2024
An autoimmune transcriptional circuit drives FOXP3+ regulatory T cell dysfunction
Sumida T, Lincoln M, He L, Park Y, Ota M, Oguchi A, Son R, Yi A, Stillwell H, Leissa G, Fujio K, Murakawa Y, Kulminski A, Epstein C, Bernstein B, Kellis M, Hafler D. An autoimmune transcriptional circuit drives FOXP3+ regulatory T cell dysfunction. Science Translational Medicine 2024, 16: eadp1720. PMID: 39196959, DOI: 10.1126/scitranslmed.adp1720.Peer-Reviewed Original ResearchConceptsForkhead box P3Autoimmune diseasesCD4<sup>+</sup>Foxp3<sup>+</sup> regulatory T cellsMultiple sclerosisFoxp3<sup>+</sup> regulatory T cellsRegulatory T cell dysfunctionPR domain zinc finger protein 1Zinc finger protein 1Glucocorticoid-regulated kinase 1Regulatory T cellsT cell dysfunctionDisorder of young adultsAutoimmune disease multiple sclerosisDisease multiple sclerosisExpression of serumTranscriptional circuitsEpigenomic profilingShort isoformPrevent autoimmunityUpstream regulatorT cellsHuman autoimmunityEvolutionary emergenceKinase 1Molecular mechanismsMeta-analysis identifies common gut microbiota associated with multiple sclerosis
Lin Q, Dorsett Y, Mirza A, Tremlett H, Piccio L, Longbrake E, Choileain S, Hafler D, Cox L, Weiner H, Yamamura T, Chen K, Wu Y, Zhou Y. Meta-analysis identifies common gut microbiota associated with multiple sclerosis. Genome Medicine 2024, 16: 94. PMID: 39085949, PMCID: PMC11293023, DOI: 10.1186/s13073-024-01364-x.Peer-Reviewed Original ResearchMeSH KeywordsAdultBacteriaCase-Control StudiesFemaleGastrointestinal MicrobiomeHumansMaleMultiple SclerosisRNA, Ribosomal, 16SConceptsRRNA gene sequence dataGroups of microbial taxaGene sequence dataMicrobiome community structureAbundance of FaecalibacteriumAbundance of PrevotellaAbundance of ActinomycesSequence dataBeta diversityMicrobial taxaGut microbiotaMicrobial compositionCommunity structureNetwork analysisGutBacterial correlationsMicrobiotaAbundanceMultiple sclerosisDiverse groupMeta-analysisDiversityTaxaFaecalibacteriumConclusionsOur meta-analysis
2023
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Zhu B, Wang Y, Ku L, van Dijk D, Zhang L, Hafler D, Zhao H. scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles. Genome Biology 2023, 24: 292. PMID: 38111007, PMCID: PMC10726524, DOI: 10.1186/s13059-023-03129-y.Peer-Reviewed Original ResearchDifferential effects of anti-CD20 therapy on CD4 and CD8 T cells and implication of CD20-expressing CD8 T cells in MS disease activity
Shinoda K, Li R, Rezk A, Mexhitaj I, Patterson K, Kakara M, Zuroff L, Bennett J, von Büdingen H, Carruthers R, Edwards K, Fallis R, Giacomini P, Greenberg B, Hafler D, Ionete C, Kaunzner U, Lock C, Longbrake E, Pardo G, Piehl F, Weber M, Ziemssen T, Jacobs D, Gelfand J, Cross A, Cameron B, Musch B, Winger R, Jia X, Harp C, Herman A, Bar-Or A. Differential effects of anti-CD20 therapy on CD4 and CD8 T cells and implication of CD20-expressing CD8 T cells in MS disease activity. Proceedings Of The National Academy Of Sciences Of The United States Of America 2023, 120: e2207291120. PMID: 36634138, PMCID: PMC9934304, DOI: 10.1073/pnas.2207291120.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, CD20CD8-Positive T-LymphocytesFlow CytometryHumansLeukocytes, MononuclearMultiple SclerosisRecurrenceConceptsEarly disease activityDisease activityCD8 T cellsT cellsCD20 therapyPeripheral blood mononuclear cellsCellular immune profilesNew disease activityMS disease activityT cell poolMultiple sclerosis patientsAnti-inflammatory profileBlood mononuclear cellsTreatment-associated changesMultiparametric flow cytometryCentral nervous systemFurther dosingRepeat infusionsImmune profileMS patientsSclerosis patientsValidation cohortMononuclear cellsRelapse developmentImmune cascade
