, 17.5 and 35 mg 

atrazine/kg/day, from GD10 through PND 23, as in the original studies. Litters were 

standardized for number and gender of pups, following the same procedures described in the 

published studies. Antibody and delayed hypersensitivity responses were evaluated, following 

the same operating procedures as before. However, only male pups were evaluated 

immunologically, based on our previous results and the need to reduce the experiment size to 

accommodate the workload in my lab. The second study also included a group of adult rats that 

were injected as adults with the known immunotoxicant, cyclophosphamide, as a positive 

control for suppression of the antibody assay. Maternal atrazine exposure did not affect 

immune function in the offspring. Cyclophosphamide significantly (p<0.001) suppressed 

antibody production, indicating that the assay was able to detect immunosuppression. To 

assess possible strain effects, a third study was done in which timed pregnant Sprague Dawley, 

Long Evans and Wistar rats, all from the same supplier, were exposed to 35 mg atrazine/kg/d, 

following the same exposure and evaluation protocols used in previous studies; only male 

offspring were evaluated. As in the first two studies, immune function was not affected in the 

offspring. 

I have complete confidence in the technical soundness and results of our published studies and 

in our attempts to generate a dose response. The same personnel were involved in both sets of 

studies, the same operating procedures were followed for exposure and assessment of immune 

function and reagents and supplies were all obtained from the same vendors as before. Three 

different lots of atrazine were used in these studies, all from the same vendor. Two different lots 

of atrazine were used in the initial and replicate studies reported by Rooney et al. and the 

outcome of both studies was the same. It is possible that the lot used for the dose response 

series was compromised in some way, but that seems unlikely. Animal dosing was completed 

between 7 and 10 AM for all studies. Animal health was monitored in both the old and new 

facility; sentinel animals were housed in the same rooms as experimental animals and routinely 

evaluated for selected pathogenic viral, bacterial and parasitic infections and the results were 

consistently negative. 

Based on these facts, I believe that both sets of studies are “correct” and reflect all conditions 

under which the experiments were done. I believe that the disparate outcomes are the result of 

unknown environmental factors, which are unlikely to be identified, and that the lack of effects in 

the second set of studies do not negate our published conclusions that exposure to ATR during 

immune system development and maturation may modulate immune function. I will be happy to 

discuss our data with you and with members of the SAP.
Page 220 of 263 

Appendix C 

Artificial Neural Network Modeling of Atrazine 

Occurrence Patterns 
Page 221 of 263 

Artificial Neural Network Modeling of Atrazine Occurrence Patterns22

by Michael J. Messner, Ph.D. 

USEPA Office of Ground Water and Drinking Water 

March 3, 2010 

Contents 

ABSTRACT........................................................................................... 222 

BACKGROUND .................................................................................... 223 

MONITORING STRATEGIES .......................................................................................................................223 

DATA QUALITY OBJECTIVES.....................................................................................................................223 

ATRAZINE OCCURRENCE PATTERNS ........................................................................................................224 

OCCURRENCE DATA.......................................................................... 226 

FREQUENT MONITORING DATA. .................................................................................................................95 

TIME SERIES PLOTS..................................................................................................................................95 

DATASETS SUITABLE FOR MODELING .......................................................................................................231 

ARTIFICIAL NEURAL NETWORK MODELING..................................... 98 

ANN MODELS. ..........................................................................................................................................98 

ANN MODELING FOR THE MAUMEE RIVER, 1998. .....................................................................................235 

ANN MODELING FOR THE SANDUSKY RIVER, 1995. ..................................................................................239 

PREDICTIVE ANALYTICS ................................................................... 100 

DIRECT DERIVATION OF THE EXPOSURE...................................................................................................242 

SCALING THE OCCURRENCE PATTERNS ...................................................................................................243 

SIMULATING DAILY LEVELS ......................................................................................................................243 

EVALUATING A MONITORING STRATEGY ...................................................................................................103 

SUMMARY – ADVANTAGES AND DISADVANTAGES OF USING THE ANN 

MODELS ............................................................................................... 105 

Disclaimer: Views and opinions expressed in this paper are those of the author and do 

not necessarily state or reflect those of the Office of Ground Water and Drinking Water, 

the Environmental Protection Agency of the US Government. 

