Featured Publications
Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung
Schupp JC, Adams TS, Cosme C, Raredon MSB, Yuan Y, Omote N, Poli S, Chioccioli M, Rose KA, Manning EP, Sauler M, DeIuliis G, Ahangari F, Neumark N, Habermann AC, Gutierrez AJ, Bui LT, Lafyatis R, Pierce RW, Meyer KB, Nawijn MC, Teichmann SA, Banovich NE, Kropski JA, Niklason LE, Pe’er D, Yan X, Homer RJ, Rosas IO, Kaminski N. Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung. Circulation 2021, 144: 286-302. PMID: 34030460, PMCID: PMC8300155, DOI: 10.1161/circulationaha.120.052318.Peer-Reviewed Original ResearchConceptsDifferential expression analysisPrimary lung endothelial cellsLung endothelial cellsCell typesMarker genesExpression analysisSingle-cell RNA sequencing dataCross-species analysisVenous endothelial cellsEndothelial marker genesSingle-cell atlasMarker gene setsRNA sequencing dataEndothelial cellsSubsequent differential expression analysisDifferent lung cell typesResident cell typesLung cell typesCellular diversityEndothelial cell typesCapillary endothelial cellsHuman lung endothelial cellsPhenotypic diversityEndothelial diversityIndistinguishable populations
2024
SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original Research
2023
iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects
Liu Y, Zhao J, Adams T, Wang N, Schupp J, Wu W, McDonough J, Chupp G, Kaminski N, Wang Z, Yan X. iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. BMC Bioinformatics 2023, 24: 318. PMID: 37608264, PMCID: PMC10463720, DOI: 10.1186/s12859-023-05432-8.Peer-Reviewed Original ResearchA novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy
Deng W, Li B, Wang J, Jiang W, Yan X, Li N, Vukmirovic M, Kaminski N, Wang J, Zhao H. A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy. Briefings In Bioinformatics 2023, 24: bbac616. PMID: 36631398, PMCID: PMC9851324, DOI: 10.1093/bib/bbac616.Peer-Reviewed Original Research
2022
Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES
Raredon M, Yang J, Kothapalli N, Lewis W, Kaminski N, Niklason L, Kluger Y. Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES. Bioinformatics 2022, 39: btac775. PMID: 36458905, PMCID: PMC9825783, DOI: 10.1093/bioinformatics/btac775.Peer-Reviewed Original ResearchConceptsCell-cell interactionsCell-cell signalingSingle-cell resolutionSingle-cell dataLocal cellular microenvironmentSingle-cell levelSpatial transcriptomics dataCell clustersExtracellular signalingTranscriptomic dataGene expression valuesSpatial transcriptomicsSignaling mechanismCellular microenvironmentNicheExpression valuesSupplementary dataSignalingTranscriptomicsComprehensive visualizationBioinformaticsInteractionBAL Transcriptomes Characterize Idiopathic Pulmonary Fibrosis Endotypes With Prognostic Impact
De Sadeleer LJ, Verleden SE, Schupp JC, McDonough JE, Goos T, Yserbyt J, Bargagli E, Rottoli P, Kaminski N, Prasse A, Wuyts WA. BAL Transcriptomes Characterize Idiopathic Pulmonary Fibrosis Endotypes With Prognostic Impact. CHEST Journal 2022, 161: 1576-1588. PMID: 35063449, PMCID: PMC9424328, DOI: 10.1016/j.chest.2021.12.668.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisIPF samplesIndependent validation cohortAvailable gene expression datasetsClinical characteristicsPrognostic impactWorse survivalPathophysiologic mechanismsPulmonary fibrosisClinical evolutionClinical variablesValidation cohortEnrichment analysisBAL samplesSurvival-associated genesBlood samplesEndotypesStudy designControl participantsMitochondrial dysfunctionPatientsFibrosisSurvivalTranscription factorsNumeric trendsLung 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
Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells.
