Featured Publications
SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure
Tang D, Park S, Zhao H. SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure. Genome Biology 2022, 23: 129. PMID: 35706040, PMCID: PMC9199219, DOI: 10.1186/s13059-022-02688-w.Peer-Reviewed Original ResearchConceptsCell type-specific gene expressionType-specific gene expressionCell type proportionsDifferential expression analysisCell type-specific gene expression profilesExpression analysisGene expressionSingle-cell RNA-seq dataRNA-seq dataGene differential expression analysisGene expression profilesType proportionsExpression profilesExpressionGenesCellsTranscriptomic organization of the human brain in post-traumatic stress disorder
Girgenti MJ, Wang J, Ji D, Cruz DA, Stein M, Gelernter J, Young K, Huber B, Williamson D, Friedman M, Krystal J, Zhao H, Duman R. Transcriptomic organization of the human brain in post-traumatic stress disorder. Nature Neuroscience 2020, 24: 24-33. PMID: 33349712, DOI: 10.1038/s41593-020-00748-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultAutopsyBrain ChemistryCohort StudiesDepressive Disorder, MajorFemaleGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInterneuronsMaleMiddle AgedNerve Tissue ProteinsSex CharacteristicsStress Disorders, Post-TraumaticTranscriptomeYoung AdultConceptsGenome-wide association studiesSignificant gene networksDifferential gene expressionSystems-level evidenceSignificant genetic liabilityMajor depressive disorder cohortGene networksTranscriptomic organizationTranscriptomic landscapeDownregulated setsGenomic networksGene expressionAssociation studiesMolecular determinantsExtensive remodelingGenotype dataSexual dimorphismSignificant divergenceMolecular profileNetwork analysisELFN1TranscriptsDimorphismPostmortem tissueDivergence
2024
DNA methylation profiles of cancer-related fatigue associated with markers of inflammation and immunometabolism
Xiao C, Peng G, Conneely K, Zhao H, Felger J, Wommack E, Higgins K, Shin D, Saba N, Bruner D, Miller A. DNA methylation profiles of cancer-related fatigue associated with markers of inflammation and immunometabolism. Molecular Psychiatry 2024, 1-8. PMID: 38977918, DOI: 10.1038/s41380-024-02652-z.Peer-Reviewed Original ResearchGene expressionMethylation lociAssociated with gene expressionHead and neck cancerDNA methylation profilesProtein markersLipid metabolismInvolvement of genesIllumina MethylationEPICDNA methylationRelevant gene expressionEpigenetic modificationsExpression pairsInflammatory markersInflammatory responseLociHead and neck cancer patientsAssociated with inflammatory markersGenesDNAMarkers of inflammationAssociated with fatigueExpressionMethylationPost-radiotherapy
2023
eQTL studies: from bulk tissues to single cells
Zhang J, Zhao H. eQTL studies: from bulk tissues to single cells. Journal Of Genetics And Genomics 2023, 50: 925-933. PMID: 37207929, PMCID: PMC10656365, DOI: 10.1016/j.jgg.2023.05.003.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociBulk tissueIdentification of eQTLContext-dependent gene regulationCell typesQuantitative trait lociMost eQTL studiesSingle cellsComplex traitsGene regulationEQTL studiesFunctional genesTrait lociSpecific genesChromosomal regionsDynamic regulationGene expressionBiological processesDifferent tissuesGenetic variantsExpression levelsDisease mechanismsGenesRegulationRecent studiesLive imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo
