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 smokingBi-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 directionsGenesLociReproducible 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 GWASsGenome-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 factorsRegionSubdomainsEnrichmentGenetic associations with suicide attempt severity and genetic overlap with major depression
Levey DF, Polimanti R, Cheng Z, Zhou H, Nuñez YZ, Jain S, He F, Sun X, Ursano RJ, Kessler RC, Smoller JW, Stein MB, Kranzler HR, Gelernter J. Genetic associations with suicide attempt severity and genetic overlap with major depression. Translational Psychiatry 2019, 9: 22. PMID: 30655502, PMCID: PMC6336846, DOI: 10.1038/s41398-018-0340-2.Peer-Reviewed Original ResearchConceptsGWS associationsGenome-wide significant signalsCircadian clock regulationWide association studyGenetic overlapCatabolism of tyrosineClock regulationFirst GWASSignificant genetic overlapDiscovery GWASChromosome 12Large GWASMolecular mechanismsAssociation studiesChromosome 15Chromosome 18Genetic influencesDiscovery sampleGenetic associationSuicide attempt severityReplication analysisGWASAnaerobic energy productionGenetic risk factorsPolygenic risk scoresDepression 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 comorbidityGenome-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 numberTowards understanding and predicting suicidality in women: biomarkers and clinical risk assessment
Levey DF, Niculescu EM, Le-Niculescu H, Dainton HL, Phalen PL, Ladd TB, Weber H, Belanger E, Graham DL, Khan FN, Vanipenta NP, Stage EC, Ballew A, Yard M, Gelbart T, Shekhar A, Schork NJ, Kurian SM, Sandusky GE, Salomon DR, Niculescu AB. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment. Molecular Psychiatry 2016, 21: 768-785. PMID: 27046645, DOI: 10.1038/mp.2016.31.Peer-Reviewed Original ResearchConceptsFuture hospitalizationConvergent functional genomics approachSuicide completersPrimary end pointSingle blood biomarkerTop biomarkersReceiver-operating characteristic areaRisk prediction scoreClinical risk assessmentDisorder participantsIndependent test cohortForm of APPProphylactic benefitNeurotrophic effectsBlood biomarkersSleep abnormalitiesPsychiatric hospitalizationHospitalizationMood disordersTest cohortCandidate biomarkersSuicide completionSuicidal ideationDrug lithiumChronic stress
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 surfaceAssociation between psoriasis and obsessive-compulsive disorder: a case-control study in the All of Us research program
Craver A, Chen G, Fan R, Levey D, Cohen J. Association between psoriasis and obsessive-compulsive disorder: a case-control study in the All of Us research program. Archives Of Dermatological Research 2024, 316: 280. PMID: 38796663, DOI: 10.1007/s00403-024-03112-y.Peer-Reviewed Original ResearchGenome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder
Nievergelt C, Maihofer A, Atkinson E, Chen C, Choi K, Coleman J, Daskalakis N, Duncan L, Polimanti R, Aaronson C, Amstadter A, Andersen S, Andreassen O, Arbisi P, Ashley-Koch A, Austin S, Avdibegoviç E, Babić D, Bacanu S, Baker D, Batzler A, Beckham J, Belangero S, Benjet C, Bergner C, Bierer L, Biernacka J, Bierut L, Bisson J, Boks M, Bolger E, Brandolino A, Breen G, Bressan R, Bryant R, Bustamante A, Bybjerg-Grauholm J, Bækvad-Hansen M, Børglum A, Børte S, Cahn L, Calabrese J, Caldas-de-Almeida J, Chatzinakos C, Cheema S, Clouston S, Colodro-Conde L, Coombes B, Cruz-Fuentes C, Dale A, Dalvie S, Davis L, Deckert J, Delahanty D, Dennis M, Desarnaud F, DiPietro C, Disner S, Docherty A, Domschke K, Dyb G, Kulenović A, Edenberg H, Evans A, Fabbri C, Fani N, Farrer L, Feder A, Feeny N, Flory J, Forbes D, Franz C, Galea S, Garrett M, Gelaye B, Gelernter J, Geuze E, Gillespie C, Goleva S, Gordon S, Goçi A, Grasser L, Guindalini C, Haas M, Hagenaars S, Hauser M, Heath A, Hemmings S, Hesselbrock V, Hickie I, Hogan K, Hougaard D, Huang H, Huckins L, Hveem K, Jakovljević M, Javanbakht A, Jenkins G, Johnson J, Jones I, Jovanovic T, Karstoft K, Kaufman M, Kennedy J, Kessler R, Khan A, Kimbrel N, King A, Koen N, Kotov R, Kranzler H, Krebs K, Kremen W, Kuan P, Lawford B, Lebois L, Lehto K, Levey D, Lewis C, Liberzon I, Linnstaedt S, Logue M, Lori A, Lu Y, Luft B, Lupton M, Luykx J, Makotkine I, Maples-Keller J, Marchese S, Marmar C, Martin N, Martínez-Levy G, McAloney K, McFarlane A, McLaughlin K, McLean S, Medland S, Mehta D, Meyers J, Michopoulos V, Mikita E, Milani L, Milberg W, Miller M, Morey R, Morris C, Mors O, Mortensen P, Mufford M, Nelson E, Nordentoft M, Norman S, Nugent N, O’Donnell M, Orcutt H, Pan P, Panizzon M, Pathak G, Peters E, Peterson A, Peverill M, Pietrzak R, Polusny M, Porjesz B, Powers A, Qin X, Ratanatharathorn A, Risbrough V, Roberts A, Rothbaum A, Rothbaum B, Roy-Byrne P, Ruggiero K, Rung A, Runz H, Rutten B, de Viteri S, Salum G, Sampson L, Sanchez S, Santoro M, Seah C, Seedat S, Seng J, Shabalin A, Sheerin C, Silove D, Smith A, Smoller J, Sponheim S, Stein D, Stensland S, Stevens J, Sumner J, Teicher M, Thompson W, Tiwari A, Trapido E, Uddin M, Ursano R, Valdimarsdóttir U, Van Hooff M, Vermetten E, Vinkers C, Voisey J, Wang Y, Wang Z, Waszczuk M, Weber H, Wendt F, Werge T, Williams M, Williamson D, Winsvold B, Winternitz S, Wolf C, Wolf E, Xia Y, Xiong Y, Yehuda R, Young K, Young R, Zai C, Zai G, Zervas M, Zhao H, Zoellner L, Zwart J, deRoon-Cassini T, van Rooij S, van den Heuvel L, Stein M, Ressler K, Koenen K. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder. Nature Genetics 2024, 56: 792-808. PMID: 38637617, PMCID: PMC11396662, DOI: 10.1038/s41588-024-01707-9.Peer-Reviewed Original ResearchConceptsMeta-analysis of genome-wide association studiesGenome-wide significant lociMulti-ancestry meta-analysisGenome-wide association analysisGenome-wide association studiesIndividuals of European ancestryPotential causal genesNative American ancestryMulti-omics approachPost-traumatic stress disorderAdmixed individualsSignificant lociRisk lociCausal genesAssociation studiesAssociation analysisFunctional genesTranscription factorsGenetic studiesAmerican ancestryEuropean ancestryAxon guidanceSynaptic structureLociGenesWhole-exome sequencing in UK Biobank reveals rare genetic architecture for depression
Tian R, Ge T, Kweon H, Rocha D, Lam M, Liu J, Singh K, Levey D, Gelernter J, Stein M, Tsai E, Huang H, Chabris C, Lencz T, Runz H, Chen C. Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression. Nature Communications 2024, 15: 1755. PMID: 38409228, PMCID: PMC10897433, DOI: 10.1038/s41467-024-45774-2.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesRare coding variantsWhole-exome sequencingGenetic architectureGenetic relationshipsLoss-of-function intolerant genesContribution of rare coding variantsRare damagingAssociated with risk of depressionElectronic health recordsUK Biobank participantsPolygenic risk scoresRisk of depressionAssociated with riskIntolerant genesRisk lociAssociation studiesCoding variantsBiobank participantsHealth recordsUK BiobankDepression definitionsDepression riskBurden analysisRare variantsGenetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders
Koller D, Mitjans M, Kouakou M, Friligkou E, Cabrera-Mendoza B, Deak J, Llonga N, Pathak G, Stiltner B, Løkhammer S, Levey D, Zhou H, Hatoum A, Kember R, Kranzler H, Stein M, Corominas R, Demontis D, Artigas M, Ramos-Quiroga J, Gelernter J, Ribasés M, Cormand B, Polimanti R. Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders. Psychiatry Research 2024, 333: 115758. PMID: 38335780, PMCID: PMC11157987, DOI: 10.1016/j.psychres.2024.115758.Peer-Reviewed Original ResearchConceptsUse disorderGenome-wide association studiesGenomic structural equation modelingCannabis use disorderAlcohol Use Disorders Identification TestAttention-deficit/hyperactivity disorderAlcohol use disorderProblematic alcohol useSubstance use disordersTwo-sample Mendelian randomization analysisLinkage disequilibrium score regression analysisDisorders Identification TestMendelian randomization analysisAssociated with increased oddsOdds of ADHDOpioid use disorderAttention-deficit/hyperactivityGWAS meta-analysesAlcohol dependenceStructural equation modelingNicotine dependenceInvestigate genetic correlationsADHDPolygenic riskStrength of evidenceAssociation between cannabis use and brain structure and function: an observational and Mendelian randomisation study
Ishrat S, Levey D, Gelernter J, Ebmeier K, Topiwala A. Association between cannabis use and brain structure and function: an observational and Mendelian randomisation study. BMJ Mental Health 2024, 27: e301065. PMID: 39477366, PMCID: PMC11529520, DOI: 10.1136/bmjment-2024-301065.Peer-Reviewed Original ResearchConceptsCannabis useBrain structuresFunctional connectivityHistory of cannabis useResting-state functional connectivityMeasures of brain structureLifetime cannabis useCentral executive networkLifetime cannabis usersWhite matter integrityGenu of the corpus callosumMendelian randomisation analysisAssociated with multiple measuresPoorer white matter integrityInvestigate potential causal relationshipsCannabis usersExecutive networkBrain regionsImaging-derived phenotypesBrain healthCannabisRandomisation analysesTwo-sample Mendelian randomisation analysisFractional anisotropyYoung adulthood
2023
Multi-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 ResearchObsessive–compulsive disorder among patients with atopic dermatitis: a case–control study in the All of Us research program
Chen G, Fan R, Leasure A, Levey D, Damsky W, Cohen J. Obsessive–compulsive disorder among patients with atopic dermatitis: a case–control study in the All of Us research program. Archives Of Dermatological Research 2023, 316: 11. PMID: 38038754, DOI: 10.1007/s00403-023-02767-3.Peer-Reviewed Original ResearchGenome-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 phenotypesModeling 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 Research