Dataset Information

Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.

ABSTRACT: Traditional methods for chemical risk assessment are too time-consuming and resource-intensive to characterize either the diversity of chemicals to which humans are exposed or how that diversity may manifest in population susceptibility differences. The advent of novel toxicological data sources and their integration with bioinformatic databases affords opportunities for modern approaches that consider gene-environment (GxE) interactions in population risk assessment. Here, we present an approach that systematically links multiple data sources to relate chemical risk values to diseases and gene-disease variants. These data sources include high-throughput screening (HTS) results from Tox21/ToxCast, chemical-disease relationships from the Comparative Toxicogenomics Database (CTD), hazard data from resources like the Integrated Risk Information System, exposure data from the ExpoCast initiative, and gene-variant-disease information from the DisGeNET database. We use these integrated data to identify variants implicated in chemical-disease enrichments and develop a new value that estimates the risk of these associations toward differential population responses. Finally, we use this value to prioritize chemical-disease associations by exploring the genomic distribution of variants implicated in high-risk diseases. We offer this modular approach, termed DisQGOS (Disease Quotient Genetic Overview Score), for relating overall chemical-disease risk to potential for population variable responses, as a complement to methods aiming to modernize aspects of risk assessment.

SUBMITTER: Kosnik MB

PROVIDER: S-EPMC6708494 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.

Kosnik Marissa B MB Reif David M DM

Toxicology and applied pharmacology 20190716

Traditional methods for chemical risk assessment are too time-consuming and resource-intensive to characterize either the diversity of chemicals to which humans are exposed or how that diversity may manifest in population susceptibility differences. The advent of novel toxicological data sources and their integration with bioinformatic databases affords opportunities for modern approaches that consider gene-environment (GxE) interactions in population risk assessment. Here, we present an approac ...[more]

PMID: 31323264

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Project description:BACKGROUND & AIMS:Genome-wide association studies (GWAS) have identified more than 20 susceptibility loci for esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). However, variants in these loci account for a small fraction of cases of EA and BE. Genetic factors might interact with environmental factors to affect risk of EA and BE. We aimed to identify single nucleotide polymorphisms (SNPs) that may modify the associations of body mass index (BMI), smoking, and gastroesophageal reflux disease (GERD), with risks of EA and BE. METHODS:We collected data on single BMI measurements, smoking status, and symptoms of GERD from 2284 patients with EA, 3104 patients with BE, and 2182 healthy individuals (controls) participating in the Barrett's and Esophageal Adenocarcinoma Consortium GWAS, the UK Barrett's Esophagus Gene Study, and the UK Stomach and Oesophageal Cancer Study. We analyzed 993,501 SNPs in DNA samples of all study subjects. We used standard case-control logistic regression to test for gene-environment interactions. RESULTS:For EA, rs13429103 at chromosome 2p25.1, near the RNF144A-LOC339788 gene, showed a borderline significant interaction with smoking status (P = 2.18×10-7). Ever smoking was associated with an almost 12-fold increase in risk of EA among individuals with rs13429103-AA genotype (odds ratio=11.82; 95% CI, 4.03-34.67). Three SNPs (rs12465911, rs2341926, rs13396805) at chromosome 2q23.3, near the RND3-RBM43 gene, interacted with GERD symptoms (P = 1.70×10-7, P = 1.83×10-7, and P = 3.58×10-7, respectively) to affect risk of EA. For BE, rs491603 at chromosome 1p34.3, near the EIF2C3 gene, and rs11631094 at chromosome 15q14, at the SLC12A6 gene, interacted with BMI (P = 4.44×10-7) and pack-years of smoking history (P = 2.82×10-7), respectively. CONCLUSION:The associations of BMI, smoking, and GERD symptoms with risks of EA and BE appear to vary with SNPs at chromosomes 1, 2, and 15. Validation of these suggestive interactions is warranted.

Dataset Information

Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.

Publications

Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.

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