### Appendix 4Page 2 of 14 

### UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON, D.C. 20460

OFFICE OF CHEMICAL SAFETY AND

POLLUTION PREVENTION



### MEMORANDUM

Date: Ju ne 30

, 2011

SUBJECT: Chlorpyrifos Correspondence with Columbia Researchers : (1) Responses to Scientific Advisory Panel (SAP) comments (Whyatt and Rauh 2010) , and (2) R espon ses to Dow AgroSciences inquiries (Whyatt 2010).

P C Code: 059101 DP Barcode: D 391257

Decision No.: NA Registration No. : NA

Petition No.: NA Regulatory Action: NA Risk Assessment Type: Single Chemical Aggregate Case No.: NA

T XR No.: 0056066 CAS No.: NA

MRID No.: NA 40 CFR: NA

FROM: Debor ah Smegal, MPH,

Immediate Office (IO) Health Effects Division (7509P)

TO: Danette Drew, Risk Assessor

RABV Health Effects Division (7509P)

Backrgound

On September 16

- 19, 2008, the Agency held a FIFRA Scientific Advisory Panel (SAP) meeting (SAP 2008) to discuss t he Agency's Evaluation of the Toxicity Profile of Chlorpyrifos , which

includes more recent and extensive research on various aspects of chlorpyrifos including its neurological effects in animals and humans following gestational and p ost

- natal exposures, its pharmacokinetics, and mechanism of action. Details can be found at the Scientific Advisory Panel website ( http://www.epa.gov/scipoly/sap/meetings/2008/091608 _mtg.htm ), and in the Chlorpyrifos Final SAP report ( http://www.epa.gov/scipoly/sap/meetings/2008/september/sap0908report.pdf .)

Attached is a response to the SAP comments on the “Epidemiologic Appendix: Columbia Study” that Deborah Smegal summarized and sent to Robin Whyatt and Virginia Rauh, dated 1/28/2010.Page 3 of 14 

### In addition, the Columbia researchers prepared responses to questions raised by Dow AgroSciences.Page 4 of 14 

### Columbia Response to the SAP Queries

2/19/2010

The following is a response to the Scientific Advisory Panel comments on the “Epidemiologic Appendix: Columbia Study” that Deborah Smegal summarized and sent to Robin Whyatt and Virginia Rauh , dated 1/28/2010

.

1. SAP comment: EPA should continue its collaboration with Columbia researchers in analyzing the epidemiologic data ...[and] should seek clarification of the reported exposure levels . . . EPA should use the epidemiological cohort data for bounding

exposure levels and in conjunction with PBPK models, address current or potential human exposures and to determine the final RfD/RfC . . . PBPK models enable estimation of exposure dose metric for multiple sources (e.g., air, food, water etc). EPA should pursue si mpler PBPK model in short

- term.

Response: We are happy to continue the collaboration. In addition, as described in our letter, Dr. Dale Hattis at Clark University is conducting PBPK modeling of the Columbia data under a U.S. EPA Star Grant. The grant is entitled “Use of Biomarkers and Physiologically Based Pharmacokinetic [PBPK] Modeling in Risk Analysis for Developmental Effects of Chlorpyrifos”. We believe that the PBPK model being developed by Dr. Hattis will prove extremely helpful to EPA in addressi ng the SAP comments and in clarifying the exposure concentrations that correspond to the chlorpyrifos levels in umbilical cord blood at which we begin to see statistically significant adverse effects on fetal growth and child neurocognitive development. Th us this data should be helpful in bounding the exposure data as recommended by the SAP. We recommend that EPA contact Dr. Hattis.

2. SAP comment: Determine if the chlorpyrifos effect on birth weight would result in more infants in “low birth weight” category

.

Response: We are not able to address this question as our cohort was predominantly full term by design. This is because we did not conduct our environmental monitoring until the 3 rd 

### trimester of pregnancy and completion of the environmental monitoring was a prerequisite for enrollment. For example, of the subjects in our 2004 analyses (Whyatt et al., EHP, 112:1125

- 1132, 2004), only 12/314 (3.8%) of the women delivered prior to 37 weeks gestation and only 12/314 (3.8%) of the infants were <2500 grams at birth. We, therefore, do not have adequate statistical power to evaluate the relationship between prenatal chlorpyrifos exposure and low birth weight.