May D, Yun S, Gonzalez D, Park S, Chen Y, Lathrop E, Cai B, Xin T, Zhao H, Wang S, Gonzalez L, Cockburn K, Greco V. Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo. ELife 2023, 12: e83444. PMID: 36880644, PMCID: PMC10027315, DOI: 10.7554/elife.83444.Peer-Reviewed Original ResearchConceptsStem cell differentiationCell differentiationStem cell compartmentCompaction changesChromatin compaction statesDynamic transcriptional statesCell compartmentChromatin architectureCell cycle statusChromatin rearrangementNascent RNATranscriptional burstingTranscriptional statesLive imagingTissue contextGene expressionDifferentiating cellsGlobal remodelingIndividual cellsCycle statusStem cellsDifferentiation statusDifferentiationCellsMorphological changesRobustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression
Lin C, Liu W, Jiang W, Zhao H. Robustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression. Biology Methods And Protocols 2023, 8: bpad024. PMID: 37901453, PMCID: PMC10599978, DOI: 10.1093/biomethods/bpad024.Peer-Reviewed Original ResearchExpression quantitative trait lociGenome-wide association studiesComplex traitsGene expression regulationGenetic association signalsQuantitative trait lociScore regressionDisease-associated variantsSNP annotationGene annotationExpression regulationGWAS resultsTrait lociTrait heritabilityEQTL effectsAssociation signalsGene expressionAssociation studiesGene effectsSNP effectsHuman diseasesHeritabilityTraitsBiological realityAnnotation
2022
Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19
Unterman A, Sumida TS, Nouri N, Yan X, Zhao AY, Gasque V, Schupp JC, Asashima H, Liu Y, Cosme C, Deng W, Chen M, Raredon MSB, Hoehn KB, Wang G, Wang Z, DeIuliis G, Ravindra NG, Li N, Castaldi C, Wong P, Fournier J, Bermejo S, Sharma L, Casanovas-Massana A, Vogels CBF, Wyllie AL, Grubaugh ND, Melillo A, Meng H, Stein Y, Minasyan M, Mohanty S, Ruff WE, Cohen I, Raddassi K, Niklason L, Ko A, Montgomery R, Farhadian S, Iwasaki A, Shaw A, van Dijk D, Zhao H, Kleinstein S, Hafler D, Kaminski N, Dela Cruz C. Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nature Communications 2022, 13: 440. PMID: 35064122, PMCID: PMC8782894, DOI: 10.1038/s41467-021-27716-4.Peer-Reviewed Original ResearchMeSH KeywordsAdaptive ImmunityAgedAntibodies, Monoclonal, HumanizedCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCells, CulturedCOVID-19COVID-19 Drug TreatmentFemaleGene Expression ProfilingGene Expression RegulationHumansImmunity, InnateMaleReceptors, Antigen, B-CellReceptors, Antigen, T-CellRNA-SeqSARS-CoV-2Single-Cell AnalysisConceptsProgressive COVID-19B cell clonesSingle-cell analysisT cellsImmune responseMulti-omics single-cell analysisCOVID-19Cell clonesAdaptive immune interactionsSevere COVID-19Dynamic immune responsesGene expressionSARS-CoV-2 virusAdaptive immune systemSomatic hypermutation frequenciesCellular effectsProtein markersEffector CD8Immune signaturesProgressive diseaseHypermutation frequencyProgressive courseClassical monocytesClonesImmune interactions
2021
Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program
Stein MB, Levey DF, Cheng Z, Wendt FR, Harrington K, Pathak GA, Cho K, Quaden R, Radhakrishnan K, Girgenti MJ, Ho YA, Posner D, Aslan M, Duman RS, Zhao H, Polimanti R, Concato J, Gelernter J. Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program. Nature Genetics 2021, 53: 174-184. PMID: 33510476, PMCID: PMC7972521, DOI: 10.1038/s41588-020-00767-x.Peer-Reviewed Original ResearchConceptsGenome-wide association analysisAssociation analysisMillion Veteran ProgramGenomic structural equation modelingSignificant lociGenetic varianceGene expressionDrug repositioning candidatesBiological coherenceVeteran ProgramMultiple testing correctionSymptom phenotypeLociRepositioning candidatesAfrican ancestryHeritabilityPhenotypeAncestryExpressionPTSD symptom factorsRegionSubdomainsEnrichment
