2025
Moderation of treatment outcomes by polygenic risk for alcohol‐related traits in placebo‐controlled trials of topiramate
Kranzler H, Jinwala Z, Davis C, Xu H, Biernacka J, Zhou H, Kember R, Gelernter J, Feinn R. Moderation of treatment outcomes by polygenic risk for alcohol‐related traits in placebo‐controlled trials of topiramate. Alcohol Clinical And Experimental Research 2025, 49: 1297-1305. PMID: 40445294, PMCID: PMC12173784, DOI: 10.1111/acer.70052.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlcoholismFemaleFructoseGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMiddle AgedMultifactorial InheritanceTopiramateTreatment OutcomeConceptsHeavy drinking daysAlcohol use disorderProblematic alcohol useAlcohol-related problemsPlacebo-controlled trialModerators of treatment outcomePlacebo-controlled trial of topiramateReduce heavy drinking daysTreat alcohol use disorderAlcohol-related traitsTrial of topiramateResponse to topiramateEffects of topiramateTime to relapseGenome-wide association studiesTopiramate's effectsAUD treatmentDrinking daysUse disorderTopiramate groupPolygenic riskHeavy drinkingAlcohol usePharmacogenetic approachShort IndexPTPN2 and Leukopenia in Individuals With Normal TPMT and NUDT15 Metabolizer Status Taking Azathioprine
Daniel L, Nepal P, Zanussi J, Dickson A, Straub P, Miller‐Fleming T, Wei W, Hung A, Cox N, Kawai V, Mosley J, Stein C, Feng Q, Liu G, Tao R, Chung C. PTPN2 and Leukopenia in Individuals With Normal TPMT and NUDT15 Metabolizer Status Taking Azathioprine. Clinical And Translational Science 2025, 18: e70220. PMID: 40442974, PMCID: PMC12122386, DOI: 10.1111/cts.70220.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significancePrincipal components of ancestryImmune cell developmentGenetic risk factorsDose-dependent side effectsAssociation studiesGenetic dataSide effects of azathioprineIntronic variantsElectronic health recordsVanderbilt's electronic health recordEffect of azathioprineCell developmentPTPN2Replication cohortTPMTHealth recordsNUDT15NIH-funded projectDrug discontinuationThiopurine useBioVUXanthine oxidase inhibitorLeukopeniaThe Eating Disorders Genetics Initiative 2 (EDGI2): study protocol
Berthold N, MacDermod C, Thornton L, Parker R, Morales S, Hog L, Kennedy H, Guintivano J, Sullivan P, Crowley J, Johnson J, Birgegård A, Fundín B, Frans E, Xu J, “Ngāti Pūkenga” M, Miller A, Aguilar M, Barakat S, Abdulkadir M, White J, Larsen J, Trujillo E, Winterman B, Zhang R, Lawson R, Wonderlich S, Wonderlich J, Schaefer L, Mehler P, Oakes J, Foster M, Gaudiani J, Vacuán E, Compte E, Petersen L, Yilmaz Z, Micali N, Jordan J, Kennedy M, Maguire S, Huckins L, Lu Y, Dinkler L, Martin N, Bulik C. The Eating Disorders Genetics Initiative 2 (EDGI2): study protocol. BMC Psychiatry 2025, 25: 532. PMID: 40419993, PMCID: PMC12105188, DOI: 10.1186/s12888-025-06777-5.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresAvoidant/restrictive food intake disorderCalculate polygenic risk scoresNational Patient RegisterPsychiatric Genomics ConsortiumEating disordersLongstanding illnessEating Disorders Working GroupUnited StatesPatient RegisterCase-controlNew ZealandCase identificationGenetic architectureEvaluate clinical outcomesFood intake disorderRisk scoreClinically relevant phenotypesStudy protocolQuestionnaire batteryFunctional biologySymptom levelsAncestral backgroundMetabolic traitsGenomics ConsortiumExamining socioeconomic differences in sepsis risk and mediation by modifiable factors: a Mendelian randomization study