3. SAP comment: Ascertain whether there are statistically significant differences in neurodevelopmental o utcomes at 3 yrs between chlorpyrifos levels in cord blood below LOD and those with chlorpyrifos >6.17 pg/g . . . Verify/clarify there is no suggestion of an effect as the most highly exposed group and the group with values

below the LOD had lower MDI and PDI scores than did the middle levels.

Response: Table 1 below provide the same type of information as Table 2 in the 2006 Pediatrics paper (Rauh et al., Pediatrics, 118:e1845

- e1859, 2006) with respect to the % of subjects whose

tests scores indicated d evelopmental delay with respect to the PDI and the MDI, as a function ofPage 5 of 14 

### chlorpyrifos exposure. However, here we provide the % delayed for all four exposure groups, rather than just the ‘high’ and ‘low’ exposure groups shown in the paper. For both the PDI and MDI the rate of delay is clearly highest in the high chlorpyrifos group (Group 4).For the 36 month PDI, the rate of developmental delay is relatively low in all 3 low

- exposure groups, and is about three times higher in the highest exposure group. And for the 36 month MDI, while the <LOD group experienced a higher rate of delay than group 2 and 3, the very highest rate of delay is among the most exposed children. In univariate analyses, the difference in % delay between the highest exposure (>6.17pg/g ) group versus the lowest exposure (<LOD) group, was statistically significant for PDI (chi

- square p=.018, 1 sided; p=.031 two

- sided), but not significant for MDI. However, importantly, there was no significant difference in the rate of delay between group s 1, 2 and 3 for either the PDI (chi

- squared= 0.97, p=0.61) or MDI (chi

squared= 4.4, p=0.11). And the rate of developmental delay in terms of both PDI and MDI in group four was significantly greater than in groups 1

- 3 combined, as reported in our paper.

Table 1. The proportion of children at age 36 month who were at risk of delay (score < 85) on the Psychomotor Development Index (PDI) or Mental Development Index (MDI) of the Bayley Scales of Infant Development by chlorpyrifos exposure group Group 1 (< LOD) Group 2 (1 st tertile > LOD) Group 3 (2 nd tertile > LOD) Group 4 (3 rd tertile > LOD)

PDI 7/80 (8.8%) 3/65 (4.6%) 3/38 (7.95) 11/45 (24.4%)

MDI 30/80 (37.5%) 14/65 (21.5%) 11/39 (28.2%) 20/44 (45.5%)



### 4. SAP comment: Conduct an analysis of exposure leve ls as dependent variable and year (an ordinal variable) as the primary independent variable, while adjusting for any factors associated with both exposure levels and year of study.

Response : We have already published on changes in indoor and personal a ir levels, as well as in multiple biomarker levels by year of monitoring and have enclosed the most relevant articles ( Whyatt et al., 2007; Whyatt et al., 2009). In addition, Dr. Hattis has also recently completed analyses looking at changes in chlorp yrifos levels by year in the context of other factors such as season of monitoring. As stated above, we recommend that EPA contact Dr. Hattis to review his

results.

5. SAP comment: EPA should request additional details on the loss to follow

- up in

each of the 4 exposure groups and provide additional details on how the exposure groups were combined.

Response: Subjects were eligible for inclusion in the Pediatric paper if they had been born by 7//12/02 and thus had reached age three years by the time of the analyses and also had: (1) measures of chlorpyrifos in blood at birth; (2) neurologic assessments at least once between ages

12

- 36 months and (3) data on model covairates. A total of 381 subjects in the cohort had been born by 7/12/02 and had birth chlorpy rifos blood measure; of these 254 (67%) met the above criteria for inclusion, including 228 who had developmental outcomes at age 36 months. The remaining subjects had either been lost to follow

- up (accounting for approximately 14%) or were missing outco me and/or covariate data. Table 2 below shows the 254 subjects included in the analyses over all 381 subjects by the chlorpyrifos groups. (The numbers per group just for the 228 subjects with outcome data at 36 months are given in the Pediatric manuscript. ) Group 1Page 6 of 14 

### includes all subjects with chlorpyrifos blood levels below LOD; the remaining subjects were ranked into tertiles based on ascending levels (Groups 2

- 4). However, as describe in the Pediatric manuscript, this grouping was done on subjects born pr ior to 1/1/01 to be consistent with our prior publication (see Whyatt et al. 2004). This was essential in order to compare results across analyses moving forward, given that chlorpyrifos concentrations were changing rapidly following the ban and thus we ne eded consistent cutpoints. Groups 1

- 3 were combined and compared with group 4 for the analyses presented in the Pediatrics manuscript.

