Featured Publications
Synergistic effects of common schizophrenia risk variants
Schrode N, Ho SM, Yamamuro K, Dobbyn A, Huckins L, Matos MR, Cheng E, Deans PJM, Flaherty E, Barretto N, Topol A, Alganem K, Abadali S, Gregory J, Hoelzli E, Phatnani H, Singh V, Girish D, Aronow B, Mccullumsmith R, Hoffman GE, Stahl EA, Morishita H, Sklar P, Brennand KJ. Synergistic effects of common schizophrenia risk variants. Nature Genetics 2019, 51: 1475-1485. PMID: 31548722, PMCID: PMC6778520, DOI: 10.1038/s41588-019-0497-5.Peer-Reviewed Original ResearchMeSH KeywordsChloride ChannelsCRISPR-Cas SystemsFemaleFurinGene EditingGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInduced Pluripotent Stem CellsMaleMonomeric Clathrin Assembly ProteinsPolymorphism, Single NucleotideQuantitative Trait LociSchizophreniaSNARE ProteinsConceptsExpression quantitative trait lociComplex genetic disorderEQTL genesCommon variantsQuantitative trait lociRisk variantsGene expression differencesPsychiatric disease riskCommon risk variantsPluripotent stem cellsSchizophrenia risk variantsGenetic disordersTrait lociGene perturbationsGenetic approachesExpression differencesGene editingStem cellsGeneralizable phenomenonSynaptic functionGenesVariantsCRISPRLociSpecific effectsModelling schizophrenia using human induced pluripotent stem cells
Brennand K, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, Gage F. Modelling schizophrenia using human induced pluripotent stem cells. Nature 2011, 473: 221-225. PMID: 21490598, PMCID: PMC3392969, DOI: 10.1038/nature09915.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAntipsychotic AgentsCell DifferentiationCells, CulturedCellular ReprogrammingChildDisks Large Homolog 4 ProteinFemaleFibroblastsGene Expression ProfilingGene Expression RegulationHumansIntracellular Signaling Peptides and ProteinsLoxapineMaleMembrane ProteinsModels, BiologicalNeuritesNeuronsPhenotypePluripotent Stem CellsReceptors, GlutamateSchizophreniaYoung Adult
2023
Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders
Ma Y, Bendl J, Hartley B, Fullard J, Abdelaal R, Ho S, Kosoy R, Gochman P, Rapoport J, Hoffman G, Brennand K, Roussos P. Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders. Biological Psychiatry 2023, 95: 187-198. PMID: 37454787, PMCID: PMC10787819, DOI: 10.1016/j.biopsych.2023.07.003.Peer-Reviewed Original ResearchMeSH KeywordsBrainGene Expression RegulationHumansInduced Pluripotent Stem CellsNeuronsSchizophreniaConceptsTranscriptional programsBrain-related disordersGlutamatergic neuronsGene coexpression network analysisSignificant heritability enrichmentsEnhancer-promoter interactionsCoexpression network analysisDisease-associated genesExpression of genesLarge-scale geneticMultiomics data integrationChromatin accessibilityEpigenomic changesHeritability enrichmentGenetic regulationRegulatory elementsMultiple genesSequence variationGene expressionAxon guidanceGenetic riskPotassium chloride-induced depolarizationActivity-dependent changesDepolarization-induced changesGenes
2022
Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders
Seah C, Huckins L, Brennand K. Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders. Biological Psychiatry 2022, 93: 642-650. PMID: 36658083, DOI: 10.1016/j.biopsych.2022.09.033.Peer-Reviewed Original ResearchMeSH KeywordsGene Expression RegulationGenome-Wide Association StudyHumansInduced Pluripotent Stem CellsMental DisordersQuantitative Trait LociConceptsStem cell modelCell typesTarget genesGenome-wide association study (GWAS) lociExpression quantitative trait lociGenome-wide association studiesParallel reporter assaysQuantitative trait lociStem cell-derived cell typesPluripotent stem cell modelsComplex polygenic architectureContext-specific mannerPsychiatric disorder riskTrait lociRegulates transcriptionStudy lociGenetic regulationPolygenic architectureCRISPR screensCell modelCausal variantsRegulated expressionPatient-specific humanReporter assaysAssociation studiesA bidirectional competitive interaction between circHomer1 and Homer1b within the orbitofrontal cortex regulates reversal learning