Stensrud V, Rogne T, Flatby H, Mohus R, Gustad L, Nilsen T. Examining socioeconomic differences in sepsis risk and mediation by modifiable factors: a Mendelian randomization study. BMC Infectious Diseases 2025, 25: 739. PMID: 40410669, PMCID: PMC12103053, DOI: 10.1186/s12879-025-11130-y.Peer-Reviewed Original ResearchMeSH KeywordsEducational StatusFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisRisk FactorsSepsisSocioeconomic FactorsConceptsSummary-level dataSocioeconomic differencesGenome-wide association studiesGenetic instrumentsEducational attainmentMendelian randomizationMR analysisStandard deviation increaseBias due to population stratificationOdds ratioPreventive factorsMR-Egger regressionExamined socioeconomic differencesMultivariable MR analysisEffect of smoking initiationAssociation studiesMendelian randomization studiesEffects of educational attainmentDeviation increaseYears of educationBody mass indexBackgroundEducational attainmentDynastic effectsMedian OREgger regressionCharacterizing the Social Epigenome in Mexican Patients with Early-Onset Psychosis
Ruiz-Ramos D, Martínez-Magaña J, Juárez-Rojop I, Nolasco-Rosales G, Sosa-Hernández F, Cruz-Castillo J, Cavazos J, Callejas A, Zavaleta-Ramírez P, Zorrilla-Dosal J, Lanzagorta N, Nicolini H, Montalvo-Ortiz J, Glahn D, Genis-Mendoza A. Characterizing the Social Epigenome in Mexican Patients with Early-Onset Psychosis. Genes 2025, 16: 591. PMID: 40428414, PMCID: PMC12111507, DOI: 10.3390/genes16050591.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge of OnsetCpG IslandsDNA MethylationEpigenesis, GeneticEpigenomeEpigenomicsFemaleGenome-Wide Association StudyHumansMaleMexicoPsychotic DisordersYoung AdultConceptsEarly-onset psychosisRisk scoreEpigenetic ageEpigenome-wide association studiesAssociation studiesYears of educationShort life expectancyMexican patientsPsychiatric admissionsAssociation of DNA methylationSocial epigenomicsYears of schoolingAccelerated epigenetic agingLife expectancyAssociated with panic disorderEnvironmental exposuresEarly-onsetGlobal functioningClinical characteristicsClinical manifestationsDNA methylationAgeEpigenetic mechanismsPsychosisManifestation of psychosisCharacterizing pleiotropy among bipolar disorder, schizophrenia, and major depression: a genome-wide cross-disorder meta-analysis
Friligkou E, Pathak G, Tylee D, De Lillo A, Koller D, Cabrera-Mendoza B, Polimanti R. Characterizing pleiotropy among bipolar disorder, schizophrenia, and major depression: a genome-wide cross-disorder meta-analysis. Psychological Medicine 2025, 55: e145. PMID: 40357923, PMCID: PMC12094657, DOI: 10.1017/s0033291725001217.Peer-Reviewed Original ResearchMeSH KeywordsBipolar DisorderDepressive Disorder, MajorGenetic PleiotropyGenome-Wide Association StudyHumansSchizophreniaTranscriptomeConceptsBipolar disorderPleiotropic lociCross-disorder meta-analysisGenome-wide association datasetGenome-wide analysisGenome-wide significanceTissue enrichment analysisBrain transcriptomic dataBrain transcriptome profilesPsychiatric Genomics ConsortiumCadherin signalingGenome-wideGenetic architectureGene discoveryDiagnostic boundariesPleiotropic variantsFrontal cortexReceptor-mediated signalingTranscriptome dataSchizophreniaGenetic mechanismsGenomics ConsortiumTranscriptome profilingAssociation datasetEnrichment analysisGenome-wide analyses identify 30 loci associated with obsessive–compulsive disorder