Table 2. Subjects included in the Pediatric paper over all cohort subjects born at or before 7/12/02 who had chlorpyr ifos measured in cord blood at birth Group 1 (<LOD) Group 2 (1 st tertile > LOD) Group 3 (2 nd tertile > LOD) Group 4 (3 rd tertile > LOD)

88/121 (72%) 72/127 (56.7%) 44/63 (69.8%) 50/70 (71.4%)



### 6. SAP comment: Post ban declines in effects are based on 1 su bject being classified as highly exposed, which lacks statistical power and may be sensitive to the cutoff value chosen to classify subjects as highly exposed. Can an analysis be conducted to look at relationships between more equally sized exposure group s that separate between the lower exposure levels?

0 2 4 6 8 10

chlopyrifos 1999 68/71 (96%)

2001 26/86 (30%) 2000 101/120 (84%)

2002 18/59 (31%) Figure 1. Chlorpyrifos levels in maternal and umbilical cord blood samples (pg/gram) at delivery by year of birth

2003 0/58 (0%)

2004 0/30 (0%)

Cord blood (N=395) Year N > LOD (%)

0 2 4 6 8 10

chlopyrifos Maternal blood (N=424) Year N > LOD (%)

1999 93/110 (85%)

2001 18/71 (25%) 2000 88/110 (80%)

2002 14/36 (39%)

2003 0/43 (0%)

2004 0/25 (0%)



### Response: We believe the SAP has misunderstood that our post ban declines were based not on the change in the number of subjects that fell into the highly exposure group but on the decrease we had seen in chlorpyrifos concentrations in both maternal and cord blood among all cohort subjects by year of birth (see Figure 1). As can be seen in the above figure, chlorpyrifos levels had dropped dramatically by 2001. Our 2004 study categorized the full cohort available at that time (most born prior to1/1/01) into four groups based on ascending levels of chlorpyrifos in umbilical cord blood. The only significant difference we saw was between infants in the highest

exposure group (group 4) compared to those with levels below the limit of detection (group 1). By contrast, there was no significant difference in birth outcomes between subjects in thePage 7 of 14 

### intermediate exposure groups (2 or 3) compared to group 1 (see Whyatt et al. EHP, 11 2: 1125

- 1132. 2004). At the time we conducted the analyses for our 2004 paper, only n=77 infants were born after 1/1/01, which limited our power to determine whether or not there was any continuing effect of prenatal chlorpyrifos exposure on birth outcom es after2001. In April 23, 2008, we presented undated analyses to EPA that included more infants (n=193) born after 1/1/01. Results are shown in Table 3 below and are consistent with our 2004 publication. Specifically, we saw a highly significant decrease in birth weight for each log unit increase in umbilical cord

Table 3

. Change in birth weight for each log unit increase inchlorpyrifos concentrations in umbilical cord plasma among

babies born before and after 1/1/01

B (95% CI) P

- value

Born b efore 1/1/01 (n=233)

- 71/4 (

- 121/1,

- 21.8 P=0.005

Born after 1/1/01 (n=193) 32.7 (

- 59.3, 124.7) P=0.48

chlorpyrifos concentrations among babies born before 1/1/01, but no association between chlorpyrifos and birth outcomes among infants born after 1/1/01. Of those infants born after 1/1/01, only 16% had chlorpyrifos levels in cord blood above the LOD and only one of these was in the previously defined ‘high exposure’ group. It is obvious that this marked reduction in chlorpyrifos exposure, and the virtual eli mination of high exposure levels after 1/1/01, is due to the chlorpyrifos ban , . To address the SAP comments further, we have conducted analyses that categorize infants born after 1/1/01 into those with chlorpyrifos above and below the LOD. Keeping in min d that there was only one child with high (group 4) chlorpyrifos exposure in this

post

- ban sample, it is not surprising that there was no significant difference in birth weight between the <lod group and the small group with some exposure during this post

- ban period. These findings thus support the hypothesis that chlorpyrifos exposures following the ban had dropped below concentrations that have adverse effects on fetal growth. However, it is also possible that our sample size is simply too small to detect relatively small but real negative effects on birth outcomes associated with the much reduced exposure levels after 1/1/01.

