2024
Genetic mapping across autoimmune diseases reveals shared associations and mechanisms
Lincoln M, Connally N, Axisa P, Gasperi C, Mitrovic M, van Heel D, Wijmenga C, Withoff S, Jonkers I, Padyukov L, Rich S, Graham R, Gaffney P, Langefeld C, Vyse T, Hafler D, Chun S, Sunyaev S, Cotsapas C. Genetic mapping across autoimmune diseases reveals shared associations and mechanisms. Nature Genetics 2024, 56: 838-845. PMID: 38741015, DOI: 10.1038/s41588-024-01732-8.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAutoimmune DiseasesCase-Control StudiesChromosome MappingGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultifactorial InheritancePolymorphism, Single NucleotideQuantitative Trait LociConceptsGenetic mapResolution of genetic mappingExpression quantitative trait lociFine-mapping resolutionQuantitative trait lociGenomic lociTrait lociPolygenic disorderAllelesRisk allelesLociPathogenic mechanismsImmune systemAutoimmune mechanismsAutoimmune diseasesInflammatory diseasesTraitsMechanismDiseaseSample collectionExpression
2023
Common genetic factors among autoimmune diseases
Harroud A, Hafler D. Common genetic factors among autoimmune diseases. Science 2023, 380: 485-490. PMID: 37141355, DOI: 10.1126/science.adg2992.Peer-Reviewed Original ResearchMeSH KeywordsAutoimmune DiseasesGenetic Predisposition to DiseaseGenomeGenome-Wide Association StudyHumansRisk FactorsConceptsGenome-wide association studiesMultimodal genomic dataEvolutionary originDisease geneticsPolygenic basisPrecise geneSelection pressureGenomic dataMolecular consequencesAssociation studiesGenetic studiesFunctional experimentsGenetic effectsRisk variantsCommon genetic factorsAncient populationsCurrent understandingPotential therapeutic implicationsGenetic factorsKey immune cellsGenesGeneticsWidespread sharingImmune cellsValuable insights
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 Research
2019
Latent autoimmunity across disease-specific boundaries in at-risk first-degree relatives of SLE and RA patients
James JA, Chen H, Young KA, Bemis EA, Seifert J, Bourn RL, Deane KD, Demoruelle MK, Feser M, O'Dell JR, Weisman MH, Keating RM, Gaffney PM, Kelly JA, Langefeld CD, Harley JB, Robinson W, Hafler DA, O'Connor KC, Buckner J, Guthridge JM, Norris JM, Holers VM. Latent autoimmunity across disease-specific boundaries in at-risk first-degree relatives of SLE and RA patients. EBioMedicine 2019, 42: 76-85. PMID: 30952617, PMCID: PMC6491794, DOI: 10.1016/j.ebiom.2019.03.063.Peer-Reviewed Original ResearchConceptsSystemic lupus erythematosusFirst-degree relativesGenetic risk scoreRA patientsRheumatoid arthritisSLE patientsT1D patientsAutoantibody-positive systemic lupus erythematosusRisk first-degree relativesOrgan-specific autoimmune diseasesType 1 diabetes patientsAutoimmune disease preventionAnti-tissue transglutaminaseDisease-associated autoantibodiesDisease prevention studiesUnaffected first-degree relativesCross-sectional studyLatent autoimmunityLupus erythematosusAutoimmune diseasesDiabetes patientsPrevention StudyRisk scoreAutoimmunityPreclinical period
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 ResearchMeSH KeywordsAstrocytesCells, CulturedCentral Nervous SystemGenetic Predisposition to DiseaseHumansMultiple SclerosisNF-kappa B p50 SubunitPolymorphism, Single NucleotideRisk FactorsTranscription Factor RelAConceptsMultiple 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 ResearchMeSH KeywordsEpistasis, GeneticFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLinkage DisequilibriumMaleMultiple SclerosisMutationOpen Reading FramesRisk FactorsConceptsRare 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 diseases
2016
Multiple 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 ResearchMeSH KeywordsBiomarkersDisease ProgressionGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansImmunologic FactorsMultiple SclerosisConceptsMultiple 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 functionProgressionThe Link Between CD6 and Autoimmunity: Genetic and Cellular Associations.