 22 File is ANN_Occurrence 3_3_2010.docx 
Page 222 of 263 

C.1 Abstract 

This paper assumes that EPA/OPP has developed or will develop some quantitative 

performance criteria for their Atrazine Monitoring Program (AMP) and that these criteria will 

include some that relate to the detection of short-lived, high-concentration periods, called 

“spikes” or “peaks.” This paper describes one form of model (Artificial Neural Network) that can 

be used to simulate this kind of occurrence pattern and shows how these models can be used 

to assess how well candidate monitoring strategies satisfy quantitative performance criteria. 
Page 223 of 263 

C.2 Background 

C.2.1 Monitoring Strategies 

A “monitoring strategy” is a combination of (a) a plan for obtaining new contaminant 

occurrence data and (b) a decision rule, in which the occurrence data are used to make 

a binary decision, such as to decide whether exposure levels are above or below some 

health-based level of concern. 

Crafting a suitable water monitoring strategy involves many considerations. These 

include the following: 

• The cost of obtaining and testing samples of drinking water (or source water) 

• The spatial and temporal variability of the contaminant, particularly when occurring at 

levels of concern. 

• The occurrence levels and durations that are associated with different health endpoints 

• The severity of the adverse health outcomes 

• The utility of monitoring data for informing treatment decisions 

• Consequences of failing to detect and address high occurrence (false negative) 

• Consequences of false alarm (false positive) 

When the above considerations lead to quantitative performance criteria, those criteria become 

the benchmarks for evaluating different monitoring strategies. When available strategies fail to 

satisfy the criteria, for example, because they too often raise false alarm or too often fail to 

detect high occurrence, planners may need to reconsider the performance criteria. 

This paper assumes that EPA/OPP has developed or will develop some quantitative 

performance criteria for their Atrazine Monitoring Program (AMP) and that these criteria will 

include some that relate to the detection of short-lived, high-concentration periods, called 

“spikes” or “peaks.” This paper describes a form of occurrence modeling that can be used to 

simulate this kind of occurrence pattern and shows how these models can be used to assess 

how well candidate monitoring strategies satisfy quantitative performance criteria. 

C.2.2 Data Quality Objectives 

Executive order 5360.1 requires the use of “a systematic planning process to develop 

acceptance or performance criteria” for environmental monitoring projects.23 Over the 

past 25 years, EPA’s QA Staff has developed and promoted a systematic planning 

process for just this purpose, called “Data Quality Objectives” or DQOs.24 

 

23 USEPA Executive Order 5360.1, Policy and Program Requirements for the Mandatory Agency-Wide 

Quality System, Chg 1, 7/16/1998. http://www.dpnr.gov.vi/dep/5360-1c1.pdf 24 USEPA, 2006, Guidance on Systematic Planning Using the Data Quality Objectives Process (EPA 

QA/G4). EPA/240/B-06/001. http://www.epa.gov/quality/qs-docs/g4-final.pdf
Page 224 of 263 

The DQO process applies systematic planning and statistical hypothesis testing 

methodology to facilitate the design and selection of environmental monitoring 

strategies. The seven steps of the process are: 

1. State the Problem 

2. Identify the goal of the study 

3. Identify information inputs 

4. Define the boundaries of the study 

5. Develop the analytic approach 

6. Specify performance or acceptance criteria 

7. Develop the plan for obtaining data 

The process really gets quantitative in Step 6, where two kinds of errors and their 

consequences are expressed and considered. The outputs of Step 6 are quantitative 

limits for the probabilities of false positives and false negatives. A statistician can then 

evaluate how well selected monitoring strategies satisfy these criteria, given different 

occurrence scenarios or patterns. In general, waters with high variability are the most 

challenging. Water having a low occurrence level, but high variability, can experience a 

false positive whenever a sample is taken during a short-lived occurrence spike. 

Similarly, water with a high occurrence level with high variability can “get lucky,” and 

experience a false negative because infrequent monitoring failed to catch a large 

occurrence spike. 