Hafez A, Zimmerman A, Papageorgiou G, Chandrasekaran J, Amoah S, Lin R, Lozano E, Pierotti C, Dell'Orco M, Hartley B, Alural B, Lalonde J, Esposito J, Berretta S, Squassina A, Chillotti C, Voloudakis G, Shao Z, Fullard J, Brennand K, Turecki G, Roussos P, Perlis R, Haggarty S, Perrone-Bizzozero N, Brigman J, Mellios N. A bidirectional competitive interaction between circHomer1 and Homer1b within the orbitofrontal cortex regulates reversal learning. Cell Reports 2022, 38: 110282. PMID: 35045295, PMCID: PMC8809079, DOI: 10.1016/j.celrep.2021.110282.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBipolar DisorderGene Expression RegulationGene Knockdown TechniquesHomer Scaffolding ProteinsHumansMaleMiceMice, Inbred C57BLPrefrontal CortexReversal LearningRNA, CircularConceptsImportance of circRNAsRNA-binding proteinSynaptic gene expressionCircular RNAsGene expressionOrbitofrontal cortexCompetitive interactionsComplete rescuePsychiatric disordersKnockdownSynaptic expressionMechanistic insightsBrain functionMRNAHomer1bBehavioral flexibilityNeuronal culturesExpressionBiogenesisCircRNAsRNAProteinRegulatesReversal learningDisorders
2021
Using the dCas9-KRAB system to repress gene expression in hiPSC-derived NGN2 neurons
Li A, Cartwright S, Yu A, Ho SM, Schrode N, Deans PJM, Matos MR, Garcia MF, Townsley KG, Zhang B, Brennand KJ. Using the dCas9-KRAB system to repress gene expression in hiPSC-derived NGN2 neurons. STAR Protocols 2021, 2: 100580. PMID: 34151300, PMCID: PMC8188621, DOI: 10.1016/j.xpro.2021.100580.Peer-Reviewed Original ResearchMeSH KeywordsCRISPR-Cas SystemsGene Expression RegulationHumansInduced Pluripotent Stem CellsNerve Tissue ProteinsNeuronsTranscriptomeConceptsCRISPR inhibitionGene expressionDCas9-KRAB systemEndogenous gene expressionMultiple target genesGene repressionGene activationTarget genesGene manipulationFusion proteinComplete detailsPluripotent stemExpressionGlutamatergic neuronsRepressionGenesPhenotypicProteinStemNeuronsActivationBrain diseasesInhibitionAnalysis framework and experimental design for evaluating synergy-driving gene expression
Schrode N, Seah C, Deans P, Hoffman G, Brennand K. Analysis framework and experimental design for evaluating synergy-driving gene expression. Nature Protocols 2021, 16: 812-840. PMID: 33432232, PMCID: PMC8609447, DOI: 10.1038/s41596-020-00436-7.Peer-Reviewed Original ResearchConceptsRaw read countsPluripotent stem cell-derived neuronsRNA sequencing experimentsRNA sequencing datasetsStem cell-derived neuronsDifferential expression analysisCell-derived neuronsComplex genetic disorderNon-additive interactionsGenetic risk variantsChemical perturbagensBioinformatics skillsExpression analysisSequencing datasetsGene expressionTranscriptomic effectsSequencing experimentsComputational pipelineRead countsRisk variantsCareful experimental designCombinatorial manipulationGenetic variantsComplex diseasesPerturbation studies
2020
Massively parallel techniques for cataloguing the regulome of the human brain
Townsley KG, Brennand KJ, Huckins LM. Massively parallel techniques for cataloguing the regulome of the human brain. Nature Neuroscience 2020, 23: 1509-1521. PMID: 33199899, PMCID: PMC8018778, DOI: 10.1038/s41593-020-00740-1.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsRegulatory elementsTarget genesParallel reporter assaysPutative regulatory elementsNon-coding regionsDisease-associated lociSpecific expression patternsCandidate risk lociPluripotent stem cellsHigh-throughput assaysRelevant molecular pathwaysTranscriptional responseRegulatory architectureRisk lociExpression patternsReporter assaysComplex brain disordersMolecular pathwaysRegulomeStem cellsRisk architectureGenetic riskGenesLociGenetic diagnosisTranscriptional signatures of participant-derived neural progenitor cells and neurons implicate altered Wnt signaling in Phelan-McDermid syndrome and autism