Kofler DM, Farkas A, von Bergwelt-Baildon M, Hafler DA. The Link Between CD6 and Autoimmunity: Genetic and Cellular Associations. Current Drug Targets 2016, 17: 651-65. PMID: 26844569, DOI: 10.2174/1389450117666160201105934.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntigens, CDAntigens, Differentiation, T-LymphocyteArthritis, RheumatoidAutoimmunityCD4-Positive T-LymphocytesCell Adhesion Molecules, NeuronalClinical Trials as TopicDisease Models, AnimalFetal ProteinsGenetic Predisposition to DiseaseHumansMultiple SclerosisPolymorphism, Single NucleotideConceptsMultiple sclerosisRheumatoid arthritisCentral nervous systemNervous systemSingle nucleotide polymorphismsDevelopment of MSTreatment of RARole of CD6T cell traffickingT cell functionGenetic risk factorsEndothelial cell barrierCD6 geneClinical responseGenetic associationClinical featuresAutoimmune diseasesSynovial cellsRisk factorsTumor necrosisSynovial fibroblastsPossible common mechanismT cellsT lymphocytesLeukocyte trafficking
2015
Genetic variants associated with autoimmunity drive NFκB signaling and responses to inflammatory stimuli
Housley WJ, Fernandez SD, Vera K, Murikinati SR, Grutzendler J, Cuerdon N, Glick L, De Jager PL, Mitrovic M, Cotsapas C, Hafler DA. Genetic variants associated with autoimmunity drive NFκB signaling and responses to inflammatory stimuli. Science Translational Medicine 2015, 7: 291ra93. PMID: 26062845, PMCID: PMC4574294, DOI: 10.1126/scitranslmed.aaa9223.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAllelesAutoimmunityCase-Control StudiesCD4-Positive T-LymphocytesCell NucleusCytokinesFemaleGenetic Predisposition to DiseaseHumansInflammationMaleMiddle AgedMultiple SclerosisNF-kappa BPolymorphism, Single NucleotideProtein TransportReceptors, Tumor Necrosis Factor, Type IRisk FactorsSex CharacteristicsSignal TransductionTime FactorsTumor Necrosis Factor-alphaConceptsB-cell leukemia 3Multiple sclerosisNegative regulatorInflammatory stimuliGenetic variantsWide association studyDisease susceptibility variantsNaïve CD4 T cellsRapid genetic screeningCD4 T cellsActivation of p65Transcription factor nuclear factor κBExpression of NFκBNuclear factor κBApoptosis 1Cellular inhibitorGG risk genotypeDegradation of inhibitorCentral regulatorAssociation studiesCytokine blockadeUlcerative colitisAutoimmune diseasesTumor necrosisSusceptibility variants
2014
Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes
Raj T, Rothamel K, Mostafavi S, Ye C, Lee MN, Replogle JM, Feng T, Lee M, Asinovski N, Frohlich I, Imboywa S, Von Korff A, Okada Y, Patsopoulos NA, Davis S, McCabe C, Paik HI, Srivastava GP, Raychaudhuri S, Hafler DA, Koller D, Regev A, Hacohen N, Mathis D, Benoist C, Stranger BE, De Jager PL. Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes. Science 2014, 344: 519-523. PMID: 24786080, PMCID: PMC4910825, DOI: 10.1126/science.1249547.Peer-Reviewed Original ResearchMeSH KeywordsAdaptive ImmunityAllelesAlzheimer DiseaseAutoimmune DiseasesAutoimmunityCD4-Positive T-LymphocytesEthnicityGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansImmunity, InnateMonocytesMultiple SclerosisNeurodegenerative DiseasesParkinson DiseasePolymorphism, Single NucleotideQuantitative Trait LociRheumatic FeverTranscriptomeConceptsSpecific immune cell typesHuman immune functionImmune cell typesMulti-ethnic cohortCell-autonomous effectsAutoimmune diseasesT cellsImmune functionParkinson's diseaseHealthy individualsInnate immunityRisk allelesDiseaseExpression quantitative trait loci (eQTL) studiesQuantitative trait loci studiesSusceptibility allelesPutative functional assignmentsCausal regulatory variantsDisease-associated lociDisease susceptibility variantsCell typesSusceptibility variantsTrans-eQTLsFunctional assignmentRegulatory variants
2013
Fine-Mapping the Genetic Association of the Major Histocompatibility Complex in Multiple Sclerosis: HLA and Non-HLA Effects
