2021
Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study
, , Rouphael N, Maecker H, Montgomery R, Diray-Arce J, Kleinstein S, Altman M, Bosinger S, Eckalbar W, Guan L, Hough C, Krammer F, Langelier C, Levy O, McEnaney K, Peters B, Rahman A, Rajan J, Sigelman S, Steen H, van Bakel H, Ward A, Wilson M, Woodruff P, Zamecnik C, Augustine A, Ozonoff A, Reed E, Becker P, Higuita N, Altman M, Atkinson M, Baden L, Becker P, Bime C, Brakenridge S, Calfee C, Cairns C, Corry D, Davis M, Augustine A, Ehrlich L, Haddad E, Erle D, Fernandez-Sesma A, Hafler D, Hough C, Kheradmand F, Kleinstein S, Kraft M, Levy O, McComsey G, Melamed E, Messer W, Metcalf J, Montgomery R, Nadeau K, Ozonoff A, Peters B, Pulendran B, Reed E, Rouphael N, Sarwal M, Schaenman J, Sekaly R, Shaw A, Simon V. Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study. Science Immunology 2021, 6: eabf3733. PMID: 34376480, PMCID: PMC8713959, DOI: 10.1126/sciimmunol.abf3733.Peer-Reviewed Original ResearchConceptsCOVID-19 cohortProspective longitudinal studyHost immune responseLongitudinal studyCOVID-19Identification of biomarkersHospitalized patientsRespiratory secretionsClinical criteriaDisease progressionImmune responseRadiographic dataImmunologic assaysEffective therapeuticsOptimal timingStudy designBiologic samplingSuch interventionsCohortSeveritySample collectionAssay protocolsPatients
2016
AKT isoforms modulate Th1‐like Treg generation and function in human autoimmune disease
Kitz A, de Marcken M, Gautron AS, Mitrovic M, Hafler DA, Dominguez-Villar M. AKT isoforms modulate Th1‐like Treg generation and function in human autoimmune disease. EMBO Reports 2016, 17: 1169-1183. PMID: 27312110, PMCID: PMC4967959, DOI: 10.15252/embr.201541905.Peer-Reviewed Original ResearchMeSH KeywordsAutoimmune DiseasesBiomarkersCell DifferentiationCytokinesForkhead Transcription FactorsGene Expression ProfilingGene SilencingHumansImmunomodulationInterferon-gammaPhenotypePhosphatidylinositol 3-KinasesProtein IsoformsProto-Oncogene Proteins c-aktSignal TransductionT-Lymphocyte SubsetsT-Lymphocytes, RegulatoryTranscriptomeConceptsAutoimmune diseasesIFNγ secretionHuman TregsGenome-wide gene expression approachUntreated relapsing-remitting MS patientsRelapsing-remitting MS patientsImmune suppressive functionHuman autoimmune diseasesT helper 1Inflammatory cytokines IFNγTreg suppressor functionNovel treatment paradigmEffector phenotypeMS patientsTreg generationCytokines IFNγHelper 1Multiple sclerosisTreatment paradigmSuppressive functionTregsVivo modelDiseaseSecretionSuppressor functionMultiple sclerosis
Axisa PP, Hafler DA. Multiple sclerosis. Current Opinion In Neurology 2016, 29: 345-353. PMID: 27058221, PMCID: PMC7882195, DOI: 10.1097/wco.0000000000000319.Peer-Reviewed Original ResearchConceptsMultiple sclerosisGenome-wide association studiesAssociation studiesMultiple sclerosis (MS) etiologyMultiple sclerosis progressionMultiple sclerosis patientsHigh-throughput genetic analysisImmune cell functionNumerous candidate biomarkersWide association studyMechanisms of neurodegenerationImmunomodulatory treatmentSclerosis patientsClinical outcomesTreatment arsenalDisease progressionImmune regulationSclerosisNew biomarkersCandidate biomarkersPatient careGenetic variationGenetic analysisCell functionProgressionEvaluation of KIR4.1 as an Immune Target in Multiple Sclerosis
Chastre A, Hafler DA, O'Connor KC. Evaluation of KIR4.1 as an Immune Target in Multiple Sclerosis. New England Journal Of Medicine 2016, 374: 1495-1496. PMID: 27074083, PMCID: PMC4918464, DOI: 10.1056/nejmc1513302.Peer-Reviewed Original Research
2015
Biomarkers in multiple sclerosis
