Featured Publications
Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications
Levey D, Galimberti M, Deak J, Wendt F, Bhattacharya A, Koller D, Harrington K, Quaden R, Johnson E, Gupta P, Biradar M, Lam M, Cooke M, Rajagopal V, Empke S, Zhou H, Nunez Y, Kranzler H, Edenberg H, Agrawal A, Smoller J, Lencz T, Hougaard D, Børglum A, Demontis D, Gaziano J, Gandal M, Polimanti R, Stein M, Gelernter J. Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications. Nature Genetics 2023, 55: 2094-2103. PMID: 37985822, PMCID: PMC10703690, DOI: 10.1038/s41588-023-01563-z.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphism-based heritabilityMulti-ancestry genome-wide association studyAssociation studiesMillion Veteran ProgramGenome-wide association studiesWide significant lociWide association studySignificant lociReference panelSmall populationDisease biologyAncestryAmerican ancestryHeritabilityVeteran ProgramNumerous medical comorbiditiesLung cancer riskRelationship analysisLociBiologyPublic health implicationsEast AsiansPublic health consequencesMedical comorbiditiesCigarette smokingGenome-wide association studies and cross-population meta-analyses investigating short and long sleep duration
Austin-Zimmerman I, Levey D, Giannakopoulou O, Deak J, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse D, Gaziano J, Gottlieb D, Polimanti R, Stein M, Bramon E, Gelernter J. Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. Nature Communications 2023, 14: 6059. PMID: 37770476, PMCID: PMC10539313, DOI: 10.1038/s41467-023-41249-y.Peer-Reviewed Original ResearchConceptsAssociation studiesGenome-wide association studiesGenetic correlationsWide association studyLinkage disequilibrium scorePositive genetic correlationSleep traitsIndependent lociMillion Veteran ProgramTraitsAncestryUK BiobankVeteran ProgramMendelian randomisationLociHeritabilitySNPsPhenotypeEast AsiansSimilar patternCardiometabolic phenotypesGenome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci
Deak JD, Zhou H, Galimberti M, Levey DF, Wendt FR, Sanchez-Roige S, Hatoum AS, Johnson EC, Nunez YZ, Demontis D, Børglum AD, Rajagopal VM, Jennings MV, Kember RL, Justice AC, Edenberg HJ, Agrawal A, Polimanti R, Kranzler HR, Gelernter J. Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci. Molecular Psychiatry 2022, 27: 3970-3979. PMID: 35879402, PMCID: PMC9718667, DOI: 10.1038/s41380-022-01709-1.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant risk lociAssociation studiesVariant associationsLarge-scale genome-wide association studiesGenetic correlationsSignificant risk lociPsychiatric Genomics ConsortiumMulti-trait analysisPolygenic risk score analysisSingle-variant associationsGWS lociGenetic architectureIndividuals of EuropeanGWS associationsRisk lociGene regionGenomics ConsortiumMillion Veteran ProgramSusceptibility lociAfrican ancestryLociRisk score analysisGenetic informativenessSNPs oneBi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions
Levey DF, Stein MB, Wendt FR, Pathak GA, Zhou H, Aslan M, Quaden R, Harrington KM, Nuñez YZ, Overstreet C, Radhakrishnan K, Sanacora G, McIntosh AM, Shi J, Shringarpure SS, Concato J, Polimanti R, Gelernter J. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nature Neuroscience 2021, 24: 954-963. PMID: 34045744, PMCID: PMC8404304, DOI: 10.1038/s41593-021-00860-2.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association studyMillion Veteran ProgramTranscriptome-wide association study (TWAS) analysisGenomic risk lociComplex psychiatric traitsGenetic architectureRisk lociGene expressionAssociation studiesLikely pathogenicityPsychiatric traitsVeteran ProgramNew therapeutic directionEuropean ancestryNew insightsAncestryUK BiobankAfrican ancestrySubstantial replicationExpressionLarge independent cohortsGWASTherapeutic directionsGenesLociGenome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program
Stein MB, Levey DF, Cheng Z, Wendt FR, Harrington K, Pathak GA, Cho K, Quaden R, Radhakrishnan K, Girgenti MJ, Ho YA, Posner D, Aslan M, Duman RS, Zhao H, Polimanti R, Concato J, Gelernter J. Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program. Nature Genetics 2021, 53: 174-184. PMID: 33510476, PMCID: PMC7972521, DOI: 10.1038/s41588-020-00767-x.Peer-Reviewed Original ResearchConceptsGenome-wide association analysisAssociation analysisMillion Veteran ProgramGenomic structural equation modelingSignificant lociGenetic varianceGene expressionDrug repositioning candidatesBiological coherenceVeteran ProgramMultiple testing correctionSymptom phenotypeLociRepositioning candidatesAfrican ancestryHeritabilityPhenotypeAncestryExpressionPTSD symptom factorsRegionSubdomainsEnrichmentGenome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
Zhou H, Sealock JM, Sanchez-Roige S, Clarke TK, Levey DF, Cheng Z, Li B, Polimanti R, Kember RL, Smith RV, Thygesen JH, Morgan MY, Atkinson SR, Thursz MR, Nyegaard M, Mattheisen M, Børglum AD, Johnson EC, Justice AC, Palmer AA, McQuillin A, Davis LK, Edenberg HJ, Agrawal A, Kranzler HR, Gelernter J. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nature Neuroscience 2020, 23: 809-818. PMID: 32451486, PMCID: PMC7485556, DOI: 10.1038/s41593-020-0643-5.Peer-Reviewed Original ResearchConceptsRegulatory genomic regionsGenome-wide association studiesNovel risk lociEuropean ancestry individualsPolygenic risk score analysisIndependent risk variantsGenetic architectureGenomic regionsRisk lociAssociation studiesGenetic relationshipsRisk genesGenetic correlationsPsychiatric traitsRisk variantsRisk score analysisTraitsGenetic heritabilityYields insightsBiobank samplesMendelian randomizationGenesLociBiologyHeritabilityGenome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations
Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nature Communications 2019, 10: 1499. PMID: 30940813, PMCID: PMC6445072, DOI: 10.1038/s41467-019-09480-8.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesMillion Veteran Program sampleGenetic correlationsWide significant lociSignificant genetic correlationsPolygenic risk scoresCell type groupSignificant lociHeritable traitEnrichment analysisTraitsMultiple populationsLociPhenotypeProgram samples
2024
Genome-wide meta-analysis of myasthenia gravis uncovers new loci and provides insights into polygenic prediction