7. SAP comment: The panel felt it might be helpful to have a longitudinal component to the study to determine if the adverse eff ect persisted in children who exhibited poor birth

outcomes or neurobehavioral deficits.

Response: As described in the attached letter, we have just completed statistical analyses on the relationship between prenatal chlorpyrifos exposure and outcomes on the Wechsler Intelligence Scale for Children (Fourth Edition) and the Child Behavior Check List, which have been administered to cohort children at age 7 years. We anticipate that a manuscript on these findings will be completed and ready for submission wi thin several months.

8 . SAP comment: It would be useful to examine the results of a statistical analysis that

includes all three AChE

- inhibiting insecticides in the analysis model as dichotomous variables (above or below the LOD) in combination with conti nuous measurements for these variables. This is not likely to change the results but could be helpful in illustrating threshold or dose response effects . . . Are all 3 AChE inhibiting insecticides correlated (if

lack of correlation

— less likely would con found cyp and neuro outcomes) . . . ConductPage 8 of 14 

### additional analysis controlling for multiple exposures examining additive effects to elucidate the role of other Ops. This is important for AChEI to be considered as mode of

action.

Response : It should be not ed that our 2004 paper (Whyatt et al., EHP, 112: 1125

- 1132) looked at the additive effects of chlorpyrifos and diazinon on birth outcomes using the U. S. EPA guidelines for conducting cumulative risk assessments for the organophosphates. However, in

respon se to the SAP comments, we have now conducted a number of additional analyses both to evaluate the correlations among the three AChE inhibiting insecticides (chlorpyrifos, diazinon and propoxur) detected in our cohort and to look at the effects of chlorpyr ifos on both birth outcomes and child neurocognitive development after controlling for diazinon and propoxur. Specifically we have devloped 4 additional models for birth weight and birth length and 4 models for the psychomotor development index (PDI) and m ental development index (MDI) on the Bayley Scales of Infant Development at age 36 months. All models controlled for the same covariates as in our 2004 and 2006 publications. Model 1 includes only chlorpyrifos as the independent variable (i.e. is identic al to the data in our initial publications); model 2 includes chlorpyrifos and diazinon; model 3 includes chlorpyrifos and 2

- isopropoxyphenol (the chemical

specific metabolite of propoxu r ); and model 4 includes all three acetylcholinesterase inhibiting

in secticidess Results are presented below:

Correlations among pesticides : For infants born prior to the chlorpyrifos phase out (the relevant time period), there was a modest correlation between 2

- isopropoxyphenol (the chemical specific metabolite of propoxu r) and both chlorpyrifos (r=0.25, p<0.001, n=222) and diazinon (r=0.21, p=0.002, p=227) in umbilical cord blood samples. However, there was a higher correlation between chlorpyrifos and diazinon (r=0.63, p<0.0001, n=222), incdicating that approximately

33 % shared variabilitybetween these two pesticides. Given this relationship between chlorpyrifos and diazinon, the question raised by the SAP

— whether the chlorpyrifos effects we report could be due to confounding by diazinon

— is therefore very appropriate. T his question is addressed in the new analyses reported below.

Results on birth outcomes. Results are presented in Tables 4 and 5 below. As can be seen, chlorpyrifos remained inversely associated with birth weight and length in all models after

controllin g for diazinon and 2

- isopropoxyphenol, and the magnitude of the significant negative effect of chlorpyrifos on infant size remained relatively constant across the models, indicating that neither of these two other acetylcholinesterase inhibitors was confou nding the relationship between chlorpyrifos and birth outcomes. Further neither diazinon nor 2

- isopropoxyphenol, either individually or in combination, was associated with birth weight, although the inverse association reported previously between 2

- isoprop oxyphenol and birth length (see Whyatt et al., 2004) remains of borderline significant (p=0.05). Consistent with our prior findings, birth weight decrease significantly by 198 grams among infants in the highest compared to the lowest chlorpyrifos groups (G roup 4 versus Group 1) after controlling for both diazinon and 2

- isopropoxyphenol, as well as the other model covariates (p<0.05). These analyses thus indicate that it is primarily prenatal chlorpyrifos and not the other two acetylcholinesterase

- inhibiting insecticides that is having an adverse effect on fetal growth. Further, the findings suggest that the effect of chlorpyrifos on fetal growth may well be mediated by mechanisms other thanPage 9 of 14 

### acetylcholinesterase inhibition, given the lack of an association be tween the other two acetylchlolinesterase inhibitors and birth weight.

