2023
The β1-adrenergic receptor links sympathetic nerves to T cell exhaustion
Globig A, Zhao S, Roginsky J, Maltez V, Guiza J, Avina-Ochoa N, Heeg M, Araujo Hoffmann F, Chaudhary O, Wang J, Senturk G, Chen D, O’Connor C, Pfaff S, Germain R, Schalper K, Emu B, Kaech S. The β1-adrenergic receptor links sympathetic nerves to T cell exhaustion. Nature 2023, 622: 383-392. PMID: 37731001, PMCID: PMC10871066, DOI: 10.1038/s41586-023-06568-6.Peer-Reviewed Original ResearchConceptsImmune checkpoint blockadeCell exhaustionExhausted CD8Sympathetic nervesT cell exhaustionSympathetic stress responsePancreatic cancer modelAnti-tumor functionCheckpoint blockadeCatecholamine levelsTissue innervationCytokine productionChronic antigenMalignant diseaseChronic infectionCD8Immune responseAdrenergic signalingEffector functionsΒ-blockersViral infectionCancer modelExhausted stateCell responsesCell functionDectin-1 stimulation promotes a distinct inflammatory signature in the setting of HIV-infection and aging
Kumar A, Wang J, Esterly A, Radcliffe C, Zhou H, Wyk B, Allore H, Tsang S, Barakat L, Mohanty S, Zhao H, Shaw A, Zapata H. Dectin-1 stimulation promotes a distinct inflammatory signature in the setting of HIV-infection and aging. Aging 2023, 15: 7866-7908. PMID: 37606991, PMCID: PMC10497004, DOI: 10.18632/aging.204927.Peer-Reviewed Original ResearchConceptsDectin-1 stimulationDendritic cellsHIV-positive older adultsOlder adultsDectin-1 functionDistinct immune signaturesDistinct inflammatory signatureMonocytes of HIVCohort of HIVIFN-α productionPro-inflammatory environmentIFN-γ responsesPro-inflammatory phenotypeInnate immune receptorsDistinct gene signaturesStimulation of monocytesInflammatory signatureImmune signaturesHIV infectionIL-12Macrophage signatureCytokine productionIL-6Cytokine increaseHIVProfiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex
Rompala G, Nagamatsu S, Martínez-Magaña J, Nuñez-Ríos D, Wang J, Girgenti M, Krystal J, Gelernter J, Hurd Y, Montalvo-Ortiz J. Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex. Nature Communications 2023, 14: 4544. PMID: 37507366, PMCID: PMC10382503, DOI: 10.1038/s41467-023-40285-y.Peer-Reviewed Original ResearchConceptsOpioid use disorderMulti-omics findingsGene expression patternsCo-methylation analysisGene expression profilesMulti-omics profilingGene networksDNA methylationNeuronal methylomesDNA hydroxymethylationMethylomic analysisExpression patternsExpression profilesEpigenetic disturbancesUse disordersPsychiatric traitsOrbitofrontal cortexOpioid-related drugsPostmortem orbitofrontal cortexEnvironmental factorsDrug interaction analysisOUD treatmentHuman orbitofrontal cortexOpioid signalingInteraction analysis
2022
Commensal microbiota from patients with inflammatory bowel disease produce genotoxic metabolites
Cao Y, Oh J, Xue M, Huh WJ, Wang J, Gonzalez-Hernandez JA, Rice TA, Martin AL, Song D, Crawford JM, Herzon SB, Palm NW. Commensal microbiota from patients with inflammatory bowel disease produce genotoxic metabolites. Science 2022, 378: eabm3233. PMID: 36302024, PMCID: PMC9993714, DOI: 10.1126/science.abm3233.Peer-Reviewed Original ResearchConceptsColorectal cancerInflammatory bowel disease patientsBowel disease patientsInflammatory bowel diseaseIndigenous gut microbesBowel diseaseDisease patientsCommensal microbiotaDNA damageColon tumorigenesisElicit DNA damageGut microbesGenotoxic metabolitesGut commensalsMorganella morganiiPatientsGenotoxic chemicalsDiseaseMicrobiotaMetabolitesGenotoxicityCancerMiceFull spectrumDamage
2021
Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses
Cui C, Wang J, Fagerberg E, Chen PM, Connolly KA, Damo M, Cheung JF, Mao T, Askari AS, Chen S, Fitzgerald B, Foster GG, Eisenbarth SC, Zhao H, Craft J, Joshi NS. Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses. Cell 2021, 184: 6101-6118.e13. PMID: 34852236, PMCID: PMC8671355, DOI: 10.1016/j.cell.2021.11.007.Peer-Reviewed Original ResearchConceptsCD8 TB cellsTfh cellsLung adenocarcinomaTfh-B cell interactionsTumor-specific B cellsFollicular helper cellsAnti-tumor immunityB cell signaturesCell effector functionsGerminal center formationGC B cellsCD4 THelper cellsTumor controlTumor neoantigensEffector functionsCell collaborationCell responsesCell signatureTumor cellsSignature correlatesNeoantigensCell functionCD4Posttraumatic Stress Disorder Brain Transcriptomics: Convergent Genomic Signatures Across Biological Sex