C.2.3 Atrazine Occurrence Patterns 

Atrazine occurrence is known to be greatest following rainfall events in the spring and 

summer and lowest prior to the pesticide’s first use in the spring.25 Occurrence is more 

variable in flowing streams than in reservoirs and lakes, and variability tends to be 

inversely related to flowing stream size, with greatest variability in headwater streams in 

regions where the pesticide is used.26

Monitoring data provided by Missouri American Water Company and displayed in Figure 

18 reveals a strong seasonal occurrence pattern with high variability.27

 

25 USGS. Herbicides in Rainfall Across the Midwestern and Northeastern United States, USGS Fact 

Sheet 181-97, June 1998, http://ks.water.usgs.gov/pubs/fact-sheets/fs.181-97.html 

26 Graziano, N., et.al, 2004 National Atrazine Occurrence Monitoring Program Using Abraxis ELISA 

Method, ES&T, 40, 1163-1171, 2006. 

27 Data provided by Dr. Mark LeChevallier, American Water Works Service Company. 
Page 225 of 263 

Figure 18 Atrazine Occurrence at Missouri-American Water Intake 

Drinking water sources monitored under the Atrazine Monitoring Program (AMP) include 

some with variability like that shown above, but also include many waters with less 

variability like those shown in Figures 19 and 20. 
Page 226 of 263 

Figure 19: Source Water with Low Variability 

Figure 20: Source Water with Moderate Variability 

In the Figures above, the actual monitoring data are displayed as black dots. The red 

lines are Artificial Neural Network curves that have been fit to the data. 

C.3 Occurrence Data 

C.3.1 Frequent Monitoring Data. 

The data used for the modeling described below was collected by the Heidelberg 

University’s National Center for Water Quality Research (NCWQR) file for large rivers. 

Other data from Headwater Streams and CWS were plotted and evaluated, but were 

not used in the modeling exercise. 
Page 227 of 263 

C.3.2 Time Series Plots. 

Figure 21 displays 2001 data from the Maumee River, one of the Large Rivers. The 

Figure has been marked to highlight some features of the data, including: 

• Data that are not consistent with their near-time neighbors due to rapid changes in the 

occurrence level or measurement error. 

• Single measurements that appear to be repeated on following days. It turns out that 

days without data were filled in with the most recent previous measurement result. 

• A short-lived occurrence peak appears near day 200, but another, smaller peak may 

have occurred around day 120. With a single measurement, it is difficult to say whether 

that point is an actual occurrence spike or a measurement error. 
Page 228 of 263 

Figure 21: Data for Maumee River 2001 
Page 229 of 263 

Figure 22 is a plot of Maumee 1998 (one of the data sets used for ANN modeling) data, 

showing larger short-term day-to-day variability or “noise” (in log units) when 

concentrations are below e-1.5 than when above e-1.5. Based on this and other plots, it 

appears reasonable to treat 0.25 g/L as a censoring limit. The natural log of 0.25 is 

about -1.4. This figure clearly shows two occurrence peaks. 

Figure 22: Data for Maumee River 1998 
Page 230 of 263 

Figure 23 displays data from headwater stream NE 07 2005 revealing several sharp 

occurrence peaks (marked by red arrows in the plot below). This number of peaks 

would be very difficult to model with such a small amount of data. 

Figure 23: Data for a Headwater Stream 
Page 231 of 263 

C.3.3 Datasets Suitable for Modeling 

Two datasets are used to illustrate Artificial Neural Network modeling. Both Maumee 

1998 and Sandusky 1995 exhibit high variability, with at most two occurrence peaks. 

The data seem to be randomly dispersed, with no obvious outliers – at least, at first 

glance. Both sets have mostly-daily monitoring in high-occurrence periods. 

Original data were processed in R to (a) replace the repeated values with “NA” and (b) 

replace concentrations below 0.25 with 0. 

Figure 24 is a plot of Sandusky 1995 original data (black) overlaid with data that were 

retained as measured values (red). Red points that are followed by horizontal strings of 

black dots represent single measured values followed by days without measurements. 

