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 interactionsLung Microenvironments and Disease Progression in Fibrotic Hypersensitivity Pneumonitis.
De Sadeleer LJ, McDonough JE, Schupp JC, Yan X, Vanstapel A, Van Herck A, Everaerts S, Geudens V, Sacreas A, Goos T, Aelbrecht C, Nawrot TS, Martens DS, Schols D, Claes S, Verschakelen JA, Verbeken EK, Ackermann M, Decottignies A, Mahieu M, Hackett TL, Hogg JC, Vanaudenaerde BM, Verleden SE, Kaminski N, Wuyts WA. Lung Microenvironments and Disease Progression in Fibrotic Hypersensitivity Pneumonitis. American Journal Of Respiratory And Critical Care Medicine 2022, 205: 60-74. PMID: 34724391, PMCID: PMC8865586, DOI: 10.1164/rccm.202103-0569oc.Peer-Reviewed Original ResearchConceptsFibrotic hypersensitivity pneumonitisIdiopathic pulmonary fibrosisHypersensitivity pneumonitisLung zonesMolecular traitsUnused donor lungsInterstitial lung diseaseLocal disease extentProgression of fibrosisSevere fibrosis groupGene co-expression network analysisCo-expression network analysisExplant lungsDonor lungsLung involvementEndothelial functionLung findingsDisease extentPulmonary fibrosisLung diseaseFibrosis groupLung microenvironmentClinical behaviorDisease progressionBAL samples
2021
MicroRNA miR-24-3p reduces DNA damage responses, apoptosis, and susceptibility to chronic obstructive pulmonary disease
Nouws J, Wan F, Finnemore E, Roque W, Kim SJ, Bazan IS, Li CX, Sköld C, Dai Q, Yan X, Chioccioli M, Neumeister V, Britto CJ, Sweasy J, Bindra RS, Wheelock ÅM, Gomez JL, Kaminski N, Lee PJ, Sauler M. MicroRNA miR-24-3p reduces DNA damage responses, apoptosis, and susceptibility to chronic obstructive pulmonary disease. JCI Insight 2021, 6: e134218. PMID: 33290275, PMCID: PMC7934877, DOI: 10.1172/jci.insight.134218.Peer-Reviewed Original ResearchConceptsCellular stress responseStress responseHomology-directed DNA repairDNA damage responseProtein BRCA1Damage responseCellular stressDNA repairProtein BimCOPD lung tissueLung epithelial cellsCellular responsesExpression arraysEpithelial cell apoptosisDNA damageChronic obstructive pulmonary diseaseBRCA1 expressionCell apoptosisApoptosisEpithelial cellsCritical mechanismMicroRNAsRegulatorObstructive pulmonary diseaseIncreases Susceptibility
2020
Regulation and characterization of tumor-infiltrating immune cells in breast cancer
Dai Q, Wu W, Amei A, Yan X, Lu L, Wang Z. Regulation and characterization of tumor-infiltrating immune cells in breast cancer. International Immunopharmacology 2020, 90: 107167. PMID: 33223469, PMCID: PMC7855363, DOI: 10.1016/j.intimp.2020.107167.Peer-Reviewed Original ResearchConceptsTumor-infiltrating immune cellsT cell activation statusImmune cellsCell activation statusT cell activationPatient survivalM2 macrophagesT cellsBreast cancerCell activationT cell peripheral toleranceTumor-infiltrating B cellsMultivariate Cox regression modelActivation statusBreast cancer patient survivalEffector T cellsT cell subsetsBreast cancer patientsImmune cell infiltrationAbundant plasma cellsCox regression modelKaplan-Meier survivalImmune cell typesMolecular pathwaysCancer patient survivalSingle-Cell Transcriptional Archetypes of Airway Inflammation in Cystic Fibrosis.
Schupp JC, Khanal S, Gomez JL, Sauler M, Adams TS, Chupp GL, Yan X, Poli S, Zhao Y, Montgomery RR, Rosas IO, Dela Cruz CS, Bruscia EM, Egan ME, Kaminski N, Britto CJ. Single-Cell Transcriptional Archetypes of Airway Inflammation in Cystic Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2020, 202: 1419-1429. PMID: 32603604, PMCID: PMC7667912, DOI: 10.1164/rccm.202004-0991oc.Peer-Reviewed Original ResearchConceptsCF lung diseaseHealthy control subjectsImmune dysfunctionLung diseaseCystic fibrosisControl subjectsSputum cellsAbnormal chloride transportLung mononuclear phagocytesInnate immune dysfunctionDivergent clinical coursesImmune cell repertoireMonocyte-derived macrophagesCF monocytesAirway inflammationClinical courseProinflammatory featuresCell survival programInflammatory responseTissue injuryCell repertoireImmune functionTranscriptional profilesAlveolar macrophagesMononuclear phagocytesSevere respiratory viral infection induces procalcitonin in the absence of bacterial pneumonia
Gautam S, Cohen AJ, Stahl Y, Toro P, Young GM, Datta R, Yan X, Ristic NT, Bermejo SD, Sharma L, Restrepo M, Dela Cruz CS. Severe respiratory viral infection induces procalcitonin in the absence of bacterial pneumonia. Thorax 2020, 75: 974-981. PMID: 32826284, DOI: 10.1136/thoraxjnl-2020-214896.Peer-Reviewed Original ResearchConceptsPure viral infectionBacterial coinfectionViral infectionInfluenza infectionSevere respiratory viral infectionsAbility of procalcitoninRetrospective cohort studyViral respiratory infectionsRespiratory viral infectionsMarker of severityRespiratory viral illnessSevere viral infectionsSpecificity of procalcitoninCharacteristic curve analysisCellular modelHigher procalcitoninProcalcitonin expressionElevated procalcitoninCohort studyViral illnessRespiratory infectionsAntibiotic administrationBacterial pneumoniaSevere diseaseProcalcitoninA Network of Sputum MicroRNAs is Associated with Neutrophilic Airway Inflammation in Asthma