Huang Y, Oldham JM, Ma SF, Unterman A, Liao SY, Barros AJ, Bonham CA, Kim JS, Vij R, Adegunsoye A, Strek ME, Molyneaux PL, Maher TM, Herazo-Maya JD, Kaminski N, Moore BB, Martinez FJ, Noth I. Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells. American Journal Of Respiratory And Critical Care Medicine 2021, 204: 197-208. PMID: 33689671, PMCID: PMC8650792, DOI: 10.1164/rccm.202008-3093oc.Peer-Reviewed Original ResearchChronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity
Bui LT, Winters NI, Chung MI, Joseph C, Gutierrez AJ, Habermann AC, Adams TS, Schupp JC, Poli S, Peter LM, Taylor CJ, Blackburn JB, Richmond BW, Nicholson AG, Rassl D, Wallace WA, Rosas IO, Jenkins RG, Kaminski N, Kropski JA, Banovich NE. Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity. Nature Communications 2021, 12: 4314. PMID: 34262047, PMCID: PMC8280215, DOI: 10.1038/s41467-021-24467-0.Peer-Reviewed Original ResearchConceptsChronic lung diseaseLung diseaseImmune responseSARS-CoV-2 entry factorsSevere coronavirus disease-19SARS-CoV-2 infectionWorse COVID-19 outcomesSARS-CoV-2 entryAdaptive immune responsesCoronavirus disease-19COVID-19 outcomesInnate immune responseInflammatory gene expression programSimilar cellular distributionPoor outcomePeripheral lungViral exposureDisease-19Inflammatory microenvironmentEntry factorsLung epitheliumLung cellsViral replicationAT2 cellsBasal differencesTranscriptomics of bronchoalveolar lavage cells identifies new molecular endotypes of sarcoidosis
Vukmirovic M, Yan X, Gibson KF, Gulati M, Schupp JC, DeIuliis G, Adams TS, Hu B, Mihaljinec A, Woolard TN, Lynn H, Emeagwali N, Herzog EL, Chen ES, Morris A, Leader JK, Zhang Y, Garcia JGN, Maier LA, Collman RG, Drake WP, Becich MJ, Hochheiser H, Wisniewski SR, Benos PV, Moller DR, Prasse A, Koth LL, Kaminski N. Transcriptomics of bronchoalveolar lavage cells identifies new molecular endotypes of sarcoidosis. European Respiratory Journal 2021, 58: 2002950. PMID: 34083402, PMCID: PMC9759791, DOI: 10.1183/13993003.02950-2020.Peer-Reviewed Original ResearchMeSH KeywordsBronchoalveolar LavageBronchoalveolar Lavage FluidHumansSarcoidosisSarcoidosis, PulmonaryTranscriptomeConceptsWeighted gene co-expression network analysisGene co-expression network analysisCo-expression network analysisGene expression programsGene expression patternsDistinct transcriptional programsImmune response pathwaysIon Torrent ProtonMicroarray expression datasetsExpression programsTranscriptional programsPhenotypic traitsGene modulesResponse pathwaysRNA sequencingMolecular endotypesExpression patternsGene expressionHilar lymphadenopathyOrgan involvementGenomic researchMechanistic targetExpression datasetsT helper type 1T cell immune responsesMicroRNA 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
Gene coexpression networks reveal novel molecular endotypes in alpha-1 antitrypsin deficiency
Chu JH, Zang W, Vukmirovic M, Yan X, Adams T, DeIuliis G, Hu B, Mihaljinec A, Schupp JC, Becich MJ, Hochheiser H, Gibson KF, Chen ES, Morris A, Leader JK, Wisniewski SR, Zhang Y, Sciurba FC, Collman RG, Sandhaus R, Herzog EL, Patterson KC, Sauler M, Strange C, Kaminski N. Gene coexpression networks reveal novel molecular endotypes in alpha-1 antitrypsin deficiency. Thorax 2020, 76: 134-143. PMID: 33303696, PMCID: PMC10794043, DOI: 10.1136/thoraxjnl-2019-214301.Peer-Reviewed Original ResearchConceptsWeighted gene co-expression network analysisAlpha-1 antitrypsin deficiencyGene modulesGene co-expression network analysisDifferential gene expression analysisCo-expression network analysisPeripheral blood mononuclear cellsGene expression patternsPBMC gene expression patternsGene coexpression networksAATD individualsGene expression profilesGene expression analysisBronchoalveolar lavageAugmentation therapyClinical variablesAntitrypsin deficiencyGene expression assaysRNA-seqCoexpression networkGene validationExpression analysisExpression assaysWGCNA modulesExpression patternsGenetic determinants of ammonia-induced acute lung injury in mice