The horizontal red line represents our censoring limit (log(0.25) = -1.4). Below that line, 

horizontal strings of black dots are days that followed measured values less than our 

censoring limit. Red points for those measurements don’t show on the plot because 

they were replaced by zeros before log transformation, but they do appear in the “rug,” 

where a fiber is shown for each day having a measured value, whether above or below 

our censoring limit. 
Page 232 of 263 

Figure 24: Data for Sandusky River 1995 
Page 233 of 263 

C.4 Artificial Neural Network Modeling 

C.4.1 ANN models. 

Artificial Neural Networks (ANNs) are often seen as magical “black boxes” that 

magically learn from data, and end up predicting how one or more “dependent 

variables” change in response to “independent variables.” A recent book by Herbert K. 

H. Lee opens up the ANN black box, providing mathematical forms of ANN models and 

some real-world interpretations of the model parameters.28 The book goes on to 

describe parameter estimation in a Bayesian framework for multivariate regression, 

classification, and other applications. 

The equation below describes one form of ANN used to model Atrazine occurrence. 

Subscript day is the day of a calendar year (0:364) and lnC is the natural logarithm of 

the concentration, g/L. 

lnCday b0

b1

1 e− b5 b6 day ⋅− +

+

b2

1 e− b7 b8 day ⋅− +

+

b3

1 e− b9 b10 day ⋅− +

+

b4

1 e− b11 b12 day ⋅− +

:= +

The first parameter (b0) is an intercept term in the sense that, as the denominators of 

the other terms get large, the contributions of the other terms become negligible. 

Parameters b1 through b4 determine the potential magnitudes of the increases and 

decreases of concentration due to those four terms, called “hidden nodes.” Parameters 

in the denominators determine how quickly the nodes’ contributions increase or 

decrease with time and the location or day on which the incremental increase or 

decrease is greatest. The first fraction’s contribution per unit time is greatest around 

day –b5/b6 and parameter b6 determines the magnitude of the increase on neighboring 

days. On days far removed from day = -b5/b6, the first node’s contribution approaches 

either zero (when the denominator is huge) or b1 (when the denominator is nearly 1). 

Figure 25 shows the sum of b0 and a single hidden node together with the observed log 

concentrations for the Maumee River in 1998. A second node with a decreasing effect 

will be needed to pull the ANN curve down after day 130 and a third node will be 

needed to explain the occurrence peak around day 166. 

 

28 Lee, Herbert H.K., Bayesian Nonparametrics via Neural Networks, ASA-SIAM, 2004. 
Page 234 of 263 

Figure 25: Maumee 1998 and ANN Model with One Node 

0 100 200 300 400 − 5

0

5

10

The “best” ANN model for any one-year data set will be the model with fewest hidden 

nodes that does an adequate job of explaining the occurrence data. “Adequate” will be 

expressed in terms of log-likelihood. 

The ANN model describes the expected log-concentration, but clearly, the concentration 

on any given day will not be exactly that predicted by the model. Some amount of noise 

can be seen in all plots of occurrence data. We assume the difference between a day’s 

measured log-concentration and that given by the underlying model will be normal with 

mean zero and some variance that we can estimate using the model and the data. We 

assume the variance is constant. A day’s log-concentration is regarded as a normal 

random variable with mean equal to the model prediction and, for measured values 

above a censoring limit, the likelihood is the normal probability density. For nondetects 

and measured values below a censoring limit, the likelihood is the value of the 

cumulative normal distribution function (the probability of a log concentration below the 

censoring limit). 

Rather than a full Bayesian treatment, where prior probabilities and data combine to 

reduce uncertainty about the model parameters, we seek maximum likelihood models. 

This simplifies the evaluation of monitoring strategies, where the true model and its 

parameters are fixed and data are random (simulated) based on the fixed occurrence 

model. 

Once a best-fitting ANN model is identified, the autoregressive (AR) structure can be 

explored and modeled. AR structure explains how the deviation of one day’s logconcentration from the model is related to the deviation of previous days. It turns out 

that days with log-concentration greater (or less) than expected tend to also be followed 
Page 235 of 263 

by days with log-concentration greater (or less) than expected. This is explained by 

positive coefficients in the AR model. 

