2022
Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits
Highland H, Wojcik G, Graff M, Nishimura K, Hodonsky C, Baldassari A, Cote A, Cheng I, Gignoux C, Tao R, Li Y, Boerwinkle E, Fornage M, Haessler J, Hindorff L, Hu Y, Justice A, Lin B, Lin D, Stram D, Haiman C, Kooperberg C, Le Marchand L, Matise T, Kenny E, Carlson C, Stahl E, Avery C, North K, Ambite J, Buyske S, Loos R, Peters U, Young K, Bien S, Huckins L. Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits. American Journal Of Human Genetics 2022, 109: 669-679. PMID: 35263625, PMCID: PMC9069067, DOI: 10.1016/j.ajhg.2022.02.013.Peer-Reviewed Original ResearchConceptsAncestrally diverse populationsBody mass indexCardiometabolic traitsEuropean ancestryGene expressionTranscriptomic imputation modelsNon-EA populationsDiverse populationsWhite British participantsReference panelGenetically regulated gene expressionGene-trait associationsTissue-specific gene expressionPopulation ArchitectureUK BiobankMeasurement of gene expressionPredicting gene expressionMulti-omics datasetsRelevant tissuesSusceptibility lociMass indexComplex traitsIdentified genesNovel associationsDiverse sample
2020
Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts
Huckins L, Chatzinakos C, Breen M, Hartmann J, Klengel T, da Silva Almeida A, Dobbyn A, Girdhar K, Hoffman G, Klengel C, Logue M, Lori A, Maihofer A, Morrison F, Nguyen H, Park Y, Ruderfer D, Sloofman L, van Rooij S, Consortium P, Baker D, Chen C, Cox N, Duncan L, Geyer M, Glatt S, Im H, Risbrough V, Smoller J, Stein D, Yehuda R, Liberzon I, Koenen K, Jovanovic T, Kellis M, Miller M, Bacanu S, Nievergelt C, Buxbaum J, Sklar P, Ressler K, Stahl E, Daskalakis N. Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts. Cell Reports 2020, 31: 107716. PMID: 32492425, PMCID: PMC7359754, DOI: 10.1016/j.celrep.2020.107716.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCase-Control StudiesCohort StudiesDexamethasoneDown-RegulationGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseHumansLeukocytesMaleMiceMice, Inbred C57BLMilitary PersonnelPrefrontal CortexRepressor ProteinsRibonucleoproteins, Small NuclearRNA InterferenceRNA, Small InterferingStress Disorders, Post-TraumaticConceptsPost-traumatic stress disorderGenetically regulated gene expressionPost-traumatic stress disorder casesDorsolateral prefrontal cortexGene expressionU12 intron splicingPrefrontal cortexStress disorderDeployment stressTranscriptome imputationTissue-specific gene expressionDifferential gene expressionMilitary cohortZNF140U12 intronsGenetic heterogeneityExpression changesFunctional roleExogenous glucocorticoidsPeripheral leukocytesEuropean cohortCortexCohortDisordersExpression
2019
63 TRANSCRIPTOMIC IMPUTATION ANALYSIS IN ANOREXIA NERVOSA IDENTIFIES BOTH METABOLIC AND PSYCHIATRIC AETIOLOGIES
Huckins L, Dobbyn A, Thornton L, Group of the PGC E, Devlin B, Sieberts S, Cox N, Im H, Breen G, Sklar P, Bulik C, Stahl E. 63 TRANSCRIPTOMIC IMPUTATION ANALYSIS IN ANOREXIA NERVOSA IDENTIFIES BOTH METABOLIC AND PSYCHIATRIC AETIOLOGIES. European Neuropsychopharmacology 2019, 29: s818. DOI: 10.1016/j.euroneuro.2017.08.064.Peer-Reviewed Original ResearchGene-tissue associationsTranscriptome imputationCommonMind ConsortiumGene expression prediction modelsGenome-wide significant lociTissue-specific gene expressionExpression prediction modelsMetabolic tissuesCaudate basal gangliaSignificant lociGenotype dataCharacterization of AnGene associationsReference panelGene expressionAetiology of ANMetabolic phenotypeMolecular pathwaysGenetic correlationsAssociation TestPsychiatric disordersAN riskMetabolic systemsImputation analysisBackground Anorexia nervosa