Bein K, Ganguly K, Martin TM, Concel VJ, Brant KA, Di YPP, Upadhyay S, Fabisiak JP, Vuga LJ, Kaminski N, Kostem E, Eskin E, Prows DR, Jang AS, Leikauf GD. Genetic determinants of ammonia-induced acute lung injury in mice. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2020, 320: l41-l62. PMID: 33050709, PMCID: PMC7847062, DOI: 10.1152/ajplung.00276.2020.Peer-Reviewed Original ResearchConceptsSNP associationsWide association mappingGenetic determinantsSignificant SNP associationsAcute lung injuryIntegrative functional approachAssociation mappingMolecular functionsTranscriptomic analysisCandidate genesFunctional domainsNonsynonymous SNPsPromoter regionLung injuryDiverse panelGenesSNPsMouse strainsPathophysiological roleAATFInjuryProteinLAMA3ExpressionAssemblyExpression of SARS-CoV-2 receptor ACE2 and coincident host response signature varies by asthma inflammatory phenotype
Camiolo M, Gauthier M, Kaminski N, Ray A, Wenzel SE. Expression of SARS-CoV-2 receptor ACE2 and coincident host response signature varies by asthma inflammatory phenotype. Journal Of Allergy And Clinical Immunology 2020, 146: 315-324.e7. PMID: 32531372, PMCID: PMC7283064, DOI: 10.1016/j.jaci.2020.05.051.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAngiotensin-Converting Enzyme 2AsthmaBetacoronavirusBiomarkersBronchiBronchoalveolar Lavage FluidCohort StudiesCoronavirus InfectionsCOVID-19EosinophilsFemaleGene Expression ProfilingHumansInterferon Type IInterferon-gammaMaleMiddle AgedPandemicsPeptidyl-Dipeptidase APneumonia, ViralProtein Interaction MappingReceptors, VirusRisk FactorsSARS-CoV-2Severity of Illness IndexT-LymphocytesTranscriptomeUnited StatesConceptsCoronavirus disease 2019Severe coronavirus disease 2019Subset of patientsDisease 2019Risk factorsBronchial epitheliumAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionSevere acute respiratory syndrome coronavirus 2Syndrome coronavirus 2 infectionType 2 inflammatory biomarkersAcute respiratory syndrome coronavirus 2Receptor ACE2SARS-CoV-2 receptor ACE2Respiratory syndrome coronavirus 2Asthma inflammatory phenotypesLarge asthma cohortsLower peripheral bloodT cell-activating factorCoronavirus 2 infectionEnzyme 2 (ACE2) expressionHistory of hypertensionDiagnosis of asthmaBronchoalveolar lavage lymphocytesT cell recruitmentPlatform Effects on Regeneration by Pulmonary Basal Cells as Evaluated by Single-Cell RNA Sequencing
Greaney AM, Adams TS, Raredon M, Gubbins E, Schupp JC, Engler AJ, Ghaedi M, Yuan Y, Kaminski N, Niklason LE. Platform Effects on Regeneration by Pulmonary Basal Cells as Evaluated by Single-Cell RNA Sequencing. Cell Reports 2020, 30: 4250-4265.e6. PMID: 32209482, PMCID: PMC7175071, DOI: 10.1016/j.celrep.2020.03.004.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingBasal marker expressionBasal cellsChronic pulmonary diseaseRat tracheal epitheliumPulmonary diseaseRNA sequencingCell-based therapiesRat tracheaAir-liquid interfaceTissue graftMarker expressionTracheal epitheliumRegenerative outcomesTracheaEpithelial progenitorsDifferential outcomesEpitheliumOutcomesWhole organPopulation level
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 modelsIntegrating multiomics longitudinal data to reconstruct networks underlying lung development
Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N. Integrating multiomics longitudinal data to reconstruct networks underlying lung development. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2019, 317: l556-l568. PMID: 31432713, PMCID: PMC6879899, DOI: 10.1152/ajplung.00554.2018.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAnimals, NewbornChildChild, PreschoolDNA MethylationEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHumansImmunity, InnateInfantInfant, NewbornLungMaleMiceMice, Inbred C57BLMicroRNAsOrganogenesisProteomicsPulmonary AlveoliRNA, MessengerSingle-Cell AnalysisTranscriptomeConceptsSingle-cell RNA-seq dataLung developmentDynamic regulatory networksOmics data setsRNA-seq dataIndividual cell typesHuman lung developmentRegulatory networksDNA methylationLaser capture microdissectionEpigenetic changesExpression trajectoriesKey pathwaysCell typesActive pathwaysCapture microdissectionRegulatorKey eventsInnate immunityNew insightsSpecific key eventsPathwayComprehensive understandingProteomicsMethylationThe Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease
Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Braga F, Timens W, Koppelman GH, Budinger GRS, Burgess JK, Waghray A, van den Berge M, Theis F, Regev A, Kaminski N, Rajagopal J, Teichmann S, Misharin A, Nawijn M. The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. American Journal Of Respiratory Cell And Molecular Biology 2019, 61: 31-41. PMID: 30995076, PMCID: PMC6604220, DOI: 10.1165/rcmb.2018-0416tr.Peer-Reviewed Original ResearchConceptsCell atlasHuman Cell Atlas consortiumCell typesCell-cell interactionsHigh-throughput techniquesFunction of geneticsLung cell typesTranscriptomic analysisDevelopmental processesIndividual cellsMolecular descriptionReference mapTissue microenvironmentDisease mechanismsCellular neighborhoodsHealthy human bodyMolecular profilePersonalized therapeutic regimensCellsLung diseaseTherapeutic regimensImmune cellsLung tissueRecent progressTissue matrixSialylation of MUC4β N-glycans by ST6GAL1 orchestrates human airway epithelial cell differentiation associated with Type-2 inflammation
Zhou X, Kinlough CL, Hughey RP, Jin M, Inoue H, Etling E, Modena BD, Kaminski N, Bleecker ER, Meyers DA, Jarjour NN, Trudeau JB, Holguin F, Ray A, Wenzel SE. Sialylation of MUC4β N-glycans by ST6GAL1 orchestrates human airway epithelial cell differentiation associated with Type-2 inflammation. JCI Insight 2019, 4 PMID: 30730306, PMCID: PMC6483602, DOI: 10.1172/jci.insight.122475.Peer-Reviewed Original ResearchConceptsHuman airway epithelial cellsEpithelial dysfunctionPrimary human airway epithelial cellsAirway epithelial cell differentiationT2-high asthmaType 2 inflammationAirway epithelial cellsGoblet cell differentiationEpithelial cell proliferationAirway specimensT2 biomarkersAsthmatic patientsSputum supernatantsT2 inflammationIL-13Cell differentiationAsthmaEpithelial cell differentiationSpecific mucinsEpithelial cell fateΒ-galactoside αEpithelial glycoproteinEpithelial cellsPotential targetEpithelial differentiation
2018
Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis
McDonough JE, Kaminski N, Thienpont B, Hogg JC, Vanaudenaerde BM, Wuyts WA. Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis. Thorax 2018, 74: 132. PMID: 30366970, PMCID: PMC6467239, DOI: 10.1136/thoraxjnl-2018-211929.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisLung functionPulmonary fibrosisExtensive pathological changesSevere lung diseaseLung Tissue Research ConsortiumCorrelation network analysisIPF cohortIPF groupLung diseaseControl subjectsUpregulated modulesT cellsImmune responsePathological changesLeucocyte activationB cellsClinical relevanceSurfactant metabolismDisease pathologyInterferon responseFibrosisBlood vesselsPathological processesGene correlation network analysis