Featured Publications
Sex-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 ResearchMeSH KeywordsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHSP27 Heat-Shock ProteinsHumansMaleMental DisordersNeuroticismPhenotypePolymorphism, Single NucleotideTranscription FactorsTranscriptomeConceptsGenome-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 riskNCOA6GeneticsHeritabilityPathwayFemalesAn Atlas of Genetic Correlations and Genetically Informed Associations Linking Psychiatric and Immune-Related Phenotypes
Tylee DS, Lee YK, Wendt FR, Pathak GA, Levey DF, De Angelis F, Gelernter J, Polimanti R. An Atlas of Genetic Correlations and Genetically Informed Associations Linking Psychiatric and Immune-Related Phenotypes. JAMA Psychiatry 2022, 79: 667-676. PMID: 35507366, PMCID: PMC9069342, DOI: 10.1001/jamapsychiatry.2022.0914.Peer-Reviewed Original ResearchMeSH KeywordsAsthmaColitis, UlcerativeCrohn DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideRhinitis, AllergicConceptsRisk factorsImmune-related phenotypesMultivariable adjustmentUlcerative colitisCrohn's diseaseMendelian randomizationImmune-related disordersReciprocal risk factorsHealth-related behaviorsPsychiatric phenotypesFalse discovery rate correctionAllergic rhinitisGenetic association studiesGenetic associationInflammatory disordersClinical associationsMajor depressionImmune disordersMAIN OUTCOMEPsychiatric disordersSocial determinantsDisordersAssociation studiesColitisAsthmaWidespread signatures of positive selection in common risk alleles associated to autism spectrum disorder
Polimanti R, Gelernter J. Widespread signatures of positive selection in common risk alleles associated to autism spectrum disorder. PLOS Genetics 2017, 13: e1006618. PMID: 28187187, PMCID: PMC5328401, DOI: 10.1371/journal.pgen.1006618.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAttention Deficit Disorder with HyperactivityAutism Spectrum DisorderBipolar DisorderBrainComputational BiologyDepressive Disorder, MajorGene Expression ProfilingGene OntologyGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansPituitary GlandPolymorphism, Single NucleotideRisk FactorsSchizophreniaTranscriptomeConceptsPositive selectionGene Ontology enrichmentGene expression enrichmentPrevious genetic studiesGWAS summary statisticsNervous system developmentCommon risk allelesPsychiatric Genomics ConsortiumSystems geneticsOntology enrichmentRisk allelesSynapse organizationWidespread signaturesEvolutionary processesGenetic studiesGenomics ConsortiumGWASHuman evolutionAllelesIncomplete selectionEffect directionMinor alleleComplete selectionEnrichmentSummary statistics
2024
Diversity 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 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 ResearchMeSH KeywordsGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansNeurobiologyPolymorphism, Single NucleotideStress Disorders, Post-TraumaticWhite PeopleConceptsMeta-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 structureLociGenes
2023
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 phenotypesCharacterizing the polygenic architecture of complex traits in populations of East Asian and European descent
De Lillo A, Wendt F, Pathak G, Polimanti R. Characterizing the polygenic architecture of complex traits in populations of East Asian and European descent. Human Genomics 2023, 17: 67. PMID: 37475089, PMCID: PMC10360343, DOI: 10.1186/s40246-023-00514-3.Peer-Reviewed Original ResearchModeling 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 ResearchDeclining autozygosity over time: An exploration in over 1 million individuals from three diverse cohorts
Colbert S, Wendt F, Pathak G, Helmer D, Hauser E, Keller M, Polimanti R, Johnson E. Declining autozygosity over time: An exploration in over 1 million individuals from three diverse cohorts. American Journal Of Human Genetics 2023, 110: 1008-1014. PMID: 37178685, PMCID: PMC10257001, DOI: 10.1016/j.ajhg.2023.04.007.Peer-Reviewed Original ResearchMulti‐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 biologyLociDiscovery
2022
Phenome-wide association study of loci harboring de novo tandem repeat mutations in UK Biobank exomes
Wendt F, Pathak G, Polimanti R. Phenome-wide association study of loci harboring de novo tandem repeat mutations in UK Biobank exomes. Nature Communications 2022, 13: 7682. PMID: 36509785, PMCID: PMC9744822, DOI: 10.1038/s41467-022-35423-x.Peer-Reviewed Original ResearchMeSH KeywordsBiological Specimen BanksCarotid Intima-Media ThicknessGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideProteinsTandem Repeat SequencesUnited KingdomConceptsProtein structureTandem repeatsTandem repeat mutationsPhenome-wide association studyAlters protein structureGenetic variationAssociation studiesEuropean ancestry participantsUK BiobankCarotid intima-media thicknessTR mutationsIntima-media thicknessMicroRNA-184Repeat mutationsFamily-based designsTestable hypothesesLociPopulation levelRespiratory outcomesMutationsDisease outcomeFAN1FNBP4RepeatsGenetic 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 variantsCellsCD4VariantsUnderstanding 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 disorderGenome-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 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 ResearchMeSH KeywordsBrainGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultifactorial InheritancePolymorphism, Single NucleotideSleep Initiation and Maintenance DisordersConceptsRisk 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 numberThe association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study
