Wright et al. that bone lead levels are associated with lower LINE­1 element DNA methylation may have direct, rather than indirect, implica­ tions for the mechanistic role of lead exposure on health during aging. Future work target­ ing methylation at specific, intact LINE­1 sequence is needed to test this possibility. Use of DNA methylation changes in WBCs as a biomarker. The growing interest in epi­ genetic biomarkers is due to their potential to explain fetal origins of disease or, even more broadly, to explain the latency between expo­ sure to toxic substances and subsequent disease phenotypes. Measures of DNA methylation hold substantial promise as a biomarker for toxic environmental exposures, but because such marks are specific to cell type, much work is still needed to determine what role, if any, WBC DNA methylation may have for diseases that occur in inaccessible target tis­ sues, such as the brain. Measuring target organ DNA methylation would be ideal, but in many human studies obtaining such measures is not feasible. Nevertheless, peripheral WBC DNA methylation might hold promise as an exposure biomarker (as opposed to a biomarker of effect) by demonstrating that environmental factors can alter WBC DNA methylation patterns. LINE1­ and Alu are relatively primitive mark ­ ers of global methylation because they are aver­ aged across thousands of repetitive sequences. A more specific epigenomic measure, such as pat­ terns of DNA methylation within genes­pecific promoter sequences, might yield a more specific pattern quantifying past lead exposure. This finding raises the question of whether DNA methylation patterns could be a methodology to reconstruct past chemical exposure. Recently, Chanda et al. (2006) observed significant hypermethylation of the p16 gene promoter in DNA from peripheral blood lymphocytes of subjects exposed to arsenic­ contaminated water, showing that DNA from peripheral blood cells may be a suitable tissue for the development of epigenetic biomark­ ers. An expansion of this concept (i.e., that gene­ specific methylation is altered by envi­ ronment) to epigenomics may allow investiga­ tors to determine whether signature patterns of DNA methylation occur across the WBC epigenome that are specific to exposure to certain types of chemicals. This is effectively the concept underlying the field of proteom­ ics. Epigenomics, because its marks are stable but modifiable and because the technology is already highly developed, may be an alterna­ tive means for such biomarker development. Because WBCs are not a target for many diseases, changes in DNA methylation from peripheral blood cells may not reflect mecha­ nistic pathways in the target tissue. However, our results suggest that WBC DNA methyla­ tion may be useful as a biomarker of expo­ sure, possibly allowing investigators to confirm 794 whether exposures are chronic versus short term. Given that exposure assessment is the “Achilles heel” of environmental epidemiol­ ogy, particularly with respect to case–control studies of chronic disease, the potential for epigenetic or epigenomic marks to establish or confirm the presence or chronicity of environ­ mental exposures deserves further study. Limitations and future research. Our understanding of the role of DNA methyla­ tion and other epigenetic marks on gene expression and disease is clearly rudimentary at this stage. It is difficult therefore to ascribe the direct consequences of our findings to specific lead­ associated health effects. We believe that epigenetic marks may play a sig­ nificant role in the biological pathway from environmental exposures to disease and health states, and perhaps are critical to explaining the long latencies often observed between lead exposure and health effects. However, we also believe that to fully interpret such data, we must first establish norms and whenever possi­ ble study the target organ directly, rather than WBCs. Unlike DNA sequence, for which a large inventory of data has established a con­ sensus baseline sequence, there is no blueprint of what are “normal” DNA methylation pat­ terns. Such an inventory will be complex, as it is cell type–specific and will also change with different life stages. Establishing baseline pat­ terns of methylation across the epigenome in tissues readily accessible to researchers (e.g., blood, saliva, buccal cells) will be critical to understanding the relationship between environmental exposures, DNA methylation changes, and health. Because methylation pat­ terns are not inert, inventories will need to account for changes in methylation patterns specific to life stages. Work conducted con­ currently in animal models may also allow us to better understand how changes in WBC DNA methylation in response to environ­ mental stimuli correlate to changes in target tissues/cells that are not readily accessible, such