2024
Chronic Overlapping Pain Conditions and Nociplastic Pain
Johnston K, Signer R, Huckins L. Chronic Overlapping Pain Conditions and Nociplastic Pain. Human Genetics And Genomics Advances 2024, 100381. PMID: 39497418, DOI: 10.1016/j.xhgg.2024.100381.Peer-Reviewed Original ResearchGenome wide association studiesTranscriptome-wide associationChronic overlapping pain conditionsTissue enrichment analysisSingle nucleotide polymorphismsEnrichment analysisNociplastic painPain conditionsIndependent single nucleotide polymorphismsMultisite chronic painGene set enrichment analysisSNP heritabilityUnique genesNeuropathic pain phenotypesAssociation studiesPolygenic traitChronic pain conditionsGene setsNucleotide polymorphismsMetabolic traitsHeritable traitGenetic overlapPain phenotypesPain descriptorsPain experience23. GENOME-WIDE ASSOCIATION STUDIES OF BINGE-EATING BEHAVIOUR AND ANOREXIA NERVOSA YIELD INSIGHTS INTO THE UNIQUE AND SHARED BIOLOGY OF EATING DISORDER PHENOTYPES
Huckins L, Termorshuizen J, Davies H, Lee S, Johnson J, Munn-Chernoff M, Thornton L, Källberg J, Bulik C, Breen G, Coleman J. 23. GENOME-WIDE ASSOCIATION STUDIES OF BINGE-EATING BEHAVIOUR AND ANOREXIA NERVOSA YIELD INSIGHTS INTO THE UNIQUE AND SHARED BIOLOGY OF EATING DISORDER PHENOTYPES. European Neuropsychopharmacology 2024, 87: 60. DOI: 10.1016/j.euroneuro.2024.08.137.Peer-Reviewed Original ResearchGenome-wide association studiesIdentification of novel lociGenome-wide association study meta-analysisGenetic correlationsEating Disorders Working GroupBinge-eating behaviorNovel lociGenome-wideGenomic lociAssociation studiesLociGenetic componentEating disorder phenotypesPhenotypeEarly onset obesityBE phenotypeSevere early onset obesityDisorder phenotypesTrans-diagnosticAN subtypesAN-BPAN-RAN-R.Eating disordersBinge-eating/purgingShared Genetic Architecture Between Schizophrenia and Anorexia Nervosa: A Cross-trait Genome-Wide Analysis
Lu Z, Ploner A, Birgegård A, Adan R, Alfredsson L, Ando T, Andreassen O, Baker J, Bergen A, Berrettini W, Birgegård A, Boden J, Boehm I, Perica V, Brandt H, Breen G, Bryois J, Buehren K, Bulik C, Burghardt R, Cassina M, Cichon S, Coleman J, Cone R, Courtet P, Crawford S, Crow S, Crowley J, Danner U, Davis O, de Zwaan M, Dedoussis G, DeSocio J, Dick D, Dikeos D, Dina C, Dmitrzak-Weglarz M, Docampo E, Duncan L, Egberts K, Ehrlich S, Escaramís G, Esko T, Estivill X, Farmer A, Favaro A, Fernández-Aranda F, Fischer K, Föcker M, Foretova L, Forstner A, Forzan M, Franklin C, Gallinger S, Giegling I, Giusti-Rodríguez P, Gonidakis F, Gordon S, Gorwood P, Mayora M, Grove J, Guillaume S, Guo Y, Hakonarson H, Halmi K, Hanscombe K, Hatzikotoulas K, Hauser J, Hebebrand J, Helder S, Herms S, Herpertz-Dahlmann B, Herzog W, Hinney A, Horwood L, Hübel C, Huckins L, Hudson J, Imgart H, Inoko H, Janout V, Jiménez-Murcia S, Johnson C, Jordan J, Julià A, Kalsi G, Kaminská D, Kaplan A, Kaprio J, Karhunen L, Karwautz A, Kas M, Kaye W, Kennedy J, Kennedy M, Keski-Rahkonen A, Kiezebrink K, Kim Y, Klareskog L, Klump K, Landén M, Larsen J, Le Hellard S, Leppä V, Li D, Lichtenstein P, Lilenfeld L, Lin B, Lissowska J, Luykx J, Maj M, Marsal S, Martin N, Mattheisen M, Mattingsdal M, Medland S, Metspalu A, Meulenbelt I, Micali N, Mitchell K, Mitchell J, Monteleone A, Monteleone