Featured Publications
Modelling 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
2024
A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex
Huuki-Myers L, Spangler A, Eagles N, Montgomery K, Kwon S, Guo B, Grant-Peters M, Divecha H, Tippani M, Sriworarat C, Nguyen A, Ravichandran P, Tran M, Seyedian A, Hyde T, Kleinman J, Battle A, Page S, Ryten M, Hicks S, Martinowich K, Collado-Torres L, Maynard K, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Bendl J, Berretta S, Bharadwaj R, Bhattacharya A, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clarke D, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Fullard J, Galani K, Galeev T, Gandal M, Gaynor S, Gerstein M, Geschwind D, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Haroutunian V, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Hoffman G, Huang Y, Huuki-Myers L, Hwang A, Hyde T, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu C, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Margolis M, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollard K, Pollen A, Pratt H, Przytycki P, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Roussos P, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Sestan N, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Weinberger D, Wen C, Weng Z, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science 2024, 384: eadh1938. PMID: 38781370, PMCID: PMC11398705, DOI: 10.1126/science.adh1938.Peer-Reviewed Original ResearchConceptsRNA sequencing dataCell type compositionGene expression platformSpatial transcriptomics technologiesAnterior-posterior axisCell-cell interactionsTranscriptome mapExpression platformHuman dorsolateral prefrontal cortexTranscriptomic technologiesSingle-cellCell typesPrefrontal cortexMolecular organizationDorsolateral prefrontal cortexHuman prefrontal cortex
2021
Analysis 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
Transcriptional 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 neuronsRiboTagCells
2019
Differential transcriptional response following glucocorticoid activation in cultured blood immune cells: a novel approach to PTSD biomarker development
Breen MS, Bierer LM, Daskalakis NP, Bader HN, Makotkine I, Chattopadhyay M, Xu C, Buxbaum Grice A, Tocheva AS, Flory JD, Buxbaum JD, Meaney MJ, Brennand K, Yehuda R. Differential transcriptional response following glucocorticoid activation in cultured blood immune cells: a novel approach to PTSD biomarker development. Translational Psychiatry 2019, 9: 201. PMID: 31434874, PMCID: PMC6704073, DOI: 10.1038/s41398-019-0539-x.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiomarkersConstitutive Androstane ReceptorDexamethasoneDose-Response Relationship, DrugGene ExpressionGene Expression ProfilingGene Regulatory NetworksGlucocorticoidsHumansLeukocytes, MononuclearMaleMiddle AgedStress Disorders, Post-TraumaticTranscription, GeneticVeteransYoung AdultConceptsPeripheral blood mononuclear cellsPost-traumatic stress disorderGlucocorticoid signalingCultured peripheral blood mononuclear cellsBlood immune cellsBlood mononuclear cellsTranscriptional responseConcentrations of dexamethasoneDifferential transcriptional changesGenome-wide gene expression profilingCombat-exposed veteransStress-responsive pathwaysMolecular responseClinical manifestationsInflammatory cytokinesDynamic transcriptional responseMononuclear cellsApoptosis-related pathwaysImmune cellsBaseline differencesDifferential transcriptional responsesDifferential molecular responsesGlucocorticoid stimulationNovel markerReliable marker
2018
THC 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
Evaluating Synthetic Activation and Repression of Neuropsychiatric-Related Genes in hiPSC-Derived NPCs, Neurons, and Astrocytes
Ho S, Hartley B, Flaherty E, Rajarajan P, Abdelaal R, Obiorah I, Barretto N, Muhammad H, Phatnani H, Akbarian S, Brennand K. Evaluating Synthetic Activation and Repression of Neuropsychiatric-Related Genes in hiPSC-Derived NPCs, Neurons, and Astrocytes. Stem Cell Reports 2017, 9: 615-628. PMID: 28757163, PMCID: PMC5550013, DOI: 10.1016/j.stemcr.2017.06.012.Peer-Reviewed Original ResearchConceptsSynthetic activationRisk genesCell typesModulation of transcriptionNeuropsychiatric risk genesCommon single nucleotide variantsCas9 fusion proteinsEndogenous expression levelsNeural cell typesPluripotent stem cell-derived neural progenitor cellsRare copy number variationsCopy number variationsSingle nucleotide variantsNeural progenitor cellsGene functionFunctional annotationGenetic studiesGenesRisk variantsProgenitor cellsExpression levelsTranscriptionRepressionPositional effectsProteinAn Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells
Julia T, Wang M, Pimenova A, Bowles K, Hartley B, Lacin E, Machlovi S, Abdelaal R, Karch C, Phatnani H, Slesinger P, Zhang B, Goate A, Brennand K. An Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells. Stem Cell Reports 2017, 9: 600-614. PMID: 28757165, PMCID: PMC5550034, DOI: 10.1016/j.stemcr.2017.06.018.Peer-Reviewed Original Research
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 pathwaysDysregulation 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