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 ResearchMeSH KeywordsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMarijuana AbusePolymorphism, Single NucleotidePublic HealthRacial GroupsVeteransConceptsSingle 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 ResearchMeSH KeywordsAdultGenome-Wide Association StudyHumansMendelian Randomization AnalysisPhenotypePolymorphism, Single NucleotideSleepSleep DurationConceptsAssociation studiesGenome-wide association studiesGenetic correlationsWide association studyLinkage disequilibrium scorePositive genetic correlationSleep traitsIndependent lociMillion Veteran ProgramTraitsAncestryUK BiobankVeteran ProgramMendelian randomisationLociHeritabilitySNPsPhenotypeEast AsiansSimilar patternCardiometabolic phenotypesMulti-ancestry study of the genetics of problematic alcohol use in over 1 million individuals
Zhou H, Kember R, Deak J, Xu H, Toikumo S, Yuan K, Lind P, Farajzadeh L, Wang L, Hatoum A, Johnson J, Lee H, Mallard T, Xu J, Johnston K, Johnson E, Nielsen T, Galimberti M, Dao C, Levey D, Overstreet C, Byrne E, Gillespie N, Gordon S, Hickie I, Whitfield J, Xu K, Zhao H, Huckins L, Davis L, Sanchez-Roige S, Madden P, Heath A, Medland S, Martin N, Ge T, Smoller J, Hougaard D, Børglum A, Demontis D, Krystal J, Gaziano J, Edenberg H, Agrawal A, Justice A, Stein M, Kranzler H, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. Nature Medicine 2023, 29: 3184-3192. PMID: 38062264, PMCID: PMC10719093, DOI: 10.1038/s41591-023-02653-5.Peer-Reviewed Original ResearchAlcoholismGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideRacial GroupsGenome-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 ResearchMeSH KeywordsAlcoholismBlack PeopleFurinGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansOpioid-Related DisordersPhenotypePolymorphism, Single NucleotideWhite PeopleConceptsGenome-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 oneGenome-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 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 ResearchMeSH KeywordsAdultAgedAged, 80 and overAlcohol DrinkingAlcoholismFemaleGenome-Wide Association StudyHumansLongitudinal StudiesMaleMiddle AgedMultifactorial InheritancePhenotypePolymorphism, Single NucleotideYoung AdultConceptsGenome-wide association studiesAssociation studiesMillion Veteran Program sampleGenetic correlationsWide significant lociSignificant genetic correlationsPolygenic risk scoresCell type groupSignificant lociHeritable traitEnrichment analysisTraitsMultiple populationsLociPhenotypeProgram samplesUnderstanding the comorbidity between posttraumatic stress severity and coronary artery disease using genome-wide information and electronic health records
Polimanti R, Wendt FR, Pathak GA, Tylee DS, Tcheandjieu C, Hilliard AT, Levey DF, Adhikari K, Gaziano JM, O’Donnell C, Assimes TL, Stein MB, Gelernter J. Understanding the comorbidity between posttraumatic stress severity and coronary artery disease using genome-wide information and electronic health records. Molecular Psychiatry 2022, 27: 3961-3969. PMID: 35986173, PMCID: PMC10986859, DOI: 10.1038/s41380-022-01735-z.Peer-Reviewed Original ResearchMeSH KeywordsComorbidityCoronary Artery DiseaseElectronic Health RecordsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideRisk FactorsStress Disorders, Post-TraumaticConceptsCoronary artery diseasePosttraumatic stress disorderElectronic health recordsMillion Veteran ProgramArtery diseaseTotal scoreCAD diagnosisPlatelet amyloid precursor proteinHealth recordsPosttraumatic stress severityAmyloid precursor proteinEarly CAD diagnosisUK BiobankBidirectional relationshipTwo-sample Mendelian randomization (MR) analysisMendelian randomization analysisCAD riskHigh morbidityPTSD symptom severityCARDIoGRAMplusC4D consortiumPleiotropic mechanismsSymptom severityLongitudinal changesDiscordant effectsStress disorder