Patsopoulos NA, Barcellos LF, Hintzen RQ, Schaefer C, van Duijn CM, Noble JA, Raj T, , , Gourraud PA, Stranger BE, Oksenberg J, Olsson T, Taylor BV, Sawcer S, Hafler DA, Carrington M, De Jager PL, de Bakker PI. Fine-Mapping the Genetic Association of the Major Histocompatibility Complex in Multiple Sclerosis: HLA and Non-HLA Effects. PLOS Genetics 2013, 9: e1003926. PMID: 24278027, PMCID: PMC3836799, DOI: 10.1371/journal.pgen.1003926.Peer-Reviewed Original ResearchMeSH KeywordsAllelesChromosome MappingGenetic Predisposition to DiseaseGenome-Wide Association StudyHaplotypesHistocompatibility Antigens Class IHLA-DP beta-ChainsHLA-DRB1 ChainsHumansIntracellular Signaling Peptides and ProteinsLinkage DisequilibriumMajor Histocompatibility ComplexMembrane ProteinsMultiple SclerosisPolymorphism, Single NucleotideReceptors, Tumor Necrosis Factor, Type IConceptsHuman leukocyte antigenNon-HLA risk allelesRisk allelesClassical human leukocyte antigenClass IMultiple sclerosis susceptibilityHLA class IIndependent effectsMS susceptibility geneMajor histocompatibility complexMajor histocompatibility complex regionHLA effectMultiple sclerosisLeukocyte antigenHLA-DRB1MS susceptibilityMultiple risk allelesDPB1 allelesClass IIPeptide-binding grooveHistocompatibility complexPolymorphic amino acid positionsTNF geneClassical allelesSusceptibility genesClinical relevance and functional consequences of the TNFRSF1A multiple sclerosis locus
Ottoboni L, Frohlich IY, Lee M, Healy BC, Keenan BT, Xia Z, Chitnis T, Guttmann CR, Khoury SJ, Weiner HL, Hafler DA, De Jager PL. Clinical relevance and functional consequences of the TNFRSF1A multiple sclerosis locus. Neurology 2013, 81: 1891-1899. PMID: 24174586, PMCID: PMC3843384, DOI: 10.1212/01.wnl.0000436612.66328.8a.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsArginineChemokine CXCL10FemaleGene Expression RegulationGenetic Predisposition to DiseaseGenotypeGlutamineHEK293 CellsHumansImmunologic FactorsLongitudinal StudiesMaleMonocytesMultiple SclerosisMutationPhorbol EstersReceptors, Tumor Necrosis Factor, Type IRNA IsoformsSignal TransductionTumor Necrosis Factor-alphaConceptsTNFRSF1A locusSusceptibility allelesFunctional consequencesRobust transcriptional responseTranscriptional responseCytoplasmic domainRNA isoformsTNF-α stimulationRho GTPaseMS susceptibility genesMS geneG proteinsSusceptibility genesMolecular levelTNF pathwayGenesAltered expressionLociTNF-α pathwayAllelesRisk allelesPathwayGTPaseImmune functionTransmembraneNetwork-Based Multiple Sclerosis Pathway Analysis with GWAS Data from 15,000 Cases and 30,000 Controls
Consortium I, Baranzini S, Khankhanian P, Patsopoulos N, Li M, Stankovich J, Cotsapas C, Søndergaard H, Ban M, Barizzone N, Bergamaschi L, Booth D, Buck D, Cavalla P, Celius E, Comabella M, Comi G, Compston A, Cournu-Rebeix I, D’alfonso S, Damotte V, Din L, Dubois B, Elovaara I, Esposito F, Fontaine B, Franke A, Goris A, Gourraud P, Graetz C, Guerini F, Guillot-Noel L, Hafler D, Hakonarson H, Hall P, Hamsten A, Harbo H, Hemmer B, Hillert J, Kemppinen A, Kockum I, Koivisto K, Larsson M, Lathrop M, Leone M, Lill C, Macciardi F, Martin R, Martinelli V, Martinelli-Boneschi F, McCauley J, Myhr K, Naldi P, Olsson T, Oturai A, Pericak-Vance M, Perla F, Reunanen M, Saarela J, Saker-Delye S, Salvetti M, Sellebjerg F, Sørensen P, Spurkland A, Stewart G, Taylor B, Tienari P, Winkelmann J, Consortium W, Zipp F, Ivinson A, Haines J, Sawcer S, DeJager P, Hauser S, Oksenberg J. Network-Based Multiple Sclerosis Pathway Analysis with GWAS Data from 15,000 Cases and 30,000 Controls. American Journal Of Human Genetics 2013, 92: 854-865. PMID: 23731539, PMCID: PMC3958952, DOI: 10.1016/j.ajhg.2013.04.019.Peer-Reviewed Original ResearchConceptsPathway analysisNetwork-based pathway analysisGenome-wide association studiesSubnetworks of genesExtended linkage disequilibriumNon-HLA susceptibility lociHigh-confidence candidatesSubsequent genetic studiesComplex traitsSubstantial genetic componentSignificant lociGWAS dataAssociation studiesGene levelGenetic studiesNominal statistical evidenceSusceptibility lociGenesLinkage disequilibriumSusceptibility variantsGenetic componentRelated pathwaysLociHuman leukocyte antigen (HLA) regionPowerful approach
