2022
Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits
Highland H, Wojcik G, Graff M, Nishimura K, Hodonsky C, Baldassari A, Cote A, Cheng I, Gignoux C, Tao R, Li Y, Boerwinkle E, Fornage M, Haessler J, Hindorff L, Hu Y, Justice A, Lin B, Lin D, Stram D, Haiman C, Kooperberg C, Le Marchand L, Matise T, Kenny E, Carlson C, Stahl E, Avery C, North K, Ambite J, Buyske S, Loos R, Peters U, Young K, Bien S, Huckins L. Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits. American Journal Of Human Genetics 2022, 109: 669-679. PMID: 35263625, PMCID: PMC9069067, DOI: 10.1016/j.ajhg.2022.02.013.Peer-Reviewed Original ResearchConceptsAncestrally diverse populationsBody mass indexCardiometabolic traitsEuropean ancestryGene expressionTranscriptomic imputation modelsNon-EA populationsDiverse populationsWhite British participantsReference panelGenetically regulated gene expressionGene-trait associationsTissue-specific gene expressionPopulation ArchitectureUK BiobankMeasurement of gene expressionPredicting gene expressionMulti-omics datasetsRelevant tissuesSusceptibility lociMass indexComplex traitsIdentified genesNovel associationsDiverse sample
2021
Correction to: Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) Study
Hu Y, Bien S, Nishimura K, Haessler J, Hodonsky C, Baldassari A, Highland H, Wang Z, Preuss M, Sitlani C, Wojcik G, Tao R, Graff M, Huckins L, Sun Q, Chen M, Mousas A, Auer P, Lettre G, Tang W, Qi L, Thyagarajan B, Buyske S, Fornage M, Hindorff L, Li Y, Lin D, Reiner A, North K, Loos R, Raffield L, Peters U, Avery C, Kooperberg C. Correction to: Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) Study. BMC Genomics 2021, 22: 656. PMID: 34517814, PMCID: PMC8436530, DOI: 10.1186/s12864-021-07919-1.Peer-Reviewed Original ResearchMulti-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study
Hu Y, Bien S, Nishimura K, Haessler J, Hodonsky C, Baldassari A, Highland H, Wang Z, Preuss M, Sitlani C, Wojcik G, Tao R, Graff M, Huckins L, Sun Q, Chen M, Mousas A, Auer P, Lettre G, Tang W, Qi L, Thyagarajan B, Buyske S, Fornage M, Hindorff L, Li Y, Lin D, Reiner A, North K, Loos R, Raffield L, Peters U, Avery C, Kooperberg C. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study. BMC Genomics 2021, 22: 432. PMID: 34107879, PMCID: PMC8191001, DOI: 10.1186/s12864-021-07745-5.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesPlatelet traitsAfrican AmericansPopulation ArchitectureAssociation studiesAssociation analysisAncestry-specific genome-wide association studiesEuropean ancestryGenome-wide association analysisAttenuation of effect estimatesGenome-wide significant variantsVariant association analysisGenome-wide significanceRacially/ethnically diverse populationsPopulations of European ancestryGenetic association studiesAncestry-specificComplex traitsSignificant variantsHispanics/LatinosMultiple genesAncestry groupsEffect estimatesEA populationsEA participants
2019
Genetic analyses of diverse populations improves discovery for complex traits
Wojcik G, Graff M, Nishimura K, Tao R, Haessler J, Gignoux C, Highland H, Patel Y, Sorokin E, Avery C, Belbin G, Bien S, Cheng I, Cullina S, Hodonsky C, Hu Y, Huckins L, Jeff J, Justice A, Kocarnik J, Lim U, Lin B, Lu Y, Nelson S, Park S, Poisner H, Preuss M, Richard M, Schurmann C, Setiawan V, Sockell A, Vahi K, Verbanck M, Vishnu A, Walker R, Young K, Zubair N, Acuña-Alonso V, Ambite J, Barnes K, Boerwinkle E, Bottinger E, Bustamante C, Caberto C, Canizales-Quinteros S, Conomos M, Deelman E, Do R, Doheny K, Fernández-Rhodes L, Fornage M, Hailu B, Heiss G, Henn B, Hindorff L, Jackson R, Laurie C, Laurie C, Li Y, Lin D, Moreno-Estrada A, Nadkarni G, Norman P, Pooler L, Reiner A, Romm J, Sabatti C, Sandoval K, Sheng X, Stahl E, Stram D, Thornton T, Wassel C, Wilkens L, Winkler C, Yoneyama S, Buyske S, Haiman C, Kooperberg C, Le Marchand L, Loos R, Matise T, North K, Peters U, Kenny E, Carlson C. Genetic analyses of diverse populations improves discovery for complex traits. Nature 2019, 570: 514-518. PMID: 31217584, PMCID: PMC6785182, DOI: 10.1038/s41586-019-1310-4.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesComplex traitsBiology of complex traitsDiverse populationsEvidence of effect-size heterogeneityGenome-wide effortsLarge-scale genomic studiesReduce health disparitiesNon-European individualsHighest burden of diseaseMulti-ethnic participantsEffect-size heterogeneityBurden of diseaseRepresentation of diverse populationsGWAS associationsNovel lociRisk prediction scoreAdmixed populationsFine-mappingGenetic architectureAssociation studiesGenomic studiesHealth disparitiesHealthcare disparitiesPopulation Architecture