J Am Med Inform Assoc - Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases.

Tópicos

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Resumo

CKGROUND: While genome-wide association studies (GWAS) of complex traits have revealed thousands of reproducible genetic associations to date, these loci collectively confer very little of the heritability of their respective diseases and, in general, have contributed little to our understanding the underlying disease biology. Physical protein interactions have been utilized to increase our understanding of human Mendelian disease loci but have yet to be fully exploited for complex traits.METHODS: We hypothesized that protein interaction modeling of GWAS findings could highlight important disease-associated loci and unveil the role of their network topology in the genetic architecture of diseases with complex inheritance.RESULTS: Network modeling of proteins associated with the intragenic single nucleotide polymorphisms of the National Human Genome Research Institute catalog of complex trait GWAS revealed that complex trait associated loci are more likely to be hub and bottleneck genes in available, albeit incomplete, networks (OR=1.59, Fisher's exact test p < 2.24 ? 10(-12)). Network modeling also prioritized novel type 2 diabetes (T2D) genetic variations from the Finland-USA Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics and the Wellcome Trust GWAS data, and demonstrated the enrichment of hubs and bottlenecks in prioritized T2D GWAS genes. The potential biological relevance of the T2D hub and bottleneck genes was revealed by their increased number of first degree protein interactions with known T2D genes according to several independent sources (p<0.01, probability of being first interactors of known T2D genes).CONCLUSION: Virtually all common diseases are complex human traits, and thus the topological centrality in protein networks of complex trait genes has implications in genetics, personal genomics, and therapy.

Resumo Limpo

ckground genomewid associ studi gwas complex trait reveal thousand reproduc genet associ date loci collect confer littl herit respect diseas general contribut littl understand under diseas biolog physic protein interact util increas understand human mendelian diseas loci yet fulli exploit complex traitsmethod hypothes protein interact model gwas find highlight import diseaseassoci loci unveil role network topolog genet architectur diseas complex inheritanceresult network model protein associ intragen singl nucleotid polymorph nation human genom research institut catalog complex trait gwas reveal complex trait associ loci like hub bottleneck gene avail albeit incomplet network fisher exact test p network model also priorit novel type diabet td genet variat finlandusa investig noninsulindepend diabet mellitus genet wellcom trust gwas data demonstr enrich hub bottleneck priorit td gwas gene potenti biolog relev td hub bottleneck gene reveal increas number first degre protein interact known td gene accord sever independ sourc p probabl first interactor known td genesconclus virtual common diseas complex human trait thus topolog central protein network complex trait gene implic genet person genom therapi

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