2024
Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits
Galimberti M, Levey D, Deak J, Zhou H, Stein M, Gelernter J. Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits. Molecular Psychiatry 2024, 29: 2905-2910. PMID: 38580809, PMCID: PMC11419938, DOI: 10.1038/s41380-024-02548-y.Peer-Reviewed Original ResearchSubstance use disordersProblematic alcohol useSubstance use traitsCannabis use disorderCannabis useOpioid use disorderUse disorderGenomic structural equation modelingSmoking initiationLifetime cannabis useLegalization of cannabis useGlobal genetic correlationsProblematic substance useStructural equation modelingNicotine dependenceGenetic influencesCannabisSubstance useFagerstrom TestAlcohol useMendelian randomizationBidirectional relationshipGenetic correlationsDisordersSmoking cessationPleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders
Koller D, Friligkou E, Stiltner B, Pathak G, Løkhammer S, Levey D, Zhou H, Hatoum A, Deak J, Kember R, Treur J, Kranzler H, Johnson E, Stein M, Gelernter J, Polimanti R. Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders. Molecular Psychiatry 2024, 29: 2021-2030. PMID: 38355787, PMCID: PMC11324857, DOI: 10.1038/s41380-024-02446-3.Peer-Reviewed Original ResearchMultisite chronic painSubstance use disordersChronic painUK BiobankUse disorderMillion Veteran ProgramSNP-based heritabilityGenome-wide association statisticsMR analysisPotential causal relationshipVeteran ProgramPleiotropy analysisTobacco usePleiotropic variantsOpioid use disorderAssociation statisticsCannabis use disorderAlcohol use disorderMeta-analysesBrain-wide analysisImaging phenotypesBi-directional relationshipPainPleiotropyBiobankGenetic and non-genetic predictors of risk for opioid dependence.
Na P, Deak J, Kranzler H, Pietrzak R, Gelernter J. Genetic and non-genetic predictors of risk for opioid dependence. Psychological Medicine 2024, 54: 1779-1786. PMID: 38317430, PMCID: PMC11132928, DOI: 10.1017/s0033291723003732.Peer-Reviewed Original ResearchPolygenic risk scoresMulti-trait analysis of genome-wide association studyOpioid use disorderPosttraumatic stress disorderPsychosocial/environmental factorsAnalysis of genome-wide association studiesHigher education levelGenome-wide association studiesNon-genetic predictorsEuropean-ancestry adultsEtiology of ODPublic health crisisPsychosocial factorsPolygenic riskMulti-trait analysisEducation levelPsychosocial environmentHousehold incomeRisk scoreAssociation studiesOpioid dependenceDiagnosis of ODLifetime diagnosisYale-PennAssociated with ODGenetic 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 evidence
2023
Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex
Rompala G, Nagamatsu S, Martínez-Magaña J, Nuñez-Ríos D, Wang J, Girgenti M, Krystal J, Gelernter J, Hurd Y, Montalvo-Ortiz J. Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex. Nature Communications 2023, 14: 4544. PMID: 37507366, PMCID: PMC10382503, DOI: 10.1038/s41467-023-40285-y.Peer-Reviewed Original ResearchConceptsOpioid use disorderMulti-omics findingsGene expression patternsCo-methylation analysisGene expression profilesMulti-omics profilingGene networksDNA methylationNeuronal methylomesDNA hydroxymethylationMethylomic analysisExpression patternsExpression profilesEpigenetic disturbancesUse disordersPsychiatric traitsOrbitofrontal cortexOpioid-related drugsPostmortem orbitofrontal cortexEnvironmental factorsDrug interaction analysisOUD treatmentHuman orbitofrontal cortexOpioid signalingInteraction analysisDoes polygenic risk for substance‐related traits predict ages of onset and progression of symptoms?
Kranzler H, Feinn R, Xu H, Ho B, Saini D, Nicastro O, Jacoby A, Toikumo S, Gelernter J, Hartwell E, Kember R. Does polygenic risk for substance‐related traits predict ages of onset and progression of symptoms? Addiction 2023, 118: 1675-1686. PMID: 37069489, PMCID: PMC10525011, DOI: 10.1111/add.16210.Peer-Reviewed Original ResearchConceptsOpioid use disorderSubstance use disordersProgression of symptomsPolygenic risk scoresAlcohol use disorderUse disordersAfrican ancestry individualsGenetic riskRegular useEuropean ancestry individualsEarly onsetMore rapid progressionRegular alcohol useShorter progression timeAge of onsetFirst substance useDiscovery sampleUS inpatientsOnset of problemsOutpatient settingDisease progressionRapid progressionSymptom progressionRisk scoreGenome-wide association studies
2022
Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction
Kember RL, Vickers-Smith R, Xu H, Toikumo S, Niarchou M, Zhou H, Hartwell EE, Crist RC, Rentsch CT, Davis L, Justice A, Sanchez-Roige S, Kampman K, Gelernter J, Kranzler H. Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction. Nature Neuroscience 2022, 25: 1279-1287. PMID: 36171425, PMCID: PMC9682545, DOI: 10.1038/s41593-022-01160-z.Peer-Reviewed Original ResearchConceptsOpioid use disorderGenome-wide association studiesWide significant lociGene expression enrichmentSignificant genetic correlationsCell type groupSignificant lociAssociation studiesExpression enrichmentMillion Veteran ProgramGenetic correlationsUse disordersLociBrain regionsExonic variantsIntronic variantsSubstance use disordersTraitsBiological basisOpioid epidemicPsychiatric disordersVeteran ProgramBrain diseasesTSNARE1FBXW4Phenome-wide Association Analysis of Substance Use Disorders in a Deeply Phenotyped Sample
Kember RL, Hartwell EE, Xu H, Rotenberg J, Almasy L, Zhou H, Gelernter J, Kranzler HR. Phenome-wide Association Analysis of Substance Use Disorders in a Deeply Phenotyped Sample. Biological Psychiatry 2022, 93: 536-545. PMID: 36273948, PMCID: PMC9931661, DOI: 10.1016/j.biopsych.2022.08.010.Peer-Reviewed Original ResearchConceptsSubstance use disordersAlcohol use disorderOpioid use disorderPolygenic risk scoresUse disordersCo-occurring psychiatric disordersComprehensive psychiatric interviewSemi-Structured AssessmentElectronic health recordsControl subjectsLow prevalencePsychiatric interviewRisk scorePsychiatric disordersPhenome-wide association analysisDrug dependenceEuropean individualsHealth recordsLifetime cannabisPhenome-wide association studyDisordersAfrican ancestry individualsDSM diagnosesPopulation sampleGenetic liabilityIntegrating 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 genesUnique and joint associations of polygenic risk for major depression and opioid use disorder with endogenous opioid system function
Love T, Shabalin AA, Kember RL, Docherty AR, Zhou H, Koppelmans V, Gelernter J, Baker AK, Hartwell E, Dubroff J, Zubieta JK, Kranzler HR. Unique and joint associations of polygenic risk for major depression and opioid use disorder with endogenous opioid system function. Neuropsychopharmacology 2022, 47: 1784-1790. PMID: 35545664, PMCID: PMC9372136, DOI: 10.1038/s41386-022-01325-1.Peer-Reviewed Original ResearchConceptsOpioid use disorderMajor depressive disorderPolygenic risk scoresUse disordersEndogenous opioid system functionOpioid system functionOpioid system activityMDD polygenic risk scoresPolygenic riskAssociation of PRSEndogenous opioid responseOpioid system activationNon-displaceable bindingPathophysiologic linkOpioid responseMOR availabilityOpioid releaseDepressive disorderMajor depressionNeurotransmitter systemsVentral pallidumRisk scoreReceptor concentrationSystem activationRegion of interest
2020
Association of OPRM1 Functional Coding Variant With Opioid Use Disorder
Zhou H, Rentsch CT, Cheng Z, Kember RL, Nunez YZ, Sherva RM, Tate JP, Dao C, Xu K, Polimanti R, Farrer LA, Justice AC, Kranzler HR, Gelernter J. Association of OPRM1 Functional Coding Variant With Opioid Use Disorder. JAMA Psychiatry 2020, 77: 1072-1080. PMID: 32492095, PMCID: PMC7270886, DOI: 10.1001/jamapsychiatry.2020.1206.Peer-Reviewed Original ResearchConceptsOpioid use disorderUse disordersMendelian randomization analysisAfrican American individualsMAIN OUTCOMEFunctional coding variantSignificant associationCausal associationRandomization analysisElectronic health record dataCurrent opioid crisisAmerican individualsHealth record dataCognitive performanceInternational Statistical ClassificationRelated Health ProblemsPotential causal associationAmerican controlsEuropean American controlsAfrican-American controlsCoding variantBuprenorphine treatmentOUD diagnosisTobacco smokingNinth Revision
2019
FUNCTIONAL CODING VARIANT IN OPRM1 GENE ASSOCIATED WITH OPIOID USE DISORDER: EVIDENCE FROM GWAS ON LARGE COHORTS
Zhou H, Rentsch C, Cheng Z, Kember R, Nunex Y, Tate J, Dao C, Polimanti R, Justice A, Kranzler H, Gelernter J. FUNCTIONAL CODING VARIANT IN OPRM1 GENE ASSOCIATED WITH OPIOID USE DISORDER: EVIDENCE FROM GWAS ON LARGE COHORTS. European Neuropsychopharmacology 2019, 29: s34-s35. DOI: 10.1016/j.euroneuro.2019.07.070.Peer-Reviewed Original ResearchPatterns and Correlates of Prescription Opioid Receipt Among US Veterans: A National, 18-Year Observational Cohort Study
Rentsch CT, Edelman EJ, Justice AC, Marshall BDL, Xu K, Smith AH, Crystal S, Gaither JR, Gordon AJ, Smith RV, Kember RL, Polimanti R, Gelernter J, Fiellin DA, Tate JP, Kranzler HR, Becker WC. Patterns and Correlates of Prescription Opioid Receipt Among US Veterans: A National, 18-Year Observational Cohort Study. AIDS And Behavior 2019, 23: 3340-3349. PMID: 31317364, PMCID: PMC7344341, DOI: 10.1007/s10461-019-02608-3.Peer-Reviewed Original ResearchConceptsOpioid use disorderOpioid receiptCohort studyLong-term opioid therapyVeterans Aging Cohort StudyLatent growth mixture modellingPrescription opioid receiptObservational cohort studyAging Cohort StudyOpioid therapyCause mortalityHepatitis COpioid prescriptionsFuture prevention researchOUD diagnosisGrowth mixture modellingUS veteransHigh prevalenceLow doseHigh incidenceUse disordersPrevention researchGenetic discoveriesReceiptHIV