2022
A multiple sclerosis–protective coding variant reveals an essential role for HDAC7 in regulatory T cells
Axisa P, Yoshida T, Lucca L, Kasler H, Lincoln M, Pham G, Del Priore D, Carpier J, Lucas C, Verdin E, Sumida T, Hafler D. A multiple sclerosis–protective coding variant reveals an essential role for HDAC7 in regulatory T cells. Science Translational Medicine 2022, 14: eabl3651. PMID: 36516268, DOI: 10.1126/scitranslmed.abl3651.Peer-Reviewed Original ResearchConceptsExperimental autoimmune encephalitisRegulatory T cellsHistone deacetylase 7Multiple sclerosisT cellsMouse modelFunction of Foxp3CD4 T cellsHigher suppressive capacityVivo modelingAutoimmune encephalitisEAE severityImmunosuppressive subsetAutoimmune diseasesImmunomodulatory roleSuppressive capacityImmune cellsDisease onsetDistinct molecular classesSusceptibility lociGenetic susceptibility lociSingle-cell RNA sequencingDisease riskPatient samplesProtective variantsImpaired TIGIT expression on B cells drives circulating follicular helper T cell expansion in multiple sclerosis
Asashima H, Axisa PP, Pham THG, Longbrake EE, Ruff WE, Lele N, Cohen I, Raddassi K, Sumida TS, Hafler DA. Impaired TIGIT expression on B cells drives circulating follicular helper T cell expansion in multiple sclerosis. Journal Of Clinical Investigation 2022, 132: e156254. PMID: 36250467, PMCID: PMC9566906, DOI: 10.1172/jci156254.Peer-Reviewed Original ResearchConceptsRelapsing-remitting multiple sclerosisMemory B cellsCTfh cellsB cellsTIGIT expressionMultiple sclerosisT cellsFollicular helper T cellsHealthy age-matched controlsB-cell depletionT cell expansionHelper T cellsAge-matched controlsB cell functionB-cell pathwayDifferential gene expression signaturesTfh cellsDisease activityGene expression signaturesCell depletionCD40 ligandTranscription factor TCF4Disease pathogenesisImmune systemNew MRIThe CELLO trial: Protocol of a planned phase 4 study to assess the efficacy of Ocrelizumab in patients with radiologically isolated syndrome
Longbrake EE, Hua LH, Mowry EM, Gauthier SA, Alvarez E, Cross AH, Pei J, Priest J, Raposo C, Hafler DA, Winger RC. The CELLO trial: Protocol of a planned phase 4 study to assess the efficacy of Ocrelizumab in patients with radiologically isolated syndrome. Multiple Sclerosis And Related Disorders 2022, 68: 104143. PMID: 36031693, PMCID: PMC9772048, DOI: 10.1016/j.msard.2022.104143.Peer-Reviewed Original ResearchConceptsEfficacy of ocrelizumabMultiple sclerosisImmunologic biomarkersClinical trialsTransient B-cell depletionClinical multiple sclerosisCSF immune cellsEffects of ocrelizumabMS disease pathophysiologyNew brain lesionsOvert neurological symptomsB-cell depletionPlacebo-controlled studyPhase 4 studyLong-term outcomesPatient-reported outcomesPrimary progressive MSHumanized monoclonal antibodyFirst-degree relativesB cell biologySubtle cognitive impairmentEligible patientsImmune recoveryProgressive MSWeek 48Fatty Acid Metabolism and T Cells in Multiple Sclerosis