as brain regions. In summary, we have found that LINE­1 DNA methylation is inversely associated with patella lead levels in a population of elderly men. Our work sug­ gests that changes in DNA methylation may be part of the underlying biological pathway between lead exposure and multiple lead­ as­ sociated health effects. There are many caveats to our findings, including whether findings in WBC DNA are representative of target tissue changes and whether the association of lead with decreased LINE­1 methylation is functional or merely representative of the impact of lead on DNA methylation glob­ ally. Despite these limitations, we believe that a better understanding of epigenetic marks as they relate to environmental exposure is critical to our understanding of human health and development. Future work is needed to establish baseline norms for epigenetic marks, to establish whether specific environmental exposures alter such marks, to determine whether WBC DNA methylation changes correlate with target tissue changes, and finally, to determine whether such changes are part of the causal pathway between environ­ ment and disease. Ref Rencs Aro ACA, Todd AC, Amarasiriwardena C, Hu H. 1994. Improve- ments in the calibration of 109Cd K X-ray fluorescence systems for measuring bone lead in vivo. Phys Med Biol 39:2263–2271. Axume J, Smith SS, Pogribny IP, Moriarty DJ, Caudill MA. 2007. The methylenetetrahydrofolate reductase 677TT genotype and folate intake interact to lower global leukocyte DNA methylation in young Mexican American women. Nutr Res 27(1):13–17. Baccarelli A, Bollati V. 2009. Epigenetics and environmental chemicals. Curr Opin Pediatr 21(2):243–251. Baccarelli A, Wright RO, Bollati V, Tarantini L, Litonjua AA, Suh HH, et al. 2009. Rapid DNA methylation changes after exposure to traffic particles. Am J Respir Crit Care Med 179(7):572–578. Belancio VP, Deininger PL, Roy-Engel AM. 2009. LINE dancing in the human genome: transposable elements and disease. Genome Med 1(10):97; doi:10.1186/gm97 [Online 27 October 2009]. Bell B, Rose CL, Damon A. 1966. The Veterans Administration longitudinal study of healthy aging. Gerontologist 6:179–184. Bestor TH, Tycko B. 1996. Creation of genomic methylation patterns. Nat Genet 12:363–367. Bollati V, Baccarelli A, Hou L, Bonzini M, Fustinoni S, Cavallo D, et al. 2007. Changes in DNA methylation patterns in subjects exposed to low-dose benzene. Cancer Res 67(3):876–880. Bollati V, Schwartz J, Wright R, Litonjua A, Tarantini L, Suh H, et al. 2009. Decline in genomic DNA methylation through aging in a cohort of elderly subjects. Mech Ageing Dev 130(4):234–239. Brouha B, Schustak J, Badge RM, Lutz-Prigge S, Farley AH, Moran JV, et al. 2003. Hot L1s account for the bulk of retro- transposition in the human population. Proc Natl Acad Sci USA 100:5280–5285. Carey VJ, Walters EE, Colditz GA, Solomon CG, Willett WC, Rosner BA, et al. 1997. Body fat distribution and risk of non-insulin-dependent diabetes mellitus in women. The Nurses’ Health Study. Am J Epidemiol 145:614–619. Carnell AN, Goodman JI. 2003. The long (LINEs) and the short (SINEs) of it: altered methylation as a precursor to toxicity. Toxicol Sci 75(2):229–235. Chanda S, Dasgupta UB, Guhamazumder D, Gupta M, Chaudhuri U, Lahiri S, et al. 2006. DNA hypermethylation of promoter of gene p53 and p16 in arsenic exposed people with and without malignancy. Toxicol Sci 89(2):431–437. Colella S, Shen L, Baggerly KA, Issa JP, Krahe R. 2003. Sensitive and quantitative universal pyrosequencing methylation analysis of CpG sites. Biotechniques 35:146–150. Coufal NG, Garcia-Perez JL, Peng GE, Yeo GW, Mu Y, Lovci MT, et al. 2009. L1 retrotransposition in human neural progenitor cells. Nature 460(7259):1127–1131. Fowler BA, Whittaker MH, Lipsky M, Wang G, Chen XQ. 2004. Oxidative stress induced by lead, cadmium and arsenic mix- tures: 30-day, 90-day, and 180-day drinking water studies in rats: an overview. Biometals 17:567–568. Garcia-Perez JL, Doucet AJ, Bucheton A, Moran JV, Gilbert N. 2007. Distinct mechanisms for trans-mediated mobiliza- tion of cellular RNAs by the LINE-1 reverse transcriptase. Genome Res 17(5):602–611. Han JS, Boeke JD. 2005. LINE-1 retrotransposons: modulators of quantity and quality of mammalian gene expression? Bioessays 27(8):775–784. Hu H, Aro A, Payton M, Korrick S, Sparrow D, Weiss ST, et al. 1996. The relationship of bone and blood lead to hyperten- sion. The Normative Aging Study. JAMA 275:1171–1176. Hu H, Milder FL, Burger DE. 1990. X-ray fluorescence measure- ments of lead burden in subjects with low-level community lead exposure. Arch Environ Health 45:335–341. Hu H, Rabinowitz M, Smith D. 1998. Bone lead as a biological marker in epidemiologic studies of chronic toxicity: con- ceptual paradigms. Environ Health Perspect 106:1–8. ovlume 118 | number 6 | June 2010 • Environmental Health Perspectives