2025
Mapping phenotypic and genetic relationships among irritability, depression and ADHD in adolescence using network analysis
Shakeshaft A, Farhat L, Dennison C, Eyre O, Oginni O, O'Donovan M, Stringaris A, Leibenluft E, Polanczyk G, Riglin L, Thapar A. Mapping phenotypic and genetic relationships among irritability, depression and ADHD in adolescence using network analysis. Journal Of Child Psychology And Psychiatry 2025 PMID: 40974183, DOI: 10.1111/jcpp.70040.Peer-Reviewed Original ResearchShort Mood and Feelings QuestionnaireMillennium Cohort StudyStrengths and Difficulties QuestionnaireAvon Longitudinal StudyPolygenic scoresOdd-itemBehavior problemsCore symptomsMood and Feelings QuestionnaireAvon Longitudinal Study of ParentsAdolescent mental health servicesDepression polygenic scoresLongitudinal Study of ParentsCore symptoms of ADHDADHD polygenic scoresMental health servicesICD-11 approachOppositional defiant disorderSymptoms of ADHDStudy of parentsHealth servicesFeelings QuestionnaireADHD phenotypeAdolescent irritabilityMood disordersGenetically determined body mass index is associated with diffuse large B‐cell lymphoma in polygenic and Mendelian randomization analyses
Moore A, Kane E, Teras L, Machiela M, Arias J, Panagiotou O, Monnereau A, Doo N, Wang Z, Slager S, Vermeulen R, Vajdic C, Smedby K, Spinelli J, Vijai J, Giles G, Link B, Arslan A, Nieters A, Bracci P, Camp N, Salles G, Cozen W, Hjalgrim H, De Vivo I, Adami H, Albanes D, Becker N, Benavente Y, Bisanzi S, Boffetta P, Brennan P, Brooks‐Wilson A, Canzian F, Clavel J, Conde L, Cox D, Curtin K, Foretova L, Ghesquières H, Glimelius B, Habermann T, Hofmann J, Lan Q, Liebow M, Lincoln A, Maynadie M, McKay J, Melbye M, Miligi L, Milne R, Molina T, Morton L, North K, Offit K, Padoan M, Piro S, Patel A, Purdue M, Ravichandran V, Riboli E, Severson R, Southey M, Staines A, Tinker L, Travis R, Wang S, Weiderpass E, Weinstein S, Zheng T, Chanock S, Rothman N, Birmann B, Cerhan J, Berndt S. Genetically determined body mass index is associated with diffuse large B‐cell lymphoma in polygenic and Mendelian randomization analyses. International Journal Of Cancer 2025 PMID: 40910475, DOI: 10.1002/ijc.70039.Peer-Reviewed Original ResearchWaist-to-hip ratioBody mass indexDiffuse large B-cell lymphomaMendelian randomization analysisRisk of diffuse large B-cell lymphomaWaist-to-hipNon-Hodgkin's lymphomaGenome-wide association studiesNon-Hodgkin lymphoma subtypesLarge B-cell lymphomaRandomization analysisGenome-wide association studies of European ancestryB-cell lymphomaStudies of European ancestryMass indexAssociated with non-Hodgkin lymphomaAssociated with diffuse large B-cell lymphomaNo significant associationPolygenic scoresMarginal zone lymphomaChronic lymphocytic leukemiaEuropean ancestrySignificant associationRisk factorsFollicular lymphomaMulti-ancestral genome-wide association study of clinically defined nicotine dependence reveals strong genetic correlations with other substance use disorders and health-related traits