Braun A, Shekhar S, Levey D, Straub P, Kraft J, Panagiotaropoulou G, Heilbron K, Awasthi S, Meleka Hanna R, Hoffmann S, Stein M, Lehnerer S, Mergenthaler P, Elnahas A, Topaloudi A, Koromina M, Palviainen T, Asbjornsdottir B, Stefansson H, Skuladóttir A, Jónsdóttir I, Stefansson K, Reis K, Esko T, Palotie A, Leypoldt F, Stein M, Fontanillas P, Kaprio J, Gelernter J, Davis L, Paschou P, Tannemaat M, Verschuuren J, Kuhlenbäumer G, Gregersen P, Huijbers M, Stascheit F, Meisel A, Ripke S. Genome-wide meta-analysis of myasthenia gravis uncovers new loci and provides insights into polygenic prediction. Nature Communications 2024, 15: 9839. PMID: 39537604, PMCID: PMC11560923, DOI: 10.1038/s41467-024-53595-6.Peer-Reviewed Original ResearchConceptsPerformance of polygenic risk scoresGenome-wide significant hitsGenome-wide association studiesGenome-wide meta-analysisControls of European ancestryGenetic architecturePolygenic risk scoresSignificant hitsAssociation studiesPhenotypic variationPolygenic predictionEuropean ancestryAssociated with early-onsetHuman leukocyte antigen allelesLociEarly-onsetReplication studyNeuromuscular junctionMyasthenia gravisAutoantibody-mediated diseasesAntigen allelesAllelesAncestryDisease manifestationsLate-onset MGGenome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations
Gelernter J, Levey D, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Program V, Gaziano J, Eliott D, Stein M. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. Cell Genomics 2024, 4: 100582. PMID: 38870908, PMCID: PMC11228954, DOI: 10.1016/j.xgen.2024.100582.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMillion Veteran ProgramRisk lociAssociation studiesTrans-ancestry meta-analysisSignificant risk lociPathway enrichment analysisEpiretinal membraneTrans-ancestryGenome-wideMultiple traitsGenetic associationEnrichment analysisGene expressionEuropean AmericansLoss of visual acuityVeteran ProgramGenetic correlationsLociBiological mechanismsAmerican populationVisual acuityRetinal conditionsControl individualsRetinal surface
2023
Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses
Als T, Kurki M, Grove J, Voloudakis G, Therrien K, Tasanko E, Nielsen T, Naamanka J, Veerapen K, Levey D, Bendl J, Bybjerg-Grauholm J, Zeng B, Demontis D, Rosengren A, Athanasiadis G, Bækved-Hansen M, Qvist P, Bragi Walters G, Thorgeirsson T, Stefánsson H, Musliner K, Rajagopal V, Farajzadeh L, Thirstrup J, Vilhjálmsson B, McGrath J, Mattheisen M, Meier S, Agerbo E, Stefánsson K, Nordentoft M, Werge T, Hougaard D, Mortensen P, Stein M, Gelernter J, Hovatta I, Roussos P, Daly M, Mors O, Palotie A, Børglum A. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nature Medicine 2023, 29: 1832-1844. PMID: 37464041, PMCID: PMC10839245, DOI: 10.1038/s41591-023-02352-1.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphism heritabilityGenome-wide analysisLikely causal genesFunctional genomics dataRisk variantsWide association studyPolygenic burdenPsychiatric disordersCausal genesPolygenic architectureGenomic dataRisk lociAssociation studiesSubgroups of depressionCause of disabilityDepression genetic riskCommon psychiatric disordersPrecision medicine approachCases of depressionOligodendrocyte lineageGenesLociConsiderable sex differencesGABAergic neuronsPsychiatric comorbidityIdentifying genetic loci and phenomic associations of substance use traits: A multi‐trait analysis of GWAS (MTAG) study
