2024
Cross-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
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 studies
2020
A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles
Sey NYA, Hu B, Mah W, Fauni H, McAfee JC, Rajarajan P, Brennand KJ, Akbarian S, Won H. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nature Neuroscience 2020, 23: 583-593. PMID: 32152537, PMCID: PMC7131892, DOI: 10.1038/s41593-020-0603-0.Peer-Reviewed Original ResearchConceptsChromatin interaction profilesH-MAGMARisk genesMost risk variantsGenome-wide association studiesCell typesGene regulatory relationshipsRelevant target genesCell-type specificitySingle nucleotide polymorphism associationsBrain cell typesDisease-relevant tissuesInteraction profilesGenomic annotationsNearest geneTarget genesRegulatory relationshipsAssociation studiesBiological pathwaysGenesRisk variantsDevelopmental windowBiological mechanismsNeurodegenerative disordersHuman brain tissue
2016
The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample
Oedegaard K, Alda M, Anand A, Andreassen O, Balaraman Y, Berrettini W, Bhattacharjee A, Brennand K, Burdick K, Calabrese J, Calkin C, Claasen A, Coryell W, Craig D, DeModena A, Frye M, Gage F, Gao K, Garnham J, Gershon E, Jakobsen P, Leckband S, McCarthy M, McInnis M, Maihofer A, Mertens J, Morken G, Nievergelt C, Nurnberger J, Pham S, Schoeyen H, Shekhtman T, Shilling P, Szelinger S, Tarwater B, Yao J, Zandi P, Kelsoe J. The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample. BMC Psychiatry 2016, 16: 129. PMID: 27150464, PMCID: PMC4857276, DOI: 10.1186/s12888-016-0732-x.Peer-Reviewed Original ResearchConceptsLithium monotherapyBipolar disorderLithium responseMechanism of actionClinical managementValproic acidLithium respondersSingle nucleotide polymorphismsMethods/designThis studyCox proportional hazards modelProspective study sampleLarge prospective cohortLarge prospective studiesClinical Global ImpressionInitiation of treatmentMood-stabilizing medicationsBipolar Disorder (STEP-BD) studyProportional hazards modelResults of treatmentCommon psychiatric disordersMEq/L.Genome-wide association studiesClinical relapseProspective cohortRemitting course
2011
Concise Review: The Promise of Human Induced Pluripotent Stem Cell‐Based Studies of Schizophrenia
Brennand K, Gage F. Concise Review: The Promise of Human Induced Pluripotent Stem Cell‐Based Studies of Schizophrenia. Stem Cells 2011, 29: 1915-1922. PMID: 22009633, PMCID: PMC3381343, DOI: 10.1002/stem.762.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsGenome-wide association studiesHuman induced pluripotent stem cellsHiPSC neuronsMolecular mechanismsStem cell-based studiesGene expression changesLive human neuronsInduced pluripotent stem cellsPluripotent stem cellsCommon single nucleotide polymorphismsRare copy number variantsCell-based studiesCopy number variantsSingle nucleotide polymorphismsExpression changesAssociation studiesCellular defectsHuman diseasesPost-mortem humanHeritable developmental disorderNumber variantsNucleotide polymorphismsHuman neuronsStem cellsGenes