2023
56. USING HIPSC-NEURONS AND CRISPR TO UNCOVER NON-ADDITIVE EFFECTS OF SCZ RISK GENES
Deans M, Seah C, Johnson J, García-González J, Townsley K, Cao E, Schrode N, Stahl E, O'Reilly P, Huckins L, Brennand K. 56. USING HIPSC-NEURONS AND CRISPR TO UNCOVER NON-ADDITIVE EFFECTS OF SCZ RISK GENES. European Neuropsychopharmacology 2023, 75: s86. DOI: 10.1016/j.euroneuro.2023.08.162.Peer-Reviewed Original ResearchSCZ risk genesNon-additive effectsRisk genesCombinatorial perturbationsTranscriptomic effectsFunctional roleRisk variantsGene expression changesBulk RNA-seqMultiple functional rolesSynaptic functionHigh-throughput imagingFunctional redundancyTranscriptional regulatorsRNA-seqCRISPR activationCellular phenotypesRNA interferenceEGenesGene expressionExpression changesHiPSC neuronsPolygenic risk scoresGenetic studiesGenesT65. GENES IN POSTMORTEM BRAIN TISSUE DIFFERENTIALLY EXPRESSED IN CHRONIC PAIN
Collier L, Seah C, Kozik E, Group T, Girgenti M, Huckins L, Johnston K. T65. GENES IN POSTMORTEM BRAIN TISSUE DIFFERENTIALLY EXPRESSED IN CHRONIC PAIN. European Neuropsychopharmacology 2023, 75: s196-s197. DOI: 10.1016/j.euroneuro.2023.08.350.Peer-Reviewed Original ResearchChronic painBackground Chronic painBone cancer painPain-related conditionsVEGF BFalse discovery rate correctionCancer painEndometrial cancerRheumatoid arthritisBrain gene expression datasetsGene expressionPainPsychiatric conditionsLinear regression modelsMultiple testingSpecific cell typesGene expression analysisCell typesRate correctionRegression modelsSurrogate variablesDifferential gene expression analysisDACCMeasured variablesExpressionGenetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing
Johnston K, Cote A, Hicks E, Johnson J, Huckins L. Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing. Biological Psychiatry 2023, 95: 745-761. PMID: 37678542, PMCID: PMC10924073, DOI: 10.1016/j.biopsych.2023.08.023.Peer-Reviewed Original ResearchConceptsGenetically regulated gene expressionMultisite chronic painGene-tissue associationsMean pain scoreUnique genesChronic painAssociation studiesS-PrediXcanGene expressionPain scoresTranscriptome-wide association studyPhenome-wide association studyCardiac dysrhythmiasMetabolic syndromeGenome-wide association studiesAssociated with cardiac dysrhythmiasDrug targetsGenotype-phenotype gapChronic pain developmentAssociation study resultsGene expression changesJoint/ligament sprainsDirection of effectTranscriptome imputationPain traits
2022
Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression
Seah C, Breen M, Rusielewicz T, Bader H, Xu C, Hunter C, McCarthy B, Deans P, Chattopadhyay M, Goldberg J, Desarnaud F, Makotkine I, Flory J, Bierer L, Staniskyte M, Noggle S, Huckins L, Paull D, Brennand K, Yehuda R. Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression. Nature Neuroscience 2022, 25: 1434-1445. PMID: 36266471, PMCID: PMC9630117, DOI: 10.1038/s41593-022-01161-y.Peer-Reviewed Original ResearchConceptsPost-traumatic stress disorderPeripheral blood mononuclear cellsGlucocorticoid-induced changesGlucocorticoid-induced gene expressionBlood mononuclear cellsIndividual clinical outcomesEnvironmental risk factorsHuman postmortem brainGlucocorticoid hypersensitivityClinical outcomesGlutamatergic neuronsMononuclear cellsRisk factorsHydrocortisone exposureSevere traumaPostmortem brainsHuman neuronsGlucocorticoid responseInduced neuronsStress disorderNeuronsNew therapeuticsGene expressionGene × environment interactionsCombat veteransPredicted 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 sampleAltered gene expression and PTSD symptom dimensions in World Trade Center responders
Marchese S, Cancelmo L, Diab O, Cahn L, Aaronson C, Daskalakis NP, Schaffer J, Horn SR, Johnson JS, Schechter C, Desarnaud F, Bierer LM, Makotkine I, Flory JD, Crane M, Moline JM, Udasin IG, Harrison DJ, Roussos P, Charney DS, Koenen KC, Southwick SM, Yehuda R, Pietrzak RH, Huckins LM, Feder A. Altered gene expression and PTSD symptom dimensions in World Trade Center responders. Molecular Psychiatry 2022, 27: 2225-2246. PMID: 35177824, DOI: 10.1038/s41380-022-01457-2.Peer-Reviewed Original ResearchConceptsPTSD symptom dimensionsPosttraumatic stress disorderCAPS scoresAnxious arousal symptomsSymptom dimensionsWorld Trade Center rescueClinician-Administered PTSD Scale scoresBiomarker of PTSDArousal symptomsCD4 T cellsWorld Trade Center respondersDevelopment of PTSDTotal CAPS scoresCase/control statusTherapeutic target developmentIdentification of biomarkersClinical interview dataResponder cohortPTSD symptom severityPotential biological differencesWTC respondersT cellsGene expressionPTSD studiesPsychiatric disorders