Wang J, Zhao H, Girgenti MJ. Posttraumatic Stress Disorder Brain Transcriptomics: Convergent Genomic Signatures Across Biological Sex. Biological Psychiatry 2021, 91: 6-13. PMID: 33840456, DOI: 10.1016/j.biopsych.2021.02.012.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsPosttraumatic stress disorderConvergent genomic signaturesSpecific cell typesGene regulationGenomic regulationGenomic signaturesGenomic technologiesMolecular determinantsCell typesBrains of malesMolecular effectsGABAergic signalingMolecular pathologyImmune functionPTSD brainsSex impactRegulationStress disorderStructural differencesEffects of sex
2020
Transcriptomic 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 tissueDivergenceCD4+ follicular regulatory T cells optimize the influenza virus–specific B cell response
Lu Y, Jiang R, Freyn AW, Wang J, Strohmeier S, Lederer K, Locci M, Zhao H, Angeletti D, O’Connor K, Kleinstein SH, Nachbagauer R, Craft J. CD4+ follicular regulatory T cells optimize the influenza virus–specific B cell response. Journal Of Experimental Medicine 2020, 218: e20200547. PMID: 33326020, PMCID: PMC7748821, DOI: 10.1084/jem.20200547.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntibody FormationAntigensB-LymphocytesCD4 AntigensDisease Models, AnimalEpitopesForkhead Transcription FactorsGerminal CenterHumansImmunityImmunologic MemoryInfluenza, HumanInfluenzavirus BIntegrasesMice, Inbred C57BLOrthomyxoviridae InfectionsReceptors, Antigen, B-CellSpecies SpecificityT-Lymphocytes, RegulatoryVaccinationConceptsB cell responsesGerminal center B cell responsesFollicular regulatory T cellsRegulatory T cellsTfr cellsCell responsesT cellsViral challengeHumoral memoryVirus-specific B cell responsesAntigen-specific B cell responsesFollicular helper T cellsHA stalk regionHelper T cellsInfluenza virus infectionGerminal center developmentAntibody responsePlasma cellsVirus infectionImmunization modelAntibody productionBCR repertoireInfluenza virusRepeated exposureInfluenza virus glycoproteinsLeveraging 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 diseasesGWASCortical Transcriptomic Alterations in Association With Appetitive Neuropeptides and Body Mass Index in Posttraumatic Stress Disorder
Stone LA, Girgenti MJ, Wang J, Ji D, Zhao H, Krystal JH, Duman R. Cortical Transcriptomic Alterations in Association With Appetitive Neuropeptides and Body Mass Index in Posttraumatic Stress Disorder. The International Journal Of Neuropsychopharmacology 2020, 24: 118-129. PMID: 32951025, PMCID: PMC8611677, DOI: 10.1093/ijnp/pyaa072.Peer-Reviewed Original ResearchConceptsUpstream regulatorGene co-expression network analysisCo-expression network analysisFunctional genomic studiesPutative upstream regulatorsIngenuity Pathway Analysis softwarePathway Analysis softwarePathway annotationGenomic studiesTranscriptomic modulesTranscriptomic dataTranscriptomic alterationsGene expression
2019
Dependency of the Cancer-Specific Transcriptional Regulation Circuitry on the Promoter DNA Methylome
Liu Y, Liu Y, Huang R, Song W, Wang J, Xiao Z, Dong S, Yang Y, Yang X. Dependency of the Cancer-Specific Transcriptional Regulation Circuitry on the Promoter DNA Methylome. Cell Reports 2019, 26: 3461-3474.e5. PMID: 30893615, DOI: 10.1016/j.celrep.2019.02.084.Peer-Reviewed Original ResearchConceptsDNA methylomeTranscription factorsTranscriptional regulation circuitsCpG sitesGene expression dysregulationIntegrative analysis pipelineCpG methylation profilesSignature of cancerRegulation machineryExpression regulationCancer Genome AtlasCancer-related genesGene expression abnormalitiesExpression dysregulationMethylation profilesMethylomeDynamic dysregulationPhysiological relevanceGenome AtlasExpression abnormalitiesAnalysis pipelineRegulation circuitCancer typesDysregulationComprehensive understandingA 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