Housley WJ, Pitt D, Hafler DA. Biomarkers in multiple sclerosis. Clinical Immunology 2015, 161: 51-58. PMID: 26143623, DOI: 10.1016/j.clim.2015.06.015.Peer-Reviewed Original ResearchConceptsMultiple sclerosisB cell chemoattractant CXCL13Myelin-reactive T cellsMacrophage marker CD163Reactive T cellsMarkers of neurodegenerationKIR4.1 antibodiesMS seraClinical outcomesOligoclonal bandsYKL-40Disease progressionT cellsMS susceptibilityCerebrospinal fluidPotential biomarkersViral titersClinical useBiomarkersBiomarker researchSclerosisProgressionDisease diagnosisCD163CXCL13
2011
Interferon regulatory factor 5 gene variants and pharmacological and clinical outcome of Interferonβ therapy in multiple sclerosis
Vosslamber S, van der Voort LF, van den Elskamp IJ, Heijmans R, Aubin C, Uitdehaag BM, Crusius JB, van der PouwKraan T, Comabella M, Montalban X, Hafler DA, De Jager PL, Killestein J, Polman CH, Verweij CL. Interferon regulatory factor 5 gene variants and pharmacological and clinical outcome of Interferonβ therapy in multiple sclerosis. Genes & Immunity 2011, 12: 466-472. PMID: 21471993, DOI: 10.1038/gene.2011.18.Peer-Reviewed Original ResearchConceptsRelapsing-remitting multiple sclerosisNon-responder statusInterferon regulatory factor 5IFNβ treatmentMultiple sclerosisT2 lesionsClinical outcomesMore magnetic resonance imagingMore T2 lesionsStart of therapyGene variantsInterferon-β TherapyIFN response genesRegulatory factor 5Poor pharmacological responseMagnetic resonance imagingIFNβ therapyClinical responseFirst relapseIndependent cohortPharmacological responseClinical relevanceG allelePatientsResonance imaging
2009
Automated high-dimensional flow cytometric data analysis
Pyne S, Hu X, Wang K, Rossin E, Lin TI, Maier LM, Baecher-Allan C, McLachlan GJ, Tamayo P, Hafler DA, De Jager PL, Mesirov JP. Automated high-dimensional flow cytometric data analysis. Proceedings Of The National Academy Of Sciences Of The United States Of America 2009, 106: 8519-8524. PMID: 19443687, PMCID: PMC2682540, DOI: 10.1073/pnas.0903028106.Peer-Reviewed Original Research
2008
Integrating risk factors
De Jager PL, Simon KC, Munger KL, Rioux JD, Hafler DA, Ascherio A. Integrating risk factors. Neurology 2008, 70: 1113-1118. PMID: 18272866, DOI: 10.1212/01.wnl.0000294325.63006.f8.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntibodiesBiomarkersCase-Control StudiesComorbidityEpstein-Barr Virus InfectionsEpstein-Barr Virus Nuclear AntigensFemaleGene FrequencyGenetic Predisposition to DiseaseGenotypeHerpesvirus 4, HumanHeterozygoteHLA-DR AntigensHLA-DRB1 ChainsHumansMiddle AgedMultiple SclerosisRisk FactorsConceptsMultiple sclerosisHuman leukocyte antigenAntibody titersRisk factorsDR15 alleleEpstein-Barr virus (EBV) antibody titersAge-matched healthy womenRisk of MSEpstein-Barr virus nuclear antigen 1Independent risk factorVirus antibody titersCase-control studyNuclear antigen 1Healthy womenMS riskLeukocyte antigenRelative riskGenetic susceptibilityAntigen 1TitersWomenSclerosisRiskDR15Association
2006
Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers
O’Connor K, Roy SM, Becker CH, Hafler DA, Kantor AB. Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers. Disease Markers 2006, 22: 213-225. PMID: 17124343, PMCID: PMC3851054, DOI: 10.1155/2006/670439.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsMultiple sclerosisMagnetic resonance imagingPutative biomarkersComprehensive phenotypingMonitoring of progressionComponent expression levelsClinical evaluationCSF proteinAccurate biomarkersCerebrospinal fluid chemistryControl groupTherapeutic interventionsPatient careAccurate diagnosisResonance imagingDisease pathologyFurther evaluationBiomarkersPreliminary dataExpression levelsSclerosisDiagnosisCSFSingle testNovel assessment