Cabrera-Mendoza B, Wendt FR, Pathak GA, De Angelis F, De Lillo A, Koller D, Polimanti R. The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study. International Journal Of Epidemiology 2022, 51: 1371-1383. PMID: 35751636, PMCID: PMC9278255, DOI: 10.1093/ije/dyac129.Peer-Reviewed Original ResearchMeSH KeywordsBody Mass IndexCOVID-19Economic StatusGenome-Wide Association StudyHospitalizationHumansMendelian Randomization AnalysisObesityPolymorphism, Single NucleotideConceptsSevere respiratory COVID-19COVID-19 severityCOVID-19 outcomesSocio-economic statusMendelian randomization studyObesity-related traitsLower oddsCOVID-19Randomization studyCoronavirus disease 2019 (COVID-19) severityBody mass indexWaist-hip ratioCOVID-19 infectionTwo-sample MR approachAssociation of incomeMultivariable Mendelian randomization studyA Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
Verma A, Tsao NL, Thomann LO, Ho YL, Iyengar SK, Luoh SW, Carr R, Crawford DC, Efird JT, Huffman JE, Hung A, Ivey KL, Levin MG, Lynch J, Natarajan P, Pyarajan S, Bick AG, Costa L, Genovese G, Hauger R, Madduri R, Pathak GA, Polimanti R, Voight B, Vujkovic M, Zekavat SM, Zhao H, Ritchie MD, Initiative V, Chang KM, Cho K, Casas JP, Tsao PS, Gaziano JM, O’Donnell C, Damrauer SM, Liao KP. A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program. PLOS Genetics 2022, 18: e1010113. PMID: 35482673, PMCID: PMC9049369, DOI: 10.1371/journal.pgen.1010113.Peer-Reviewed Original ResearchMeSH KeywordsCOVID-19Genetic Association StudiesGenome-Wide Association StudyHumansPolymorphism, Single NucleotideVeteransConceptsSevere COVID-19Million Veteran ProgramPhenome-wide association studyHost Genetics InitiativeGenetic architectureGenotype-phenotype dataAssociation studiesVeterans Affairs Million Veteran ProgramElectronic health record dataCOVID-19 severityHealth record dataCOVID-19Genetic variantsGenetics InitiativeABO locusPhenotypeVenous embolismCritical illnessDiseases codesMedical conditionsInternational ClassificationRecord dataStrong associationVeteran ProgramVariants
2021
Ancestry may confound genetic machine learning: Candidate-gene prediction of opioid use disorder as an example
Hatoum AS, Wendt FR, Galimberti M, Polimanti R, Neale B, Kranzler HR, Gelernter J, Edenberg HJ, Agrawal A. Ancestry may confound genetic machine learning: Candidate-gene prediction of opioid use disorder as an example. Drug And Alcohol Dependence 2021, 229: 109115. PMID: 34710714, PMCID: PMC9358969, DOI: 10.1016/j.drugalcdep.2021.109115.Peer-Reviewed Original ResearchMeSH KeywordsBlack PeopleHumansMachine LearningMultifactorial InheritanceOpioid-Related DisordersPolymorphism, Single NucleotideConceptsGenome-wide significant variantsCandidate gene predictionGenetic predictionRandom SNPsPolygenic traitRandom phenotypeCandidate SNPsSimulated phenotypesPsychiatric geneticsGenetic machineSignificant variantsBinary phenotypesCandidate variantsSNPsAncestryPhenotypeAllele frequenciesVariantsMachine learning modelsGenetic testsLearning modelEnhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information
Maihofer AX, Choi KW, Coleman JRI, Daskalakis NP, Denckla CA, Ketema E, Morey RA, Polimanti R, Ratanatharathorn A, Torres K, Wingo AP, Zai CC, Aiello AE, Almli LM, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegović E, Borglum AD, Babić D, Bækvad-Hansen M, Baker DG, Beckham JC, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Bradley B, Brashear M, Breen G, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Calabrese JR, Caldas-de-Almeida JM, Chen CY, Dale AM, Dalvie S, Deckert J, Delahanty DL, Dennis MF, Disner SG, Domschke K, Duncan LE, Džubur Kulenović A, Erbes CR, Evans A, Farrer LA, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gautam A, Gelaye B, Gelernter J, Geuze E, Gillespie CF, Goçi A, Gordon SD, Guffanti G, Hammamieh R, Hauser MA, Heath AC, Hemmings SMJ, Hougaard DM, Jakovljević M, Jett M, Johnson EO, Jones I, Jovanovic T, Qin XJ, Karstoft KI, Kaufman ML, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kranzler HR, Kremen WS, Lawford BR, Lebois LAM, Lewis C, Liberzon I, Linnstaedt SD, Logue MW, Lori A, Lugonja B, Luykx JJ, Lyons MJ, Maples-Keller JL, Marmar C, Martin NG, Maurer D, Mavissakalian MR, McFarlane A, McGlinchey RE, McLaughlin KA, McLean SA, Mehta D, Mellor R, Michopoulos V, Milberg W, Miller MW, Morris CP, Mors O, Mortensen PB, Nelson EC, Nordentoft M, Norman SB, O'Donnell M, Orcutt HK, Panizzon MS, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Rice JP, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero KJ, Rung A, Rutten BPF, Saccone NL, Sanchez SE, Schijven D, Seedat S, Seligowski AV, Seng JS, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stevens JS, Teicher MH, Thompson WK, Trapido E, Uddin M, Ursano RJ, van den Heuvel LL, Van Hooff M, Vermetten E, Vinkers CH, Voisey J, Wang Y, Wang Z, Werge T, Williams MA, Williamson DE, Winternitz S, Wolf C, Wolf EJ, Yehuda R, Young KA, Young RM, Zhao H, Zoellner LA, Haas M, Lasseter H, Provost AC, Salem RM, Sebat J, Shaffer RA, Wu T, Ripke S, Daly MJ, Ressler KJ, Koenen KC, Stein MB, Nievergelt CM. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information. Biological Psychiatry 2021, 91: 626-636. PMID: 34865855, PMCID: PMC8917986, DOI: 10.1016/j.biopsych.2021.09.020.Peer-Reviewed Original Research
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