Pompura SL, Hafler DA, Dominguez-Villar M. Fatty Acid Metabolism and T Cells in Multiple Sclerosis. Frontiers In Immunology 2022, 13: 869197. PMID: 35603182, PMCID: PMC9116144, DOI: 10.3389/fimmu.2022.869197.Peer-Reviewed Original ResearchConceptsT cell functionT cellsMultiple sclerosisSpecific lipid speciesEffector T cellsRegulatory T cellsCell functionT helper subsetsMetabolic programsT cell activationT cell transitionLipid speciesFatty acid metabolismTh subsetsHelper subsetsEffector stateBody of evidenceCell activationDisease settingsDisease statesFunctional phenotypeOrganismal levelAcid metabolismMetabolic remodelingNutrient availability
2021
23Na imaging: Worth its salt for understanding multiple sclerosis
Longbrake EE, Hafler DA. 23Na imaging: Worth its salt for understanding multiple sclerosis. Proceedings Of The National Academy Of Sciences Of The United States Of America 2021, 118: e2110799118. PMID: 34376559, PMCID: PMC8379906, DOI: 10.1073/pnas.2110799118.Commentaries, Editorials and LettersOleic acid restores suppressive defects in tissue-resident FOXP3 regulatory T cells from patients with multiple sclerosis
Pompura SL, Wagner A, Kitz A, Laperche J, Yosef N, Dominguez-Villar M, Hafler D. Oleic acid restores suppressive defects in tissue-resident FOXP3 regulatory T cells from patients with multiple sclerosis. Journal Of Clinical Investigation 2021, 131 PMID: 33170805, PMCID: PMC7810477, DOI: 10.1172/jci138519.Peer-Reviewed Original ResearchMeSH KeywordsAdultFemaleForkhead Transcription FactorsHumansImmune ToleranceMaleMiddle AgedMultiple SclerosisOleic AcidT-Lymphocytes, RegulatoryConceptsMultiple sclerosisAdipose tissueFoxp3 regulatory T cellsExpression of Foxp3Regulatory T cellsTreg suppressive functionProinflammatory arachidonic acidHuman adipose tissuePhosphorylation of STAT5Treg homeostasisFatty acidsPeripheral bloodTissue residencyHealthy donorsInflammatory signalsT cellsTregsFree fatty acidsSuppressive functionArachidonic acidPatientsOleic acidOxidative phosphorylationTranscriptomic programsFoxp3
2020
Two genetic variants explain the association of European ancestry with multiple sclerosis risk in African-Americans
Nakatsuka N, Patterson N, Patsopoulos NA, Altemose N, Tandon A, Beecham AH, McCauley JL, Isobe N, Hauser S, De Jager PL, Hafler DA, Oksenberg JR, Reich D. Two genetic variants explain the association of European ancestry with multiple sclerosis risk in African-Americans. Scientific Reports 2020, 10: 16902. PMID: 33037294, PMCID: PMC7547691, DOI: 10.1038/s41598-020-74035-7.Peer-Reviewed Original ResearchDifferential expression of the T-cell inhibitor TIGIT in glioblastoma and MS
Lucca LE, Lerner BA, Park C, DeBartolo D, Harnett B, Kumar VP, Ponath G, Raddassi K, Huttner A, Hafler DA, Pitt D. Differential expression of the T-cell inhibitor TIGIT in glioblastoma and MS. Neurology Neuroimmunology & Neuroinflammation 2020, 7: e712. PMID: 32269065, PMCID: PMC7188477, DOI: 10.1212/nxi.0000000000000712.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedCentral Nervous System NeoplasmsFemaleGlioblastomaHumansMaleMiddle AgedMultiple SclerosisReceptors, ImmunologicUp-RegulationConceptsTumor-infiltrating T cellsT cellsPD-1/PD-L1Anti-TIGIT therapyExpression of CD226Expression of TIGITPostmortem CNS tissueLymphocytes of patientsFresh surgical resectionsLigand CD155TIGIT expressionSurgical resectionPD-1PD-L1CNS diseaseHealthy controlsHealthy donorsLymphocytic expressionImmune responseCNS tissueMS lesionsTIGITImmune pathwaysPatientsGlioblastoma multiforme
