Multi-generational impacts of arsenic exposure on genome-wide DNA methylation and the implications for arsenic-induced skin lesions

Abstract

As a nonmutagenic human carcinogen, arsenic (As)'s carcinogenic activity is likely the result of epigenetic changes, particularly alterations in DNA methylation. While increasing studies indicate a potentially important role for timing of As exposure on DNA methylation patterns and the subsequent differential risks for As toxicity and carcinogenesis, there is a lack of research that tackles these critical questions, particularly in human based populations. Here we reported a family-based study including three generations, in which each generation living in the same household had a distinctive timing of As exposure: in adulthood, in utero and during early childhood, and in germlines exposure for grandparents, parents, and grandchildren, respectively. We generated genome-wide DNA methylation data for 18 As-exposed families, nine control families, as well as 18 arsenical skin lesion patients. Our analysis showed that As exposure may leave detectable DNA methylation changes even though exposure occurred decades ago, and the most significant changes of global DNA methylation were observed among patients afflicted with arsenical skin lesions. As exposure across generations shared common differentially methylated DNA loci and regions (744 DML and 15 DMRs) despite the distinctive exposure timing in each generation. Importantly, based on these DML, clustering analysis grouped skin lesion patients together with grandparents in exposed families in the same cluster, separated from grandparents in control families. Further analysis identified a number of DML and several molecular pathways that were significantly distinguished between controls, exposed populations, as well as skin lesion patients. Finally, our exploratory analysis suggested that some of these DML altered by As exposure, may have the potential to be inherited affecting not only those directly exposed but also later generations. Together, our results suggest that common DML and/or DMRs associated with an increased risk for disease development could be identified regardless of when exposure to As occurred during their life span, and thus may be able to serve as biomarkers for identifying individuals at risk for As-induced skin lesions and possible cancers.

Locus-Specific Differential DNA Methylation and Urinary Arsenic: An Epigenome-Wide Association Study in Blood among Adults with Low-to-Moderate Arsenic Exposure

“…2019 ). In addition, cg15019001 ( HLA-DPB2 ), cg22809683 ( LAMC1 ), cg07466788 ( SLC16A3 ), cg19504605 ( ZFP41 ), cg22143856 ( ZNF389 ), cg13251666, and cg13844779, identified as differentially methylated between As-exposed and control families in China ( ) ( Guo et al. 2018 ), were nominally significant in our analyses.…”

“…Studies of adult populations have included cohorts in Bangladesh, identifying 4 CpGs associated with As measured in urine or blood at p Bonferroni < 0:05 (n = 400; 3 CpGs overlapped for both exposure measures) (Argos et al 2015) and 50 CpGs associated with As measured in urine or drinking water at FDR < 0:05 (n = 396; 8 CpGs overlapped for both exposure measures) (Demanelis et al 2019). In addition, in a study of women in Argentina (n = 93), differential methylation was found at 6 loci (Ameer et al 2017), and in a study of families in China (adults and children; n = 102), differential methylation was found at 85 loci (Guo et al 2018). To understand the overlap between loci previously identified as differentially methylated with As exposure, we used a lookup approach of studies analyzing the association between As exposure and DNA methylation measured using the 450K or 850K microarrays.…”

“…These CpGs included cg06121226 (located in SLC4A4), identified as significantly associated with total blood and urinary As levels among adults in Bangladesh (n = 400) (Argos et al 2015), and cg05428706, cg19534475 (ATP1B3), and cg06466147 (GBAP1) identified as significantly associated with urinary or water As levels among a separate cohort of adults in Bangladesh (n = 396); cg14718533 was found to be significantly associated with urinary As levels in a meta-analysis, including both Bangladeshi cohorts (Demanelis et al 2019). In addition, cg15019001 (HLA-DPB2), cg22809683 (LAMC1), cg07466788 (SLC16A3), cg19504605 (ZFP41), cg22143856 (ZNF389), cg13251666, and cg13844779, identified as differentially methylated between As-exposed and control families in China (n = 102) (Guo et al 2018), were nominally significant in our analyses. Among 4,427 CpGs previously associated with in utero As exposure (Cardenas et al 2015;Gliga et al 2018;Green et al 2016;Kaushal et al 2017;Kile et al 2014;Rojas et al 2015) 179 were nominally significant in the current study.…”

“…Inconsistent results among epidemiological studies of the association between As exposure and epigenetic dysregulation may be due to differences between populations studied (e.g., age, sex, genetic structure), levels of As exposure, differential residual confounding, and methods for quantifying DNA methylation (Argos 2015). Previous EWAS of As exposure have included birth cohorts in the United States (Green et al 2016;Koestler et al 2013), Bangladesh (Broberg et al 2014;Cardenas et al 2015;Gliga et al 2018;Kile et al 2012), Mexico (Rojas et al 2015), and Taiwan (Kaushal et al 2017), and studies of adults in the United States , Bangladesh (Argos et al 2015;Demanelis et al 2019), Argentina (Ameer et al 2017), and China (Guo et al 2018). In addition, the samples sizes of previous EWAS have ranged from <50-400, resulting in limited statistical, particularly when interrogating a large number of CpG sites (Argos 2015).…”

Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing

“…Illumina's Infinium Human Methylation 450K BeadChip and EPIC BeadChip, which cover more than 450,000 and 850,000 CpG methylation sites respectively, are two predominant products in the market. The availability of these high-density methylation arrays has fueled epigenome-wide association studies (EWAS), which seek to identify methylation variants associated with an outcome or exposure of interest [18][19][20][21][22][23]. Analysis of EWAS data typically involves testing all the CpG sites simultaneously, leading to a massive multiple testing problem.…”