P, Mortensen P, Munn-Chernoff M, Nacmias B, Navratilova M, Ntalla I, Olsen C, Ophoff R, Padyukov L, Pantel J, Papezova H, Parker R, Pearson J, Pedersen N, Petersen L, Pinto D, Purves K, Raevuori A, Ramoz N, Reichborn-Kjennerud T, Ricca V, Ripatti S, Ripke S, Ritschel F, Roberts M, Rujescu D, Rybakowski F, Santonastaso P, Scherag A, Scherer S, Schmidt U, Schork N, Schosser A, Seitz J, Slachtova L, Slagboom P, Landt M, Slopien A, Sorbi S, Strober M, Sullivan P, Świątkowska B, Szatkiewicz J, Tenconi E, Thornton L, Tortorella A, Treasure J, Tsitsika A, Tyszkiewicz-Nwafor M, van Elburg A, van Furth E, Wade T, Wagner G, Watson H, Werge T, Whiteman D, Widen E, Woodside D, Yao S, Yilmaz Z, Zeggini E, Zerwas S, Zipfel S, Breen G, Bulik C, Bulik C, Bergen S. Shared Genetic Architecture Between Schizophrenia and Anorexia Nervosa: A Cross-trait Genome-Wide Analysis. Schizophrenia Bulletin 2024, 50: 1255-1265. PMID: 38848516, PMCID: PMC11349005, DOI: 10.1093/schbul/sbae087.Peer-Reviewed Original ResearchPolygenic overlapConditional/conjunctional false discovery rateGenome-wide association studiesGenome-wide analysisConcordant effect directionsProportion of variantsNovel lociFalse discovery rateFunctional annotationGenetic architectureGenetic enrichmentAssociation studiesMultiple genesSynapse organizationMendelian randomization analysisGenetic associationCo-aggregationLociGenetic componentGenetic etiologyAnorexia nervosaFamilial co-aggregationDiscovery rateGenetic factorsRandomization analysisDissecting the biology of feeding and eating disorders
Huckins L, Brennand K, Bulik C. Dissecting the biology of feeding and eating disorders. Trends In Molecular Medicine 2024, 30: 380-391. PMID: 38431502, DOI: 10.1016/j.molmed.2024.01.009.Peer-Reviewed Original ResearchGenome-wide association studiesVariants to genesGenes to pathwaysSignificant lociFunctional genomicsAssociation studiesGenetic relationshipsIntestinal microbiotaGenetic researchGenomeGenetic correlationsGenesMetabolic contributorsAnorexia nervosaEating disordersPathwayBiologyMetabolic outcomesRisk factorsLociMicrobiotaPhenomicsLethal illnessTraitsFeeding
2023
W22. DISENTANGLING THE ROLES OF GENETICS AND BODY MASS INDEX ACROSS PSYCHIATRIC DISORDERS
Signer R, Seah C, Young H, de Pins A, Johnson J, Cote A, Huckins L. W22. DISENTANGLING THE ROLES OF GENETICS AND BODY MASS INDEX ACROSS PSYCHIATRIC DISORDERS. European Neuropsychopharmacology 2023, 75: s116. DOI: 10.1016/j.euroneuro.2023.08.213.Peer-Reviewed Original ResearchExpression quantitative trait lociBody mass indexGenome-wide association studiesEffect of body mass indexAssociation studiesAvailability of genome-wide association studyGenetic riskPhenome-wide association studyIndirect effect of body mass indexPsychiatric disordersBody mass index spectrumStatistical fine-mappingQuantitative trait lociGenetic risk modelsCell-type specific mannerTissue enrichmentImpact of body mass indexGWAS lociTranscriptome imputationGenomic lociWhole genomeFine-mappingTrait lociGenomic underpinningsPhenotypic consequencesGenetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing
Johnston K, Cote A, Hicks E, Johnson J, Huckins L. Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing. Biological Psychiatry 2023, 95: 745-761. PMID: 37678542, PMCID: PMC10924073, DOI: 10.1016/j.biopsych.2023.08.023.Peer-Reviewed Original ResearchConceptsGenetically regulated gene expressionMultisite chronic painGene-tissue associationsMean pain scoreUnique genesChronic painAssociation studiesS-PrediXcanGene expressionPain scoresTranscriptome-wide association studyPhenome-wide association studyCardiac dysrhythmiasMetabolic syndromeGenome-wide association studiesAssociated with cardiac dysrhythmiasDrug targetsGenotype-phenotype gapChronic pain developmentAssociation study resultsGene expression changesJoint/ligament sprainsDirection of effectTranscriptome imputationPain traitsOpen Science Practices in Psychiatric Genetics: A Primer
Kępińska A, Johnson J, Huckins L. Open Science Practices in Psychiatric Genetics: A Primer. Biological Psychiatry Global Open Science 2023, 4: 110-119. PMID: 38298792, PMCID: PMC10829621, DOI: 10.1016/j.bpsgos.2023.08.007.Peer-Reviewed Original ResearchLeveraging base-pair mammalian constraint to understand genetic variation and human disease
Sullivan P, Meadows J, Gazal S, Phan B, Li X, Genereux D, Dong M, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas M, Marinescu V, Wang C, Wallerman O, Xue J, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins L, Lawler A, Keough K, Zheng Z, Zeng J, Wray N, Li Y, Johnson J, Chen J, Paten B, Reilly S, Hughes G, Weng Z, Pollard K, Pfenning A, Forsberg-Nilsson K, Karlsson E, Lindblad-Toh K, Andrews G, Armstrong J, Bianchi M, Birren B, Bredemeyer K, Breit A, Christmas M, Clawson H, Damas J, Di Palma F, Diekhans M, Dong M, Eizirik E, Fan K, Fanter C, Foley N, Forsberg-Nilsson K, Garcia C, Gatesy J, Gazal S, Genereux D, Goodman L, Grimshaw J, Halsey M, Harris A, Hickey G, Hiller M, Hindle A, Hubley R, Hughes G, Johnson J, Juan D, Kaplow I, Karlsson E, Keough K, Kirilenko B, Koepfli K, Korstian J, Kowalczyk A, Kozyrev S, Lawler A, Lawless C, Lehmann T, Levesque D, Lewin H, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu V, Marques-Bonet T, Mason V, Meadows J, Meyer W, Moore J, Moreira L, Moreno-Santillan D, Morrill K, Muntané G, Murphy W, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat N, Pfenning A, Phan B, Pollard K, Pratt H, Ray D, Reilly S, Rosen J, Ruf I, Ryan L, Ryder O, Sabeti P, Schäffer D, Serres A, Shapiro B, Smit A, Springer M, Srinivasan C, Steiner C, Storer J, Sullivan K, Sullivan P, Sundström E, Supple M, Swofford R, Talbot J, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder A, Wirthlin M, Xue J, Zhang X. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 2023, 380: eabn2937. PMID: 37104612, PMCID: PMC10259825, DOI: 10.1126/science.abn2937.Peer-Reviewed Original ResearchConceptsHuman genomeHuman diseasesCopy-number variationsHeritable human diseasesGenome annotationVariant annotationGenomic positionsGenomic regionsDisease heritabilityFunctional annotationEvolutionary constraintsAssociation studiesCopy-numberGenetic variationGenetic findingsGenomeCell typesRegulatory landscapeDisease mechanismsAnnotationBiological mechanismsCancer dataMammalsPredictor of functionHeritability
2022
Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders
Seah C, Huckins L, Brennand K. Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders. Biological Psychiatry 2022, 93: 642-650. PMID: 36658083, DOI: 10.1016/j.biopsych.2022.09.033.Peer-Reviewed Original ResearchConceptsStem cell modelCell typesTarget genesGenome-wide association study (GWAS) lociExpression quantitative trait lociGenome-wide association studiesParallel reporter assaysQuantitative trait lociStem cell-derived cell typesPluripotent stem cell modelsComplex polygenic architectureContext-specific mannerPsychiatric disorder riskTrait lociRegulates transcriptionStudy lociGenetic regulationPolygenic architectureCRISPR screensCell modelCausal variantsRegulated expressionPatient-specific humanReporter assaysAssociation studiesMapping anorexia nervosa genes to clinical phenotypes
Johnson J, Cote A, Dobbyn A, Sloofman L, Xu J, Cotter L, Charney A, Consortium E, Birgegård A, Jordan J, Kennedy M, Landén M, Maguire S, Martin N, Mortensen P, Thornton L, Bulik C, Huckins L. Mapping anorexia nervosa genes to clinical phenotypes. Psychological Medicine 2022, 53: 2619-2633. PMID: 35379376, PMCID: PMC10123844, DOI: 10.1017/s0033291721004554.Peer-Reviewed Original ResearchConceptsBody mass indexGenome-wide association studiesTranscriptome imputationElectronic health record phenotypingAssociation studiesPhenome-wide association studyS-PrediXcan analysisMeasurement of cholesterolTraditional genome-wide association studiesGenes associated with ANAssociation of genetic variantsSubstance useGenetically regulated gene expressionImpact of body mass indexConsequences of aberrant expressionBiobank cohortBiobank populationAssociated with measuresAssociation of ANGWAS findingsSecondary analysisS-PrediXcanDisease riskMass indexSignificant genesUsing phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder
Wendt FR, Pathak GA, Deak JD, De Angelis F, Koller D, Cabrera-Mendoza B, Lebovitch DS, Levey DF, Stein MB, Kranzler HR, Koenen KC, Gelernter J, Huckins LM, Polimanti R. Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder. Molecular Psychiatry 2022, 27: 2206-2215. PMID: 35181757, PMCID: PMC9133008, DOI: 10.1038/s41380-022-01469-y.Peer-Reviewed Original ResearchChapter 14 Integration with systems biology approaches and -omics data to characterize risk variation
Young H, Cote A, Huckins L. Chapter 14 Integration with systems biology approaches and -omics data to characterize risk variation. 2022, 289-315. DOI: 10.1016/b978-0-12-819602-1.00017-6.Peer-Reviewed Original ResearchAssociation studiesPatterns of linkage disequilibriumTranscriptome-wide association studyGenome-wide association studiesFunctional genomic annotationsSystems biology approachGenome annotationNoncoding variantsNoncoding regionsLinkage disequilibriumGene regulationRegulatory regionsGene networksGenetic variantsBiology approachFunctional pathwaysRisk variationDevelopmental stagesGenetic riskGenesPathwayUnique considerationsVariantsVariation researchPsychiatric disorders
2021
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. 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
2020
Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data