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 MGDiversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Verma A, Huffman J, Rodriguez A, Conery M, Liu M, Ho Y, Kim Y, Heise D, Guare L, Panickan V, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner D, Sangar R, Murray M, Wang X, Dochtermann D, Devineni P, Shi Y, Nandi T, Assimes T, Brunette C, Carroll R, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar S, Joseph J, Kember R, Kranzler H, Kripke C, Levey D, Luoh S, Merritt V, Overstreet C, Deak J, Grant S, Polimanti R, Roussos P, Shakt G, Sun Y, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell C, Muralidhar S, Moser J, Casas J, Bick A, Zhou W, Cai T, Voight B, Cho K, Gaziano J, Madduri R, Damrauer S, Liao K. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 2024, 385: eadj1182. PMID: 39024449, DOI: 10.1126/science.adj1182.Peer-Reviewed Original ResearchConceptsMillion Veteran ProgramNon-European populationsVeteran ProgramGenetic architectureAtlas of genetic associationsVeterans Affairs Million Veteran ProgramVA Million Veteran ProgramGenomic risk lociGenome-wide associationHuman genetic studiesHealth disparitiesUnited States veteransCausal variantsRisk lociGenetic insightsGenetic studiesGenetic associationGenetic causeStates veteransDiverse populationsDisease factorsLack of inclusionLongitudinal studyParticipantsTraitsGenome-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 surfaceA phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals
Jennings M, Martínez-Magaña J, Courchesne-Krak N, Cupertino R, Vilar-Ribó L, Bianchi S, Hatoum A, Atkinson E, Giusti-Rodriguez P, Montalvo-Ortiz J, Gelernter J, Artigas M, 23andMe I, Aslibekyan S, Auton A, Babalola E, Bell R, Bielenberg J, Bryc K, Bullis E, Coker D, Partida G, Dhamija D, Das S, Elson S, Eriksson N, Filshtein T, Fitch A, Fletez-Brant K, Fontanillas P, Freyman W, Granka J, Heilbron K, Hernandez A, Hicks B, Hinds D, Jewett E, Jiang Y, Kukar K, Kwong A, Lin K, Llamas B, Lowe M, McCreight J, McIntyre M, Micheletti S, Moreno M, Nandakumar P, Nguyen D, Noblin E, O'Connell J, Petrakovitz A, Poznik G, Reynoso A, Schumacher M, Shastri A, Shelton J, Shi J, Shringarpure S, Su Q, Tat S, Tchakouté C, Tran V, Tung J, Wang X, Wang W, Weldon C, Wilton P, Wong C, Elson S, Edenberg H, Fontanillas P, Palmer A, Sanchez-Roige S. A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals. EBioMedicine 2024, 103: 105086. PMID: 38580523, PMCID: PMC11121167, DOI: 10.1016/j.ebiom.2024.105086.Peer-Reviewed Original ResearchConceptsMultiple domains of healthDomains of healthEffects of alcohol consumptionAlcohol consumptionHealth outcomesPhenome-wide association studyAlcohol-related behaviorsCardio-metabolic healthPotential causal effectMendelian randomisation studiesGenome-wide association studiesPhenome-wide associationMR analysisPheWAS associationsMultiple domainsHypothesis-free approachPreventive medicineDiverse cohortPheWASAssociation studiesHealthReproductive healthAlcohol behaviorConsequences of drinkingEuropean cohort
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 ResearchMeSH KeywordsAttention Deficit Disorder with HyperactivityBipolar DisorderDepressionFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMalePolymorphism, Single NucleotideSchizophreniaConceptsSingle 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 comorbidityModeling the longitudinal changes of ancestry diversity in the Million Veteran Program
