Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
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Abstract
Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
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The record
- Venue
- Nature Communications
- Topic
- Genetic Associations and Epidemiology
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- McGill UniversityMcGill Genome Centre
- Funders
- Common FundNational Institute of Neurological Disorders and StrokeNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteNIH Office of the DirectorNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteDirectorate for Biological SciencesNational Institutes of HealthBroad InstituteUniversité de GenèveLoyola University ChicagoUniversity of ChicagoHarvard UniversityNational Center for Advancing Translational SciencesNational Human Genome Research InstituteWellcome TrustUniversity of PennsylvaniaGeorgia Clinical and Translational Science AllianceNational Institute on Drug AbuseUniversity of Miami
- Keywords
- Genome-wide association studyPhenotypeVariation (astronomy)Computational biologyBiologyGene expressionSummary statisticsGeneEvolutionary biologyGeneticsStatisticsSingle-nucleotide polymorphismGenotype
- Has abstract in OpenAlex
- yes