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

鉴定与多基因疾病相关的基因具有挑战性，部分原因是这些疾病也可能受到环境和行为因素的极大影响。为了克服这些挑战，有必要更深入地了解与血统和性别相关的遗传变异如何影响疾病风险的差异。更好地了解这种遗传变异也可能有助于鉴定多基因疾病相关基因。我们假设，与多基因疾病相关的基因的发现可能受到过度依赖基于单核苷酸多态性（SNP）的基因组调查的限制，因为在全基因组SNP关联研究中发现的大多数重要变异都映射到基因组的内含子和基因间区域。为了克服这种潜在的限制，我们正在开发以编码帧移、停止增益或剪接位点中断的高风险变异（hrV）为中心的基因约束和基于功能的分析方法，但也可以考虑具有潜在较小影响的变异，如编码错义突变的变异。基于功能、血统和性别的遗传变异分析可能会加速识别与多基因疾病相关的基因，这些疾病也受到环境和行为因素的极大影响，如2型糖尿病（T2DM）、肥胖、高血压和阿尔茨海默病。

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.