Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring
Campos A, Ingold N, Huang Y, Mitchell B, Kho P, Han X, García-Marín L, Ong J, Agee M, Aslibekyan S, Auton A, Babalola E, Bell R, Bielenberg J, Bryc K, Bullis E, Cameron B, Coker D, Dhamija D, Das S, Elson S, Filshtein T, Fletez-Brant K, Fontanillas P, Freyman W, Gandhi P, Heilbron K, Hicks B, Hinds D, Huber K, Jewett E, Jiang Y, Kleinman A, Kukar K, Lin K, Lowe M, Luff M, McCreight J, McIntyre M, McManus K, Micheletti S, Moreno M, Mountain J, Mozaffari S, Nandakumar P, Noblin E, O’Connell J, Petrakovitz A, Poznik G, Shastri A, Shelton J, Shi J, Shringarpure S, Tian C, Tran V, Tung J, Wang X, Wang W, Weldon C, Wilton P, Law M, Yokoyama J, Martin N, Dong X, Cuellar-Partida G, MacGregor S, Aslibekyan S, Rentería M. Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring. Sleep 2022, 46: zsac308. PMID: 36525587, PMCID: PMC9995783, DOI: 10.1093/sleep/zsac308.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesBody mass indexComplex traitsLatent causal variable methodSA riskAnalysis of genome-wide association studiesMulti-trait analysis of genome-wide association studyMultisite chronic painPhenome-wide screenGenome-wide significant variantsEffect of body mass indexGenetic correlationsMeta-analysisGenome-wide significanceEvidence of associationCohort of participantsSevere health conditionsChronic obstructive pulmonary diseaseHigh blood pressureObstructive pulmonary diseaseMulti-trait analysisHealth conditionsGWAS analysisAssociation studiesSignificant variants
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