2020
Leveraging functional annotation to identify genes associated with complex diseases
Liu W, Li M, Zhang W, Zhou G, Wu X, Wang J, Lu Q, Zhao H. Leveraging functional annotation to identify genes associated with complex diseases. PLOS Computational Biology 2020, 16: e1008315. PMID: 33137096, PMCID: PMC7660930, DOI: 10.1371/journal.pcbi.1008315.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociComplex traitsNovel lociIdentification of eQTLGene expressionTranscriptome-wide association study methodLinkage disequilibriumQuantitative trait lociAssociation study methodsCombined Annotation Dependent Depletion (CADD) scoresAnnotation-dependent depletion scoreExpression levelsDisease-associated genesEpigenetic annotationsEpigenetic informationFunctional annotationTrait lociGenetic variationGenesPrevious GWASLociGenetic effectsTraitsComplex diseasesGWAS
2019
A statistical framework for cross-tissue transcriptome-wide association analysis
Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, Yu Z, Li B, Gu J, Muchnik S, Shi Y, Kunkle BW, Mukherjee S, Natarajan P, Naj A, Kuzma A, Zhao Y, Crane PK, Lu H, Zhao H. A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics 2019, 51: 568-576. PMID: 30804563, PMCID: PMC6788740, DOI: 10.1038/s41588-019-0345-7.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association analysisAssociation analysisGene-trait associationsGene expression dataGene expression levelsGenetic architectureComplex traitsMore genesGene expressionSingle tissueExpression dataAssociation resultsExpression levelsPowerful approachImputation modelHuman tissuesImputation accuracyGenotypesStatistical frameworkTissueGenesKey componentTraitsPowerful metricExpression
2017
Dissecting Pathway Disturbances Using Network Topology and Multi-platform Genomics Data
Zhang Y, Linder M, Shojaie A, Ouyang Z, Shen R, Baggerly K, Baladandayuthapani V, Zhao H. Dissecting Pathway Disturbances Using Network Topology and Multi-platform Genomics Data. Statistics In Biosciences 2017, 10: 86-106. PMID: 37388623, PMCID: PMC10309155, DOI: 10.1007/s12561-017-9193-0.Peer-Reviewed Original ResearchMolecular regulatory elementsCopy number variantsRegulatory elementsMRNA moleculesPathway-based analysisBRAF pathwayCancer Genome Atlas (TCGA) projectMultiple tumor lineagesTumor-specific aberrationsRegulatory topologyRelevant copy number variantsDiverse cancer typesMultiple omicsGenomic dataMajor geneCancer typesGene expressionSingle-platform analysisOncogenic pathwaysNumber variantsMethylationComplex diseasesTumor lineageAtlas projectPathwayMetabolic Regulation of Gene Expression by Histone Lysine β‐hydroxybutyrylation
Zhang D, Xie Z, Chung D, Tang Z, Huang H, Dai L, Qi S, Li J, Colak G, Chen Y, Peng C, Ruan H, Wang D, Jensen L, Kwon O, Lee S, Pletcher S, Tan M, Lombard D, White K, Zhao H, Li J, Roeder R, Yang X, Zhao Y. Metabolic Regulation of Gene Expression by Histone Lysine β‐hydroxybutyrylation. The FASEB Journal 2017, 31 DOI: 10.1096/fasebj.31.1_supplement.755.2.Peer-Reviewed Original ResearchKetone bodiesNeuro-protective roleDiabetic ketoacidosisAdjunctive treatmentKetogenic dietBrain tumorsPharmacological effectsNeurodegenerative diseasesPathophysiological statesCultured cell linesMedical FoundationLines of evidenceCell linesEpilepsyΒ-hydroxybutyrylationNIHRNA-seq analysisMetabolic regulationRegulatory roleGene expressionShanghai Municipal ScienceMetabolic pathwaysKetoacidosisDiabetesPatients