Strom N, Gerring Z, Galimberti M, Yu D, Halvorsen M, Abdellaoui A, Rodriguez-Fontenla C, Sealock J, Bigdeli T, Coleman J, Mahjani B, Thorp J, Bey K, Burton C, Luykx J, Zai G, Alemany S, Andre C, Askland K, Bäckman J, Banaj N, Barlassina C, Nissen J, Bienvenu O, Black D, Bloch M, Børte S, Bosch R, Breen M, Brennan B, Brentani H, Buxbaum J, Bybjerg-Grauholm J, Byrne E, Cabana-Dominguez J, Camarena B, Camarena A, Cappi C, Carracedo A, Casas M, Cavallini M, Ciullo V, Cook E, Crosby J, Cullen B, De Schipper E, Delorme R, Djurovic S, Elias J, Estivill X, Falkenstein M, Fundin B, Garner L, Gironda C, Goes F, Grados M, Grove J, Guo W, Haavik J, Hagen K, Harrington K, Havdahl A, Höffler K, Hounie A, Hucks D, Hultman C, Janecka M, Jenike E, Karlsson E, Kelley K, Klawohn J, Krasnow J, Krebs K, Lange C, Lanzagorta N, Levey D, Lindblad-Toh K, Macciardi F, Maher B, Mathes B, McArthur E, McGregor N, McLaughlin N, Meier S, Miguel E, Mulhern M, Nestadt P, Nurmi E, O’Connell K, Osiecki L, Ousdal O, Palviainen T, Pedersen N, Piras F, Piras F, Potluri S, Rabionet R, Ramirez A, Rauch S, Reichenberg A, Riddle M, Ripke S, Rosário M, Sampaio A, Schiele M, Skogholt A, Sloofman L, Smit J, Artigas M, Thomas L, Tifft E, Vallada H, van Kirk N, Veenstra-VanderWeele J, Vulink N, Walker C, Wang Y, Wendland J, Winsvold B, Yao Y, Zhou H, Agrawal A, Alonso P, Berberich G, Bucholz K, Bulik C, Cath D, Denys D, Eapen V, Edenberg H, Falkai P, Fernandez T, Fyer A, Gaziano J, Geller D, Grabe H, Greenberg B, Hanna G, Hickie I, Hougaard D, Kathmann N, Kennedy J, Lai D, Landén M, Hellard S, Leboyer M, Lochner C, McCracken J, Medland S, Mortensen P, Neale B, Nicolini H, Nordentoft M, Pato M, Pato C, Pauls D, Piacentini J, Pittenger C, Posthuma D, Ramos-Quiroga J, Rasmussen S, Richter M, Rosenberg D, Ruhrmann S, Samuels J, Sandin S, Sandor P, Spalletta G, Stein D, Stewart S, Storch E, Stranger B, Turiel M, Werge T, Andreassen O, Børglum A, Walitza S, Hveem K, Hansen B, Rück C, Martin N, Milani L, Mors O, Reichborn-Kjennerud T, Ribasés M, Kvale G, Mataix-Cols D, Domschke K, Grünblatt E, Wagner M, Zwart J, Breen G, Nestadt G, Kaprio J, Arnold P, Grice D, Knowles J, Ask H, Verweij K, Davis L, Smit D, Crowley J, Scharf J, Stein M, Gelernter J, Mathews C, Derks E, Mattheisen M. Genome-wide analyses identify 30 loci associated with obsessive–compulsive disorder. Nature Genetics 2025, 57: 1389-1401. PMID: 40360802, PMCID: PMC12165847, DOI: 10.1038/s41588-025-02189-z.Peer-Reviewed Original ResearchMeSH KeywordsAdultCase-Control StudiesFemaleGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleObsessive-Compulsive DisorderPolymorphism, Single NucleotideConceptsObsessive-compulsive disorderGenome-wide association studiesGenetic riskObsessive-compulsive disorder casesGenome-wide significant lociMedium spiny neuronsGenome-wide analysisMajor histocompatibility complexGene-based approachPsychiatric disordersSpiny neuronsTourette syndromeAnorexia nervosaSignificant lociEffector genesAssociation studiesAssociated with excitatory neuronsMultiple genesGenetic variantsAssociated with inflammatory bowel diseaseBody mass indexGenetic heritabilityDisordersExcitatory neuronsInflammatory bowel diseaseIntegrating HiTOP and RDoC frameworks part II: shared and distinct biological mechanisms of externalizing and internalizing psychopathology
Davis C, Khan Y, Toikumo S, Jinwala Z, Boomsma D, Levey D, Gelernter J, Kember R, Kranzler H. Integrating HiTOP and RDoC frameworks part II: shared and distinct biological mechanisms of externalizing and internalizing psychopathology. Psychological Medicine 2025, 55: e137. PMID: 40340892, PMCID: PMC12094665, DOI: 10.1017/s0033291725000819.Peer-Reviewed Original ResearchMeSH KeywordsBrainDrug RepositioningGenome-Wide Association StudyHumansMagnetic Resonance ImagingMaleMental DisordersPsychopathologyConceptsDrug repurposing analysisAssociated with reduced gray matter volumeHierarchical Taxonomy of PsychopathologyGenome-wide association studiesTaxonomy of PsychopathologyResearch Domain CriteriaTissue-specific expression patternsAspects of psychopathologyGray matter volumeSingle-cell RNA sequencing dataGene identification methodsMagnetic resonance imaging dataMulti-omics approachRNA sequencing dataBrain cell typesHiTOP frameworkInternalizing psychopathologyPhysical health conditionsPsychopathological spectrumSubcallosal cortexGene annotationMatter volumeGenomic insightsSequence dataGenetic liabilityIntegrating HiTOP and RDoC frameworks Part I: Genetic architecture of externalizing and internalizing psychopathology
