Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk
Yin X, Bose D, Kwon A, Hanks S, Jackson A, Stringham H, Welch R, Oravilahti A, Silva L, FinnGen, Locke A, Fuchsberger C, Service S, Erdos M, Bonnycastle L, Kuusisto J, Stitziel N, Hall I, Morrison J, Ripatti S, Palotie A, Freimer N, Collins F, Mohlke K, Scott L, Fauman E, Burant C, Boehnke M, Laakso M, Wen X. Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. American Journal Of Human Genetics 2022, 109: 1727-1741. PMID: 36055244, PMCID: PMC9606383, DOI: 10.1016/j.ajhg.2022.08.007.Peer-Reviewed Original ResearchMeSH KeywordsBilirubinCarnitineGenome-Wide Association StudyGlycerophospholipidsHumansMaleMetabolomicsQuantitative Trait LociSolute Carrier Family 22 Member 5TranscriptomeConceptsGenome-wide association studiesMolecular mechanismsGWAS resultsDisease traitsGene expressionMetabolic pathwaysTranscriptome-wide associationSame causal variantsMetabolomics resultsTranscriptomic resultsMolecular traitsTranscriptomic dataGTEx projectCausal variantsGlycerophospholipid metabolic pathwayTranscriptomicsAssociation studiesColocalization analysisMetabolite levelsDistinct pathwaysPutative causal effectGenetic variantsGenesUGT1A4 expressionGenetic association