Wendt F, Pathak G, Vahey J, Qin X, Koller D, Cabrera-Mendoza B, Haeny A, Harrington K, Rajeevan N, Duong L, Levey D, De Angelis F, De Lillo A, Bigdeli T, Pyarajan S, Gaziano J, Gelernter J, Aslan M, Provenzale D, Helmer D, Hauser E, Polimanti R. Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program. Human Genomics 2023, 17: 46. PMID: 37268996, PMCID: PMC10239111, DOI: 10.1186/s40246-023-00487-3.Peer-Reviewed Original ResearchIdentifying 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 ResearchMeSH KeywordsAlcoholismGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenomicsPhenotypePolymorphism, Single NucleotideConceptsGenome-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 ResearchMeSH KeywordsAlcohol DrinkingAlcoholismGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideSmokingVeteransConceptsSingle-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 ResearchMeSH KeywordsGene Expression ProfilingGenome-Wide Association StudyMultiomicsPhenotypePolymorphism, Single NucleotideSample SizeConceptsGenome-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 biologyLociDiscoveryIdentification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans
Kimbrel N, Ashley-Koch A, Qin X, Lindquist J, Garrett M, Dennis M, Hair L, Huffman J, Jacobson D, Madduri R, Trafton J, Coon H, Docherty A, Mullins N, Ruderfer D, Harvey P, McMahon B, Oslin D, Beckham J, Hauser E, Hauser M, Agarwal K, Ashley-Koch A, Aslan M, Beckham J, Begoli E, Bhattacharya T, Brown B, Calhoun P, Cheung K, Choudhury S, Cliff A, Cohn J, Crivelli S, Cuellar-Hengartner L, Deangelis H, Dennis M, Dhaubhadel S, Finley P, Ganguly K, Garvin M, Gelernter J, Hair L, Harvey P, Hauser E, Hauser M, Hengartner N, Jacobson D, Jones P, Kainer D, Kaplan A, Katz I, Kember R, Kimbrel N, Kirby A, Ko J, Kolade B, Lagergren J, Lane M, Levey D, Levin D, Lindquist J, Liu X, Madduri R, Manore C, Martins S, McCarthy J, McDevitt-Cashman M, McMahon B, Miller I, Morrow D, Oslin D, Pavicic-Venegas M, Pestian J, Pyarajan S, Qin X, Rajeevan N, Ramsey C, Ribeiro R, Rodriguez A, Romero J, Santel D, Schaefferkoetter N, Shi Y, Stein M, Sullivan K, Sun N, Tamang S, Townsend A, Trafton J, Walker A, Wang X, Wangia-Anderson V, Yang R, Yoon H, Yoo S, Zamora-Resendiz R, Zhao H, Docherty A, Mullins N, Coleman J, Shabalin A, Kang J, Murnyak B, Wendt F, Adams M, Campos A, DiBlasi E, Fullerton J, Kranzler H, Bakian A, Monson E, Rentería M, Andreassen O, Bulik C, Edenberg H, Kessler R, Mann J, Nurnberger J, Pistis G, Streit F, Ursano R, Awasthi S, Bergen A, Berrettini W, Bohus M, Brandt H, Chang X, Chen H, Chen W, Christensen E, Crawford S, Crow S, Duriez P, Edwards A, Fernández-Aranda F, Fichter M, Galfalvy H, Gallinger S, Gandal M, Gorwood P, Guo Y, Hafferty J, Hakonarson H, Halmi K, Hishimoto A, Jain S, Jamain S, Jiménez-Murcia S, Johnson C, Kaplan A, Kaye W, Keel P, Kennedy J, Kim M, Klump K, Levey D, Li D, Liao S, Lieb K, Lilenfeld L, Lori A, Magistretti P, Marshall C, Mitchell J, Myers R, Okazaki S, Otsuka I, Pinto D, Powers A, Ramoz N, Ripke S, Roepke S, Rozanov V, Scherer S, Schmahl C, Sokolowski M, Starnawska A, Strober M, Su M, Thornton L, Treasure J, Ware E, Watson H, Witt S, Woodside D, Yilmaz Z, Zillich L, Agerbo E, Børglum A, Breen G, Demontis D, Erlangsen A, Esko T, Gelernter J, Glatt S, Hougaard D, Hwu H, Kuo P, Lewis C, Li Q, Liu C, Martin N, McIntosh A, Medland S, Mors O, Nordentoft M, Nurnberger J, Olsen C, Porteous D, Smith D, Stahl E, Stein M, Wasserman D, Werge T, Whiteman D, Willour V, Coon H, Ruderfer D, Dedert E, Elbogen E, Fairbank J, Hurley R, Kilts J, Martindale S, Marx C, McDonald S, Moore S, Morey R, Naylor J, Rowland J, Shura R, Swinkels C, Tupler L, Van Voorhees E, Yoash-Gantz R, Gaziano J, Muralidhar S, Ramoni R, Chang K, O’Donnell C, Tsao P, Breeling J, Hauser E, Sun Y, Huang G, Casas J, Moser J, Whitbourne S, Brewer J, Conner T, Argyres