Breen MS, Browne A, Hoffman GE, Stathopoulos S, Brennand K, Buxbaum JD, Drapeau E. Transcriptional signatures of participant-derived neural progenitor cells and neurons implicate altered Wnt signaling in Phelan-McDermid syndrome and autism. Molecular Autism 2020, 11: 53. PMID: 32560742, PMCID: PMC7304190, DOI: 10.1186/s13229-020-00355-0.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAutistic DisorderChildChild, PreschoolChromosome DeletionChromosome DisordersChromosomes, Human, Pair 22FemaleGene Expression ProfilingGene Expression RegulationHumansInduced Pluripotent Stem CellsMaleNeural Stem CellsNeuronsReproducibility of ResultsWnt Signaling PathwayConceptsNeural progenitor cellsTranscriptional signatureGene co-expression network analysisHiPSC-NPCsCo-expression network analysisIndependent biological samplesHiPSC-derived neural cellsProgenitor cellsPostsynaptic density genesDistinct transcriptional signaturesGenetic risk lociHuman-induced pluripotent stem cellsPluripotent stem cellsPotassium channel activityProtein translationSpecific neurobiological pathwaysTranscriptional differencesEmbryonic developmentLoss of SHANK3Risk lociHiPSC neuronsMorphological phenotypesWnt pathwayGenesHiPSC clonesFunctional annotation of rare structural variation in the human brain
Han L, Zhao X, Benton ML, Perumal T, Collins RL, Hoffman GE, Johnson JS, Sloofman L, Wang HZ, Stone MR, Brennand K, Brand H, Sieberts S, Marenco S, Peters M, Lipska B, Roussos P, Capra J, Talkowski M, Ruderfer D. Functional annotation of rare structural variation in the human brain. Nature Communications 2020, 11: 2990. PMID: 32533064, PMCID: PMC7293301, DOI: 10.1038/s41467-020-16736-1.Peer-Reviewed Original ResearchCell Type-Specific In Vitro Gene Expression Profiling of Stem Cell-Derived Neural Models
Gregory JA, Hoelzli E, Abdelaal R, Braine C, Cuevas M, Halpern M, Barretto N, Schrode N, Akbalik G, Kang K, Cheng E, Bowles K, Lotz S, Goderie S, Karch CM, Temple S, Goate A, Brennand KJ, Phatnani H. Cell Type-Specific In Vitro Gene Expression Profiling of Stem Cell-Derived Neural Models. Cells 2020, 9: 1406. PMID: 32516938, PMCID: PMC7349756, DOI: 10.3390/cells9061406.Peer-Reviewed Original ResearchConceptsCell type-restricted expressionDisease-associated interactionsGene expression profilingHiPSC-derived motor neuronsHuman-induced pluripotent stem cellsPluripotent stem cellsCell-type specific perturbationsImmortalized cell linesRibosomal proteinsGenomic studiesExpression profilingMolecular mechanismsOff-target RNAMouse tissuesCell typesStem cellsPrimary mouse astrocytesExperimental replicatesCell linesMixed speciesMouse astrocytesExpressionMotor neuronsRiboTagCellsA psychiatric disease-related circular RNA controls synaptic gene expression and cognition
Zimmerman AJ, Hafez AK, Amoah SK, Rodriguez BA, Dell’Orco M, Lozano E, Hartley BJ, Alural B, Lalonde J, Chander P, Webster MJ, Perlis RH, Brennand KJ, Haggarty SJ, Weick J, Perrone-Bizzozero N, Brigman JL, Mellios N. A psychiatric disease-related circular RNA controls synaptic gene expression and cognition. Molecular Psychiatry 2020, 25: 2712-2727. PMID: 31988434, PMCID: PMC7577899, DOI: 10.1038/s41380-020-0653-4.Peer-Reviewed Original ResearchConceptsSynaptic gene expressionCircular RNAsGene expressionAlternative mRNA transcriptsDisease-associated circRNAsHomolog 1Neuronal RNAMRNA transcriptsRNASynaptic expressionAge of onsetMammalian brainCircRNAsPotential involvementDorsolateral prefrontal cortexOrbitofrontal cortexBipolar disorderPrefrontal cortexKnockdownExpressionFrontal cortexSynaptic plasticityNeuronal culturesPsychiatric diseasesMouse orbitofrontal cortex