Davis C, Khan Y, Toikumo S, Jinwala Z, Boomsma D, Levey D, Gelernter J, Kember R, Kranzler H. Integrating HiTOP and RDoC frameworks Part I: Genetic architecture of externalizing and internalizing psychopathology. Psychological Medicine 2025, 55: e138. PMID: 40336358, PMCID: PMC12094639, DOI: 10.1017/s0033291725000856.Peer-Reviewed Original ResearchMeSH KeywordsAdultComorbidityDepressive Disorder, MajorFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLatent Class AnalysisMaleMental DisordersPsychopathologyConceptsGenome-wide association studiesMultivariate genome-wide association studyGenetic architectureComorbid forms of psychopathologyHierarchical Taxonomy of PsychopathologyBivariate causal mixture modelResearch Domain CriteriaTaxonomy of PsychopathologyPsychiatric classification systemsConfirmatory factor modelsInternalizing psychopathologyComorbid formsGenetic liabilityPsychopathologyTwo-factorHierarchical taxonomyModerate genetic correlationLatent factorsAssociation studiesBiological basisHiTOPReference panelGenetic underpinningsFactor modelGenetic variantsMulti‐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 ResearchMeSH KeywordsAdultAgedAlcohol DrinkingAlcoholismFemaleGenome-Wide Association StudyHumansMaleMiddle AgedTopiramateConceptsGenome-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 responseAdvancing translational exposomics: bridging genome, exposome and personalized medicine
Sarigiannis D, Karakitsios S, Anesti O, Stem A, Valvi D, Sumner S, Chatzi L, Snyder M, Thompson D, Vasiliou V. Advancing translational exposomics: bridging genome, exposome and personalized medicine. Human Genomics 2025, 19: 48. PMID: 40307849, PMCID: PMC12044731, DOI: 10.1186/s40246-025-00761-6.Peer-Reviewed Original ResearchMeSH KeywordsEnvironmental ExposureExposomeGenetic Predisposition to DiseaseGenome, HumanGenome-Wide Association StudyGenomicsHumansPrecision MedicineTranslational Research, BiomedicalConceptsExposome-wide association studyBridge genomicsLifestyle exposuresEnhancing causal inferencePublic health decision-makingEnvironmental health researchHealth decision-makingMulti-omics technologiesGenomic variationGenomic dataAssociation studiesHealth outcomesBioinformatics approachHealth researchPrecision preventionGenetic variabilityExposome dataExposure-response relationshipMulti-omicsGenomeInternal exposomeVulnerable populationsComplex diseasesDisease phenotypePublic healthA multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder
Wang J, Liu Y, Li H, Nguyen T, Soto-Vargas J, Wilson R, Wang W, Lam T, Zhang C, Lin C, Lewis D, Glausier J, Holtzheimer P, Friedman M, Williams K, Picciotto M, Nairn A, Krystal J, Duman R, Young K, Zhao H, Girgenti M. A multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder. Genome Medicine 2025, 17: 43. PMID: 40301990, PMCID: PMC12042318, DOI: 10.1186/s13073-025-01473-1.Peer-Reviewed Original ResearchConceptsPost-traumatic stress disorderDorsolateral prefrontal cortexPsychiatric disordersAutism spectrum disorderPrefrontal cortexDepressive disorderStress disorderGamma-aminobutyric acidGenome-wide association studiesPTSD brainsGenome-wide measurementsStudies of postmortem brainsSubgenual prefrontal cortexDisabling psychiatric disorderMultiple psychiatric disordersPrefrontal cortical areasPTSD casesHuman brain studiesBrain regionsSpectrum disorderGABAergic processesPostmortem brainsMDDProtein co-expression modulesProteomic profilingBayesian Longitudinal Network Regression With Application to Brain Connectome Genetics