The following sections describe ANN model development for two river-years of data; 

Maumee 1998 and Sandusky 1995. The preferred model for Maumee 1998 has three 

hidden nodes and AR(2) behavior, while the preferred model for Sandusky 1995 has 

two hidden nodes and AR(1) behavior. 

C.4.2 ANN modeling for the Maumee River, 1998. 

Modeling begins with simple plots of log-concentration vs. time. All plotting and 

analyses are done using R version 2.10.0.29 R-code for this can be found at 

https://kestrel.rtpnc.epa.gov/OGWDW_Strategies/index.php/ModelingMaumee1998

The time-series plot reveals two occurrence peaks. ANN modeling begins with a node 

to generate the increase of concentration to the first peak and a node to begin reducing 

log-concentration to where the second spike begins. A third node is added to generate 

the increase to the second peak and a fourth node is added to bring the level back 

down following the second peak. 

lnCday b0

b1

1 e− b5 b6 day ⋅− +

+

b2

1 e− b7 b8 day ⋅− +

+

b3

1 e− b9 b10 day ⋅− +

+

b4

1 e− b11 b12 day ⋅− +

:= +

Initial values for the model parameters were selected using professional judgment. The 

process for the first node went something like this: 

• b0 was set to ln(0.1) to establish an “intercept” of ln(0.1 g/L), as that appeared to be a 

reasonable “floor” for Atrazine occurrence 

• b1 was set to ln(8/0.1) = 4.382 so that this second fraction could max out at ln(8 g/L), 

which is a bit greater than the highest value of the first occurrence peak. This allows the 

second fraction to begin having an effect some time before the peak. 

• The day of steepest ascent was set at 120 and this was set equal to the ratio of –b5/b6, 

where b5 and b6 are in the node’s denominator (exp(-b5-b6*day)). 

• Various levels of b6 were selected, and b5 found to fit the day of steepest ascent, and 

the resulting model was plotted against the data. Parameter b6 was then adjusted up or 

down to better fit the rate of increase seen in the data. 

Once good initial values were found for all four nodes, a mean deviance was calculated 

and a log likelihood function was constructed. Given fixed data, this is a function of the 

parameters (the 13 model coefficients and the precision, 1/variance). Log likelihood is a 

sum of the log likelihood contribution of each observation. For observations that fall 

above ln(0.25), a censoring limit, the contribution is natural log of the following 

probability density (dnorm): 

 

29 The R Foundation for Statistical Computing, http://www.r-project.org/
Page 236 of 263 

dnorm Zj 2, b0

b1

1 e− b5 b6 Zj 0, ⋅− +

+

b2

1 e− b7 b8 Zj 0, ⋅− ( ) +

+

b3

1 e− b9 b10 Zj 0, ⋅− ( ) +

+

b4

1 e− b11 b12 Zj 0, ⋅− ( ) +

, + b13− 0.5 , ⎡

⎢

⎣

⎤

⎥

⎦

For observations that fall below the censoring limit, the contribution is the natural log of 

the distribution function (pnorm): 

pnorm DL b0

b1

1 e− b5 b6 Zj 0, ⋅− +

+

b2

1 e− b7 b8 Zj 0, ⋅− +

+

b3

1 e− b9 b10 Zj 0, ⋅− +

+

b4

1 e− b11 b12 Zj 0, ⋅− +

, + b13− 0.5 , ⎛

⎜

⎝

⎞

⎟

⎠

The precision (b13) also contributes a value to the log likelihood, ln(b13), which gently 

penalizes small precisions. In a Bayesian framework, this would be consistent with 

having a vague, flat prior on the precision. 

