Featured Publications
Bi-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 factorsRegionSubdomainsEnrichment
2024
Genome-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
2022
Integrating 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 ResearchConceptsSubstance 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
2021
Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder
Johnson EC, Kapoor M, Hatoum AS, Zhou H, Polimanti R, Wendt FR, Walters RK, Lai D, Kember RL, Hartz S, Meyers JL, Peterson RE, Ripke S, Bigdeli TB, Fanous AH, Pato CN, Pato MT, Goate AM, Kranzler HR, O'Donovan MC, Walters JTR, Gelernter J, Edenberg HJ, Agrawal A. Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder. Psychological Medicine 2021, 53: 1196-1204. PMID: 34231451, PMCID: PMC8738774, DOI: 10.1017/s003329172100266x.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant single nucleotide polymorphismsLarge-scale genome-wide association studiesSignificant single nucleotide polymorphismsIndependent genome-wide significant single nucleotide polymorphismsSignificant genetic correlationsGenomic regionsSingle nucleotide polymorphismsGene expressionGenetic covariancePleiotropic associationsAssociation studiesGenetic correlationsGenetic variantsNucleotide polymorphismsGenetic overlapDisorder-specific effectsAlcohol use disorderGenetic influencesGenesUse disordersGenome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
Mullins N, Forstner AJ, O’Connell K, Coombes B, Coleman JRI, Qiao Z, Als TD, Bigdeli TB, Børte S, Bryois J, Charney AW, Drange OK, Gandal MJ, Hagenaars SP, Ikeda M, Kamitaki N, Kim M, Krebs K, Panagiotaropoulou G, Schilder BM, Sloofman LG, Steinberg S, Trubetskoy V, Winsvold BS, Won HH, Abramova L, Adorjan K, Agerbo E, Al Eissa M, Albani D, Alliey-Rodriguez N, Anjorin A, Antilla V, Antoniou A, Awasthi S, Baek JH, Bækvad-Hansen M, Bass N, Bauer M, Beins EC, Bergen SE, Birner A, Bøcker Pedersen C, Bøen E, Boks MP, Bosch R, Brum M, Brumpton BM, Brunkhorst-Kanaan N, Budde M, Bybjerg-Grauholm J, Byerley W, Cairns M, Casas M, Cervantes P, Clarke TK, Cruceanu C, Cuellar-Barboza A, Cunningham J, Curtis D, Czerski PM, Dale AM, Dalkner N, David FS, Degenhardt F, Djurovic S, Dobbyn AL, Douzenis A, Elvsåshagen T, Escott-Price V, Ferrier IN, Fiorentino A, Foroud TM, Forty L, Frank J, Frei O, Freimer NB, Frisén L, Gade K, Garnham J, Gelernter J, Giørtz Pedersen M, Gizer IR, Gordon SD, Gordon-Smith K, Greenwood TA, Grove J, Guzman-Parra J, Ha K, Haraldsson M, Hautzinger M, Heilbronner U, Hellgren D, Herms S, Hoffmann P, Holmans PA, Huckins L, Jamain S, Johnson JS, Kalman JL, Kamatani Y, Kennedy JL, Kittel-Schneider S, Knowles JA, Kogevinas M, Koromina M, Kranz TM, Kranzler HR, Kubo M, Kupka R, Kushner SA, Lavebratt C, Lawrence J, Leber M, Lee HJ, Lee PH, Levy SE, Lewis C, Liao C, Lucae S, Lundberg M, MacIntyre DJ, Magnusson SH, Maier W, Maihofer A, Malaspina D, Maratou E, Martinsson L, Mattheisen M, McCarroll SA, McGregor NW, McGuffin P, McKay JD, Medeiros H, Medland SE, Millischer V, Montgomery GW, Moran JL, Morris DW, Mühleisen TW, O’Brien N, O’Donovan C, Olde Loohuis LM, Oruc L, Papiol S, Pardiñas AF, Perry A, Pfennig A, Porichi E, Potash JB, Quested D, Raj T, Rapaport MH, DePaulo JR, Regeer EJ, Rice JP, Rivas F, Rivera M, Roth J, Roussos P, Ruderfer DM, Sánchez-Mora C, Schulte EC, Senner F, Sharp S, Shilling PD, Sigurdsson E, Sirignano L, Slaney C, Smeland OB, Smith DJ, Sobell JL, Søholm Hansen C, Soler Artigas M, Spijker AT, Stein DJ, Strauss JS, Świątkowska B, Terao