2018
GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis
Kajiwara Y, Wang E, Wang M, Sin WC, Brennand KJ, Schadt E, Naus CC, Buxbaum J, Zhang B. GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis. Acta Neuropathologica Communications 2018, 6: 144. PMID: 30577786, PMCID: PMC6303945, DOI: 10.1186/s40478-018-0642-x.Peer-Reviewed Original ResearchConceptsPost-mortem Alzheimer's diseaseAlzheimer's diseaseTop key driverRNA sequencing analysisDisease pathogenesisProteomic datasetsKey regulatorNormal control brainsGJA1 expressionAlzheimer's disease (AD) pathogenesisApoE protein levelsPromising pharmacological targetSequencing analysisGJA1Wildtype astrocytesWildtype neuronsAβ metabolismAβ phagocytosisProtein levelsControl brainsAD pathogenesisAD amyloidPharmacological targetsAstrocytesCognitive functionTHC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders
Guennewig B, Bitar M, Obiorah I, Hanks J, O’Brien E, Kaczorowski DC, Hurd YL, Roussos P, Brennand KJ, Barry G. THC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders. Translational Psychiatry 2018, 8: 89. PMID: 29691375, PMCID: PMC5915454, DOI: 10.1038/s41398-018-0137-3.Peer-Reviewed Original ResearchConceptsHuman-induced pluripotent stem cellsPluripotent stem cellsHuman iPSC neuronsTranscriptional responseTranscriptomic analysisRNA transcriptomic analysisHuman neural cellsIPSC-neuronsMolecular pathwaysNeuropsychiatric disordersStem cellsNeural cellsDiagnosis-specific differencesGenesTHC exposureNeuronal depolarizationTHC administrationChronic exposureCannabis useNeuronsΔ9-tetrahydrocannabinolStrong associationSignificant alterationsCellsDynamic changes
2017
The methyltransferase SETDB1 regulates a large neuron-specific topological chromatin domain
Jiang Y, Loh YE, Rajarajan P, Hirayama T, Liao W, Kassim BS, Javidfar B, Hartley BJ, Kleofas L, Park RB, Labonte B, Ho SM, Chandrasekaran S, Do C, Ramirez BR, Peter CJ, C W JT, Safaie BM, Morishita H, Roussos P, Nestler EJ, Schaefer A, Tycko B, Brennand KJ, Yagi T, Shen L, Akbarian S. The methyltransferase SETDB1 regulates a large neuron-specific topological chromatin domain. Nature Genetics 2017, 49: 1239-1250. PMID: 28671686, PMCID: PMC5560095, DOI: 10.1038/ng.3906.Peer-Reviewed Original ResearchMEF2C transcription factor is associated with the genetic and epigenetic risk architecture of schizophrenia and improves cognition in mice
Mitchell A, Javidfar B, Pothula V, Ibi D, Shen E, Peter C, Bicks L, Fehr T, Jiang Y, Brennand K, Neve R, Gonzalez-Maeso J, Akbarian S. MEF2C transcription factor is associated with the genetic and epigenetic risk architecture of schizophrenia and improves cognition in mice. Molecular Psychiatry 2017, 23: 123-132. PMID: 28115742, PMCID: PMC5966823, DOI: 10.1038/mp.2016.254.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBrainChromatin ImmunoprecipitationCognition DisordersComputational BiologyDisease Models, AnimalEpigenomicsGene Expression RegulationGreen Fluorescent ProteinsHistonesMEF2 Transcription FactorsMiceMice, Inbred C57BLMice, KnockoutNerve Tissue ProteinsNeuronsPolymorphism, Single NucleotideSchizophreniaTransduction, GeneticConceptsTherapeutic potentialPrefrontal projection neuronsNeuron-specific promoterUnexplored therapeutic potentialProjection neuronsDrug challengeDisease casesRelated disordersRisk architecturePrefrontal cortexSchizophreniaSingle nucleotide polymorphismsCognitive performancePsychiatric Genomics ConsortiumNeuronal genomeH3K4 hypermethylationRisk lociCognitive enhancement
2016
