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Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

ABSTRACT: SNPs associated with disease susceptibility often reside in enhancer clusters, or super-enhancers. Constituents of these enhancer clusters cooperate to regulate target genes and often extend beyond the linkage disequilibrium (LD) blocks containing risk SNPs identified in genome-wide association studies (GWAS). We identified 'outside variants', defined as SNPs in weak LD with GWAS risk SNPs that physically interact with risk SNPs as part of a target gene's regulatory circuitry. These outside variants further explain variation in target gene expression beyond that explained by GWAS-associated SNPs. Additionally, the clinical risk associated with GWAS SNPs is considerably modified by the genotype of outside variants. Collectively, these findings suggest a potential model in which outside variants and GWAS SNPs that physically interact in 3D chromatin collude to influence target transcript levels as well as clinical risk. This model offers an additional hypothesis for the source of missing heritability for complex traits.

SUBMITTER: Corradin O

PROVIDER: S-EPMC5083135 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

Corradin Olivia O Cohen Andrea J AJ Luppino Jennifer M JM Bayles Ian M IM Schumacher Fredrick R FR Scacheri Peter C PC

Nature genetics 20160919 11

SNPs associated with disease susceptibility often reside in enhancer clusters, or super-enhancers. Constituents of these enhancer clusters cooperate to regulate target genes and often extend beyond the linkage disequilibrium (LD) blocks containing risk SNPs identified in genome-wide association studies (GWAS). We identified 'outside variants', defined as SNPs in weak LD with GWAS risk SNPs that physically interact with risk SNPs as part of a target gene's regulatory circuitry. These outside vari ...[more]

PMID: 27643537

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Project description:BACKGROUND:Genome-wide association studies have identified many susceptibility loci for obesity. However, missing heritability problem is still challenging and ignorance of genetic interactions is believed to be an important cause. Current methods for detecting interactions usually do not consider regulatory elements in non-coding regions. Interaction analyses within chromatin regulatory circuitry may identify new susceptibility loci. METHODS:We developed a pipeline named interaction analyses within chromatin regulatory circuitry (IACRC), to identify genetic interactions impacting body mass index (BMI). Potential interacting SNP pairs were obtained based on Hi-C datasets, PreSTIGE (Predicting Specific Tissue Interactions of Genes and Enhancers) algorithm, and super enhancer regions. SNP?×?SNP analyses were next performed in three GWAS datasets, including 2286 unrelated Caucasians from Kansas City, 3062 healthy Caucasians from the Gene Environment Association Studies initiative, and 3164 Hispanic subjects from the Women's Health Initiative. RESULTS:A total of 16,643,227 SNP?×?SNP analyses were performed. Meta-analyses showed that two SNP pairs, rs6808450-rs9813534 (combined P?=?2.39?×?10-9) and rs6808450-rs3773306 (combined P?=?2.89?×?10-9) were associated with BMI after multiple testing corrections. Single-SNP analyses did not detect significant association signals for these three SNPs. In obesity relevant cells, rs6808450 is located in intergenic enhancers, while rs9813534 and rs3773306 are located in the region of strong transcription regions of CAND2 and RPL32, respectively. The expression of CAND2 was significantly downregulated after the differentiation of human Simpson-Golabi-Behmel syndrome (SGBS) preadipocyte cells (P?=?0.0241). Functional validation in the International Mouse Phenotyping Consortium database showed that CAND2 was associated with increased lean body mass and decreased total body fat amount. CONCLUSIONS:Detecting epistasis within chromatin regulatory circuitry identified CAND2 as a novel obesity susceptibility gene. We hope IACRC could facilitate the interaction analyses for complex diseases and offer new insights into solving the missing heritability problem.

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Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

Publications

Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

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