Table 4. Decrease in birth weight for each log

- unit increase in insecticide levels in umbilical cord blood at birth among infants born prior to 1/01/01 . Values shown are regression co efficient (B), 95% confidence interval, and p

- value

Model 1 Model 2 Model 3 Model 4 (ln) Chlorpyrifos

- 67.3 (

- 17.8,

- 116.8) p=0.008 - 65.9 (

- 5.7,

- 126) p=0.03 - 6 0

. 9 (

- 10.0,

- 111.8) p=0.02 - 60.2 (0.9,

- 121.3) p=0.054

(ln) Diazinon

- 4.7 (107.7,

- 117.1) p=0 .94 - 2.5 (110,

- 114) p=0.9 6

(ln) 2

- isopropoxyphenol

- 50.9 (46.1,

- 147. 8 ) p=0.30 - 50

. 8 (46.5,

- 114.9) p=0.30

All models controlled for gestational age, parity, maternal pre

- pregnancy weight and net weight gain during
pregnancy, maternal self

- reported en vironmental tobacco smoke in the home, gender of the newborn and
season of delivery.

Table 5

. Decrease in birth length for each log

- unit increase in insecticide levels in umbilical cord blood at birth among infants born prior to 1/01/01 . Values shown a re regression coefficient (B), 95% confidence interval, and p

- value

Model 1 Model 2 Model 3 Model 4 (ln) Chlorpyrifos

- 0.43 (

- 0.14,

- 0.73) p=0.004 - 0.46 (

- 0.1,

- 0.82) p=0.01 - 0.36 (

- 0.06,,

- 0.66) p=0.02 - 0.40 (

- 0.75,

- 0.35) p=0.03 (ln) Diazinon 0.09 (0.7 6,

- 0

. 58) p=0.80 0.12 (

- 0.78, 0 5 5) p=0.73
(ln) 2

- isopropoxyphenol

- 0.57 (0.002,

- 1.14) p=0.051 - 0.5 8 (

- .001,

- 1.15) p=0.05 All models controlled for gestational age, parity, maternal pre

- pregnancy weight and net weight gain during
pregnancy, maternal s elf

- reported environmental tobacco smoke in the home, gender of the newborn and

season of delivery

.



### Results on PDI and MDI are presented in Table 6 and 7 below. The findings were quite surprising. There was no significant association between 2

- isopropoxy phenol and delay on either the PDI or MDI. However, when diazinon was added to the model, the negative effect of chlorpyrifos on developmental delay for both the PDI and MDI became much stronger

. Specifically, the odds ratio almost doubled for PDI and incr eased by 40%

- 60% for the MDI. These results again indicate that it is chlorpyrifos and not the other two acetylcholinesterase insecticides that is having an adverse effect on child mental and motor development and further that the effect size appears consi derably greater than we had estimated before. The findings again support the suggestion, as discussed by the SAP, and as is suggested by the experimental evidence, that the effects of chlorpyrofos on child development may well be by a mode of action

other than acetylcholinesterase inhibition

.Page 10 of 14 Table 6. Effects of chorpyrifos on the odds of ps;ychomotor delay on the Bayley Scales of Infant Development at age 36 month

. Values shown are regression coefficient (B), 95% confidence interval, and p

- value s Model 1 Model 2 Model 3 Model 4 Chlorpyrifos 2 4.5 (1.6, 12.7) p=0.004 8.4 (2.4, 30. 2 ) p=0.001 4.0 (1.4, 11.8) p=0.01 7.9 (2.1, 29.1 ) p=0.002 (ln) Diazinon 0.45 (0.18, 1.13) p = 0.09 0.4 (0.2, 1.1) p=0.08 (ln) 2

