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 effects
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 tissuesExpressionCellsChromatinLociMultiomicsCross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain
Wen C, Margolis M, Dai R, Zhang P, Przytycki P, Vo D, Bhattacharya A, Matoba N, Tang M, Jiao C, Kim M, Tsai E, Hoh C, Aygün N, Walker R, Chatzinakos C, Clarke D, Pratt H, Peters M, Gerstein M, Daskalakis N, Weng Z, Jaffe A, Kleinman J, Hyde T, Weinberger D, Bray N, Sestan N, Geschwind D, Roeder K, Gusev A, Pasaniuc B, Stein J, Love M, Pollard K, Liu C, Gandal M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Bendl J, Berretta S, Bharadwaj R, 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, Clement A, Collado-Torres L, Cooper G, Crawford G, 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, Gaynor S, 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, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kellis M, 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 S, Lou S, Loupe J, Lu D, Ma S, Ma L, 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, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollen A, 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, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Voloudakis G, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, 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 C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain. Science 2024, 384: eadh0829. PMID: 38781368, DOI: 10.1126/science.adh0829.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide association study lociSplicing quantitative trait lociQuantitative trait lociSplicing regulationCross-ancestryTrait lociAssociation studiesRegulatory elementsCellular contextHuman brainTranscriptome regulationCoexpression networkRisk genesAutism spectrum disorderGenesCellular heterogeneityComprehensive landscapeSpectrum disorderIsoformsSplicingIncreased cellular heterogeneityLociNeuronal maturationRegulation
2023
MASSIVELY PARALLEL CHARACTERIZATION OF CONTEXT SPECIFIC REGULATORY RISK ELEMENTS ACROSS PSYCHIATRIC DISORDERS IN HUMAN-INDUCED PLURIPOTENT STEM CELL-DERIVED GLUTAMATERGIC NEURONS
Townsley K, Sen A, Lee J, Deans P, Jia M, Fernandez-Garcia M, Cartwright S, Cohen S, Goate A, Brennand K, Huckins L. MASSIVELY PARALLEL CHARACTERIZATION OF CONTEXT SPECIFIC REGULATORY RISK ELEMENTS ACROSS PSYCHIATRIC DISORDERS IN HUMAN-INDUCED PLURIPOTENT STEM CELL-DERIVED GLUTAMATERGIC NEURONS. European Neuropsychopharmacology 2023, 75: s7-s8. DOI: 10.1016/j.euroneuro.2023.08.022.Peer-Reviewed Original ResearchCandidate regulatory sequencesExpression quantitative trait lociRegulatory sequencesTranscriptional activityGWAS statisticsSingle-cell CRISPR screensCell type-specific mannerParallel reporter assaysQuantitative trait lociPutative regulatory elementsHigh-throughput sequencingFine-mapping approachFine-mapping methodsLarge-scale identificationFunctional impactTranscriptomic imputationTrait lociKey genesCRISPR screensLarge-scale screening techniquesRegulatory elementsNeuropsychiatric traitsCausal SNPsReporter assaysCasual variants
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 ResearchConceptsStem 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 studiesPopulation-level variation in enhancer expression identifies disease mechanisms in the human brain
Dong P, Hoffman G, Apontes P, Bendl J, Rahman S, Fernando M, Zeng B, Vicari J, Zhang W, Girdhar K, Townsley K, Misir R, Brennand K, Haroutunian V, Voloudakis G, Fullard J, Roussos P. Population-level variation in enhancer expression identifies disease mechanisms in the human brain. Nature Genetics 2022, 54: 1493-1503. PMID: 36163279, PMCID: PMC9547946, DOI: 10.1038/s41588-022-01170-4.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociPopulation-level variationTranscriptome-wide association studyQuantitative trait lociSpecific transcriptomeTrait lociTrait heritabilitySpecific transcriptionEnhancer functionGenetic mechanismsTarget genesAssociation studiesDisease locusNeuropsychiatric diseasesRisk variantsGenesRobust expressionTranscriptomeFunctional interpretationDisease mechanismsEnhancerDiseased statesLociHuman brainBrain samples
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
Mapping regulatory variants in hiPSC models
Hoffman GE, Brennand KJ. Mapping regulatory variants in hiPSC models. Nature Genetics 2017, 50: 1-2. PMID: 29273803, DOI: 10.1038/s41588-017-0017-4.Peer-Reviewed Original Research
2014
A Role for Noncoding Variation in Schizophrenia
Roussos P, Mitchell A, Voloudakis G, Fullard J, Pothula V, Tsang J, Stahl E, Georgakopoulos A, Ruderfer D, Charney A, Okada Y, Siminovitch K, Worthington J, Padyukov L, Klareskog L, Gregersen P, Plenge R, Raychaudhuri S, Fromer M, Purcell S, Brennand K, Robakis N, Schadt E, Akbarian S, Sklar P. A Role for Noncoding Variation in Schizophrenia. Cell Reports 2014, 9: 1417-1429. PMID: 25453756, PMCID: PMC4255904, DOI: 10.1016/j.celrep.2014.10.015.Peer-Reviewed Original ResearchMeSH KeywordsArthritis, RheumatoidCalcium Channels, L-TypeDatabases, GeneticDNA, IntergenicEnhancer Elements, GeneticGene Expression RegulationGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMolecular Sequence AnnotationOrgan SpecificityPolymorphism, Single NucleotidePromoter Regions, GeneticProtein BindingRisk FactorsSchizophreniaConceptsExpression quantitative trait lociGenome-wide significant lociCommon variant lociQuantitative trait lociPluripotent stem cell-derived neuronsDistal regulatory elementsStem cell-derived neuronsPotential physical interactionsCell-derived neuronsRegulatory element sequencesPotential functional roleGenome architectureChromosomal loopingTranscriptional regulationFunctional annotationTrait lociSignificant lociNoncoding SNPsRegulatory elementsNoncoding variationsRisk lociVariant lociUnknown functionFunctional linkElement sequences