Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWAS). Standard GWAS are well-powered to interrogate additive models;… Click to show full abstract
Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWAS). Standard GWAS are well-powered to interrogate additive models; however, new approaches are required to investigate other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected due to lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWAS excludes detection of sites in LD that may underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta D statistics) in long-range LD (> 0.25cM). We identified five significant associations across five disease phenotypes that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were 1) members of highly conserved gene families with complex roles in multiple pathways, 2) essential genes, and/or 3) associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and may especially be driving factors in conditions with a wide range of phenotypic outcomes.
               
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