Xu H, Toikumo S, Crist R, Glogowska K, Jinwala Z, Deak J, Justice A, Gelernter J, Johnson E, Kranzler H, Kember R. Identifying genetic loci and phenomic associations of substance use traits: A multi‐trait analysis of GWAS (MTAG) study. Addiction 2023, 118: 1942-1952. PMID: 37156939, PMCID: PMC10754226, DOI: 10.1111/add.16229.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSignificant single nucleotide polymorphismsSubstance use traitsMulti-trait analysisAssociation studiesGenetic architectureUse traitsGenome-wide significant single nucleotide polymorphismsProtein-protein interaction analysisTrait genetic architectureNumber of lociPolygenic risk scoresEuropean ancestry individualsNovel lociSingle nucleotide polymorphismsGenetic lociGWAS studiesLociMultiple related phenotypesNucleotide polymorphismsRelated phenotypesTraitsNovel associationsMTAgBiobank samplesMulti-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
Cheng Y, Dao C, Zhou H, Li B, Kember R, Toikumo S, Zhao H, Gelernter J, Kranzler H, Justice A, Xu K. Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program. Translational Psychiatry 2023, 13: 148. PMID: 37147289, PMCID: PMC10162964, DOI: 10.1038/s41398-023-02409-2.Peer-Reviewed Original ResearchConceptsSingle-trait genome-wide association studiesGenome-wide association studiesNovel lociPower of GWASJoint genome-wide association studyGenome-wide significant lociMillion Veteran ProgramGenome-wide associationSubstance use traitsGWAS summary statisticsNovel genetic variantsMulti-trait analysisFunctional annotationUse traitsSignificant lociHeritable traitMultiple lociAssociation studiesColocalization analysisLociPleiotropic effectsMTAgVeteran ProgramGenetic variantsTraitsMulti‐omics cannot replace sample size in genome‐wide association studies
Baranger D, Hatoum A, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multi‐omics cannot replace sample size in genome‐wide association studies. Genes Brain & Behavior 2023, 22: e12846. PMID: 36977197, PMCID: PMC10733567, DOI: 10.1111/gbb.12846.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesNovel genesMulti-omics dataMulti-omics informationAssociation studiesGenome-wide significant lociSmall genome-wide association studyBrain-related traitsGWAS sample sizesEarly genome-wide association studiesNovel gene discoveryGene discoverySignificant lociAdditional genesPositional mappingHeritable traitVariant discoverySimilar traitsGenesNovel variant discoveryTraitsDisease biologyLociDiscoveryMultivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
Hatoum A, Colbert S, Johnson E, Huggett S, Deak J, Pathak G, Jennings M, Paul S, Karcher N, Hansen I, Baranger D, Edwards A, Grotzinger A, Tucker-Drob E, Kranzler H, Davis L, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature Mental Health 2023, 1: 210-223. PMID: 37250466, PMCID: PMC10217792, DOI: 10.1038/s44220-023-00034-y.Peer-Reviewed Original ResearchGenome-wide associationGenetic risk lociIndependent single nucleotide polymorphismsProblematic tobacco useSingle nucleotide polymorphismsRisk lociHigh polygenicityLociReceptor geneAddiction risk factorsPolygenic risk scoresEuropean descentPolygenicityGenesSummary statisticsSubstance use disordersSomatic conditionsAncestryRegulationConfersUse disordersPolymorphismGenetic liabilityDopamine regulationPDE4B
2022
Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond
Gaddis N, Mathur R, Marks J, Zhou L, Quach B, Waldrop A, Levran O, Agrawal A, Randesi M, Adelson M, Jeffries PW, Martin NG, Degenhardt L, Montgomery GW, Wetherill L, Lai D, Bucholz K, Foroud T, Porjesz B, Runarsdottir V, Tyrfingsson T, Einarsson G, Gudbjartsson DF, Webb BT, Crist RC, Kranzler HR, Sherva R, Zhou H, Hulse G, Wildenauer D, Kelty E, Attia J, Holliday EG, McEvoy M, Scott RJ, Schwab SG, Maher BS, Gruza R, Kreek MJ, Nelson EC, Thorgeirsson T, Stefansson K, Berrettini WH, Gelernter J, Edenberg HJ, Bierut L, Hancock DB, Johnson EO. Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond. Scientific Reports 2022, 12: 16873. PMID: 36207451, PMCID: PMC9546890, DOI: 10.1038/s41598-022-21003-y.Peer-Reviewed Original ResearchConceptsGenome-wide significant associationMulti-trait genome-wide association studyNovel genome-wide significant associationsGenome-wide association studiesGenomic structural equationGene-based analysisRelated traitsAssociation studiesGenetic correlationsEuropean ancestryA118G variantConsortium dataNew geneticsG variantGWASPPP6CLociPleiotropicGeneticsVariantsTraitsPhenotypeOA phenotypeFurinAncestryCross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction
Kember RL, Vickers-Smith R, Xu H, Toikumo S, Niarchou M, Zhou H, Hartwell EE, Crist RC, Rentsch CT, Davis L, Justice A, Sanchez-Roige S, Kampman K, Gelernter J, Kranzler H. Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction. Nature Neuroscience 2022, 25: 1279-1287. PMID: 36171425, PMCID: PMC9682545, DOI: 10.1038/s41593-022-01160-z.Peer-Reviewed Original ResearchConceptsOpioid use disorderGenome-wide association studiesWide significant lociGene expression enrichmentSignificant genetic correlationsCell type groupSignificant lociAssociation studiesExpression enrichmentMillion Veteran ProgramGenetic correlationsUse disordersLociBrain regionsExonic variantsIntronic variantsSubstance use disordersTraitsBiological basisOpioid epidemicPsychiatric disordersVeteran ProgramBrain diseasesTSNARE1FBXW4Sex-Specific Genetic and Transcriptomic Liability to Neuroticism
Wendt FR, Pathak GA, Singh K, Stein MB, Koenen KC, Krystal JH, Gelernter J, Davis LK, Polimanti R. Sex-Specific Genetic and Transcriptomic Liability to Neuroticism. Biological Psychiatry 2022, 93: 243-252. PMID: 36244801, PMCID: PMC10508260, DOI: 10.1016/j.biopsych.2022.07.019.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesTranscriptomic profilesAssociation studiesSingle nucleotide polymorphism heritabilityGene expression variationGenome-wide significanceSex-specific geneticChromosomal variationTranscriptomic changesRisk lociExpression variationBiological processesMolecular pathwaysLociPolygenic associationSex-specific effectsGenetic correlatesPolygenic scoresUK BiobankGenetic riskNCOA6GeneticsHeritabilityPathwayFemalesGenome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways
Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds D, Gelernter J, Levey D, Polimanti R, Stein M, Van Someren E, Smit A, Posthuma D. Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. Nature Genetics 2022, 54: 1125-1132. PMID: 35835914, DOI: 10.1038/s41588-022-01124-w.Peer-Reviewed Original ResearchConceptsRisk lociGenome-wide association studiesSpecific gene setsPrevious genome-wide association studyGene prioritization strategyExternal biological resourcesExtreme polygenicityExpression specificityAssociated lociSignaling functionsGene setsAssociation studiesNeuronal differentiationFunctional interactionGenesLociBiological resourcesPolygenicityNovel strategyPrioritization strategiesSpecific hypothesesDifferentiationPathwayStatistical powerLarge numberUsing 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 Research
2021
