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Exposure to arsenic at different life-stages and DNA methylation meta-analysis in buccal cells and leukocytes

Authors
  • Bozack, Anne K.1
  • Boileau, Philippe2
  • Wei, Linqing2
  • Hubbard, Alan E.2
  • Sillé, Fenna C. M.3
  • Ferreccio, Catterina4
  • Acevedo, Johanna4, 5
  • Hou, Lifang6
  • Ilievski, Vesna7
  • Steinmaus, Craig M.1
  • Smith, Martyn T.1
  • Navas-Acien, Ana7
  • Gamble, Mary V.7
  • Cardenas, Andres1
  • 1 School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, Berkeley, CA, 94720, USA , Berkeley (United States)
  • 2 University of California, Berkeley, Berkeley, CA, USA , Berkeley (United States)
  • 3 The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA , Baltimore (United States)
  • 4 School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile , Santiago (Chile)
  • 5 Health Planning Division in the Ministry of Health, Santiago, Chile , Santiago (Chile)
  • 6 Feinberg School of Medicine, Northwestern University, Chicago, IL, USA , Chicago (United States)
  • 7 Mailman School of Public Health, Columbia University, New York City, NY, USA , New York City (United States)
Type
Published Article
Journal
Environmental Health
Publisher
BioMed Central
Publication Date
Jul 09, 2021
Volume
20
Issue
1
Identifiers
DOI: 10.1186/s12940-021-00754-7
Source
Springer Nature
Keywords
Disciplines
  • Research
License
Green

Abstract

BackgroundArsenic (As) exposure through drinking water is a global public health concern. Epigenetic dysregulation including changes in DNA methylation (DNAm), may be involved in arsenic toxicity. Epigenome-wide association studies (EWAS) of arsenic exposure have been restricted to single populations and comparison across EWAS has been limited by methodological differences. Leveraging data from epidemiological studies conducted in Chile and Bangladesh, we use a harmonized data processing and analysis pipeline and meta-analysis to combine results from four EWAS.MethodsDNAm was measured among adults in Chile with and without prenatal and early-life As exposure in PBMCs and buccal cells (N = 40, 850K array) and among men in Bangladesh with high and low As exposure in PBMCs (N = 32, 850K array; N = 48, 450K array). Linear models were used to identify differentially methylated positions (DMPs) and differentially variable positions (DVPs) adjusting for age, smoking, cell type, and sex in the Chile cohort. Probes common across EWAS were meta-analyzed using METAL, and differentially methylated and variable regions (DMRs and DVRs, respectively) were identified using comb-p. KEGG pathway analysis was used to understand biological functions of DMPs and DVPs.ResultsIn a meta-analysis restricted to PBMCs, we identified one DMP and 23 DVPs associated with arsenic exposure; including buccal cells, we identified 3 DMPs and 19 DVPs (FDR < 0.05). Using meta-analyzed results, we identified 11 DMRs and 11 DVRs in PBMC samples, and 16 DMRs and 19 DVRs in PBMC and buccal cell samples. One region annotated to LRRC27 was identified as a DMR and DVR. Arsenic-associated KEGG pathways included lysosome, autophagy, and mTOR signaling, AMPK signaling, and one carbon pool by folate.ConclusionsUsing a two-step process of (1) harmonized data processing and analysis and (2) meta-analysis, we leverage four DNAm datasets from two continents of individuals exposed to high levels of As prenatally and during adulthood to identify DMPs and DVPs associated with arsenic exposure. Our approach suggests that standardizing analytical pipelines can aid in identifying biological meaningful signals.

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