Dueñas H, Seah C, Johnson J, Huckins L. Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data. Human Molecular Genetics 2020, 29: r33-r41. PMID: 32879975, PMCID: PMC7530523, DOI: 10.1093/hmg/ddaa192.Peer-Reviewed Original ResearchConceptsElectronic health recordsUse of electronic health recordsElectronic health record dataElectronic health record analysisGenome-wide association studiesHealth recordsPhenotype definitionAssociation studiesMedical recordsClinical decisionsPhenotypic characterizationPhenotypic analysisClinically useful insightsPotential biasPresentation of diseaseDegree of biasHomogeneous cohortClinicPhenotypeScalable mannerRecordsCohortBias
2019
Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems
Zheutlin A, Dennis J, Karlsson Linnér R, Moscati A, Restrepo N, Straub P, Ruderfer D, Castro V, Chen C, Ge T, Huckins L, Charney A, Kirchner H, Stahl E, Chabris C, Davis L, Smoller J. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems. American Journal Of Psychiatry 2019, 176: 846-855. PMID: 31416338, PMCID: PMC6961974, DOI: 10.1176/appi.ajp.2019.18091085.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresHealth care systemCare systemGenetic riskAssociated with schizophreniaPolygenic risk score distributionPhenome-wide association studyMeasures of genetic riskRisk scoreHighest risk decileHealth care settingsElectronic health recordsOdds of schizophreniaAssociated with other phenotypesCare settingsRisk decileHealth recordsHigher oddsHealth consequencesResearch cohortAssociation studiesHealthEarly interventionMeta-analysisPersonality disorderGenome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa
Watson H, Yilmaz Z, Thornton L, Hübel C, Coleman J, Gaspar H, Bryois J, Hinney A, Leppä V, Mattheisen M, Medland S, Ripke S, Yao S, Giusti-Rodríguez P, Hanscombe K, Purves K, Adan R, Alfredsson L, Ando T, Andreassen O, Baker J, Berrettini W, Boehm I, Boni C, Perica V, Buehren K, Burghardt R, Cassina M, Cichon S, Clementi M, Cone R, Courtet P, Crow S, Crowley J, Danner U, Davis O, de Zwaan M, Dedoussis G, Degortes D, DeSocio J, Dick D, Dikeos D, Dina C, Dmitrzak-Weglarz M, Docampo E, Duncan L, Egberts K, Ehrlich S, Escaramís G, Esko T, Estivill X, Farmer A, Favaro A, Fernández-Aranda F, Fichter M, Fischer K, Föcker M, Foretova L, Forstner A, Forzan M, Franklin C, Gallinger S, Giegling I, Giuranna J, Gonidakis F, Gorwood P, Mayora M, Guillaume S, Guo Y, Hakonarson H, Hatzikotoulas K, Hauser J, Hebebrand J, Helder S, Herms S, Herpertz-Dahlmann B, Herzog W, Huckins L, Hudson J, Imgart H, Inoko H, Janout V, Jiménez-Murcia S, Julià A, Kalsi G, Kaminská D, Kaprio J, Karhunen L, Karwautz A, Kas M, Kennedy J, Keski-Rahkonen A, Kiezebrink K, Kim Y, Klareskog L, Klump K, Knudsen G, La Via M, Le Hellard S, Levitan R, Li D, Lilenfeld L, Lin B, Lissowska J, Luykx J, Magistretti P, Maj M, Mannik K, Marsal S, Marshall C, Mattingsdal M, McDevitt S, McGuffin P, Metspalu A, Meulenbelt I, Micali N, Mitchell K, Monteleone A, Monteleone P, Munn-Chernoff M, Nacmias B, Navratilova M, Ntalla I, O’Toole J, Ophoff R, Padyukov L, Palotie A, Pantel J, Papezova H, Pinto D, Rabionet R, Raevuori A, Ramoz N, Reichborn-Kjennerud T, Ricca V, Ripatti S, Ritschel F, Roberts M, Rotondo A, Rujescu D, Rybakowski F, Santonastaso P, Scherag A, Scherer S, Schmidt U, Schork N, Schosser A, Seitz J, Slachtova L, Slagboom P, Slof-Op ‘t Landt M, Slopien A, Sorbi S, Świątkowska B, Szatkiewicz J, Tachmazidou I, Tenconi E, Tortorella A, Tozzi F, Treasure J, Tsitsika A, Tyszkiewicz-Nwafor M, Tziouvas K, van Elburg A, van Furth E, Wagner G, Walton E, Widen E, Zeggini E, Zerwas S, Zipfel S, Bergen A, Boden J, Brandt H, Crawford S, Halmi K, Horwood L, Johnson C, Kaplan A, Kaye W, Mitchell J, Olsen C, Pearson J, Pedersen N, Strober M, Werge T, Whiteman D, Woodside D, Stuber G, Gordon S, Grove J, Henders A, Juréus A, Kirk K, Larsen J, Parker R, Petersen L, Jordan J, Kennedy M, Montgomery G, Wade T, Birgegård A, Lichtenstein P, Norring C, Landén M, Martin N, Mortensen P, Sullivan P, Breen G, Bulik C. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nature Genetics 2019, 51: 1207-1214. PMID: 31308545, PMCID: PMC6779477, DOI: 10.1038/s41588-019-0439-2.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesTwin-based heritability estimatesEating Disorders Working GroupPsychiatric Genomics ConsortiumAnorexia nervosaBody-mass indexSignificant lociGenetic architectureRisk lociGenetics InitiativeGenomics ConsortiumLow body-mass indexMetabo-psychiatric disorderGenetic correlationsMetabolic componentsLociCases of anorexia nervosaPhysical activityAnthropometric traitsPsychiatric disordersHeritability estimatesAnorexia Nervosa Genetics InitiativeNervosaImprove outcomesGenetic 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
2018
Analysis of shared heritability in common disorders of the brain
Consortium T, Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, Escott-Price V, Falcone GJ, Gormley P, Malik R, Patsopoulos NA, Ripke S, Wei Z, Yu D, Lee PH, Turley P, Grenier-Boley B, Chouraki V, Kamatani Y, Berr C, Letenneur L, Hannequin D, Amouyel P, Boland A, Deleuze JF, Duron E, Vardarajan BN, Reitz C, Goate AM, Huentelman MJ, Kamboh MI, Larson EB, Rogaeva E, St George-Hyslop P, Hakonarson H, Kukull WA, Farrer LA, Barnes LL, Beach TG, Demirci FY, Head E, Hulette CM, Jicha GA, Kauwe JSK, Kaye JA, Leverenz JB, Levey AI, Lieberman AP, Pankratz VS, Poon WW, Quinn JF, Saykin AJ, Schneider LS, Smith AG, Sonnen JA, Stern RA, Van Deerlin VM, Van Eldik LJ, Harold D, Russo G, Rubinsztein DC, Bayer A, Tsolaki M, Proitsi P, Fox NC, Hampel H, Owen MJ, Mead S, Passmore P, Morgan K, Nöthen MM, Schott J, Rossor M, Lupton M, Hoffmann P, Kornhuber J, Lawlor B, McQuillin A, Al-Chalabi A, Bis J, Ruiz A, Boada M, Seshadri S, Beiser A, Rice K, van der Lee S, De Jager P, Geschwind D, Riemenschneider M, Riedel-Heller S, Rotter J, Ransmayr G, Hyman B, Cruchaga C, Alegret M, Winsvold B, Palta P, Farh K, Cuenca-Leon E, Furlotte N, Kurth T, Ligthart L, Terwindt G, Freilinger T, Ran C, Gordon S, Borck G, Adams H, Lehtimäki T, Wedenoja J, Buring J, Schürks M, Hrafnsdottir M, Hottenga J, Penninx B, Artto V, Kaunisto M, Vepsäläinen S, Martin N, Montgomery G, Kurki M, Hämäläinen E, Huang H, Huang J, Sandor C, Webber C, Muller-Myhsok B, Schreiber S, Salomaa V, Loehrer E, Göbel H, Macaya A, Pozo-Rosich P, Hansen T, Werge T, Kaprio J, Metspalu A, Kubisch C, Ferrari M, Belin A, van den Maagdenberg A, Zwart J, Boomsma D, Eriksson N, Olesen J, Chasman D, Nyholt D, Anney R, Avbersek A, Baum L, Berkovic S, Bradfield J, Buono R, Catarino C, Cossette P, De Jonghe P, Depondt C, Dlugos D, Ferraro T, French J, Hjalgrim H, Jamnadas-Khoda J, Kälviäinen R, Kunz W, Lerche H, Leu C, Lindhout D, Lo W, Lowenstein D, McCormack M, Møller R, Molloy A, Ng P, Oliver K, Privitera M, Radtke R, 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