Johnson E, Lai D, Balbona J, Miller A, Hatoum A, Deak J, Jennings M, Baranger D, Galimberti M, Sanichwankul K, Thorgeirsson T, Colbert S, Adhikari K, Docherty A, Degenhardt L, Edwards T, Fox L, Giannelis A, Jeffries P, Korhonen T, Morrison C, Nunez Y, Palviainen T, Su M, Villela P, Wetherill L, Willoughby E, Zellers S, Bierut L, Buchwald J, Copeland W, Corley R, Friedman N, Foroud T, Gillespie N, Gizer I, Heath A, Hickie I, Kaprio J, Keller M, Lee J, Lind P, Madden P, Maes H, Martin N, McGue M, Medland S, Nelson E, Pearson J, Porjesz B, Stallings M, Vrieze S, Wilhelmson K, Kranzler H, Walters R, Polimanti R, Malison R, Zhou H, Stefansson K, Sanchez-Roige S, Potenza M, Mutirangura A, Shotelersuk V, Kalayasiri R, Edenberg H, Gelernter J, Agrawal A. Multi-ancestral genome-wide association study of clinically defined nicotine dependence reveals strong genetic correlations with other substance use disorders and health-related traits. Psychological Medicine 2025, 55: e234. PMID: 40831304, PMCID: PMC12360691, DOI: 10.1017/s0033291725100883.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlcoholismAsian PeopleBlack PeopleDiagnostic and Statistical Manual of Mental DisordersFemaleGenome-Wide Association StudyHumansMaleMiddle AgedNerve Tissue ProteinsPhenotypePolymorphism, Single NucleotideReceptors, NicotinicSubstance-Related DisordersTobacco Use DisorderWhite PeopleConceptsGenome-wide association studiesDiagnostic and Statistical ManualTobacco use disorderUse disorderNicotine dependenceAssociation studiesDiagnostic and Statistical Manual of Mental DisordersGenetic correlationsStatistical manual of mental disordersPolygenic scoresManual of mental disordersGenomic structural equation modelingCannabis use disorderNicotine-related phenotypesProblematic alcohol useSubstance use disordersNational Epidemiologic SurveyHealth-related traitsPositive genetic correlationIndividual diagnostic criteriaElectronic health recordsCriterion countsDSM-5Opioid use disorderPsychiatric disordersEvocative effects of children's education‐associated genetics on maternal parenting: results from the Norwegian mother, father and child cohort study
Austerberry C, Zayats T, Ronald A, Corfield E, Smajlagic D, Havdahl A, Andreassen O, Magnus P, Njølstad P, Bekkhus M, Fearon P. Evocative effects of children's education‐associated genetics on maternal parenting: results from the Norwegian mother, father and child cohort study. Journal Of Child Psychology And Psychiatry 2025 PMID: 40757461, DOI: 10.1111/jcpp.70025.Peer-Reviewed Original ResearchNorwegian MotherSelf-ReportPopulation-based pregnancy cohortMaternal reportChild Cohort StudyEvocative effectsMaternal self-reportParent-offspring triosEducation polygenic scoreGene-environment correlationGenetic effectsPolygenic scoresChild geneticsPregnancy cohortCohort studyAssociated with parentsLiteracy-focusedEducational outcomesEducational performancePositive parentingChild languageEarly languageChildren's LanguageMaternal parentParental differencesPredicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample
Jinwala Z, Green R, Khan Y, Gelernter J, Kember R, Hartwell E. Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample. Drug And Alcohol Dependence 2025, 274: 112797. PMID: 40695097, PMCID: PMC12447308, DOI: 10.1016/j.drugalcdep.2025.112797.Peer-Reviewed Original ResearchConceptsAlcohol use disorderTreatment-seeking statusTreatment-seekingPolygenic scoresUse disorderDSM-IV alcohol use disordersAlcohol usePsychological problemsYears of alcohol useMeasures of genetic riskPredictors of treatment-seekingComorbid medical disordersDSM-IVSubstance dependencePsychiatric diagnosisDrinking behaviorPsychiatric issuesClinically relevant phenotypesAge-stratified analysesMedical disordersSeekingGenetic riskDisordersHeart diseaseReceiving treatmentThe Psychiatric Genomics Consortium: discoveries and directions
