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Sex differences in disease risk from reported genome-wide association study findings.

ABSTRACT: Men and women differ in susceptibility to many diseases and in responses to treatment. Recent advances in genome-wide association studies (GWAS) provide a wealth of data for associating genetic profiles with disease risk; however, in general, these data have not been systematically probed for sex differences in gene-disease associations. Incorporating sex into the analysis of GWAS results can elucidate new relationships between single nucleotide polymorphisms (SNPs) and human disease. In this study, we performed a sex-differentiated analysis on significant SNPs from GWAS data of the seven common diseases studied by the Wellcome Trust Case Control Consortium. We employed and compared three methods: logistic regression, Woolf's test of heterogeneity, and a novel statistical metric that we developed called permutation method to assess sex effects (PMASE). After correction for false discovery, PMASE finds SNPs that are significantly associated with disease in only one sex. These sexually dimorphic SNP-disease associations occur in Coronary Artery Disease and Crohn's Disease. GWAS analyses that fail to consider sex-specific effects may miss discovering sexual dimorphism in SNP-disease associations that give new insights into differences in disease mechanism between men and women.

SUBMITTER: Liu LY

PROVIDER: S-EPMC3260375 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Sex differences in disease risk from reported genome-wide association study findings.

Liu Linda Y LY Schaub Marc A MA Sirota Marina M Butte Atul J AJ

Human genetics 20110820 3

Men and women differ in susceptibility to many diseases and in responses to treatment. Recent advances in genome-wide association studies (GWAS) provide a wealth of data for associating genetic profiles with disease risk; however, in general, these data have not been systematically probed for sex differences in gene-disease associations. Incorporating sex into the analysis of GWAS results can elucidate new relationships between single nucleotide polymorphisms (SNPs) and human disease. In this st ...[more]

PMID: 21858542

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Project description:Childhood acute lymphoblastic leukemia (ALL) occurs more frequently in males. Reasons behind sex differences in childhood ALL risk are unknown. In the present genome-wide association study (GWAS), we explored the genetic basis of sex differences by comparing genotype frequencies between male and female cases in a case-only study to assess effect-modification by sex.The case-only design included 236 incident cases of childhood ALL consecutively recruited at the Texas Children's Cancer Center in Houston, Texas from 2007 to 2012. All cases were non-Hispanic whites, aged 1 to 10 years, and diagnosed with confirmed B-cell precursor ALL. Genotyping was performed using the Illumina HumanCoreExome BeadChip on the Illumina Infinium platform. Besides the top 100 statistically most significant results, results were also analyzed by the top 100 highest effect size with a nominal statistical significance (P?<0.05).The statistically most significant sex-specific association (P?=?4 × 10) was with the single nucleotide polymorphism (SNP) rs4813720 (RASSF2), an expression quantitative trait locus (eQTL) for RASSF2 in peripheral blood. rs4813720 is also a strong methylation QTL (meQTL) for a CpG site (cg22485289) within RASSF2 in pregnancy, at birth, childhood, and adolescence. cg22485289 is one of the hypomethylated CpG sites in ALL compared with pre-B cells. Two missense SNPs, rs12722042 and 12722039, in the HLA-DQA1 gene yielded the highest effect sizes (odds ratio [OR] ? 14; P?<0.01) for sex-specific results. The HLA-DQA1 SNPs belong to DQA1*01 and confirmed the previously reported male-specific association with DQA1*01. This finding supports the proposed infection-related etiology in childhood ALL risk for males. Further analyses revealed that most SNPs (either direct effect or through linkage disequilibrium) were within active enhancers or active promoter regions and had regulatory effects on gene expression levels.Cumulative data suggested that RASSF2 rs4813720, which correlates with increased RASSF2 expression, may counteract the suppressor effect of estrogen-regulated miR-17-92 on RASSF2 resulting in protection in males. Given the amount of sex hormone-related mechanisms suggested by our findings, future studies should examine prenatal or early postnatal programming by sex hormones when hormone levels show a large variation.

Project description:Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

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Sex differences in disease risk from reported genome-wide association study findings.

Publications

Sex differences in disease risk from reported genome-wide association study findings.

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