J Am Med Inform Assoc - Complex-disease networks of trait-associated single-nucleotide polymorphisms (SNPs) unveiled by information theory.

Tópicos

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Resumo

JECTIVE: Thousands of complex-disease single-nucleotide polymorphisms (SNPs) have been discovered in genome-wide association studies (GWAS). However, these intragenic SNPs have not been collectively mined to unveil the genetic architecture between complex clinical traits. The authors hypothesize that biological annotations of host genes of trait-associated SNPs may reveal the biomolecular modularity across complex-disease traits and offer insights for drug repositioning.METHODS: Trait-to-polymorphism (SNPs) associations confirmed in GWAS were used. A novel method to quantify trait-trait similarity anchored in Gene Ontology annotations of human proteins and information theory was developed. The results were then validated with the shortest paths of physical protein interactions between biologically similar traits.RESULTS: A network was constructed consisting of 280 significant intertrait similarities among 177 disease traits, which covered 1438 well-validated disease-associated SNPs. Thirty-nine percent of intertrait connections were confirmed by curators, and the following additional studies demonstrated the validity of a proportion of the remainder. On a phenotypic trait level, higher Gene Ontology similarity between proteins correlated with smaller 'shortest distance' in protein interaction networks of complexly inherited diseases (Spearman p<2.2?10(-16)). Further, 'cancer traits' were similar to one another, as were 'metabolic syndrome traits' (Fisher's exact test p=0.001 and 3.5?10(-7), respectively).CONCLUSION: An imputed disease network by information-anchored functional similarity from GWAS trait-associated SNPs is reported. It is also demonstrated that small shortest paths of protein interactions correlate with complex-disease function. Taken together, these findings provide the framework for investigating drug targets with unbiased functional biomolecular networks rather than worn-out single-gene and subjective canonical pathway approaches.

Resumo Limpo

jectiv thousand complexdiseas singlenucleotid polymorph snps discov genomewid associ studi gwas howev intragen snps collect mine unveil genet architectur complex clinic trait author hypothes biolog annot host gene traitassoci snps may reveal biomolecular modular across complexdiseas trait offer insight drug repositioningmethod traittopolymorph snps associ confirm gwas use novel method quantifi traittrait similar anchor gene ontolog annot human protein inform theori develop result valid shortest path physic protein interact biolog similar traitsresult network construct consist signific intertrait similar among diseas trait cover wellvalid diseaseassoci snps thirtynin percent intertrait connect confirm curat follow addit studi demonstr valid proport remaind phenotyp trait level higher gene ontolog similar protein correl smaller shortest distanc protein interact network complexli inherit diseas spearman p cancer trait similar one anoth metabol syndrom trait fisher exact test p respectivelyconclus imput diseas network informationanchor function similar gwas traitassoci snps report also demonstr small shortest path protein interact correl complexdiseas function taken togeth find provid framework investig drug target unbias function biomolecular network rather wornout singlegen subject canon pathway approach

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