Agrawal A, Bulik C, Abebe D, Andreassen O, Atkinson E, Choi K, Corvin A, Davies H, Davis L, Docherty A, Edenberg H, Franke B, Gelernter J, Giusti-Rodríguez P, Hettema J, Hjerling-Leffler J, Huang H, Johnson E, Lewis C, Lu Y, Lynall M, Martin J, McIntosh A, Montalvo-Ortiz J, Mullins N, Nievergelt C, O'Connell K, O'Donovan M, Okewole A, Peterson R, Posthuma D, Sebat J, Smoller J, Sud R, Viswanath B, Walters J, Won H, Wray N, Sullivan P, Consortium T. The Psychiatric Genomics Consortium: discoveries and directions. The Lancet Psychiatry 2025, 12: 600-610. PMID: 40582370, PMCID: PMC12332855, DOI: 10.1016/s2215-0366(25)00124-5.Peer-Reviewed Original ResearchPsychiatric Genomics ConsortiumGenome-wide association studiesFunctional genomics dataRare genetic variationPsychiatric disordersGenomic dataAssociation studiesGenetic variationGenomic discoveriesNeurodevelopmental conditionsPolygenic riskPolygenic scoresGenomics ConsortiumGenetic causeRare variantsRare variationImplementation processGlobal morbidityFunctional attributesPriority areasIntegrated findingsMultiple psychiatric disordersNext phaseVariantsDiscoveryRobust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk
Hu J, Ye Y, Zhang C, Ruan Y, Natarajan P, Zhao H. Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk. PLOS Computational Biology 2025, 21: e1013191. PMID: 40570042, PMCID: PMC12212871, DOI: 10.1371/journal.pcbi.1013191.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresCAD-PRSUK BiobankCoronary artery disease polygenic risk scoreSummary-level dataCAD-related traitsSamples of European ancestryCoronary artery diseaseHigh-risk individualsPotential genetic heterogeneityCurrent smokingPolygenic scoresPolygenic riskTargeted interventionsEuropean ancestryRisk scorePleiotropic regionsRisk predictionGenetic heterogeneityBiological functionsPleiotropySignificant interactionPhenotypic heterogeneityBlood pressureDisease interpretationExploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights
Wu X, Parekh P, Lin B, Pries L, Guloksuz S, Rutten B, Andreassen O, Linden D, van der Meer D. Exploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights. Schizophrenia Bulletin 2025, sbaf096. PMID: 40579369, DOI: 10.1093/schbul/sbaf096.Peer-Reviewed Original ResearchDiffusion tensor imagingBrain measuresPolygenic scoresRs-fMRIPolygenic overlapResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingGenome-wide association study summary statisticsLinkage disequilibrium score regressionConcordant effect directionsConjunctional false discovery rateSNP-based heritabilityFunctional brain featuresBrain imaging phenotypesSchizophreniaBrain structuresFunctional connectivityBrain phenotypesGenetic overlapScore regressionBrain featuresComplex genetic relationshipsRs-fMRI measuresIndividual locus levelCausal variantsImpact of Polygenic Interactions With Anticholinergic Burden on Cognition and Brain Structure in Psychosis Spectrum Disorders
Zhang L, Ivleva E, Parker D, Hill S, Lizano P, Keefe R, Keedy S, McDowell J, Pearlson G, Clementz B, Keshavan M, Gershon E, Tamminga C, Sweeney J, Bishop J. Impact of Polygenic Interactions With Anticholinergic Burden on Cognition and Brain Structure in Psychosis Spectrum Disorders. American Journal Of Psychiatry 2025, 182: 751-762. PMID: 40432343, DOI: 10.1176/appi.ajp.20240709.Peer-Reviewed Original ResearchReduced gray matter volumePsychosis spectrum disordersGray matter volumeBrain structuresPolygenic scoresPsychotic disordersMatter volumeImpact cognitionSpectrum disorderBrief Assessment of CognitionCognitive impairmentGray matter volume reductionBipolar-Schizophrenia NetworkBrain structural outcomesAssessment of cognitionBrain structure phenotypesAnticholinergic burdenPrimary cognitive outcomeGene-by-environment interactionsModerated Mediation ModelBrief assessmentBipolar disorderStructural neuroimagingPsychiatric conditionsCognitive abilitiesAssociations of Childhood Adversity and Polygenic Scores with Substance Use Initiation and Disorder Severity – ERRATUM