- isopropoxyphenol 1.3 (0.6 5 , 2.8) p=0.4 1.4 (0. 6 7, 3.0) p=0.37 All models controlled for race/ethnically, gender, ETS, gestational age, maternal IQ, maternal education,

HOME score 1 OR = Odds ratio

2 >6.17 pg/g versus ≤ 6.17 pg/g in umbilical cord blood

Table 7. Effects of chorpyrifos on the odds of mental delay on the Bayley Scales of Infant Development at age

36 months. Values shown are regression coefficient (B), 95% confidence interval, and p

- va lue

Model 1 Model 2 Model 3 Model 4 Chlorpyrifos 2 2.3 (1.1, 5.2) p=0.03 3.8 (1.5, 9. 4 ) p=0.004 2.0 (0.9, 4.5) p=0.11 3.2 (1.3, 8.2 ) p=0.02 (ln)Diazinon 0.57 (0.35, 0.95) p = 0.03 0.6 (0.3, 0.9)

p =0.03 (ln) 2

- isopropoxyphenol 1.5 (0.9, 2.5) p=0.12 1.5 (0.9, 2.6) p=0.11 All models controlled for race/ethnically, gender, ETS, gestational age, maternal IQ, maternal education,

HOME score 1 OR = Odds ratio

2 >6.17 pg/g versus ≤ 6.17 pg/g in umbilical cord blood



### 9 . SAP comment: Is it possible to determine quantitative contribution of chlorpyrifos in exposure to mixture by accounting for differences in chemicals, potency, pharmacokinetics and possible chemical interactions

.

Response:

10. SAP comment: Look at intermediate markers of biologically effective dose and early effect that further link exposure and outcome and or a clearer idea of mode of action from exposure studies. Dr. Hattis can address this question after his PK model is implemented and

calibrated.

Response: As described in our letter, we have been conducting Magnetic Resonance Imaging (MRI) scans on cohort children with either high prenatal chlorpyrifos exposure (n=20) or no

exposure to any o f the contaminants that have been associated with adverse child cognitive development among the CCCEH cohort (n=20). The MRI results will provide a marker of biologic effect. These analyses are being undertaken under the direction of Dr. Bradley Peterson, Director of Child and Adolescent Psychiatry at the New York State Psychiatric Institute. We anticipate that a manuscript on the results will be submitted to a peer

- reviewed journal by Aug 1

2010.Page 11 of 14 

### COLUMBIA CENTER

F OR C HI LD REN ' S

EN VI RON M E NT A L

HE A L TH

MAILMAN SCHOOL OF PUBLIC HEALTH

Co lum b i a U niver s i t y

Memo to: Deborah Smegal From: Robin Whyatt Date: March 8, 2010

We are pleased that our answers to the questions raised by the Science Advisory Panel (SAP) will be of value to EPA as you move fo rward to update the chlorpyrifos risk assessment. Below are our responses to the questions raised by Dow Agrosciences which you also asked us to address in your email of March 5,2010. Please let us know if you need any additional

information or if we can b e of more help.

Question one: The Columbia birth cohort includes cord blood chlorpyrifos levels for most children and urine from many mothers (Whyatt et a L . 2005,2009). However, the authors state that "we found no association between chlorpyrifos levels i n maternal and cord blood and TCPy levels in maternal urine samples during pregnancy or after delivery." (Whyatt et a L . 2009, pg 563)

. Since the health effect papers are based solely upon chlorpyrifos levels in blood, and because blood chlorpyrifos measu rements have not been reported in any other human exposure study at these trace

- level concentrations, this is a critical point to evaluate with full transparency. Specific questions include:

a. Why is there no association between blood chlorpyrifos and ur inary TCPy? b. How many mother infant pairs in 1999 have both urine TCPy and blood chlorpyrifos?

c. Are the 1999 urine and blood levels correlated?

d. Are the 2000 urine and blood levels correlated?

e. Are the 2001 urine and blood levels correlated?

f. Wit h personal monitoring, air monitoring, blood chlorpyrifos and urinaryTCPy, what is the

estimated internal dose for the infant

- mother pairs in each year of measurement?