C, Thorgeirsson TE, Toma C, Tooney P, Tsermpini EE, Vawter MP, Vedder H, Walters JTR, Witt SH, Xi S, Xu W, Yang JMK, Young AH, Young H, Zandi PP, Zhou H, Zillich L, Adolfsson R, Agartz I, Alda M, Alfredsson L, Babadjanova G, Backlund L, Baune B, Bellivier F, Bengesser S, Berrettini W, Blackwood D, Boehnke M, Børglum A, Breen G, Carr V, Catts S, Corvin A, Craddock N, Dannlowski U, Dikeos D, Esko T, Etain B, Ferentinos P, Frye M, Fullerton J, Gawlik M, Gershon E, Goes F, Green M, Grigoroiu-Serbanescu M, Hauser J, Henskens F, Hillert J, Hong K, Hougaard D, Hultman C, Hveem K, Iwata N, Jablensky A, Jones I, Jones L, Kahn R, Kelsoe J, Kirov G, Landén M, Leboyer M, Lewis C, Li Q, Lissowska J, Lochner C, Loughland C, Martin N, Mathews C, Mayoral F, McElroy S, McIntosh A, McMahon F, Melle I, Michie P, Milani L, Mitchell P, Morken G, Mors O, Mortensen P, Mowry B, Müller-Myhsok B, Myers R, Neale B, Nievergelt C, Nordentoft M, Nöthen M, O’Donovan M, Oedegaard K, Olsson T, Owen M, Paciga S, Pantelis C, Pato C, Pato M, Patrinos G, Perlis R, Posthuma D, Ramos-Quiroga J, Reif A, Reininghaus E, Ribasés M, Rietschel M, Ripke S, Rouleau G, Saito T, Schall U, Schalling M, Schofield P, Schulze T, Scott L, Scott R, Serretti A, Shannon Weickert C, Smoller J, Stefansson H, Stefansson K, Stordal E, Streit F, Sullivan P, Turecki G, Vaaler A, Vieta E, Vincent J, Waldman I, Weickert T, Werge T, Wray N, Zwart J, Biernacka J, Nurnberger J, Cichon S, Edenberg H, Stahl E, McQuillin A, Di Florio A, Ophoff R, Andreassen O. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nature Genetics 2021, 53: 817-829. PMID: 34002096, PMCID: PMC8192451, DOI: 10.1038/s41588-021-00857-4.Peer-Reviewed Original ResearchConceptsAssociation studiesQuantitative trait loci dataExpression quantitative trait loci (eQTL) dataGenome-wide association studiesBipolar disorder casesBrain-expressed genesWide association studyHeritable mental illnessSynaptic signaling pathwaysGenomic lociTargets of antipsychoticsLoci dataImperfect genetic correlationGene expressionSignaling pathwaysFunctional followGenesGenetic correlationsDruggable targetsSignal enrichmentEuropean ancestryLociBipolar disorder risk allelesNew insightsTherapeutic leads
2020
Transcriptomic organization of the human brain in post-traumatic stress disorder
Girgenti MJ, Wang J, Ji D, Cruz DA, Stein M, Gelernter J, Young K, Huber B, Williamson D, Friedman M, Krystal J, Zhao H, Duman R. Transcriptomic organization of the human brain in post-traumatic stress disorder. Nature Neuroscience 2020, 24: 24-33. PMID: 33349712, DOI: 10.1038/s41593-020-00748-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultAutopsyBrain ChemistryCohort StudiesDepressive Disorder, MajorFemaleGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInterneuronsMaleMiddle AgedNerve Tissue ProteinsSex CharacteristicsStress Disorders, Post-TraumaticTranscriptomeYoung AdultConceptsGenome-wide association studiesSignificant gene networksDifferential gene expressionSystems-level evidenceSignificant genetic liabilityMajor depressive disorder cohortGene networksTranscriptomic organizationTranscriptomic landscapeDownregulated setsGenomic networksGene expressionAssociation studiesMolecular determinantsExtensive remodelingGenotype dataSexual dimorphismSignificant divergenceMolecular profileNetwork analysisELFN1TranscriptsDimorphismPostmortem tissueDivergenceExpanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits
Quach BC, Bray MJ, Gaddis NC, Liu M, Palviainen T, Minica CC, Zellers S, Sherva R, Aliev F, Nothnagel M, Young KA, Marks JA, Young H, Carnes MU, Guo Y, Waldrop A, Sey NYA, Landi MT, McNeil DW, Drichel D, Farrer LA, Markunas CA, Vink JM, Hottenga JJ, Iacono WG, Kranzler HR, Saccone NL, Neale MC, Madden P, Rietschel M, Marazita ML, McGue M, Won H, Winterer G, Grucza R, Dick DM, Gelernter J, Caporaso NE, Baker TB, Boomsma DI, Kaprio J, Hokanson JE, Vrieze S, Bierut LJ, Johnson EO, Hancock DB. Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits. Nature Communications 2020, 11: 5562. PMID: 33144568, PMCID: PMC7642344, DOI: 10.1038/s41467-020-19265-z.Peer-Reviewed Original ResearchConceptsGenome-wide significant lociGenome-wide association studiesNearby gene expressionExpression of genesSmoking traitsGenetic architectureSignificant lociGenetic variationMultiple traitsGene expressionAssociation studiesLociTraitsGenetic knowledgeComposite phenotypeUK BiobankExpressionTENM2GNAI1GenesGeneticsVariantsPhenotypeReproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program
Levey DF, Gelernter J, Polimanti R, Zhou H, Cheng Z, Aslan M, Quaden R, Concato J, Radhakrishnan K, Bryois J, Sullivan PF, Stein M. Reproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program. American Journal Of Psychiatry 2020, 177: 223-232. PMID: 31906708, PMCID: PMC7869502, DOI: 10.1176/appi.ajp.2019.19030256.Peer-Reviewed Original ResearchConceptsNovel genome-wide significant associationsGene expressionGenome-wide significant signalsGenome-wide significant associationMillion Veteran ProgramWide association studyGenetic risk lociSignificant genetic correlationsGenetic risk mechanismsGenetic architectureGlobal regulatorChromosome 3Risk lociChromosome 6Chromosome 7Association studiesLargest GWASLarge biobanksGlobal regulationGenetic correlationsContinuous traitsVeteran ProgramGWASsLociPrevious GWASs
2019
Alcohol-responsive genes identified in human iPSC-derived neural cultures
Jensen KP, Lieberman R, Kranzler HR, Gelernter J, Clinton K, Covault J. Alcohol-responsive genes identified in human iPSC-derived neural cultures. Translational Psychiatry 2019, 9: 96. PMID: 30862775, PMCID: PMC6414668, DOI: 10.1038/s41398-019-0426-5.Peer-Reviewed Original ResearchConceptsAlcohol-responsive genesGene expressionGene regulatory effectsTotal RNA sequencingCo-expressed genesNeural cell culturesCholesterol biosynthesis pathwayPrimary neural tissueCorrelation network analysisHuman-induced pluripotent stem cellsPluripotent stem cellsBiosynthesis pathwayCell culturesResponsive genesRNA sequencingNotch signalingEnrichment analysisMolecular mechanismsCell cycleAlcohol exposureGenesCell culture modelGenetic effectsCholesterol homeostasisStem cells
2017
Genomewide Association Study of Alcohol Dependence Identifies Risk Loci Altering Ethanol‐Response Behaviors in Model Organisms
Adkins AE, Hack LM, Bigdeli TB, Williamson VS, McMichael GO, Mamdani M, Edwards AC, Aliev F, Chan RF, Bhandari P, Raabe RC, Alaimo JT, Blackwell GG, Moscati A, Poland RS, Rood B, Patterson DG, Walsh D, Consortium C, Whitfield JB, Zhu G, Montgomery GW, Henders AK, Martin NG, Heath AC, Madden PAF, Frank J, Ridinger M, Wodarz N, Soyka M, Zill P, Ising M, Nöthen MM, Kiefer F, Rietschel M, Consortium T, Gelernter J, Sherva R, Koesterer R, Almasy L, Zhao H, Kranzler HR, Farrer LA, Maher BS, Prescott CA, Dick DM, Bacanu SA, Mathies LD, Davies AG, Vladimirov VI, Grotewiel M, Bowers MS, Bettinger JC, Webb BT, Miles MF, Kendler KS, Riley BP. Genomewide Association Study of Alcohol Dependence Identifies Risk Loci Altering Ethanol‐Response Behaviors in Model