2012
Immune-mediated disease genetics: the shared basis of pathogenesis
Cotsapas C, Hafler DA. Immune-mediated disease genetics: the shared basis of pathogenesis. Trends In Immunology 2012, 34: 22-26. PMID: 23031829, DOI: 10.1016/j.it.2012.09.001.Peer-Reviewed Original ResearchMeSH KeywordsGenetic Predisposition to DiseaseGenetic TestingGenome-Wide Association StudyHumansImmune SystemRisk FactorsConceptsRecent genetic studiesGenomic lociDisease geneticsMolecular basisGenetic studiesMolecular causesMolecular defectsRisk variantsSpecific pathwaysBasis of pathogenesisActionable discoveriesGeneticsInflammatory diseasesOverall symptomatologyDisease heterogeneityLociVariantsDiseasePathwayPathogenesisHigh rateRational approachDiscoveryPathobiologyPerspective: Deconstructing a disease
Hafler DA. Perspective: Deconstructing a disease. Nature 2012, 484: s6-s6. PMID: 22509507, DOI: 10.1038/nature11100.Peer-Reviewed Original ResearchMultiple sclerosis
Nylander A, Hafler DA. Multiple sclerosis. Journal Of Clinical Investigation 2012, 122: 1180-1188. PMID: 22466660, PMCID: PMC3314452, DOI: 10.1172/jci58649.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAutoantigensAutoimmune DiseasesB-Lymphocyte SubsetsCostimulatory and Inhibitory T-Cell ReceptorsCytokinesForecastingForkhead Transcription FactorsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLymphocyte ActivationMeningesModels, ImmunologicalMultiple SclerosisT-Lymphocyte SubsetsT-Lymphocytes, RegulatoryConceptsMultiple sclerosisImmunopathology of MSMultifocal demyelinating diseasePersistence of antigenMS prognosisDemyelinating diseaseOligoclonal expansionAutoimmune responseLymphoid folliclesHumoral responseT cellsTreatment decisionsInfectious agentsSusceptible individualsProgressive neurodegenerationCommon genetic variantsPathway disruptionPresent recent dataSclerosisRecent dataDisease susceptibilityAntigenGenetic variantsImmunopathologyPrognosis
2011
Genome‐wide meta‐analysis identifies novel multiple sclerosis susceptibility loci
Patsopoulos NA, Esposito F, Reischl J, Lehr S, Bauer D, Heubach J, Sandbrink R, Pohl C, Edan G, Kappos L, Miller D, Montalbán J, Polman C, Freedman M, Hartung H, Arnason B, Comi G, Cook S, Filippi M, Goodin D, Jeffery D, O'Connor P, Ebers G, Langdon D, Reder A, Traboulsee A, Zipp F, Schimrigk S, Hillert J, Bahlo M, Booth D, Broadley S, Brown M, Browning B, Browning S, Butzkueven H, Carroll W, Chapman C, Foote S, Griffiths L, Kermode A, Kilpatrick T, Lechner-Scott J, Marriott M, Mason D, Moscato P, Heard R, Pender M, Perreau V, Perera D, Rubio J, Scott R, Slee M, Stankovich J, Stewart G, Taylor B, Tubridy N, Willoughby E, Wiley J, Matthews P, Boneschi F, Compston A, Haines J, Hauser S, McCauley J, Ivinson A, Oksenberg J, Pericak-Vance M, Sawcer S, De Jager P, Hafler D, de Bakker P. Genome‐wide meta‐analysis identifies novel multiple sclerosis susceptibility loci. Annals Of Neurology 2011, 70: 897-912. PMID: 22190364, PMCID: PMC3247076, DOI: 10.1002/ana.22609.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSingle nucleotide polymorphismsSusceptibility lociHapMap Phase IIUnique single nucleotide polymorphismsGene discovery effortsNew susceptibility lociStrongest cis effectsMS genome-wide association studiesQuantitative trait analysisFlanking genesGenetic architectureRNA expression dataMultiple sclerosis susceptibility lociIntergenic regionSecond intronNew lociNovel susceptibility allelesAdditional lociTrait analysisAssociation studiesExpression dataChromosome 2p21LociFunctional consequencesGenome-Wide Assessment for Genetic Variants Associated with Ventricular Dysfunction after Primary Coronary Artery Bypass Graft Surgery