SooHoo J, Davis C, Han A, Jinwala Z, Gelernter J, Feinn R, Kranzler H. Associations of Childhood Adversity and Polygenic Scores with Substance Use Initiation and Disorder Severity – ERRATUM. Psychological Medicine 2025, 55: e159. PMID: 40400391, PMCID: PMC12115262, DOI: 10.1017/s0033291725100615.Peer-Reviewed Original ResearchBody fluid biomarkers and psychosis risk in The Accelerating Medicines Partnership® Schizophrenia Program: design considerations
Perkins D, Jeffries C, Clark S, Upthegrove R, Wannan C, Wray N, Li Q, Do K, Walker E, Paul Amminger G, Anticevic A, Cotter D, Ellman L, Mongan D, Phassouliotis C, Barbee J, Roth S, Billah T, Corcoran C, Calkins M, Cerrato F, Khadimallah I, Klauser P, Winter-van Rossum I, Nunez A, Bleggi R, Martin A, Bouix S, Pasternak O, Shah J, Toben C, Wolf D, Kahn R, Kane J, McGorry P, Bearden C, Nelson B, Shenton M, Woods S. Body fluid biomarkers and psychosis risk in The Accelerating Medicines Partnership® Schizophrenia Program: design considerations. Schizophrenia 2025, 11: 78. PMID: 40399418, PMCID: PMC12095529, DOI: 10.1038/s41537-025-00610-4.Peer-Reviewed Original ResearchClinical outcomesPsychosis riskChronic systemic inflammationLevels of biomarkersResults of bloodTwo-month follow-upSystemic inflammationSaliva levelsSalivary cortisol levelsFollow-upCollection of bloodBody fluid biomarkersCHR criteriaSchizophrenia ProgramPolygenic risk scoresRisk scoreMental disordersBlood proteomeSchizophreniaPreanalytical factorsBiomarkersBloodPolygenic scoresSaliva samplesCortisol levelsUnraveling the genetics of gulf war illness in diverse participants enrolled in the million veteran program
Pathak G, Koller D, Cabrera-Mendoza B, Nono Djotsa A, Wendt F, De Lillo A, Friligkou E, He J, Kouakou M, Duong L, Vahey J, Steele L, Quaden R, Harrington K, Ahmed S, Gaziano J, Concato J, Zhao H, Radhakrishnan K, Gelernter J, Gifford E, Aslan M, Helmer D, Hauser E, Polimanti R. Unraveling the genetics of gulf war illness in diverse participants enrolled in the million veteran program. Human Molecular Genetics 2025, ddaf075. PMID: 40366759, DOI: 10.1093/hmg/ddaf075.Peer-Reviewed Original ResearchPolygenic scoresGulf War IllnessGenome-wide dataDepression polygenic scoresPhenome-wide analysisDiverse ancestral backgroundsT2D polygenic scoreAssociated with higher oddsGulf War eraPolygenic architectureAncestral backgroundVeteran ProgramChronic conditionsHigher oddsType 2 diabetesGW veteransVeteransDisease pathogenesisDiverse participantsGulf WarOddsPhysical strengthIllnessComprehensive assessmentAnxietyPolygenic risk and childhood adversity as moderators of drug and alcohol withdrawal symptoms
Han A, Davis C, Jinwala Z, SooHoo J, Gelernter J, Feinn R, Kranzler H. Polygenic risk and childhood adversity as moderators of drug and alcohol withdrawal symptoms. Drug And Alcohol Dependence 2025, 273: 112712. PMID: 40449208, DOI: 10.1016/j.drugalcdep.2025.112712.Peer-Reviewed Original ResearchConceptsAdverse childhood eventsSubstance use disordersPolygenic scoresEUR individualsWithdrawal symptomsWithdrawal severityChildhood adversitySubstance useHigher polygenic scoreAssociated with tobaccoDevelopment of substance use disordersSemi-structured diagnostic instrumentMultivariate regression modelReturn to substance useTobacco withdrawal symptomsPolygenic riskManagement of withdrawal symptomsIndividual withdrawal symptomsStop substance useAlcohol withdrawal severitySecondary analysisAlcohol withdrawal symptomsSevere withdrawal symptomsOpioid withdrawal symptomsChildhood eventsMulti‐ancestry genome‐wide association study of topiramate's effects on heavy alcohol use
