Abstract
Purpose of Review
This manuscript orients the reader to the underlying motivations of environmental biomarker development for human population studies and provides the foundation for applying these novel biomarkers in future research. In this review, we focus our attention on the DNA methylation–based biomarkers of (i) smoking, among adults and pregnant women, (ii) lifetime cannabis use, (iii) alcohol consumption, and (iv) cumulative exposure to lead.
Recent Findings
Prior environmental exposures and lifestyle modulate DNA methylation levels. Exposure-related DNA methylation changes can either be persistent or reversible once the exposure is no longer present, and this combination of both persistent and reversible changes has essential value for biomarker development. Here, we present available biomarkers representing past and cumulative exposures using individual DNA methylation profiles.
Summary
In the present work, we describe how the field of environmental epigenetics can leverage machine learning algorithms to develop exposure biomarkers and reduce problems of misreporting exposures or limited access technology. We emphasize the crucial role of the individual DNA methylation profiles in those predictions, providing a summary of each biomarker, and highlighting their advantages, and limitations. Future research can cautiously leverage these DNA methylation–based biomarkers to understand the onset and progression of diseases.
Similar content being viewed by others
References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
Barros SP, Offenbacher S. Epigenetics: connecting environment and genotype to phenotype and disease. J Dent Res. 2009;88(5):400–8.
Leenen FA, Muller CP, Turner JD. DNA methylation: conducting the orchestra from exposure to phenotype? Clin Epigenetics. 2016;8:92.
Marioni RE, Shah S, McRae AF, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015;16(1):25.
Byun HM, Colicino E, Trevisi L, et al. Effects of air pollution and blood mitochondrial DNA methylation on markers of heart rate variability. J Am Heart Assoc Cardiovas Cerebrovas Dis. 2016;5(4):e003218.
Agha G, Mendelson MM, Ward-Caviness CK, Joehanes R, Huan T, Gondalia R, et al. Blood leukocyte DNA methylation predicts risk of future myocardial infarction and coronary heart disease. Circulation. 2019;140(8):645–57.
Wu S, Hivert MF, Cardenas A, Zhong J, Rifas-Shiman SL, Agha G, et al. Exposure to low levels of lead in utero and umbilical cord blood DNA methylation in project viva: an epigenome-wide association study. Environ Health Perspect. 2017;125(8):087019.
Wright RO, Schwartz J, Wright RJ, Bollati V, Tarantini L, Park SK, et al. Biomarkers of lead exposure and DNA methylation within retrotransposons. Environ Health Perspect. 2010;118(6):790–5.
Bitto A, Pizzino G, Irrera N, Galfo F, Squadrito F. Epigenetic modifications due to heavy metals exposure in children living in polluted areas. Curr Genomics. 2014;15(6):464–8.
•• Reese SE, Zhao S, Wu MC, Joubert BR, Parr CL, Håberg SE, et al. DNA methylation score as a biomarker in newborns for sustained maternal smoking during pregnancy. Environ Health Perspect. 2017;125(4):760–6. This manuscript describes of the smoking biomarker during pregnancy.
Joubert BR, Haberg SE, Nilsen RM, et al. 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environ Health Perspect. 2012;120(10):1425–31.
Baccarelli A, Wright RO, Bollati V, Tarantini L, Litonjua AA, Suh HH, et al. Rapid DNA methylation changes after exposure to traffic particles. Am J Respir Crit Care Med. 2009;179(7):572–8.
Ladd-Acosta C. Epigenetic signatures as biomarkers of exposure. Cur Environ Health Rep. 2015;2(2):117–25.
Ladd-Acosta C, Fallin MD. DNA methylation signatures as biomarkers of prior environmental exposures. Cur Epidemiol Rep. 2019;6(1):1–13.
Richmond RC, Suderman M, Langdon R, et al. DNA methylation as a marker for prenatal smoke exposure in adults. Int J Epidemiol. 2018;47(4):1120–30.
Cardenas A, Rifas-Shiman SL, Agha G, Hivert MF, Litonjua AA, DeMeo D, et al. Persistent DNA methylation changes associated with prenatal mercury exposure and cognitive performance during childhood. Sci Rep. 2017;7(1):288.
•• Bollepalli S, Korhonen T, Kaprio J, Anders S, Ollikainen M. EpiSmokEr: a robust classifier to determine smoking status from DNA methylation data. Epigenomics. 2019;11(13):1469–86. This manuscript describes of the smoking biomarker.
Zeilinger S, Kuhnel B, Klopp N, et al. Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS One. 2013;8(5):e63812.
McCartney DL, Stevenson AJ, Hillary RF, Walker RM, Bermingham ML, Morris SW, et al. Epigenetic signatures of starting and stopping smoking. EBioMedicine. 2018;37:214–20.
Joehanes R, Just AC, Marioni RE, Pilling LC, Reynolds LM, Mandaviya PR, et al. Epigenetic signatures of cigarette smoking. Circ Cardiovasc Genet. 2016;9(5):436–47.
Rakyan VK, Down TA, Balding DJ, Beck S. Epigenome-wide association studies for common human diseases. Nat Rev Genet. 2011;12(8):529–41.
Feinberg AP. Epigenomics reveals a functional genome anatomy and a new approach to common disease. Nat Biotechnol. 2010;28(10):1049–52.
Portela A, Esteller M. Epigenetic modifications and human disease. Nat Biotechnol. 2010;28(10):1057–68.
Zou H, Hastie T. Regularization and variable selection via the elastic net. J Royal Statis Soc Ser B. 2005;67(2):301–20.