D, Stephens B, Brophy M, Humphries D, Selva L, Do N, Shayan S, Cho K, Churby L, Wilson P, McArdle R, Dellitalia L, Mattocks K, Harley J, Whittle J, Jacono F, Wells J, Gutierrez S, Gibson G, Hammer K, Kaminsky L, Villareal G, Kinlay S, Xu J, Hamner M, Mathew R, Bhushan S, Iruvanti P, Godschalk M, Ballas Z, Ivins D, Mastorides S, Moorman J, Gappy S, Klein J, Ratcliffe N, Florez H, Okusaga O, Murdoch M, Sriram P, Yeh S, Tandon N, Jhala D, Liangpunsakul S, Oursler K, Whooley M, Ahuja S, Constans J, Meyer P, Greco J, Rauchman M, Servatius R, Gaddy M, Wallbom A, Morgan T, Stapley T, Sherman S, Ross G, Strollo P, Boyko E, Meyer L, Gupta S, Huq M, Fayad J, Hung A, Lichy J, Hurley R, Robey B, Striker R. Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans. JAMA Psychiatry 2023, 80: 135-145. PMID: 36515925, PMCID: PMC9857322, DOI: 10.1001/jamapsychiatry.2022.3896.Peer-Reviewed Original ResearchConceptsMolecular genetic basisRisk lociSingle nucleotide variantsGWS lociGenetic basisGenomic risk lociRisk genesGenome-wide association studiesSignificant enrichmentGene-based analysisGenetic risk lociCandidate risk genesCyclic adenosine monophosphate (cAMP) signalingIdentification of novelPolygenic risk score analysisGene clusterFocal adhesionsGenetic substructureUbiquitination processChromosome 2Enrichment analysisAssociation studiesAxon guidanceAfrican ancestryNCAM1-TTC12
2022
Genetic variants associated with psychiatric disorders are enriched at epigenetically active sites in lymphoid cells
Lynall ME, Soskic B, Hayhurst J, Schwartzentruber J, Levey DF, Pathak GA, Polimanti R, Gelernter J, Stein MB, Trynka G, Clatworthy MR, Bullmore E. Genetic variants associated with psychiatric disorders are enriched at epigenetically active sites in lymphoid cells. Nature Communications 2022, 13: 6102. PMID: 36243721, PMCID: PMC9569335, DOI: 10.1038/s41467-022-33885-7.Peer-Reviewed Original ResearchMeSH KeywordsCatalytic DomainGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLymphocytesMental DisordersPolymorphism, Single NucleotideSchizophreniaConceptsMultiple psychiatric disordersPsychiatric disordersPsychiatric risk variantT cellsLymphoid cellsRisk variantsImmune cell subsetsMental health disordersMultiple organ systemsAdaptive immune systemCell subsetsImmune cellsHealth disordersMyeloid cellsImmune systemBrain tissueOrgan systemsSpecific disordersDisordersPathogenesisAbnormalitiesGenetic variantsCellsCD4VariantsMulti-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 ResearchMeSH KeywordsFurinGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansOpioid-Related DisordersPhenotypePolymorphism, Single NucleotideReceptors, Opioid, muConceptsGenome-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 phenotypeFurinAncestryIntegrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits
Toikumo S, Xu H, Gelernter J, Kember RL, Kranzler HR. Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits. Neuropsychopharmacology 2022, 47: 2292-2299. PMID: 35941285, PMCID: PMC9630289, DOI: 10.1038/s41386-022-01406-1.Peer-Reviewed Original ResearchMeSH KeywordsBrainGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansOpioid-Related DisordersPhenotypePolymorphism, Single NucleotideProteomicsTranscriptomeConceptsSubstance use traitsProteome-wide association studyUse traitsProtein abundanceAssociation studiesBrain protein abundanceWide association studyGenome-wide association study summary statisticsHuman brain proteomeFine-mapping analysisGenetic risk lociBrain transcriptomic dataEuropean ancestry individualsOpioid use disorderProteomic abundanceTranscriptomic levelTranscriptomic dataAlcohol use disorderProteomic dataBrain proteomeGenetic lociTranscript levelsRisk lociGene expressionSignificant genes