Integrating SNPs-based genetic risk factor with blood epigenomic response of differentially arsenic-exposed rural subjects reveals disease-associated signaling pathways
Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systema...
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| Published in | Environmental pollution (1987) Vol. 292; no. Pt A; p. 118279 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0269-7491 1873-6424 1873-6424 |
| DOI | 10.1016/j.envpol.2021.118279 |
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| Abstract | Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals.
•Analysis of global blood methylome changes associated with As exposure via drinking water.•Integrating As-related SNPs with epigenome data yielded refined methylome profiles.•Novel As-related signaling and disease pathways found associated with As exposure.•Evidence of As-induced interplay between DNA methylation and gene expression. |
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| AbstractList | Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals. Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals. •Analysis of global blood methylome changes associated with As exposure via drinking water.•Integrating As-related SNPs with epigenome data yielded refined methylome profiles.•Novel As-related signaling and disease pathways found associated with As exposure.•Evidence of As-induced interplay between DNA methylation and gene expression. Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals.Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals. |
| ArticleNumber | 118279 |
| Author | Rehman, Muhammad Yasir Abdur Briedé, Jacco Jan van Herwijnen, Marcel Krauskopf, Julian Malik, Riffat Naseem Kleinjans, Jos C.S. Jennen, Danyel G.J. |
| Author_xml | – sequence: 1 givenname: Muhammad Yasir Abdur orcidid: 0000-0001-6635-9970 surname: Rehman fullname: Rehman, Muhammad Yasir Abdur organization: Environmental Health Laboratory, Department of Environmental Sciences, Quaid-i-Azam University, Islamabad, Pakistan – sequence: 2 givenname: Jacco Jan surname: Briedé fullname: Briedé, Jacco Jan email: J.Briede@maastrichtuniversity.nl organization: Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, the Netherlands – sequence: 3 givenname: Marcel surname: van Herwijnen fullname: van Herwijnen, Marcel organization: Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, the Netherlands – sequence: 4 givenname: Julian surname: Krauskopf fullname: Krauskopf, Julian organization: Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, the Netherlands – sequence: 5 givenname: Danyel G.J. surname: Jennen fullname: Jennen, Danyel G.J. organization: Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, the Netherlands – sequence: 6 givenname: Riffat Naseem orcidid: 0000-0003-4345-6000 surname: Malik fullname: Malik, Riffat Naseem organization: Environmental Health Laboratory, Department of Environmental Sciences, Quaid-i-Azam University, Islamabad, Pakistan – sequence: 7 givenname: Jos C.S. surname: Kleinjans fullname: Kleinjans, Jos C.S. organization: Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, the Netherlands |
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| CitedBy_id | crossref_primary_10_1007_s10653_021_01141_4 crossref_primary_10_3390_min12101326 crossref_primary_10_18311_ti_2023_v30i2_32429 crossref_primary_10_3390_antiox11040689 crossref_primary_10_1016_j_envres_2023_116600 crossref_primary_10_1039_D4RA08867K crossref_primary_10_3390_nu14102136 crossref_primary_10_3390_ijms24119618 |
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| Keywords | DNMTs Drinking water Arsenic EWAS IARC SMG LMM PBMC DCM As CTD Pakistan CHIP DDR HCM Pathways SEG SNP Risk factor SNPs SMR Epigenome WHO MeDIP |
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35 Kile (10.1016/j.envpol.2021.118279_bib75) 2008; 66 Pilsner (10.1016/j.envpol.2021.118279_bib106) 2012; 7 Acharyya (10.1016/j.envpol.2021.118279_bib1) 2010; 5 DiGiovanni (10.1016/j.envpol.2021.118279_bib30) 2020; 4 Jansen (10.1016/j.envpol.2021.118279_bib70) 2019; 20 Capote (10.1016/j.envpol.2021.118279_bib20) 2015; 763 Dorn (10.1016/j.envpol.2021.118279_bib32) 2009; 87 Reichard (10.1016/j.envpol.2021.118279_bib111) 2010; 2 Grounds (10.1016/j.envpol.2021.118279_bib52) 2020; 13 Mosharov (10.1016/j.envpol.2021.118279_bib93) 2000; 39 Naujokas (10.1016/j.envpol.2021.118279_bib95) 2013; 121 Agusa (10.1016/j.envpol.2021.118279_bib2) 2009; 236 Moon (10.1016/j.envpol.2021.118279_bib92) 2012; 14 Maréchal (10.1016/j.envpol.2021.118279_bib87) 2013; 5 Bozack (10.1016/j.envpol.2021.118279_bib17) 2020; 128 Jirtle (10.1016/j.envpol.2021.118279_bib72) 2007; 8 Rojas (10.1016/j.envpol.2021.118279_bib116) 2014; 143 |
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| SubjectTerms | alleles Arsenic blood chromatin DNA methylation Drinking water epigenetics Epigenome gene expression genotyping groundwater contamination metabolism methionine muscle contraction Pakistan Pathways Risk factor risk factors SNPs toxicity transcriptome |
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| Title | Integrating SNPs-based genetic risk factor with blood epigenomic response of differentially arsenic-exposed rural subjects reveals disease-associated signaling pathways |
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