Davis C, Jinwala Z, Justice A, Rentsch C, Kranzler H. Multi‐ancestry genome‐wide association study of topiramate's effects on heavy alcohol use. Alcohol Clinical And Experimental Research 2025, 49: 1197-1205. PMID: 40322892, PMCID: PMC12174493, DOI: 10.1111/acer.70069.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMillion Veteran ProgramGenome-wide significancePolygenic scoresAlcohol consumptionAssociation studiesAlcohol Use Disorders Identification Test-Consumption (AUDIT-C) scoresGenome-wide association study samplesPhenome-wide association studyAlcohol useElectronic health recordsMeta-analysisGWAS Meta-AnalysisMulti-ancestry genome-wide association studyTopiramate's effectsAlcohol use disorder diagnosisCross-ancestry meta-analysisFrequency of alcohol useCandidate gene studiesHeavy alcohol useHealth recordsVeteran ProgramAlcohol-related liver diseaseCross-ancestryTreatment responseAssociations of Childhood Adversity and Polygenic Scores with Substance Use Initiation and Disorder Severity
SooHoo J, Davis C, Han A, Jinwala Z, Gelernter J, Feinn R, Kranzler H. Associations of Childhood Adversity and Polygenic Scores with Substance Use Initiation and Disorder Severity. Psychological Medicine 2025, 55: e132. PMID: 40314172, PMCID: PMC12094658, DOI: 10.1017/s0033291725001163.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAdverse Childhood ExperiencesAlcoholismBlack or African AmericanFemaleGene-Environment InteractionGenetic Predisposition to DiseaseHumansMaleMarijuana AbuseMiddle AgedMultifactorial InheritanceOpioid-Related DisordersSeverity of Illness IndexSubstance-Related DisordersWhiteYoung AdultConceptsSubstance use disorder severitySubstance use disordersAdverse childhood experiencesGene-by-environment interactionsSubstance Use InitiationPolygenic scoresOpioid use disorderUse disorderEUR individualsAssociated with AUD severityCannabis use disorderAssociated with adverse childhood experiencesSeverity of alcoholismLatent factorsSubstance use disorder riskGene-environment correlationAssociation of childhood adversityAssociation of adverse childhood experiencesAncestry groupsAUD severityDisorder severityChildhood adversityPolygenic riskChildhood experiencesEnvironmental influencesEpigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses
Pathak G, Pietrzak R, Lacobelle A, Overstreet C, Wendt F, Deak J, Friligkou E, Nunez Y, Montalvo-Ortiz J, Levey D, Kranzler H, Gelernter J, Polimanti R. Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses. Molecular Psychiatry 2025, 30: 4435-4443. PMID: 40247127, PMCID: PMC12343199, DOI: 10.1038/s41380-025-03031-y.Peer-Reviewed Original ResearchSubstance dependence diagnosesLatent class analysisDependence diagnosisLatent classesComorbidity patternsPolygenic scoresPolygenic overlapSD diagnosisPsychosocial traitsEpigenetic mechanismsClass analysisEpigenome-wide significant associationsEpigenome-wide association analysisCo-occurrenceTraitsIndividualsAssociated with CpG sitesAssociationComorbidityTDSD patternSubstancesEpigenome-wide changesIndividuals of European descentSignificant associationPolygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification
D'Aoust T, Clocchiatti‐Tuozzo S, Rivier C, Mishra A, Hachiya T, Grenier‐Boley B, Soumaré A, Duperron M, Le Grand Q, Bouteloup V, Proust‐Lima C, Samieri C, Neuffer J, Sargurupremraj M, Chêne G, Helmer C, Thibault M, Amouyel P, Lambert J, Kamatani Y, Jacqmin‐Gadda H, Tregouët D, Inouye M, Dufouil C, Falcone G, Debette S. Polygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification. Alzheimer's & Dementia 2025, 21: e70014. PMID: 40042447, PMCID: PMC11881617, DOI: 10.1002/alz.70014.Peer-Reviewed Original ResearchConceptsOlder community-dwelling peopleCommunity-dwelling peopleDementia risk stratificationVascular contribution to dementiaAssociated with dementia riskGenetic riskDementia clinical trialsApo E4Polygenic risk scoresGenetic risk groupsHigh-risk individualsDementia riskImprove risk predictionEast Asian ancestryAD-PRSPopulation-basedPolygenic scoresRisk stratificationMemory-clinic patientsPrevention programsClinical risk factorsDementiaClinical participantsRisk scoreAlzheimer's diseaseIdentification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities
Loesch D, Garg M, Matelska D, Vitsios D, Jiang X, Ritchie S, Sun B, Runz H, Whelan C, Holman R, Mentz R, Moura F, Wiviott S, Sabatine M, Udler M, Gause-Nilsson I, Petrovski S, Oscarsson J, Nag A, Paul D, Inouye M. Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities. Nature Communications 2025, 16: 2124. PMID: 40032831, PMCID: PMC11876343, DOI: 10.1038/s41467-025-56695-z.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersCardiovascular DiseasesComorbidityDiabetes Mellitus, Type 2Extracellular Matrix ProteinsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInsulin-Like Growth Factor Binding Protein 2MaleMiddle AgedMultifactorial InheritanceProteomicsRisk FactorsUnited KingdomConceptsPolygenic scoresNon-coding variantsEtiology of type 2 diabetesMolecular dataVariant effectsPathway enrichmentPlasma proteomic markersPotential therapeutic targetType 2 diabetesProteinDisease biologyPolygenic riskUK BiobankProteomic markersTherapeutic targetPathwayCirculating proteinsGenomeRisk of type 2 diabetesCardiometabolic scoreBiologyInteractive portalVariantsEnrichmentDiabetes comorbiditiesUsing twin-pairs to assess potential bias in polygenic prediction of externalising behaviours across development
Bright J, Rayner C, Freeman Z, Zavos H, Ahmadzadeh Y, Viding E, McAdams T. Using twin-pairs to assess potential bias in polygenic prediction of externalising behaviours across development. Molecular Psychiatry 2025, 30: 3129-3137. PMID: 39972057, PMCID: PMC12185310, DOI: 10.1038/s41380-025-02920-6.Peer-Reviewed Original ResearchPolygenic scoresTwin pairsGenetic influencesPassive gene-environment correlationConduct problemsCallous-unemotional traitsGene-environment correlationADHD-related symptomsGenome-wide association studiesIndirect genetic effectsCU traitsADHD symptomologyExternalising behaviourPost Hoc AnalysisGenomic dataAssociation studiesPolygenic predictionEnvironmental influencesWithin-familyGenetic effectsPost-hocTraitsScoresADHDRGES154 Polygenic Scores for Psychiatric Traits Are Associated With Substance Use Phenotypes in a Deeply Phenotyped Sample
Hartwell E, Jinwala Z, Gelernter J, Kranzler H, Kember R. S154 Polygenic Scores for Psychiatric Traits Are Associated With Substance Use Phenotypes in a Deeply Phenotyped Sample. Drug And Alcohol Dependence 2025, 267: 111574. DOI: 10.1016/j.drugalcdep.2024.111574.Peer-Reviewed Original Research
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