Li C, Tian X, Gao S, Wang S, Wang G, Zhao Y, Zhao Y. Bayesian Longitudinal Network Regression With Application to Brain Connectome Genetics. Statistics In Medicine 2025, 44: e70069. PMID: 40277222, DOI: 10.1002/sim.70069.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBayes TheoremBrainComputer SimulationConnectomeGenome-Wide Association StudyHumansLongitudinal StudiesMagnetic Resonance ImagingModels, StatisticalRegression AnalysisConceptsSample relatednessLongitudinal genome-wide association studiesGenome-wide association studiesBrain imaging genetic studiesMultivariate phenotypesGenetic signalsImaging genetics studiesAssociation studiesGenetic studiesGenetic variantsGenetic underpinningsGenetic contributionGenetic effectsRelatednessAdolescent Brain Cognitive DevelopmentBrain functional connectivityFunctional organizationBiological architectureFunctional connectivityRobust inferenceGeneticsPhenotypeAnalytical challengesPosterior inferenceBrain network configurationDifferential gene expression study in whole blood identifies candidate genes for psychosis in African American individuals
Knowles E, Peralta J, Rodrigue A, Mathias S, Mollon J, Leandro A, Curran J, Blangero J, Glahn D. Differential gene expression study in whole blood identifies candidate genes for psychosis in African American individuals. Schizophrenia Research 2025, 280: 85-94. PMID: 40267851, PMCID: PMC12107465, DOI: 10.1016/j.schres.2025.04.018.Peer-Reviewed Original ResearchConceptsGene expressionGenome-wide associationDifferential gene expression studiesGene co-expression network analysisWeighted gene co-expression network analysisCo-expression network analysisGene expression phenotypesIndividuals of European descentOverrepresentation of biological processesGene expression studiesGene expression analysisAfrican American ancestryGenomic regionsPsychosis-spectrum disordersRNA-seqAfrican American individualsPopulation stratificationAssociated with psychosisEtiology of psychosisSignificant genesCellular functionsExpression phenotypesExpression studiesAmerican ancestryExpression analysisIdentification of genetic architecture shared between schizophrenia and Alzheimer’s disease
Liu H, Xie Y, Ji Y, Zhou Y, Xu J, Tang J, Liu N, Ding H, Qin W, Liu F, Yu C. Identification of genetic architecture shared between schizophrenia and Alzheimer’s disease. Translational Psychiatry 2025, 15: 150. PMID: 40240757, PMCID: PMC12003746, DOI: 10.1038/s41398-025-03348-w.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMultifactorial InheritancePolymorphism, Single NucleotideSchizophreniaConceptsPolygenic overlapFalse discovery rateGenetic architectureAlzheimer's diseaseConditional/conjunctional false discovery rateConditional false discovery rateGenome-wide association studiesIndividuals of European ancestryConcordant effect directionsGenetic risk architectureMolecular genetic mechanismsHeritable brain disorderAssociation studiesGenetic mechanismsGenetic variantsEuropean ancestryGenetic associationObserved comorbiditySchizophreniaSNPsDiscovery rateCognitive declineRisk architectureBrain disordersGenetic correlationsTranslational genomics of osteoarthritis in 1,962,069 individuals