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Mullins N, Kang J, Campos AI, Coleman JRI, Edwards AC, Galfalvy H, Levey DF, Lori A, Shabalin A, Starnawska A, Su MH, Watson HJ, Adams M, Awasthi S, Gandal M, Hafferty JD, Hishimoto A, Kim M, Okazaki S, Otsuka I, Ripke S, Ware EB, Bergen AW, Berrettini WH, Bohus M, Brandt H, Chang X, Chen WJ, Chen HC, Crawford S, Crow S, DiBlasi E, Duriez P, Fernández-Aranda F, Fichter MM, Gallinger S, Glatt SJ, Gorwood P, Guo Y, Hakonarson H, Halmi KA, Hwu HG, Jain S, Jamain S, Jiménez-Murcia S, Johnson C, Kaplan AS, Kaye WH, Keel PK, Kennedy JL, Klump KL, Li D, Liao SC, Lieb K, Lilenfeld L, Liu CM, Magistretti PJ, Marshall CR, Mitchell JE, Monson ET, Myers RM, Pinto D, Powers A, Ramoz N, Roepke S, Rozanov V, Scherer SW, Schmahl C, Sokolowski M, Strober M, Thornton LM, Treasure J, Tsuang MT, Witt SH, Woodside DB, Yilmaz Z, Zillich L, Adolfsson R, Agartz I, Air TM, Alda M, Alfredsson L, Andreassen OA, Anjorin A, Appadurai V, Artigas M, Van der Auwera S, Azevedo MH, Bass N, Bau CHD, Baune BT, Bellivier F, Berger K, Biernacka JM, Bigdeli TB, Binder EB, Boehnke M, Boks MP, Bosch R, Braff DL, Bryant R, Budde M, Byrne EM, Cahn W, Casas M, Castelao E, Cervilla JA, Chaumette B, Cichon S, Corvin A, Craddock N, Craig D, Degenhardt F, Djurovic S, Edenberg HJ, Fanous AH, Foo JC, Forstner AJ, Frye M, Fullerton JM, Gatt JM, Gejman PV, Giegling I, Grabe HJ, Green MJ, Grevet EH, Grigoroiu-Serbanescu M, Gutierrez B, Guzman-Parra J, Hamilton SP, Hamshere ML, Hartmann A, Hauser J, Heilmann-Heimbach S, Hoffmann P, Ising M, Jones I, Jones LA, Jonsson L, Kahn RS, Kelsoe JR, Kendler KS, Kloiber S, Koenen KC, Kogevinas M, Konte B, Krebs MO, Landén M, Lawrence J, Leboyer M, Lee PH, Levinson DF, Liao C, Lissowska J, Lucae S, Mayoral F, McElroy SL, McGrath P, McGuffin P, McQuillin A, Medland SE, Mehta D, Melle I, Milaneschi Y, Mitchell PB, Molina E, Morken G, Mortensen PB, Müller-Myhsok B, Nievergelt C, Nimgaonkar V, Nöthen MM, O’Donovan M, Ophoff RA, Owen MJ, Pato C, Pato MT, Penninx BWJH, Pimm J, Pistis G, Potash JB, Power RA, Preisig M, Quested D, Ramos-Quiroga JA, Reif A, Ribasés M, Richarte V, Rietschel M, Rivera M, Roberts A, Roberts G, Rouleau GA, Rovaris DL, Rujescu D, Sánchez-Mora C, Sanders AR, Schofield PR, Schulze TG, Scott LJ, Serretti A, Shi J, Shyn SI, Sirignano L, Sklar P, Smeland OB, Smoller JW, Sonuga-Barke EJS, Spalletta G, Strauss JS, Świątkowska B, Trzaskowski M, Turecki G, Vilar-Ribó L, Vincent JB, Völzke H, Walters JTR, Weickert C, Weickert TW, Weissman MM, Williams LM, Wray NR, Zai CC, Ashley-Koch AE, Beckham JC, Hauser ER, Hauser MA, Kimbrel NA, Lindquist JH, McMahon B, Oslin DW, Qin X, Agerbo E, Børglum A, Breen G, Erlangsen A, Esko T, Gelernter J, Hougaard D, Kessler R, Kranzler H, Li Y, Martin N, McIntosh A, Mors O, Nordentoft M, Olsen C, Porteous D, Ursano R, Wasserman D, Werge T, Whiteman D, Bulik C, Coon H, Demontis D, Docherty A, Kuo P, Lewis G, Mann J, Rentería M, Smith D, Stahl E, Stein D, Streit F, Willour V, Ruderfer D, Wray N, Ripke S, Mattheisen M, Trzaskowski M, Byrne E, Abdellaoui A, Adams M, Agerbo E, Air T, Andlauer T, Bacanu S, Bækvad-Hansen M, Beekman A, Bigdeli T, Binder E, Bryois J, Buttenschøn H, Bybjerg-Grauholm J, Cai N, Castelao E, Christensen J, Clarke T, Coleman J, Colodro-Conde L, Couvy-Duchesne B, Craddock N, Crawford G, Davies G, Degenhardt F, Derks E, Direk N, Dolan C, Dunn E, Eley