2019
Siponimod Chips Away at Progressive MS
Longbrake EE, Hafler DA. Siponimod Chips Away at Progressive MS. Cell 2019, 179: 1440. PMID: 31951523, PMCID: PMC8023412, DOI: 10.1016/j.cell.2019.11.034.Peer-Reviewed Original ResearchMeSH KeywordsAzetidinesBenzyl CompoundsClinical Trials as TopicHumansMultiple SclerosisUnited StatesUnited States Food and Drug AdministrationConceptsProgressive multiple sclerosisGadolinium-enhancing MRI lesionsInflammatory disease activityImmunomodulatory medicationsDisability progressionDisease activityMRI lesionsProgressive MSNeurologic disabilityPMS patientsMultiple sclerosisSiponimodMedicationsSclerosisPatientsLesionsBedsideProgressionMultiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
Patsopoulos N, Baranzini S, Santaniello A, Shoostari P, Cotsapas C, Wong G, Beecham A, James T, Replogle J, Vlachos I, McCabe C, Pers T, Brandes A, White C, Keenan B, Cimpean M, Winn P, Panteliadis I, Robbins A, Andlauer T, Zarzycki O, Dubois B, Goris A, Søndergaard H, Sellebjerg F, Sorensen P, Ullum H, Thørner L, Saarela J, Cournu-Rebeix I, Damotte V, Fontaine B, Guillot-Noel L, Lathrop M, Vukusic S, Berthele A, Pongratz V, Buck D, Gasperi C, Graetz C, Grummel V, Hemmer B, Hoshi M, Knier B, Korn T, Lill C, Luessi F, Mühlau M, Zipp F, Dardiotis E, Agliardi C, Amoroso A, Barizzone N, Benedetti M, Bernardinelli L, Cavalla P, Clarelli F, Comi G, Cusi D, Esposito F, Ferrè L, Galimberti D, Guaschino C, Leone M, Martinelli V, Moiola L, Salvetti M, Sorosina M, Vecchio D, Zauli A, Santoro S, Mancini N, Zuccalà M, Mescheriakova J, van Duijn C, Bos S, Celius E, Spurkland A, Comabella M, Montalban X, Alfredsson L, Bomfim I, Gomez-Cabrero D, Hillert J, Jagodic M, Lindén M, Piehl F, Jelčić I, Martin R, Sospedra M, Baker A, Ban M, Hawkins C, Hysi P, Kalra S, Karpe F, Khadake J, Lachance G, Molyneux P, Neville M, Thorpe J, Bradshaw E, Caillier S, Calabresi P, Cree B, Cross A, Davis M, de Bakker P, Delgado S, Dembele M, Edwards K, Fitzgerald K, Frohlich I, Gourraud P, Haines J, Hakonarson H, Kimbrough D, Isobe N, Konidari I, Lathi E, Lee M, Li T, An D, Zimmer A, Madireddy L, Manrique C, Mitrovic M, Olah M, Patrick E, Pericak-Vance M, Piccio L, Schaefer C, Weiner H, Lage K, Compston A, Hafler D, Harbo H, Hauser S, Stewart G, D’Alfonso S, Hadjigeorgiou G, Taylor B, Barcellos L, Booth D, Hintzen R, Kockum I, Martinelli-Boneschi F, McCauley J, Oksenberg J, Oturai A, Sawcer S, Ivinson A, Olsson T, De Jager P. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility. Science 2019, 365 PMID: 31604244, PMCID: PMC7241648, DOI: 10.1126/science.aav7188.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesCell Cycle ProteinsChromosome MappingChromosomes, Human, XGene FrequencyGenetic LociGenome-Wide Association StudyGenomicsGTPase-Activating ProteinsHumansInheritance PatternsMajor Histocompatibility ComplexMicrogliaMultiple SclerosisPolymorphism, Single NucleotideQuantitative Trait LociRNA-SeqTranscriptomeConceptsMajor histocompatibility complexMultiple sclerosisImmune cellsBrain-resident immune cellsPeripheral immune cellsPeripheral immune responseCentral nervous systemExtended major histocompatibility complexAutoimmune processControl subjectsHuman microgliaImmune responseNervous systemImmune systemHistocompatibility complexPutative susceptibility genesMicrogliaX variantGenetic architectureSusceptibility genesGenomic mapGenetic dataExpression profilesM geneSusceptibility variantsMultiple sclerosis enters a grey area