Answer: Please note that the primary biomarker we have measured in our cohort is chlorp yrifos concentrations in maternal and umbilical cord blood. We did not measure TCPy in maternal urine samples except for a small subset of subjects. Specifically, as described in our 2009 manuscript (Whyatt et aI., EHP, 117;559

- 567, 2009), we measured TCPy in repeat urine samples collected from only n=97 women during pregnancy. These urine samples were collected among women who delivered between 2001

- 2004. Thus the answer to la through 1 d above isPage 12 of 14 that no mother/infant pairs have both chlorpyrifos in blood and TCPy in urine in either 1999 or 2000 and we thus do not have the data to look at the correlation between TCPy in urine and chlorpyrifos in blood among subjects who delivered prior to 2001. For subjects who delivered in
2001, we can look at this relatio nship. It should be noted, however, that these data are not particularly helpful in evaluating the correlations between urinary TCPY and blood chlorpyrifos concentrations, due to small sample size. But more importantly, chlorpyrifos in blood samples

had al ready dropped substantially by 2001 following the residential ban. Specifically, by 2001 among subjects that had both TCPy measured in maternal urine and chlorpyrifos measured in blood, chlorpyrifos was only detected in 24% of maternal blood samples and 19 % of umbilical cord blood samples (See Figure 2, Whyatt et at., 2009). By contrast, as shown in Figure 1 from in the Columbia Response to the SAP Queries (2/19/2010), chlorpyrifos was detected in 98% and 85% of maternal and umbilical cord blood samples, re spectively, during 1999 and 84% and 80% during 2000. Given these caveats, the results for 2001 are as follows: For these subjects, the average chlorpyrifos concentrations in two

- week integrated indoor air samples collected over 

### the final 6

- 8 weeks of pregn ancy were positively correlated with average TCPy levels in

maternal prenatal spot urine samples (r=0.5, p= 0 . 005). However, there was no correlation (p>0.2) between TCPy levels and chlorpyrifos in either maternal blood samples (n=29) or cord blood samples (n=21) at delivery. Maternal and umbilical cord blood levels were highly correlated (r=0.85, p< 0.001 , n=21).

Regarding question "If" above, please note, that as discussed in our answers to the SAP querries, Dr. Dale Hattis at Clark University is conducti ng PBPK modeling of the Columbia data under a Us. EPA Star Grant. The gr ant is entitled “ Use of Biomarkers and Physiologically Based Pharmacokinetic [PBPK] Modeling in Risk Analysis for Developmental Effects of Chlorpyrifos ". We believe that the PBPK mode l being developed by Dr. Hattis will prove helpful in clarifying the exposure concentrations that correspond to the chlorpyrifos levels in umbilical cord blood at which we begin to see statistically significant adverse effects on fetal growth and

child neu rocognitive development and also in estimating the internal dose for the infant/mother pairs in each year of measurement. Dr. Hattis estimates that his analyses should be completed relatively shortly. We recommend that you contract Dr. Hattis.

Question Tw o: In the Rauh et al. (2006) paper the authors note a nonlinear dose trend with using 4 exposure groups. The final analyses are limited to two exposure groups. An analysis of 4 exposure groups is more information from a risk perspective and is critical for full transparency of the data. Analysis with 4 exposure groups for the results presented in Tables 2

- 8 should be replicated and made publically available.

Answer: We have already addressed this comment in our answer 

### # 3 from the Columbia Response to the SAP Queries (2/19/2010). To reiterate, we prepared a new table (Table 1 below) which provided the same type of information as Table 2 in the 2006 Pediatrics paper (Rauh et
at., Pediatrics, 11 8:el 845..;el 859, 2006) with respect to the % of subjects whose tests scores indicated developmental delay with respect to the PD I and the MD I , as a function of chlorpyrifos exposure. However, we provided the % delayed for all four exposure groups, rather than just the 'high' and 'low' exposure groups shown in the pape r. For both the PD I and MD I the rate of delay is clearly highest in the high chlorpyrifos group (Group 4). For the 36 month PD I , the rate of developmental delay is relatively low in all 3 low

- exposure groups, and is about three times 

### higher in the highest exposure group. And for the 36 month MDI, while the <LOD group experienced a higher rate of delay 

### than 2 and 3

, the very highest rate of delay is amongPage 13 of 14 the most exposed children. In univariate analyses, the difference in 

### % delay between highest

exposure ( >6. 17pg/g) group versus the lowest exposure group (<LOD) was sta tistically significant for PDI (chi

- square p=0. 018, 1 sided; p

- 0. 03 1 two

- sided), but not significant for MDI However, importantly, was no significant difference in the rate of delay between g roups 1

, 2 and 3 for either the PDI (chi

- squared= 0.97, p=0

. 61) or MDI (chi

- squared= 4.4, p= 0

. 11 ).

