2024
Single-cell genomics and regulatory networks for 388 human brains
Emani P, Liu J, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee C, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken T, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard J, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman G, Huang A, Jiang Y, Jin T, Jorstad N, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran J, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan A, Riesenmy T, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini K, Wamsley B, Wang G, Xia Y, Xiao S, Yang A, Zheng S, Gandal M, Lee D, Lein E, Roussos P, Sestan N, Weng Z, White K, Won H, Girgenti M, Zhang J, Wang D, Geschwind D, Gerstein M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Brennand K, Capauto D, Champagne F, Chatzinakos C, Chen H, Cheng L, Chess A, Chien J, 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, Duong D, Eagles N, Edelstein J, Galani K, Girdhar K, Goes F, Greenleaf W, Guo H, Guo Q, Hadas Y, Hallmayer J, Han X, Haroutunian V, He C, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hyde T, Iatrou A, Inoue F, Jajoo A, Jiang L, Jin P, Jops C, Jourdon A, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Li J, Li M, Lin X, Liu S, Liu C, Loupe J, Lu D, Ma L, Mariani J, Martinowich K, Maynard K, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Mukamel E, Nairn A, Nemeroff C, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Pinto D, Pochareddy S, Pollard K, Pollen A, Przytycki P, Purmann C, Qin Z, Qu P, Raj T, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, 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, Wang T, Wang S, Wang Y, Wei Y, Weimer A, Weinberger D, Wen C, Whalen S, Willsey A, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang Y, Ziffra R, Zeier Z, Zintel T. Single-cell genomics and regulatory networks for 388 human brains. Science 2024, 384: eadi5199. PMID: 38781369, PMCID: PMC11365579, DOI: 10.1126/science.adi5199.Peer-Reviewed Original ResearchConceptsSingle-cell genomicsSingle-cell expression quantitative trait locusExpression quantitative trait lociDrug targetsQuantitative trait lociPopulation-level variationSingle-cell expressionCell typesDisease-risk genesTrait lociGene familyRegulatory networksGene expressionCell-typeMultiomics datasetsSingle-nucleiGenomeGenesCellular changesHeterogeneous tissuesExpressionCellsChromatinLociMultiomics
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 studiesUsing Stem Cell Models to Explore the Genetics Underlying Psychiatric Disorders: Linking Risk Variants, Genes, and Biology in Brain Disease
Brennand K. Using Stem Cell Models to Explore the Genetics Underlying Psychiatric Disorders: Linking Risk Variants, Genes, and Biology in Brain Disease. American Journal Of Psychiatry 2022, 179: 322-328. PMID: 35491564, DOI: 10.1176/appi.ajp.20220235.Commentaries, Editorials and LettersMeSH KeywordsBrain DiseasesGenome-Wide Association StudyGenomicsHumansInduced Pluripotent Stem CellsMental DisordersConceptsRisk variantsFunctional genomic studiesCell typesDiverse cell typesPatient-specific variantsStem cell modelGenomic studiesSignificant lociStem cell-based approachesGenetic studiesExciting questionsCell-based approachesEngineering strategiesGenetic profileNovel therapeutic interventionsCell modelPluripotent stem cell-based approachesVariantsComplex interplayGenetic riskCRISPRGenesLociBiologyTherapeutic interventions
2020
Integration of CRISPR-engineering and hiPSC-based models of psychiatric genomics
Matos MR, Ho SM, Schrode N, Brennand KJ. Integration of CRISPR-engineering and hiPSC-based models of psychiatric genomics. Molecular And Cellular Neuroscience 2020, 107: 103532. PMID: 32712198, PMCID: PMC7484226, DOI: 10.1016/j.mcn.2020.103532.Peer-Reviewed Original ResearchConceptsPenetrant rare variantsDisease-associated variantsNeuronal cell typesPluripotent stem cellsGenomic engineeringFunctional characterizationComplex geneticsCRISPR engineeringCRISPR technologyIsogenic comparisonsPsychiatric genomicsCell typesGenetic variantsStem cellsIndividual variantsCommon variantsPolygenic disorderRare variantsVariantsComplex interplayGenomicsGenetic riskPleiotropyCRISPRGenetics