Fox AA, Pretorius M, Liu KY, Collard CD, Perry TE, Shernan SK, De Jager PL, Hafler DA, Herman DS, DePalma SR, Roden DM, Muehlschlegel JD, Donahue BS, Darbar D, Seidman JG, Body SC, Seidman CE. Genome-Wide Assessment for Genetic Variants Associated with Ventricular Dysfunction after Primary Coronary Artery Bypass Graft Surgery. PLOS ONE 2011, 6: e24593. PMID: 21980348, PMCID: PMC3184087, DOI: 10.1371/journal.pone.0024593.Peer-Reviewed Original ResearchConceptsCABG surgeryPostoperative ventricular dysfunctionVentricular dysfunctionSingle nucleotide polymorphismsPrimary coronary artery bypass graft surgeryCoronary artery bypass graft surgeryArtery bypass graft surgeryPrimary CABG surgeryBypass graft surgeryClinical risk factorsMechanical ventricular supportPatient risk stratificationGenetic variantsCABG cohortGraft surgeryPostoperative morbiditySurgical patientsCardiopulmonary bypassRisk stratificationVentricular supportRisk factorsLarge cohortPrevention strategiesSurgeryMale subjectsThe CD6 Multiple Sclerosis Susceptibility Allele Is Associated with Alterations in CD4+ T Cell Proliferation
Kofler DM, Severson CA, Mousissian N, De Jager PL, Hafler DA. The CD6 Multiple Sclerosis Susceptibility Allele Is Associated with Alterations in CD4+ T Cell Proliferation. The Journal Of Immunology 2011, 187: 3286-3291. PMID: 21849685, DOI: 10.4049/jimmunol.1100626.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAntigens, CDAntigens, Differentiation, T-LymphocyteCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCell ProliferationCell SeparationCells, CulturedFemaleFlow CytometryGenetic Predisposition to DiseaseGenotypeHumansMaleMultiple SclerosisPhenotypeReverse Transcriptase Polymerase Chain ReactionRisk FactorsRNA, Small InterferingConceptsGenome-wide association studiesAssociation studiesAllelic variantsNew susceptibility lociSusceptibility allelesRisk allelesProliferation defectExon 5Risk-associated allelesSingle nucleotide polymorphismsExtracellular binding sitesCD6 geneSusceptibility lociLinkage disequilibriumMS risk alleleSelective knockdownT cell activationNucleotide polymorphismsAltered proliferationCell proliferationGenetic associationAllelesLong-term activationBinding sitesMS susceptibility allelesInterrogating the complex role of chromosome 16p13.13 in multiple sclerosis susceptibility: independent genetic signals in the CIITA–CLEC16A–SOCS1 gene complex
Zuvich RL, Bush WS, McCauley JL, Beecham AH, De Jager PL, Consortium T, Ivinson A, Compston A, Hafler D, Hauser S, Sawcer S, Pericak-Vance M, Barcellos L, Mortlock D, Haines J. Interrogating the complex role of chromosome 16p13.13 in multiple sclerosis susceptibility: independent genetic signals in the CIITA–CLEC16A–SOCS1 gene complex. Human Molecular Genetics 2011, 20: 3517-3524. PMID: 21653641, PMCID: PMC3153306, DOI: 10.1093/hmg/ddr250.Peer-Reviewed Original ResearchMeSH KeywordsCCCTC-Binding FactorChromosomes, Human, Pair 16FemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansLectins, C-TypeLinkage DisequilibriumLogistic ModelsMaleMonosaccharide Transport ProteinsMultiple SclerosisQuantitative Trait LociRepressor ProteinsSuppressor of Cytokine Signaling 1 ProteinSuppressor of Cytokine Signaling ProteinsConceptsIndependent genetic signalsGenetic signalsLymphoblastoid cell linesChromosome 16p13Cis expression QTLsOpen chromatin configurationCell linesLinkage disequilibrium patternsExpression array dataH3K27 methylationHistone modificationsGenomic regionsKb stretchStrong genetic componentSingle nucleotide polymorphismsChromatin configurationExpression correlationGene complexDisequilibrium patternsDisease locusGenesCorrelated expressionGenetic componentFunctional mechanismsLoci