Gomez JL, Chen A, Diaz MP, Zirn N, Gupta A, Britto C, Sauler M, Yan X, Stewart E, Santerian K, Grant N, Liu Q, Fry R, Rager J, Cohn L, Alexis N, Chupp GL. A Network of Sputum MicroRNAs is Associated with Neutrophilic Airway Inflammation in Asthma. American Journal Of Respiratory And Critical Care Medicine 2020, 0: 51-64. PMID: 32255668, PMCID: PMC7328332, DOI: 10.1164/rccm.201912-2360oc.Peer-Reviewed Original ResearchConceptsEndoplasmic reticulum stressAirway inflammationNeutrophil countClinical featuresT-helper cell type 17Neutrophilic airway inflammationReticulum stressSputum of subjectsLung function impairmentHistory of hospitalizationNumber of neutrophilsPeripheral blood neutrophilsSputum of patientsMicroRNA expressionAsthma severityTh17 pathwayFunction impairmentAirway samplesMicroRNA networkBlood neutrophilsOzone exposureAsthmaSputumCellular sourceClinical phenotype
2019
Transcriptional regulatory model of fibrosis progression in the human lung
McDonough JE, Ahangari F, Li Q, Jain S, Verleden SE, Herazo-Maya J, Vukmirovic M, DeIuliis G, Tzouvelekis A, Tanabe N, Chu F, Yan X, Verschakelen J, Homer RJ, Manatakis DV, Zhang J, Ding J, Maes K, De Sadeleer L, Vos R, Neyrinck A, Benos PV, Bar-Joseph Z, Tantin D, Hogg JC, Vanaudenaerde BM, Wuyts WA, Kaminski N. Transcriptional regulatory model of fibrosis progression in the human lung. JCI Insight 2019, 4 PMID: 31600171, PMCID: PMC6948862, DOI: 10.1172/jci.insight.131597.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisAdvanced fibrosisAlveolar surface densityFibrosis progressionLung fibrosisHuman lungDynamic Regulatory Events MinerExtent of fibrosisIPF lungsPulmonary fibrosisControl lungsIPF tissueB lymphocytesFibrosisLungLinear mixed-effects modelsMixed-effects modelsGene expression changesSystems biology modelsDifferential gene expression analysisGene expression analysisProgressionGene expression networksRNA sequencingBiology models
2017
Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study
Herazo-Maya JD, Sun J, Molyneaux PL, Li Q, Villalba JA, Tzouvelekis A, Lynn H, Juan-Guardela BM, Risquez C, Osorio JC, Yan X, Michel G, Aurelien N, Lindell KO, Klesen MJ, Moffatt MF, Cookson WO, Zhang Y, Garcia JGN, Noth I, Prasse A, Bar-Joseph Z, Gibson KF, Zhao H, Herzog EL, Rosas IO, Maher TM, Kaminski N. Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study. The Lancet Respiratory Medicine 2017, 5: 857-868. PMID: 28942086, PMCID: PMC5677538, DOI: 10.1016/s2213-2600(17)30349-1.Peer-Reviewed Original ResearchMeSH KeywordsAgedCohort StudiesFemaleGene Expression ProfilingGenetic MarkersGenetic TestingHumansIdiopathic Pulmonary FibrosisLeukocytes, MononuclearLinear ModelsMaleMiddle AgedOligonucleotide Array Sequence AnalysisPrognosisProportional Hazards ModelsRisk AssessmentRisk FactorsTime FactorsVital CapacityConceptsIdiopathic pulmonary fibrosisTransplant-free survivalRisk profilePulmonary fibrosisAntifibrotic drugsPeripheral blood mononuclear cellsCox proportional hazards modelClinical prediction toolGroup of patientsBlood mononuclear cellsHigh-risk groupProportional hazards modelPulmonary Fibrosis FoundationPittsburgh cohortUntreated patientsCohort studyClinical courseIPF diagnosisBlood InstituteProspective studyVital capacityMononuclear cellsPeripheral bloodUS National InstitutesNational HeartPolysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea
Zinchuk AV, Jeon S, Koo BB, Yan X, Bravata DM, Qin L, Selim BJ, Strohl KP, Redeker NS, Concato J, Yaggi HK. Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea. Thorax 2017, 73: 472. PMID: 28935698, PMCID: PMC6693344, DOI: 10.1136/thoraxjnl-2017-210431.Peer-Reviewed Original ResearchMeSH KeywordsAcute Coronary SyndromeAgedCardiovascular DiseasesCluster AnalysisCross-Sectional StudiesFemaleHumansIschemic Attack, TransientLongitudinal StudiesMaleMiddle AgedMortalityPhenotypePolysomnographyProportional Hazards ModelsRisk AssessmentSeverity of Illness IndexSleep Apnea, ObstructiveStrokeConceptsObstructive sleep apnoeaCardiovascular outcomesPolysomnographic featuresSleep apnoeaPolysomnographic dataIncident transient ischemic attackUS Veteran cohortTransient ischemic attackAcute coronary syndromeAdverse cardiovascular outcomesPeriodic limb movementsOSA severity classificationPolysomnographic phenotypeCoronary syndromeIschemic attackCardiovascular implicationsOSA phenotypesOSA evaluationPathophysiological domainsPoor sleepMild/Patient clustersVeteran cohortSurvival analysisCombined outcome