And the rate of developmental delay in terms of both PDI and MDI in group four was s ignificantly greater than in groups 1

- 3 combined, as reported in our pap er.

Table 1. The proportion of children at age 36 month who were at risk of delay (score < 85) on the Psychomotor Development Index (PDI) or Mental Development Index (MDI) of the Bayley Scales of Infant Development by chlorpyrifos exposure group Group 1 (<LOD) Group 2 (1 st tertile > LOD) Group 3 (2 nd tertile > LOD) Group 4 (3 rd tertile > LOD)

PDI 7/80 (8.8%) 3/65 (4.6%) 3/38 (7.95) 11/45 (24.4%)

MDI 30/80 (37.5%) 14/65 (21.5%) 11/39 (28.2%) 20/44 (45.5%)

Question Three: In the Rauh et al. (2006) pa per, the authors compare results of the Bayley Mental Development Index (MDI) and Bayley Psychomotor Development (PDI) in different years. Using significance testing only, they claim there is a “preban” difference and no " postban " difference. This

natural experiment is important to control for the many confounding factors associated with the home

environment of these children. A more comprehensive and transparent analysis of these data over would provide information about role of chlorpyrifos and MDI and PD I this unique population.



### An swer : Please note that most cohort children in the 2006 paper by Rauh et at. were born prior to the residential ban on chlorpyrifos. Specifically, as described in our answers to SAP queries, subjects were eligible for inclusi on in the Pediatric paper if they had been born by 7/12/02 and

thus had reached age three by the time of the analyses and also had: (1) measures of chlorpyrifos in blood at birth; (2) neurologic assessments at least once between ages 12

- 36

mont hs and (3) data on model covar i ates. Therefore, we were not able to undertake statistical analyses relating the changes in chlorpyrifos concentrations to changes in MDI and PDI following the residential ban. However, authors concurred that this is an important resear ch question and state that “ larger epidemiologic studies will to assess the full impact of the ban (see page e1854 of the Pediatric paper)." As discussed in our February 17 th 

### letter to

Dr. Jack Fowle, we are currently preparing a manuscript on the relati onship between prenatal chlorpyrifos exposure and outcomes on the Weschler Intelligence Scale for Children (Fourth Edition) and the Child Behavior Check List, which have been administered to cohort children at

age 7 years. However, we also plan to undertak e additional analyses of the 36 th month MDI and PDI in relationship to prenatal chlorpyrifos exposures following the ban, since many more children in our cohort have now completed the 3 year developmental assessments and we have the sample size to undertak e the analysis outlined above, while controlling for the many potential confounders.

Question Four: The exp osure estimates in the Columbia and CHAMACOS studies are reported differently, thus preventing a meta

- analysis from being undertaken. Both studies reported Bayley MDI and Bayley PDI results at 24 months and neither was statistically s i g nificant (Eske n azi et al. 2007). This can be interpreted as a tendency but underpowered, or as a ch ance finding. Obtaining the

raw data and pooling the re sults s hould be undertaken and has several benefits.Page 14 of 14 a. The exposure est i mates can be unified (either by calculating an estimated dose or estimating a TCP level from the blood data). The dose cut points can be set to at least 3

doses to determine the presence of a d ose resp onse relationship.

b. The power will doubled by combining the two cohorts, thereby increasing the statistical

power.



### Answer: As discussed in our February 17t h letter to Jack Fowle, a multi

- site study has been funded the National Institute of Enviro nmental Health Sciences ($568, 000 total costs) that will pool the children's centers at the University of California

- Berkeley, Columbia University (our children’s center) and the Mount School of Medicine to address questions about relationships across the three cohorts between prenatal organophosphate exposure, fetal growth and child neurocognitive development. Dr. Brenda Eskenazi at Berkeley

is the principal investigator on project.