Maximum likelihood values were identified by repeated application of a maximization 

function. A solution was found at b = c(-3.35, 10.664, -5.008, 3.618, -7.379, -15.524, 

0.125, -36.097, 0.273, -214.029, 1.311, -7.213, 0.04, 29.062). Figure 26 shows that, 

while the model does a nice job of fitting the data, there is an odd-looking bump 

between the two peaks. The fourth node, which was supposed to explain the second 

decline, appears to have an impact mid-way through the first decline. This suggests 

that perhaps only one node is needed to explain both declines in log-concentration. 
Page 237 of 263 

Figure 26: Maumee 1998 and Max Likelihood Four-Node ANN Model 
Page 238 of 263 

The three-node equation looks like the form above, but without the final term. As 

before, initial values were identified using professional judgment. Maximum likelihood 

parameters were found to be c(-1.81,3.68,-7.194,3.844,-50.084,0.423,-7.222,0.04,-

202.475,1.241,24.58). The resulting curve and the data are shown in Figure 27. 

Figure 27: Maumee 1998 and Max Likelihood Three-Node ANN Model 

The maximum log likelihood under the four-node model was 18.109 and the error 

standard deviation (log units) was 0.185. The log likelihood of the three-node model 

shown above was 11.855, with error standard deviation 0.202. Given that the four-node 
Page 239 of 263 

model has three more parameters than the three-node model and that the difference in 

log likelihood is slightly greater than 6, the two models are nearly equal in quality-of-fit. 

The three-node model is selected for its simplicity and better “appearance.” 

Residuals for the three-node model were calculated for each non-censored 

measurement. The resulting autocorrelation function, shown in Figure 28, shows a 

wave pattern that is commonly associated with AR(2) models.30

Figure 28: Residuals for Maumee 1998 Three-Node Model 

R function “resid.ar” confirmed that the best autoregressive model is AR(2) and 

provided maximum likelihood coefficients 0.381 and 0.195. This means that, when 

simulating occurrence under the model, each day’s “error” will have two components, 

one of which is random and independent of other days’ errors, while the other is a 

function of the two previous days’ errors. 

C.4.3 ANN modeling for the Sandusky River, 1995. 

As before, modeling begins with simple time series plots of log-concentration, Figure 7. 

The plot reveals a single occurrence peak, so a two-node ANN model is needed. 

 30 Cowpertwait, Paul S.P. and Metcalfe, Andrew V., Introductory Time Series with R, Springer, 2009. 
Page 240 of 263 

Initial parameter values were set using professional judgment. The process was similar 

to that described above for Maumee 1998. Maximum likelihood estimates were found, 

and the resulting curve looked reasonable, but the log likelihood was very small (-110). 

Log likelihoods for individual observations revealed six that contributed large amounts of 

the negative likelihood. The six observations are marked in Figure 29 and include: 

• two points prior to the peak, at significantly greater concentrations than their neighbors 

(suggesting that these may have actually been two short-lived peaks) 

• one high concentration near the peak that, immediately preceded and followed by 

nondetects (suggesting large measurement error), and 

• one nondetect around day 200 that also appears to be a measurement error. 

When these six spurious observations were removed, the maximum likelihood two-node 

model’s log likelihood improved to -50.75 and the error standard deviation reduced from 

0.516 to 0.331. 
Page 241 of 263 

Figure 29: Data Contributing to Small Likelihood for Two-Node Model 

Maximum likelihood parameters were c(-1.189, 4.197, -4.138, -37.513, 0.286, -6.436, 

0.034, 9.434) and the resulting curve (not shown) was similar to that shown above. 

Residuals were plotted and evaluated using R function “resid.ar.” The best 

autoregressive model was found to be AR(1), with parameter 0.479. 
Page 242 of 263 

C.5 Predictive Analytics 

The two occurrence patterns explored above (Maumee 1998 and Sandusky 1995) are 

among the most variable or “spiky” of all drinking water sources evaluated to date. 

Headwater stream data exhibits even greater variability, with several occurrence spikes 

per year. Modeling headwater stream occurrence may be useful if the monitoring 

objectives concern contamination of headwater streams and the contaminant’s impact 

on stream ecology. 

This discussion describes how the ANN occurrence models can be used to evaluate 

source water monitoring strategies, where the concern is for detecting situations like the 

following: 

a) Distributions of daily concentrations where the 75th percentile exceeds X g/L. (We 

don’t want to have more than about 90 days per year above X g/L and the highoccurrence days do not need to be consecutive to do harm.) 

b) Distributions with mean concentrations greater than Y g/L. (Concern is for long-term 

exposures, such as associated with some cancer risk.) 

c) Distributions with an average of 1 or more times during the year when concentrations 

exceed Z g/L for W or more consecutive days. (Concern is for sustained exposure 

over consecutive days.) 