Tibshirani R. Regression shrinkage and selection via the Lasso. J R Stat Soc Ser B Methodol. 1996;58(1):267–88.
•• Colicino E, Just A, Kioumourtzoglou MA, et al. Blood DNA methylation biomarkers of cumulative lead exposure in adults. J Exposure Sci Environ Epidemiol. 2019. This manuscript describes of the lead exposure biomarkers.
•• Markunas CA, Hancock DB, Xu Z, et al. Epigenome-wide analysis uncovers a blood-based DNA methylation biomarker of lifetime cannabis use. bioRxiv. 2019:620641. This manuscript describes of the cannabis biomarker.
Gao X, Zhang Y, Breitling LP, Brenner H. Relationship of tobacco smoking and smoking-related DNA methylation with epigenetic age acceleration. Oncotarget. 2016;7(30):46878–89.
Nwanaji-Enwerem JC, Cardenas A, Chai PR, et al. Relationships of long-term smoking and moist snuff consumption with a DNA methylation age relevant smoking index: an analysis in buccal cells. Nicotine Tob Res. 2018;21(9):1267–73.
• Philibert R, Dogan M, Beach SRH, et al. AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA. Am J Med Genetic B Neuropsychiatr Genet. 2020;183(1):51–60. This manuscript describes the role of a few CpGs in the prediction of smoking status.
Gao X, Jia M, Zhang Y, et al. DNA methylation changes of whole blood cells in response to active smoking exposure in adults: a systematic review of DNA methylation studies. Clin Epigenetics. 2015;7:113.
Volkow ND, Baler RD, Compton WM, Weiss SR. Adverse health effects of marijuana use. N Engl J Med. 2014;370(23):2219–27.
Lafaye G, Karila L, Blecha L, Benyamina A. Cannabis, cannabinoids, and health. Dialogues Clin Neurosci. 2017;19(3):309–16.
Andersen AM, Dogan MV, Beach SRH, Philibert RA. Current and future prospects for epigenetic biomarkers of substance use disorders. Genes (Basel). 2015;6(4):991–1022.
Huestis MA. Human cannabinoid pharmacokinetics. Chem Biodivers. 2007;4(8):1770–804.
Steyerberg EW, Harrell FE Jr. Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016;69:245–7.
Limosin F. Epidemiologic warnings from studies on alcohol use disorders. L'Encephale. 2014;40(2):129–35.
Allen JP. Use of biomarkers of heavy drinking in health care practice. Mil Med. 2003;168(5):364–7.
•• Liu C, Marioni RE, Hedman AK, Pfeiffer L, Tsai PC, Reynolds LM, et al. A DNA methylation biomarker of alcohol consumption. Mol Psychiatry. 2018;23(2):422–33. This manuscript describes of the alcohol consumption biomarkers.
Jin Z, Mendu SK, Birnir B. GABA is an effective immunomodulatory molecule. Amino Acids. 2013;45(1):87–94.
Bakulski KM, Rozek LS, Dolinoy DC, Paulson HL, Hu H. Alzheimer’s disease and environmental exposure to lead: the epidemiologic evidence and potential role of epigenetics. Curr Alzheimer Res. 2012;9(5):563–73.
Holland MG, Cawthon D. Levels ATFoBL. workplace lead exposure. J Occup Environ Med. 2016;58(12):e371–e4.
Weisskopf MG, Proctor SP, Wright RO, et al. Cumulative lead exposure and cognitive performance among elderly men. Epidemiol. 2007;18(1):59–66.
Hu H, Shih R, Rothenberg S, Schwartz BS. The epidemiology of lead toxicity in adults: measuring dose and consideration of other methodologic issues. Environ Health Perspect. 2007;115(3):455–62.
Navas-Acien A, Schwartz BS, Rothenberg SJ, et al. Bone lead levels and blood pressure endpoints: a meta-analysis. Epidemiol. 2008;19(3):496–504.
Hu H, Rabinowitz M, Smith D. Bone lead as a biological marker in epidemiologic studies of chronic toxicity: conceptual paradigms. Environ Health Perspect. 1998;106(1):1–8.
Wilker E, Korrick S, Nie LH, Sparrow D, Vokonas P, Coull B, et al. Longitudinal changes in bone lead levels: the VA normative aging study. J Occup Environ Med. 2011;53(8):850–5.
Handy DE, Castro R, Loscalzo J. Epigenetic modifications: basic mechanisms and role in cardiovascular disease. Circulation. 2011;123(19):2145–56.
Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, et al. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging. 2016;8(9):1844–65.
• Valeri L, Reese SL, Zhao S, Page CM, Nystad W, Coull BA, et al. Misclassified exposure in epigenetic mediation analyses. Does DNA methylation mediate effects of smoking on birthweight? Epigenomics. 2017;9(3):253–65. This manuscript identifies the critical role of misclassified exposure in epidemiology.
Funding
EC was supported by the National Institute on Minority Health and Health Disparities (NIMHD) (R01MD013310) and by the National Institute of Environmental Health Sciences (NIEHS) (P30ES023515, U2CES026444, and UH3OD023337). JCN was supported by a NIH/NIA Ruth L. Kirschstein National Research Service Award (1 F31AG056124-01A1).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This article is part of the Topical Collection on Environmental Epigenetics
Rights and permissions
About this article
Cite this article
Nwanaji-Enwerem, J.C., Colicino, E. DNA Methylation–Based Biomarkers of Environmental Exposures for Human Population Studies. Curr Envir Health Rpt 7, 121–128 (2020). https://doi.org/10.1007/s40572-020-00269-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40572-020-00269-2