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
Wang M, Roussos P, McKenzie A, Zhou X, Kajiwara Y, Brennand K, De Luca G, Crary J, Casaccia P, Buxbaum J, Ehrlich M, Gandy S, Goate A, Katsel P, Schadt E, Haroutunian V, Zhang B. Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease. Genome Medicine 2016, 8: 104. PMID: 27799057, PMCID: PMC5088659, DOI: 10.1186/s13073-016-0355-3.Peer-Reviewed Original ResearchConceptsGene expression changesCell type-specific marker genesExpression changesSingle-cell RNA-sequencing dataCo-expressed gene modulesLarge-scale gene expressionTranscriptomic network analysisCo-expression networkRNA-sequencing dataIntegrative network analysisNervous system developmentSelective regional vulnerabilityCritical molecular pathwaysActin cytoskeletonGenomic studiesGene modulesGenomic analysisGene expression abnormalitiesMarker genesMolecular basisGene expressionNetwork analysisMolecular mechanismsAxon guidanceMolecular pathwaysActivity-Dependent Changes in Gene Expression in Schizophrenia Human-Induced Pluripotent Stem Cell Neurons
Roussos P, Guennewig B, Kaczorowski D, Barry G, Brennand K. Activity-Dependent Changes in Gene Expression in Schizophrenia Human-Induced Pluripotent Stem Cell Neurons. JAMA Psychiatry 2016, 73: 1180-1188. PMID: 27732689, PMCID: PMC5437975, DOI: 10.1001/jamapsychiatry.2016.2575.Peer-Reviewed Original ResearchConceptsGene coexpression analysisActivity-dependent changesGene expressionCandidate genesCoexpression analysisSchizophrenia candidate genesSpecific molecular functionsGenome-wide profilingPluripotent stem cell-derived neuronsGene expression differencesSchizophrenia-associated variantsStem cell-derived neuronsDifferential expression analysisNeuronal activity-dependent changesHuman-induced pluripotent stem cell-derived neuronsCell-derived neuronsHuman-induced pluripotent stem cellsPluripotent stem cell neuronsPluripotent stem cellsCommon molecular pathwaysSchizophrenia risk genesMolecular functionsGene networksEtiopathogenesis of schizophreniaExpression analysisGene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer M, Roussos P, Sieberts S, Johnson J, Kavanagh D, Perumal T, Ruderfer D, Oh E, Topol A, Shah H, Klei L, Kramer R, Pinto D, Gümüş Z, Cicek A, Dang K, Browne A, Lu C, Xie L, Readhead B, Stahl E, Xiao J, Parvizi M, Hamamsy T, Fullard J, Wang Y, Mahajan M, Derry J, Dudley J, Hemby S, Logsdon B, Talbot K, Raj T, Bennett D, De Jager P, Zhu J, Zhang B, Sullivan P, Chess A, Purcell S, Shinobu L, Mangravite L, Toyoshiba H, Gur R, Hahn C, Lewis D, Haroutunian V, Peters M, Lipska B, Buxbaum J, Schadt E, Hirai K, Roeder K, Brennand K, Katsanis N, Domenici E, Devlin B, Sklar P. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nature Neuroscience 2016, 19: 1442-1453. PMID: 27668389, PMCID: PMC5083142, DOI: 10.1038/nn.4399.Peer-Reviewed Original ResearchDysregulation of miRNA-9 in a Subset of Schizophrenia Patient-Derived Neural Progenitor Cells
Topol A, Zhu S, Hartley B, English J, Hauberg M, Tran N, Rittenhouse C, Simone A, Ruderfer D, Johnson J, Readhead B, Hadas Y, Gochman P, Wang Y, Shah H, Cagney G, Rapoport J, Gage F, Dudley J, Sklar P, Mattheisen M, Cotter D, Fang G, Brennand K. Dysregulation of miRNA-9 in a Subset of Schizophrenia Patient-Derived Neural Progenitor Cells. Cell Reports 2016, 15: 1024-1036. PMID: 27117414, PMCID: PMC4856588, DOI: 10.1016/j.celrep.2016.03.090.Peer-Reviewed Original ResearchConceptsNeural progenitor cellsControl neural progenitor cellsMiR-9 targetsProgenitor cellsSubset of patientsMiR-9Levels/activitiesMiR-9 expressionSchizophrenia patientsMicroRNA-9Migration deficitsDisease riskNeural migrationAberrant levelsAberrant migrationPatientsMiRNA-9SchizophreniaMigration-associated genesRNA sequencingSZ riskRiskIndirect targetsSubsetCells