C.5.1 Direct Derivation of the Exposure 

Under these models, a particular day’s concentration will vary from year-to-year as a 

lognormal random variable, so each day’s distribution function is known. The values 

shown in Tabl3 23 were calculated directly. 

Table 22: 75th Percentiles and Means for Selected Models 

Occurrence Model d) 75th

Percentile 

e) 90th

Percentile 

f) Mean 

Maumee 1998 

Three-Node AR(2) 0.0920 g/L 3.02 g/L 1.428 g/L 

Sandusky 1995 

Two-Node AR(1) 0.0958 g/L 4.50 g/L 1.375 g/L 

Estimating the expected number of episodes per year having at least W consecutive 

days’ concentrations above a level of interest is more involved, as it requires simulating 

many years of occurrence and keeping track of episodes encountered. Simulations of 

this sort have not yet been performed, but are entirely feasible, should concern be 

expressed for these kinds of exposures. 
Page 243 of 263 

C.5.2 Scaling the Occurrence Patterns 

Given maximum likelihood parameter values, the Maumee 1998 and Sandusky 1995 

occurrence levels may be considerably different than situations of interest. For 

example, neither of those occurrence levels is directly relevant if the concern is having a 

90th percentile at or above 10 g/L. 

Fortunately, the two models can be scaled easily by adjusting the intercept term, b0. 

Having homogeneous variance on the log-scale ensures that relative error (ratio of 

day’s standard deviation to the day’s expected concentration) is constant. 

Example 1: Scaling Maumee 1998 so that the resulting occurrence pattern has a 

90th percentile equal to 10 g/L. 

The original model for Maumee 1998 has a 10th percentile of 3.02 g/L, which is 

smaller than 10 by a factor of 3.31. Parameter b0 must increase from -1.81 to -

0.613, which is -1.81+ln(3.31). 

Example 2: Scaling Sandusky 1995 so that the resulting long-term average 

concentration is 10 g/L. 

 The original model for Sandusky 1995 has a long-term average concentration of 

1.375 g/L, which is smaller than 10 by a factor of 7.27. Parameter b0 must be 

increased from -1.189 to 0.795, which is -1.189+ln(7.27). 

C.5.3 Simulating Daily Levels 

Simulation is required to assess the ability of a monitoring strategy to “detect” 

occurrence situations of interest. Simulating a year of daily concentrations requires 

adding some “error” to the ANN-predicted log-concentration for each day of the year. 

These daily “errors” have two components. One component is like “white noise,” in that 

it is independently and identically distributed (i.i.d.) across days. On the log-scale, the 

white noise distributions are normal with standard deviations 0.243 and 0.265 for 

Maumee 1998 and Sandusky 1995, respectively. 

The other component of error is due to the AR behavior. In the case of Maumee 1998, 

the model is AR(2) and the error on day D includes 0.381 times the “white noise error” 

of the previous day (D-1) and 0.195 times the “white noise error” of day D-2. In the 

case of Sandusky 1995, the model is AR(1), and the error on day D includes 0.265 

times the “white noise error” of the previous day. 
Page 244 of 263 

Example 1: Maumee 1998 is scaled so that the resulting occurrence pattern has 

10 g/L as its 90thpercentile. Parameter b0 has been increased to 0.613. One 

year of simulated data is shown in Figure 30. In this particular simulated year, 10 

g/L (shown in the plot as a horizontal red line) is exceeded on 34 days, so 10 

falls just above the 90th percentile. Over many simulated years, the percentile 

associated with 10 g/L will vary. This particular simulated year just happened 

to have 9.3% of the values fall above 10 g/L. 

Figure 30: Simulation Based on the Maumee 1998 Model 
Page 245 of 263 

Example 2: Sandusky 1995 is scaled so that the resulting long-term average 

concentration is 10 g/L. Parameter b0 has been increased to 0.795. One year 

of simulated data is shown in Figure 31. In this particular simulated year, the 

average concentration is 9.68 g/L. There happen to be 79 days on which the 

concentration exceeds 10 g/L. As the number of simulated years increases, 

the average concentration will converge to 10 g/L. 

