Analysis of polygenic disease risk and etiology by indexing ancestry- and gender-specific gene variants predicted to impact function

National Institute Of Diabetes And Digestive And Kidney Diseases

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Abstract

Identification of genes associated with polygenic diseases is challenging in part because such diseases may be also greatly influenced by environmental and behavioral factors. To overcome these challenges, a deeper understanding of how ancestry-and gender-associated genetic variance affects disparities in the disease risk is merited. Better understanding of such genetic variance may also facilitate the identification of polygenic disease-associated genes. We hypothesize that the discovery of genes associated with polygenic diseases may be limited by over-reliance on single-nucleotide polymorphism (SNP)-based genomic investigation, since most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitation, we are developing gene-constrained and function-based analytical methods centered on high-risk variants (hrV) that encode frameshifts, stopgains, or splice site disruption, but that may also consider variants with potentially lesser impact such as variants that encode missense mutations. Function-based and ancestry- and gender-specific analysis of genetic variations may accelerate the identification of genes associated with polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as type 2 diabetes mellitus (T2DM), obesity, hypertension, and Alzheimers disease.