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 maturationRegulationDissecting the biology of feeding and eating disorders
Huckins L, Brennand K, Bulik C. Dissecting the biology of feeding and eating disorders. Trends In Molecular Medicine 2024, 30: 380-391. PMID: 38431502, DOI: 10.1016/j.molmed.2024.01.009.Peer-Reviewed Original ResearchGenome-wide association studiesVariants to genesGenes to pathwaysSignificant lociFunctional genomicsAssociation studiesGenetic relationshipsIntestinal microbiotaGenetic researchGenomeGenetic correlationsGenesMetabolic contributorsAnorexia nervosaEating disordersPathwayBiologyMetabolic outcomesRisk factorsLociMicrobiotaPhenomicsLethal illnessTraitsFeeding
2022
Population-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 samplesA translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility
Voloudakis G, Vicari J, Venkatesh S, Hoffman G, Dobrindt K, Zhang W, Beckmann N, Higgins C, Argyriou S, Jiang S, Hoagland D, Gao L, Corvelo A, Cho K, Lee K, Bian J, Lee J, Iyengar S, Luoh S, Akbarian S, Striker R, Assimes T, Schadt E, Lynch J, Merad M, tenOever B, Charney A, Brennand K, Fullard J, Roussos P. A translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility. Npj Genomic Medicine 2022, 7: 52. PMID: 36064543, PMCID: PMC9441828, DOI: 10.1038/s41525-022-00324-x.Peer-Reviewed Original ResearchCandidate gene targetsGene targetsTranslational genomics approachesHost susceptibilityGenomic approachesGenetic susceptibility variantsGenetic lociDruggable genesGene expressionMolecular pathwaysSusceptibility variantsCOVID-19 susceptibilityGenetic findingsApproach identifiesExpressionCOVID-19 patient bloodCritical next stepGenesLociOverexpressionTargetPathwaySusceptibilityIL10RBRecent effortsUsing 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 LettersConceptsRisk 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
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 diagnosisParsing the Functional Impact of Noncoding Genetic Variants in the Brain Epigenome
Powell SK, O'Shea C, Brennand KJ, Akbarian S. Parsing the Functional Impact of Noncoding Genetic Variants in the Brain Epigenome. Biological Psychiatry 2020, 89: 65-75. PMID: 33131715, PMCID: PMC7718420, DOI: 10.1016/j.biopsych.2020.06.033.Peer-Reviewed Original ResearchConceptsGenetic variantsDisease-associated genetic variationProtein-coding lociRisk-associated genetic variantsGene regulatory lociThousands of variantsFunctional impactRare genetic variantsEpigenomic mappingRegulatory lociBrain epigenomeGenetic variationDNA sequencesNoncoding variantsGene expressionIntegrative analysisEpigenomic architectureMolecular pathwaysPsychiatric geneticsFunctional readoutRisk variantsLociVariantsHighlight findingsEpigenome
2019
CRISPR-based functional evaluation of schizophrenia risk variants
Rajarajan P, Flaherty E, Akbarian S, Brennand KJ. CRISPR-based functional evaluation of schizophrenia risk variants. Schizophrenia Research 2019, 217: 26-36. PMID: 31277978, PMCID: PMC6939156, DOI: 10.1016/j.schres.2019.06.017.Peer-Reviewed Original ResearchConceptsSchizophrenia-associated variantsPluripotent stem cellsCRISPR genome engineeringSchizophrenia risk variantsCellular functionsGenome engineeringGenomic studiesSchizophrenia lociList of variantsGene expressionPatient-specific humanGenotype dataRisk variantsStem cellsFunctional impactCommon variantsCRISPRPost-mortem brain tissueRecent findingsVariantsNeuropsychiatric diseasesPoint of convergenceGenetic riskLociSpecific effects
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 ResearchThe 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 ResearchApplication of CRISPR/Cas9 to the study of brain development and neuropsychiatric disease
Powell S, Gregory J, Akbarian S, Brennand K. Application of CRISPR/Cas9 to the study of brain development and neuropsychiatric disease. Molecular And Cellular Neuroscience 2017, 82: 157-166. PMID: 28549865, PMCID: PMC5516945, DOI: 10.1016/j.mcn.2017.05.007.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsCRISPR/Cas9 technologyPluripotent stem cellsTranscriptional regulatorsManipulation of DNAEpigenetic pathwaysGenomic editingSpecific lociCRISPR/Basic biologyCas9 technologyGene expressionStem cellsTargeted localizationEnzyme activityBrain developmentEpigenomeNeuropsychiatric diseasesGenomeCRISPRRepressionLociBiologyRegulatorEffectorsDNA