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
SU11 GENETICALLY PREDICTED GENE EXPRESSION IN THE BRAIN AND PERIPHERAL TISSUES ASSOCIATES WITH PTSD
Huckins L, Girdhar K, Dobbyn A, Jovanovic T, Nievergelt C, Hoffman G, Maihofer A, Stein M, Sklar P, Ressler K, Buxbaum J, Stahl E, Daskalakis N, Consortium T, Group P. SU11 GENETICALLY PREDICTED GENE EXPRESSION IN THE BRAIN AND PERIPHERAL TISSUES ASSOCIATES WITH PTSD. European Neuropsychopharmacology 2019, 29: s892-s893. DOI: 10.1016/j.euroneuro.2017.08.200.Peer-Reviewed Original ResearchPost-traumatic stress disorderPsychiatric disordersBrain regionsPost-traumatic stress disorder patientsPost-traumatic stress disorder developmentGenotype-Tissue ExpressionCommonMind ConsortiumIndividuals exposed to traumaDebilitating psychiatric disorderPeripheral tissuesGene expression prediction modelsGene expressionGene-tissue associationsPGC-PTSDStress disorderPTSD riskExpression prediction modelsTrauma typesMulti-system dysregulationImmune dysregulationGenotype dataDisordersGene associationsReference panelGenetic heterogeneity63 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
2018
Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS
Dobbyn A, Huckins L, Boocock J, Sloofman L, Glicksberg B, Giambartolomei C, Hoffman G, Perumal T, Girdhar K, Jiang Y, Raj T, Ruderfer D, Kramer R, Pinto D, Akbarian S, Roussos P, Domenici E, Devlin B, Sklar P, Stahl E, Sieberts S, Sklar P, Buxbaum J, Devlin B, Lewis D, Gur R, Hahn C, Hirai K, Toyoshiba H, Domenici E, Essioux L, Mangravite L, Peters M, Lehner T, Lipska B, Cicek A, Lu C, Roeder K, Xie L, Talbot K, Hemby S, Essioux L, Browne A, Chess A, Topol A, Charney A, Dobbyn A, Readhead B, Zhang B, Pinto D, Bennett D, Kavanagh D, Ruderfer D, Stahl E, Schadt E, Hoffman G, Shah H, Zhu J, Johnson J, Fullard J, Dudley J, Girdhar K, Brennand K, Sloofman L, Huckins L, Fromer M, Mahajan M, Roussos P, Akbarian S, Purcell S, Hamamsy T, Raj T, Haroutunian V, Wang Y, Gümüş Z, Senthil G, Kramer R, Logsdon B, Derry J, Dang K, Sieberts S, Perumal T, Visintainer R, Shinobu L, Sullivan P, Klei L. Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS. American Journal Of Human Genetics 2018, 102: 1169-1184. PMID: 29805045, PMCID: PMC5993513, DOI: 10.1016/j.ajhg.2018.04.011.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociConditional expression quantitative trait lociCommonMind ConsortiumEQTL signalsGenome-wide association study (GWAS) lociSchizophrenia GWASContext-specific regulationQuantitative trait lociCo-localization analysisGene expression levelsGWAS associationsNovel genesTrait lociStudy lociCausal genesEQTL dataFine mappingGenomic featuresGWAS statisticsGene expressionGenesGWASLociExpression levelsHuman brain samples
2017
Novel Bipolar And Schizophrenia Risk Genes Identified Through Genic Associations In Transcriptome Imputation
Huckins L, Dobbyn A, Ruderfer D, Fromer M, Consortium C, Cox N, Im H, Sieberts S, Devlin B, Roussos P, Purcell S, Sklar P, Stahl E. Novel Bipolar And Schizophrenia Risk Genes Identified Through Genic Associations In Transcriptome Imputation. European Neuropsychopharmacology 2017, 27: s487. DOI: 10.1016/j.euroneuro.2016.09.577.Peer-Reviewed Original ResearchPsychiatric Genomics ConsortiumGenome-wide significanceGenic associationsGene expressionAssociation studiesPsychiatric Genomics Consortium schizophreniaRisk genesLarge-scale transcriptome datasetsVariants regulate gene expressionBackgroundGenome-wide association studiesTissue-specific gene expression levelsGWAS sample sizeNovel risk genesRNA-seq dataBipolar disorderSchizophrenia risk genesBiologically relevant dataCase-control sampleGWAS lociGene expression levelsGenome-wideGWAS datasetDisease architectureGenomic regionsTop loci