Pappalardo JL, Hafler DA. Multiple sclerosis enters a grey area. Nature 2019, 566: 465-466. PMID: 30809050, DOI: 10.1038/d41586-019-00563-6.Peer-Reviewed Original Research
2018
Enhanced astrocyte responses are driven by a genetic risk allele associated with multiple sclerosis
Ponath G, Lincoln MR, Levine-Ritterman M, Park C, Dahlawi S, Mubarak M, Sumida T, Airas L, Zhang S, Isitan C, Nguyen TD, Raine CS, Hafler DA, Pitt D. Enhanced astrocyte responses are driven by a genetic risk allele associated with multiple sclerosis. Nature Communications 2018, 9: 5337. PMID: 30559390, PMCID: PMC6297228, DOI: 10.1038/s41467-018-07785-8.Peer-Reviewed Original ResearchConceptsMultiple sclerosisAstrocyte responseRisk variantsLocal autoimmune inflammationPeripheral immune cellsCentral nervous system cellsPeripheral immune systemCultured human astrocytesNervous system cellsNF-κB signalingCNS accessDysfunctional lymphocytesAstroglial functionAutoimmune inflammationLymphocytic infiltrateLymphocyte recruitmentImmune cellsGenetic risk allelesGenetic risk variantsMS lesionsMS susceptibilityHuman astrocytesLesion sizeImmune systemSystem cellsLow-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk
Consortium I, Mitrovič M, Patsopoulos N, Beecham A, Dankowski T, Goris A, Dubois B, D’hooghe M, Lemmens R, Van Damme P, Søndergaard H, Sellebjerg F, Sorensen P, Ullum H, Thørner L, Werge T, Saarela J, Cournu-Rebeix I, Damotte V, Fontaine B, Guillot-Noel L, Lathrop M, Vukusik S, Gourraud P, Andlauer T, Pongratz V, Buck D, Gasperi C, Bayas A, Heesen C, Kümpfel T, Linker R, Paul F, Stangel M, Tackenberg B, Bergh F, Warnke C, Wiendl H, Wildemann B, Zettl U, Ziemann U, Tumani H, Gold R, Grummel V, Hemmer B, Knier B, Lill C, Luessi F, Dardiotis E, Agliardi C, Barizzone N, Mascia E, Bernardinelli L, Comi G, Cusi D, Esposito F, Ferrè L, Comi C, Galimberti D, Leone M, Sorosina M, Mescheriakova J, Hintzen R, van Duijn C, Theunissen C, Bos S, Myhr K, Celius E, Lie B, Spurkland A, Comabella M, Montalban X, Alfredsson L, Stridh P, Hillert J, Jagodic M, Piehl F, Jelčić I, Martin R, Sospedra M, Ban M, Hawkins C, Hysi P, Kalra S, Karpe F, Khadake J, Lachance G, Neville M, Santaniello A, Caillier S, Calabresi P, Cree B, Cross A, Davis M, Haines J, de Bakker P, Delgado S, Dembele M, Edwards K, Fitzgerald K, Hakonarson H, Konidari I, Lathi E, Manrique C, Pericak-Vance M, Piccio L, Schaefer C, McCabe C, Weiner H, Goldstein J, Olsson T, Hadjigeorgiou G, Taylor B, Tajouri L, Charlesworth J, Booth D, Harbo H, Ivinson A, Hauser S, Compston A, Stewart G, Zipp F, Barcellos L, Baranzini S, Martinelli-Boneschi F, D’Alfonso S, Ziegler A, Oturai A, McCauley J, Sawcer S, Oksenberg J, De Jager P, Kockum I, Hafler D, Cotsapas C. Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk. Cell 2018, 175: 1679-1687.e7. PMID: 30343897, PMCID: PMC6269166, DOI: 10.1016/j.cell.2018.09.049.Peer-Reviewed Original ResearchConceptsRare coding variationsGenome-wide association studiesNon-coding variationCommon variant signalsSubstantial linkage disequilibriumLow-frequency variantsNovel genesCell homeostasisAssociation studiesComplex neurological diseasesLinkage disequilibriumGenetic variantsCommon variantsHeritabilityRich resourceGenesVariantsKey pathogenic roleIndividual familiesEpistasisAdditive effectBiologyHomeostasisMutationsNeurological diseasesRegulatory T Cells: From Discovery to Autoimmunity