T, Escott-Price V, Kiadeh F, Finucane H, Foo J, Forstner A, Frank J, Gaspar H, Gill M, Goes F, Gordon S, Weinsheimer S, Wellmann J, Willemsen G, Witt S, Wu Y, Xi H, Yang J, Zhang F, Arolt V, Baune B, Berger K, Boomsma D, Cichon S, Dannlowski U, de Geus E, Depaulo J, Domenici E, Domschke K, Esko T, Grabe H, Hamilton S, Grove J, Hall L, Hansen C, Hansen T, Herms S, Hickie I, Hoffmann P, Homuth G, Horn C, Hottenga J, Hougaard D, Howard D, Ising M, Jansen R, Jones I, Jones L, Jorgenson E, Knowles J, Kohane I, Kraft J, Kretzschmar W, Kutalik Z, Li Q, Lind P, MacIntyre D, MacKinnon D, Maier R, Maier W, Marchini J, Mbarek H, McGrath P, McGuffin P, Medland S, Mehta D, Middeldorp C, Mihailov E, Milaneschi Y, Milani L, Mondimore F, Montgomery G, Mostafavi S, Mullins N, Nauck M, Ng B, Nivard M, Nyholt D, O’Reilly P, Oskarsson H, Hayward C, Heath A, Kendler K, Kloiber S, Lewis C, Li D, Lucae S, Madden P, Magnusson P, Martin N, McIntosh A, Metspalu A, Mors O, Mortensen P, Müller-Myhsok B, Nordentoft M, Nöthen M, O’Donovan M, Paciga S, Pedersen N, Owen M, Painter J, Pedersen C, Pedersen M, Peterson R, Peyrot W, Pistis G, Posthuma D, Quiroz J, Qvist P, Rice J, Riley B, Rivera M, Mirza S, Schoevers R, Schulte E, Shen L, Shi J, Shyn S, Sigurdsson E, Sinnamon G, Smit J, Smith D, Stefansson H, Steinberg S, Streit F, Strohmaier J, Tansey K, Teismann H, Teumer A, Thompson W, Thomson P, Thorgeirsson T, Traylor M, Treutlein J, Trubetskoy V, Uitterlinden A, Umbricht D, Van der Auwera S, van Hemert A, Viktorin A, Visscher P, Wang Y, Webb B, Penninx B, Perlis R, Porteous D, Potash J, Preisig M, Rietschel M, Schaefer C, Schulze T, Smoller J, Stefansson K, Tiemeier H, Uher R, Völzke H, Weissman M, Werge T, Lewis C, Levinson D, Breen G, Børglum A, Sullivan P, Mullins N, Forstner A, O’Connell K, Coombes B, Coleman J, Qiao Z, Als T, Bigdeli T, Børte S, Bryois J, Charney A, Drange O, Gandal M, Hagenaars S, Ikeda M, Kamitaki N, Kim M, Krebs K, Panagiotaropoulou G, Schilder B, Sloofman L, Steinberg S, Trubetskoy V, Winsvold B, Won H, Abramova L, Adorjan K, Agerbo E, Al Eissa M, Albani D, Alliey-Rodriguez N, Anjorin A, Antilla V, Antoniou A, Awasthi S, Baek J, Bækvad-Hansen M, Bass N, Bauer M, Beins E, Bergen S, Birner A, Pedersen C, Bøen E, Boks M, Bosch R, Brum M, Brumpton B, Brunkhorst-Kanaan N, Budde M, Bybjerg-Grauholm J, Byerley W, Cairns M, Casas M, Cervantes P, Clarke T, Cruceanu C, Cuellar-Barboza A, Cunningham J, Curtis D, Czerski P, Dale A, Dalkner N, David F, Degenhardt F, Djurovic S, Dobbyn A, Douzenis A, Elvsåshagen T, Escott-Price V, Ferrier I, Fiorentino A, Foroud T, Forty L, Frank J, Frei O, Freimer N, 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Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors. Biological Psychiatry 2021, 91: 313-327. PMID: 34861974, PMCID: PMC8851871, DOI: 10.1016/j.biopsych.2021.05.029.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenetic architecturePsychiatric disordersGenetic correlationsRisk factorsGenome-wide significanceDivergent genetic architecturesGWAS summary statisticsShared genetic architectureStrong genetic correlationIntergenic lociSuicide attemptsReproductive traitsKnown Risk FactorsRisk lociPoor general healthChromosome 7Association studiesRelated psychiatric disordersMillion Veteran ProgramSuicide attempt casesLow socioeconomic statusLociNonfatal suicide attemptsGenetic effects