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 changesNew considerations for hiPSC-based models of neuropsychiatric disorders
Hoffman GE, Schrode N, Flaherty E, Brennand KJ. New considerations for hiPSC-based models of neuropsychiatric disorders. Molecular Psychiatry 2018, 24: 49-66. PMID: 29483625, PMCID: PMC6109625, DOI: 10.1038/s41380-018-0029-1.Peer-Reviewed Original ResearchMeSH KeywordsCell DifferentiationHumansInduced Pluripotent Stem CellsMental DisordersModels, BiologicalNeuronsPhenotypeReproducibility of ResultsConceptsHuman-induced pluripotent stem cellsCell type compositionComplex genetic diseasesPluripotent stem cellsComplex genetic disorderField of geneticsCell biologistsBiological convergenceLevel phenotypesAdvanced geneticsCRISPR technologyHuman diseasesPsychiatric genomicsGenetic diseasesStem cellsNeural cellsCommon variantsGeneticsGenetic disordersBiological considerationsCritical insightsCellsGenomicsRecent advancesBiologists
2015
Using hiPSCs to model neuropsychiatric copy number variations (CNVs) has potential to reveal underlying disease mechanisms
Flaherty E, Brennand K. Using hiPSCs to model neuropsychiatric copy number variations (CNVs) has potential to reveal underlying disease mechanisms. Brain Research 2015, 1655: 283-293. PMID: 26581337, PMCID: PMC4865445, DOI: 10.1016/j.brainres.2015.11.009.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsCopy number variationsIsogenic hiPSC linesRare variantsFull genetic architectureGenome editing technologyPluripotent stem cellsStrong heritable componentPatient-derived humanGenetic architectureEditing technologyHeritable componentBehavioral defectsNumber variationsNew therapeutic targetsHiPSC linesGenetic backgroundStem cellsCommon variantsFunctional contributionDisease mechanismsSingle variantMouse modelHigh penetranceHiPSCsTherapeutic targetNoncoding RNAs and neurobehavioral mechanisms in psychiatric disease
Kocerha J, Dwivedi Y, Brennand K. Noncoding RNAs and neurobehavioral mechanisms in psychiatric disease. Molecular Psychiatry 2015, 20: 677-684. PMID: 25824307, PMCID: PMC4440836, DOI: 10.1038/mp.2015.30.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsAnimalsCognition DisordersHumansMental DisordersNervous System DiseasesRNA, UntranslatedConceptsPsychiatric diseasesPost-genome sequencing eraNew epigenetic targetsPotent epigenetic regulatorHuman Genome ProjectAttractive therapeutic potentialMicroRNA (miRNA) classNcRNA classesMajor neuronal pathwaysEpigenetic regulatorsSequencing eraEpigenetic targetsNoncoding RNAsGenome ProjectNeuronal pathwaysMultifactorial originPsychiatric disordersSingle proteinTherapeutic potentialReported rolesTherapeutic investigationsPleiotropic capacitySingle neuronsNeurobehavioral phenotypesDisease
2012
Modeling psychiatric disorders at the cellular and network levels
Brennand K, Simone A, Tran N, Gage F. Modeling psychiatric disorders at the cellular and network levels. Molecular Psychiatry 2012, 17: 1239-1253. PMID: 22472874, PMCID: PMC3465628, DOI: 10.1038/mp.2012.20.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsAnimalsFibroblastsHumansInduced Pluripotent Stem CellsMental DisordersModels, NeurologicalNeural PathwaysNeuronsPhenotypeConceptsCell-based studiesPluripotent stem cell-derived neuronsStem cell-derived neuronsLive human neuronsCell-derived neuronsPsychiatric disordersBasic phenotypesGenetic backgroundHuman neuronsClinical symptomsComplex arrayBipolar disorderBrain regionsDisease statesNeuronsSingle neuronsDisordersLimitless numberAutism spectrum disorderSpectrum disorderPhenotypeFibroblastsPatientsSymptomsSchizophrenia
2011
Modeling psychiatric disorders through reprogramming
Brennand K, Gage F. Modeling psychiatric disorders through reprogramming. Disease Models & Mechanisms 2011, 5: 26-32. PMID: 21954066, PMCID: PMC3255540, DOI: 10.1242/dmm.008268.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsCellular ReprogrammingFibroblastsHumansInduced Pluripotent Stem CellsMental DisordersModels, BiologicalNeurons