Figure 31: Simulation Based on the Sandusky 1995 Model 
Page 246 of 263 

C.5.4 Evaluating a Monitoring Strategy 

Having a means of simulating daily occurrence levels for an occurrence level and 

pattern of concern, one can select daily observations in accordance with a monitoring 

strategy and then process the selected observations to make the binary decision; to 

decide whether or not there is a problem. For example, if the strategy is to collect one 

sample per month (one sample every 30 days), and determine whether the maximum 

value exceeds X, one could do the following: 

1. Select an occurrence pattern and level of concern. This is a source water 

occurrence scenario where there is concern about either a false positive or false 

negative determination. The simulation exercise is crafted to determine whether 

a strategy adequately limits decision error for the selected scenario. 

2. Select a random start day in the first month. StartDay <- sample(1:31,1) 

3. Add 30, 60, ... 330 to mark the other sampling days for the year or, for random 

dates, select one day at random from every calendar month. 

4. Observe the concentrations simulated for those days in a one-year simulation 

5. Identify the maximum concentration and compare to X, recording the result 

6. Repeat the steps 2 through 5, above until many years of monitoring have been 

simulated 

7. Across all simulated years, determine the fraction of times that the result was 

positive (because the year’s sample maximum exceeded X) 

Example: Determine the probability that monthly sampling will produce a positive 

result, where a positive is defined as having a maximum greater than 10 g/L when 

the occurrence pattern is Maumee 1998 having a 75th percentile of 10 g/L. For this 

exercise, this level is considered “high” and a positive rate of at least 95% is desired. 

• The occurrence pattern is Maumee 1998 and coefficient b0 is adjusted so the 

long-term 75th percentile is 10 g/L. Figure 14 displays a year of simulated data 

for this pattern and level. 

• Steps 2 through 5 are repeated 10,000 times 

Results 

• Under systematic sampling, a random sampling date is selected for January and 

other sampling dates follow at exactly 30-day intervals. Among the 10,000 

simulated sample maxima, only 180 exceeded 10 g/L. A positive result was 

obtained 98.2% of the time. Our goal of at least 95% positives has been met. 

• With random sampling during each of 12 30-day “months,” positive results were 

obtained in only 82.1% of the simulations. The high-occurrence peak that was 

almost always detected with systematic sampling was often missed with random 

sampling. Our goal of at least 95% positives has not been met. 
Page 247 of 263 

C.6 Summary – Advantages and Disadvantages of Using the ANN Models 

Figure 31 lists some important advantages and disadvantages of using ANN models for 

the purpose of evaluating monitoring strategies for the Atrazine Monitoring Program. 

(Space is provided for additional remarks.) 

Figure 32 Utility of ANN Modeling 

Advantage Disadvantage 

Models are flexible and can potentially 

represent realistic occurrence patterns. 

The mathematical form of an ANN model 

is complex, so individual model 

parameters are difficult to interpret. 

The models account for some 

autocorrelation, so can be used to 

understand the distinction between 

consecutive days above a level of concern 

and percentiles of the occurrence 

distribution. 

We are not yet able to produce a 

hierarchical model that includes year-toyear variability in timings, numbers, and 

magnitudes of spikes. Our sense is that 

the benefit of developing such models is 

less than the cost / effort required. 

The models can be used to assess how a 

monitoring strategy’s performance is 

related not only to the sample size 

(number of samples collected each 

monitoring period) but also to the sample 

timing with respect to occurrence peaks. 

Expanding these models to account for 

year-to-year variability in parameters is 

feasible, but would require many years of 

data for each location modeled. 

Computing and interpreting occurrence 

endpoints may be challenging. 

The models are scalable, so that relative 

error (departure from the model’s baseline 

curve) is maintained on the measurement 

scale (g/L). Different magnitudes of 

occurrence are easily simulated using the 

same basic occurrence pattern. 

 
Page 248 of 263 

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