Organisms. Alcohol Clinical And Experimental Research 2017, 41: 911-928. PMID: 28226201, PMCID: PMC5404949, DOI: 10.1111/acer.13362.Peer-Reviewed Original ResearchConceptsModel organismsGenomewide association studiesLoss of functionAssociation studiesPrimate-specific genesAcute functional toleranceOrthologous genesCaenorhabditis elegansSuggestive signalsOrthologsExpression differencesGene expressionCOL6A3 expressionGenesAlcohol dependenceNucleus accumbensKLF12 expressionSuggestive associationElegansCOL6A3AD liabilityPotential involvementMultiple brain functionsEtOH sensitivityKLF12
2016
Review: DNA methylation and alcohol use disorders: Progress and challenges
Zhang H, Gelernter J. Review: DNA methylation and alcohol use disorders: Progress and challenges. American Journal On Addictions 2016, 26: 502-515. PMID: 27759945, PMCID: PMC6003819, DOI: 10.1111/ajad.12465.Peer-Reviewed Original ResearchConceptsDNA methylation changesDNA methylationMethylation changesGenome-wide DNA methylation studyGene expressionPromoter regionGlobal DNA methylation levelsDNA methylation profilesDNA methylation studiesDNA methylation levelsWidespread DNA methylationCandidate gene studiesEpigenetic mechanismsGenetic variationConsequences of AUDMethylation profilesMethylation studiesGene studiesMethylation levelsMethylationAUD subjectsGene-environment interactionsEnvironmental factorsInteractive effectsExpressionThe role of genes involved in stress, neural plasticity, and brain circuitry in depressive phenotypes: Convergent findings in a mouse model of neglect
Montalvo-Ortiz JL, Bordner KA, Carlyle BC, Gelernter J, Simen AA, Kaufman J. The role of genes involved in stress, neural plasticity, and brain circuitry in depressive phenotypes: Convergent findings in a mouse model of neglect. Behavioural Brain Research 2016, 315: 71-74. PMID: 27506655, PMCID: PMC5396458, DOI: 10.1016/j.bbr.2016.08.010.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsDepressionDisease Models, AnimalGene Expression RegulationInhibitor of Differentiation ProteinsMaleMaternal DeprivationMaze LearningMiceMice, Inbred C57BLMice, Inbred DBAMicroarray AnalysisNerve Tissue ProteinsNeuronal PlasticityPrefrontal CortexReceptors, N-Methyl-D-AspartateRNA, MessengerStress, PsychologicalSwimmingConceptsTubulin Polymerization Promoting ProteinRole of genesGene expression dataEpigenetic changesGene expressionPhenotype dataExpression dataPrefrontal cortex tissueGenesSecondary analysisMedial prefrontal cortex (mPFC) tissueGlutamate NMDA receptorsAdult male miceId-3Early life stressPhenotypeSwimming testMale miceNMDA receptorsDepression riskMaternal separationMouse modelDepressive phenotypeBrain circuitryBehavioral differences
2013
Sex-biased methylome and transcriptome in human prefrontal cortex
Xu H, Wang F, Liu Y, Yu Y, Gelernter J, Zhang H. Sex-biased methylome and transcriptome in human prefrontal cortex. Human Molecular Genetics 2013, 23: 1260-1270. PMID: 24163133, PMCID: PMC3919013, DOI: 10.1093/hmg/ddt516.Peer-Reviewed Original ResearchConceptsDNA methylationGene expressionSex-biased DNA methylationMultiple test correctionGenome-wide DNA methylationGene Ontology annotationsDAVID functional annotation analysisFunctional annotation analysisRibosome structurePhenotypic variationAnnotation analysisGO termsProtein translationRNA bindingOntology annotationsHost genesDifferential methylationExpression correlationTranscriptomic profilesDifferential brain developmentDifferential expressionMethylation levelsGenesMethylationTranscriptome