{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Tan T"],"funding":["NIA NIH HHS"],"pubmed_abstract":["Genome-wide association studies (GWAS) have discovered thousands of replicable genetic associations, guiding drug target discovery and powering genetic prediction of human phenotypes and diseases. However, genetic associations can be affected by gene-environment correlations and non-random mating, which can lead to biased inferences in downstream analyses. Family-based GWAS (FGWAS) uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) - causal effects of alleles in an individual on an individual - from other factors contributing to genetic associations. Here, we report results from an FGWAS meta-analysis of 34 phenotypes from 17 cohorts. We found evidence that factors uncorrelated with DGEs make substa"],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2024.10.01.24314703"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12633112"],"repository":["biostudies-literature"],"pubmed_title":["Family-GWAS reveals effects of environment and mating on genetic associations."],"pmcid":["PMC12633112"],"funding_grant_id":["R01 AG042568","R00 AG062787","R24 AG065184","R01 AG083379"],"pubmed_authors":["Palviainen T","Cheesman R","Havdahl A","Kaprio J","Martin NG","Mitchell BL","Reis K","de Geus E","Flint J","Okbay A","Mir M","Elnahas AG","Hveem K","Jayashankar H","Ehli EA","Medland SE","Chen Z","Langhammer A","Lee JJ","Ystrom E","Houmark MA","Latvala A","Linner RK","LifeLines Cohort Study","Hayward C","Nolte IM","Visscher PM","Nehzati SM","Walters RG","Oetjens MT","Li L","Chabris CF","Lehtovirta M","Silventoinen K","Tan T","Agerbo E","Cesarini D","Turley P","Lin K","Benjamin DJ","Vilhjalmsson BJ","Tuomi T","McGue M","Brumpton B","Oskarsson S","Bhatta L","Sidorenko J","Willoughby EA","Benonisdottir S","Kong A","Estonian Biobank Research Team","Lombardi S","Winsvold BS","Young AS","Hakaste L","Prasad RB","Hottenga JJ","Guan J","Hansen AF","Tucker-Drob EM","Border R","Metspalu A","Boomsma DI","Ni G","Pinto de Andrade Anapaz V","China Kadoorie Biobank Collaborative Group","Ganna A","Snieder H","Bennett M","Finngen","Reigo A","Yengo L","Ahlskog R","Giannelis A","Campbell A","Asvold BO"],"additional_accession":[]},"is_claimable":false,"name":"Family-GWAS reveals effects of environment and mating on genetic associations.","description":"Genome-wide association studies (GWAS) have discovered thousands of replicable genetic associations, guiding drug target discovery and powering genetic prediction of human phenotypes and diseases. However, genetic associations can be affected by gene-environment correlations and non-random mating, which can lead to biased inferences in downstream analyses. Family-based GWAS (FGWAS) uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) - causal effects of alleles in an individual on an individual - from other factors contributing to genetic associations. Here, we report results from an FGWAS meta-analysis of 34 phenotypes from 17 cohorts. We found evidence that factors uncorrelated with DGEs make substa","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-05-31T03:15:50.868Z","creation":"2026-05-31T03:10:13.354Z"},"accession":"S-EPMC12633112","cross_references":{"pubmed":["41282763"],"doi":["10.1101/2024.10.01.24314703"]}}