Kitz A, Singer E, Hafler D. Regulatory T Cells: From Discovery to Autoimmunity. Cold Spring Harbor Perspectives In Medicine 2018, 8: a029041. PMID: 29311129, PMCID: PMC6280708, DOI: 10.1101/cshperspect.a029041.Peer-Reviewed Original ResearchConceptsAutoreactive T cellsT cellsMultiple sclerosisEffector-like T cellsInterferon γ secretionEffector T cellsRegulatory T cellsTreg cell functionT-bet expressionCentral nervous systemT cell activationFunctional TregsΓ secretionProinflammatory cytokinesVitamin DAutoimmune diseasesGenetic predispositionNervous systemLoss of functionReduced suppressionConsistent findingCell functionDisease developmentActivationCellsChapter 46 Multiple sclerosis
Cotsapas C, Mitrovic M, Hafler D. Chapter 46 Multiple sclerosis. Handbook Of Clinical Neurology 2018, 148: 723-730. PMID: 29478610, DOI: 10.1016/b978-0-444-64076-5.00046-6.Peer-Reviewed Original ResearchConceptsMultiple sclerosisCentral nervous system white matterNervous system white matterAutoimmune neurologic disordersDisease-modifying therapiesImmune function modulationSpecific immune subsetsCentral nervous systemGenetic variantsImmune subsetsNeurologic symptomsAutoimmune attackLeading causeNeurologic disordersNervous systemWhite matterCommon genetic variantsOverall riskSclerosisYoung adultsEnvironmental exposuresRiskSymptomsDiseasePatients
2016
NR1H3 p.Arg415Gln Is Not Associated to Multiple Sclerosis Risk
Consortium T, Antel J, Ban M, Baranzini S, Barcellos L, Barizzone N, Beecham A, Berge T, Bernardinelli L, Booth D, Bos S, Buck D, Butkiewicz M, Celius E, Comabella M, Compston A, Dedham K, Cotsapas C, Alfonso S, De Jager P, Dubois B, Duquette P, Fontaine B, Gasperi C, Gil E, Goris A, Gourraud P, Graetz C, Gyllenberg A, Hadjigeorgiou G, Hafler D, Hribko D, Haines J, Harbo H, Hauser S, Warto S, Hawkins C, Hemmer B, Henry R, Hintzen R, Horakova D, Ivinson A, Howard M, Jelcic I, Kaskow B, Kira J, Kleinova P, Kockum I, Kucerova K, Lill C, Luessi F, Malhotra S, Martin R, Martinelli F, Matsushita T, McCabe C, McCauley J, Mescheriakkova J, Mitrovic M, Moen S, Montalban X, Muhlau M, Nakmura Y, Oksenberg J, Olsson T, Oturai A, Palotie A, Patsopoulos N, Pavlicova J, Pericak-Vance P, Piehl F, Rebeix I, Rioux J, Saarela J, Sawcer S, Sellebjerg F, Sondergaard H, Sorensen P, Sospedra M, Spurkland A, Stewart G, Taylor B, Uitterlinden A, Van Duijn C, Zipp F. NR1H3 p.Arg415Gln Is Not Associated to Multiple Sclerosis Risk. Neuron 2016, 92: 333-335. PMID: 27764667, PMCID: PMC5641967, DOI: 10.1016/j.neuron.2016.09.052.Peer-Reviewed Original ResearchConceptsPrimary progressive diseaseMultiple sclerosis riskProgressive diseaseMultiple sclerosisPatient's likelihoodDisease subtypesPatient collectionInsufficient sample sizeCommon variant associationsLow-frequency associationMendelian formsAssociationRecent studiesCertain individualsSample sizeVariant associationsSclerosisSubtypesDiseaseNeurons