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Arsenic exposure from drinking water is associated with decreased gene expression and increased DNA methylation in peripheral blood

Ameer, Syeda Shegufta LU ; Engström, Karin LU ; Hossain, Bakhtiar LU ; Concha, Gabriela; Vahter, Marie and Broberg, Karin LU (2017) In Toxicology and Applied Pharmacology 321. p.57-66
Abstract

Background Exposure to inorganic arsenic increases the risk of cancer and non-malignant diseases. Inefficient arsenic metabolism is a marker for susceptibility to arsenic toxicity. Arsenic may alter gene expression, possibly by altering DNA methylation. Objectives To elucidate the associations between arsenic exposure, gene expression, and DNA methylation in peripheral blood, and the modifying effects of arsenic metabolism. Methods The study participants, women from the Andes, Argentina, were exposed to arsenic via drinking water. Arsenic exposure was assessed as the sum of arsenic metabolites in urine (U-As), using high performance liquid-chromatography hydride-generation inductively-coupled-plasma-mass-spectrometry, and arsenic... (More)

Background Exposure to inorganic arsenic increases the risk of cancer and non-malignant diseases. Inefficient arsenic metabolism is a marker for susceptibility to arsenic toxicity. Arsenic may alter gene expression, possibly by altering DNA methylation. Objectives To elucidate the associations between arsenic exposure, gene expression, and DNA methylation in peripheral blood, and the modifying effects of arsenic metabolism. Methods The study participants, women from the Andes, Argentina, were exposed to arsenic via drinking water. Arsenic exposure was assessed as the sum of arsenic metabolites in urine (U-As), using high performance liquid-chromatography hydride-generation inductively-coupled-plasma-mass-spectrometry, and arsenic metabolism efficiency was assessed by the urinary fractions (%) of the individual metabolites. Genome-wide gene expression (N = 80 women) and DNA methylation (N = 93; 80 overlapping with gene expression) in peripheral blood were measured using Illumina DirectHyb HumanHT-12 v4.0 and Infinium Human-Methylation 450K BeadChip, respectively. Results U-As concentrations, ranging 10–1251 μg/L, was associated with decreased gene expression: 64% of the top 1000 differentially expressed genes were down-regulated with increasing U-As. U-As was also associated with hypermethylation: 87% of the top 1000 CpGs were hypermethylated with increasing U-As. The expression of six genes and six individual CpG sites were significantly associated with increased U-As concentration. Pathway analyses revealed enrichment of genes related to cell death and cancer. The pathways differed somewhat depending on arsenic metabolism efficiency. We found no overlap between arsenic-related gene expression and DNA methylation for individual genes. Conclusions Increased arsenic exposure was associated with lower gene expression and hypermethylation in peripheral blood, but with no evident overlap.

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Contribution to journal
publication status
published
subject
keywords
Arsenic metabolism efficiency, Cancer, Epigenetic, Genome-wide, Pathway analyses
in
Toxicology and Applied Pharmacology
volume
321
pages
10 pages
publisher
Academic Press
external identifiers
  • scopus:85014437630
  • wos:000397351900006
ISSN
0041-008X
DOI
10.1016/j.taap.2017.02.019
language
English
LU publication?
yes
id
f4236cad-dcc6-4f93-80e1-c4fe777c4513
date added to LUP
2017-03-14 11:05:29
date last changed
2018-01-07 11:55:07
@article{f4236cad-dcc6-4f93-80e1-c4fe777c4513,
  abstract     = {<p>Background Exposure to inorganic arsenic increases the risk of cancer and non-malignant diseases. Inefficient arsenic metabolism is a marker for susceptibility to arsenic toxicity. Arsenic may alter gene expression, possibly by altering DNA methylation. Objectives To elucidate the associations between arsenic exposure, gene expression, and DNA methylation in peripheral blood, and the modifying effects of arsenic metabolism. Methods The study participants, women from the Andes, Argentina, were exposed to arsenic via drinking water. Arsenic exposure was assessed as the sum of arsenic metabolites in urine (U-As), using high performance liquid-chromatography hydride-generation inductively-coupled-plasma-mass-spectrometry, and arsenic metabolism efficiency was assessed by the urinary fractions (%) of the individual metabolites. Genome-wide gene expression (N = 80 women) and DNA methylation (N = 93; 80 overlapping with gene expression) in peripheral blood were measured using Illumina DirectHyb HumanHT-12 v4.0 and Infinium Human-Methylation 450K BeadChip, respectively. Results U-As concentrations, ranging 10–1251 μg/L, was associated with decreased gene expression: 64% of the top 1000 differentially expressed genes were down-regulated with increasing U-As. U-As was also associated with hypermethylation: 87% of the top 1000 CpGs were hypermethylated with increasing U-As. The expression of six genes and six individual CpG sites were significantly associated with increased U-As concentration. Pathway analyses revealed enrichment of genes related to cell death and cancer. The pathways differed somewhat depending on arsenic metabolism efficiency. We found no overlap between arsenic-related gene expression and DNA methylation for individual genes. Conclusions Increased arsenic exposure was associated with lower gene expression and hypermethylation in peripheral blood, but with no evident overlap.</p>},
  author       = {Ameer, Syeda Shegufta and Engström, Karin and Hossain, Bakhtiar and Concha, Gabriela and Vahter, Marie and Broberg, Karin},
  issn         = {0041-008X},
  keyword      = {Arsenic metabolism efficiency,Cancer,Epigenetic,Genome-wide,Pathway analyses},
  language     = {eng},
  month        = {04},
  pages        = {57--66},
  publisher    = {Academic Press},
  series       = {Toxicology and Applied Pharmacology},
  title        = {Arsenic exposure from drinking water is associated with decreased gene expression and increased DNA methylation in peripheral blood},
  url          = {http://dx.doi.org/10.1016/j.taap.2017.02.019},
  volume       = {321},
  year         = {2017},
}