Hatzikotoulas K, Southam L, Stefansdottir L, Boer C, McDonald M, Pett J, Park Y, Tuerlings M, Mulders R, Barysenka A, Arruda A, Tragante V, Rocco A, Bittner N, Chen S, Horn S, Srinivasasainagendra V, To K, Katsoula G, Kreitmaier P, Tenghe A, Gilly A, Arbeeva L, Chen L, de Pins A, Dochtermann D, Henkel C, Höijer J, Ito S, Lind P, Lukusa-Sawalena B, Minn A, Mola-Caminal M, Narita A, Nguyen C, Reimann E, Silberstein M, Skogholt A, Tiwari H, Yau M, Yue M, Zhao W, Zhou J, Alexiadis G, Banasik K, Brunak S, Campbell A, Cheung J, Dowsett J, Faquih T, Faul J, Fei L, Fenstad A, Funayama T, Gabrielsen M, Gocho C, Gromov K, Hansen T, Hudjashov G, Ingvarsson T, Johnson J, Jonsson H, Kakehi S, Karjalainen J, Kasbohm E, Lemmelä S, Lin K, Liu X, Loef M, Mangino M, McCartney D, Millwood I, Richman J, Roberts M, Ryan K, Samartzis D, Shivakumar M, Skou S, Sugimoto S, Suzuki K, Takuwa H, Teder-Laving M, Thomas L, Tomizuka K, Turman C, Weiss S, Wu T, Zengini E, Zhang Y, Ferreira M, Babis G, Baras A, Barker T, Carey D, Cheah K, Chen Z, Cheung J, Daly M, de Mutsert R, Eaton C, Erikstrup C, Furnes O, Golightly Y, Gudbjartsson D, Hailer N, Hayward C, Hochberg M, Homuth G, Huckins L, Hveem K, Ikegawa S, Ishijima M, Isomura M, Jones M, Kang J, Kardia S, Kloppenburg M, Kraft P, Kumahashi N, Kuwata S, Lee M, Lee P, Lerner R, Li L, Lietman S, Lotta L, Lupton M, Mägi R, Martin N, McAlindon T, Medland S, Michaëlsson K, Mitchell B, Mook-Kanamori D, Morris A, Nabika T, Nagami F, Nelson A, Ostrowski S, Palotie A, Pedersen O, Rosendaal F, Sakurai-Yageta M, Schmidt C, Sham P, Singh J, Smelser D, Smith J, Song Y, Sørensen E, Tamiya G, Tamura Y, Terao C, Thorleifsson G, Troelsen A, Tsezou A, Uchio Y, Uitterlinden A, Ullum H, Valdes A, van Heel D, Walters R, Weir D, Wilkinson J, Winsvold B, Yamamoto M, Zwart J, Stefansson K, Meulenbelt I, Teichmann S, van Meurs J, Styrkarsdottir U, Zeggini E. Translational genomics of osteoarthritis in 1,962,069 individuals. Nature 2025, 641: 1217-1224. PMID: 40205036, PMCID: PMC12119359, DOI: 10.1038/s41586-025-08771-z.Peer-Reviewed Original ResearchConceptsEffector genesGenome-wide association study meta-analysesTargets of approved drugsVariant associationsTranslational genomicsEpigenomic profilingStudy meta-analysesCircadian clockBiological processesLines of evidenceConditions associated with disabilityRepurposing opportunitiesSignal enrichmentGenesEffectorPathwayIndependent associationsMeta-analysesEffect sizeAccelerated translationEpigenomeTranscriptomeProteomicsDisease-modifying treatmentsOsteoarthritisPsychiatric genetics in the diverse landscape of Latin American populations
Bruxel E, Rovaris D, Belangero S, Chavarría-Soley G, Cuellar-Barboza A, Martínez-Magaña J, Nagamatsu S, Nievergelt C, Núñez-Ríos D, Ota V, Peterson R, Sloofman L, Adams A, Albino E, Alvarado A, Andrade-Brito D, Arguello-Pascualli P, Bandeira C, Bau C, Bulik C, Buxbaum J, Cappi C, Corral-Frias N, Corrales A, Corsi-Zuelli F, Crowley J, Cupertino R, da Silva B, De Almeida S, De la Hoz J, Forero D, Fries G, Gelernter J, González-Giraldo Y, Grevet E, Grice D, Hernández-Garayua A, Hettema J, Ibáñez A, Ionita-Laza I, Lattig M, Lima Y, Lin Y, López-León S, Loureiro C, Martínez-Cerdeño V, Martínez-Levy G, Melin K, Moreno-De-Luca D, Muniz Carvalho C, Olivares A, Oliveira V, Ormond R, Palmer A, Panzenhagen A, Passos-Bueno M, Peng Q, Pérez-Palma E, Prieto M, Roussos P, Sanchez-Roige S, Santamaría-García H, Shansis F, Sharp R, Storch E, Tavares M, Tietz G, Torres-Hernández B, Tovo-Rodrigues L, Trelles P, Trujillo-ChiVacuan E, Velásquez M, Vera-Urbina F, Voloudakis G, Wegman-Ostrosky T, Zhen-Duan J, Zhou H, Santoro M, Nicolini H, Atkinson E, Giusti-Rodríguez P, Montalvo-Ortiz J. Psychiatric genetics in the diverse landscape of Latin American populations. Nature Genetics 2025, 57: 1074-1088. PMID: 40175716, PMCID: PMC12133068, DOI: 10.1038/s41588-025-02127-z.Peer-Reviewed Original ResearchMeSH KeywordsCaribbean RegionGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenomicsHumansLatin AmericaMental DisordersConceptsGenome-wide association studiesPsychiatric genomicsPsychiatric genome-wide association studiesLarge-scale genome-wide association studiesGenetic risk lociNon-European populationsGenetic diversityRisk lociGenetic admixtureBurden of psychiatric disordersAssociation studiesPsychiatric disordersEuropean ancestryPsychiatric geneticsGenomeHealthcare disparitiesConsortium effortLatin American populationsPromote equityEnvironmental factorsDiversityAmerican populationDiverse landscapeLociAncestryAlcohol use disorder and body mass index show genetic pleiotropy and shared neural associations
Malone S, Davis C, Piserchia Z, Setzer M, Toikumo S, Zhou H, Winterlind E, Gelernter J, Justice A, Leggio L, Rentsch C, Kranzler H, Gray J. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations. Nature Human Behaviour 2025, 9: 1056-1066. PMID: 40164914, DOI: 10.1038/s41562-025-02148-y.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlcoholismBody Mass IndexBrainFemaleGenetic PleiotropyGenome-Wide Association StudyHumansMaleMiddle AgedMultifactorial InheritancePhenotypePolymorphism, Single NucleotideConceptsAlcohol use disorderUse disorderBrain regionsGenotype-Tissue ExpressionSingle-nucleotide polymorphismsPolygenic overlapAssociated with alcohol use disorderCaudate nucleus volumeBody mass indexMultiple brain regionsConjunctional false discovery rateNeurobiological overlapExecutive functionNeurobiological mechanismsNeural associationsBrain phenotypesNucleus volumeFalse discovery rate methodFalse discovery rateGenetic architectureVariant effectsMass indexGenetic pleiotropyDiscovery rateTissue enrichmentEnhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS
Goovaerts S, Naqvi S, Hoskens H, Herrick N, Yuan M, Shriver M, Shaffer J, Walsh S, Weinberg S, Wysocka J, Claes P. Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS. Communications Biology 2025, 8: 439. PMID: 40087503, PMCID: PMC11909261, DOI: 10.1038/s42003-025-07875-6.Peer-Reviewed Original ResearchMeSH KeywordsGenetic PleiotropyGenome-Wide Association StudyHumansPolymorphism, Single NucleotideSkullConceptsCranial vault shapeVault shapeGenomic lociGenetic discovery effortsSNP discoveryCraniofacial developmentGenetic architectureGWAS dataGWAS studiesTranscription factorsGenetic studiesCranial vaultGenetic understandingShape variationSignaling pathwayBrain shapeExperimental biologyBrain shape variationCraniofacial complexFDR methodLociDiscovery effortsFacial shapeWealth of knowledgeGWASOptimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants
Yuan M, Goovaerts S, Lee M, Devine J, Richmond S, Walsh S, Shriver M, Shaffer J, Marazita M, Peeters H, Weinberg S, Claes P. Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants. Briefings In Bioinformatics 2025, 26: bbaf090. PMID: 40062617, PMCID: PMC11891655, DOI: 10.1093/bib/bbaf090.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsGenetic VariationGenome-Wide Association StudyGenotypeHumansPhenotypePolymorphism, Single NucleotidePrincipal Component AnalysisConceptsRare variant association studiesGenome-wide association studiesComplex morphological traitsGenomic lociSNP heritabilityAssociation studiesRare variantsPhenotypic variationMorphological traitsAxes of phenotypic variationContext of genome-wide association studiesVariant association studiesIndividuals of European ancestryGene-based testsLinkage disequilibrium score regressionRare genetic variantsGenomic relatednessOptimal phenotypeUnrelated individualsGenetic variantsRelevant traitsEuropean ancestryScore regressionPhenotype distributionFamily data
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