2022
Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: Results from the IMPACC study
Ozonoff A, Schaenman J, Jayavelu ND, Milliren CE, Calfee CS, Cairns CB, Kraft M, Baden LR, Shaw AC, Krammer F, van Bakel H, Esserman DA, Liu S, Sesma AF, Simon V, Hafler DA, Montgomery RR, Kleinstein SH, Levy O, Bime C, Haddad EK, Erle DJ, Pulendran B, Nadeau KC, Davis MM, Hough CL, Messer WB, Higuita NIA, Metcalf JP, Atkinson MA, Brakenridge SC, Corry D, Kheradmand F, Ehrlich LIR, Melamed E, McComsey GA, Sekaly R, Diray-Arce J, Peters B, Augustine AD, Reed EF, Altman MC, Becker PM, Rouphael N, Ozonoff A, Schaenman J, Jayavelu N, Milliren C, Calfee C, Cairns C, Kraft M, Baden L, Shaw A, Krammer F, van Bakel H, Esserman D, Liu S, Sesma A, Simon V, Hafler D, Montgomery R, Kleinstein S, Levy O, Bime C, Haddad E, Erle D, Pulendran B, Nadeau K, Davis M, Hough C, Messer W, Higuita N, Metcalf J, Atkinson M, Brakenridge S, Corry D, Kheradmand F, Ehrlich L, Melamed E, McComsey G, Sekaly R, Diray-Arce J, Peters B, Augustine A, Reed E, McEnaney K, Barton B, Lentucci C, Saluvan M, Chang A, Hoch A, Albert M, Shaheen T, Kho A, Thomas S, Chen J, Murphy M, Cooney M, Presnell S, Fragiadakis G, Patel R, Guan L, Gygi J, Pawar S, Brito A, Khalil Z, Maguire C, Fourati S, Overton J, Vita R, Westendorf K, Salehi-Rad R, Leligdowicz A, Matthay M, Singer J, Kangelaris K, Hendrickson C, Krummel M, Langelier C, Woodruff P, Powell D, Kim J, Simmons B, Goonewardene I, Smith C, Martens M, Mosier J, Kimura H, Sherman A, Walsh S, Issa N, Dela Cruz C, Farhadian S, Iwasaki A, Ko A, Chinthrajah S, Ahuja N, Rogers A, Artandi M, Siegel S, Lu Z, Drevets D, Brown B, Anderson M, Guirgis F, Thyagarajan R, Rousseau J, Wylie D, Busch J, Gandhi S, Triplett T, Yendewa G, Giddings O, Anderson E, Mehta A, Sevransky J, Khor B, Rahman A, Stadlbauer D, Dutta J, Xie H, Kim-Schulze S, Gonzalez-Reiche A, van de Guchte A, Farrugia K, Khan Z, Maecker H, Elashoff D, Brook J, Ramires-Sanchez E, Llamas M, Rivera A, Perdomo C, Ward D, Magyar C, Fulcher J, Abe-Jones Y, Asthana S, Beagle A, Bhide S, Carrillo S, Chak S, Fragiadakis G, Ghale R, Gonzalez A, Jauregui A, Jones N, Lea T, Lee D, Lota R, Milush J, Nguyen V, Pierce L, Prasad P, Rao A, Samad B, Shaw C, Sigman A, Sinha P, Ward A, Willmore A, Zhan J, Rashid S, Rodriguez N, Tang K, Altamirano L, Betancourt L, Curiel C, Sutter N, Paz M, Tietje-Ulrich G, Leroux C, Connors J, Bernui M, Kutzler M, Edwards C, Lee E, Lin E, Croen B, Semenza N, Rogowski B, Melnyk N, Woloszczuk K, Cusimano G, Bell M, Furukawa S, McLin R, Marrero P, Sheidy J, Tegos G, Nagle C, Mege N, Ulring K, Seyfert-Margolis V, Conway M, Francisco D, Molzahn A, Erickson H, Wilson C, Schunk R, Sierra B, Hughes T, Smolen K, Desjardins M, van Haren S, Mitre X, Cauley J, Li X, Tong A, Evans B, Montesano C, Licona J, Krauss J, Chang J, Izaguirre N, Chaudhary O, Coppi A, Fournier J, Mohanty S, Muenker M, Nelson A, Raddassi K, Rainone M, Ruff W, Salahuddin S, Schulz W, Vijayakumar P, Wang H, Wunder E, Young H, Zhao Y, Saksena M, Altman D, Kojic E, Srivastava K, Eaker L, Bermúdez-González M, Beach K, Sominsky L, Azad A, Carreño J, Singh G, Raskin A, Tcheou J, Bielak D, Kawabata H, Mulder L, Kleiner G, Lee A, Do Do E, Fernandes A, Manohar M, Hagan T, Blish C, Din H, Roque J, Yang S, Brunton A, Sullivan P, Strnad M, Lyski Z, Coulter F, Booth J, Sinko L, Moldawer L, Borresen B, Roth-Manning B, Song L, Nelson E, Lewis-Smith M, Smith J, Tipan P, Siles N, Bazzi S, Geltman J, Hurley K, Gabriele G, Sieg S, Vaysman T, Bristow L, Hussaini L, Hellmeister K, Samaha H, Cheng A, Spainhour C, Scherer E, Johnson B, Bechnak A, Ciric C, Hewitt L, Carter E, Mcnair N, Panganiban B, Huerta C, Usher J, Ribeiro S, Altman M, Becker P, Rouphael N. Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: Results from the IMPACC study. EBioMedicine 2022, 83: 104208. PMID: 35952496, PMCID: PMC9359694, DOI: 10.1016/j.ebiom.2022.104208.Peer-Reviewed Original ResearchConceptsRisk factorsRadiographic findingsFemale sexDisease severityHospitalized COVID-19 patientsSARS-CoV-2 antibodiesSARS-CoV-2 PCRLong COVID-19Presence of infiltratesInvasive mechanical ventilationCharacteristics of patientsOnly female sexViral load levelsClinical laboratory valuesCOVID-19 cohortMultivariable logistic regressionCOVID-19 patientsCoronavirus disease 2019PCR cycle thresholdCOVID-19Baseline creatinineBaseline lymphopeniaMedian ageOverall mortalityProlonged hospitalization
2019
CHAPTER 2 Genetics of Multiple Sclerosis
Abulaban A, Hafler D, Longbrake E. CHAPTER 2 Genetics of Multiple Sclerosis. 2019, 33-54. DOI: 10.1039/9781788016070-00033.ChaptersMultiple sclerosisCentral nervous systemImmune cell infiltratesComplex autoimmune diseaseEnvironmental risk factorsExtensive CNS demyelinationMS therapyAxonal damageCell infiltrateCNS demyelinationAutoimmune diseasesRisk factorsGenetic predispositionNervous systemDisease severityDiseaseSclerosisComplex genetic diseasesChapter 2 GeneticsGenetic diseasesDemyelinationInfiltratesAutoimmunityPathogenesisTherapy
2016
The 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
2012
High salt induces pathogenic Th17 cells and exacerbates autoimmune diseases (60.13)
Kleinewietfeld M, Manzel A, Wu C, Titze J, Kuchroo V, Linker R, Muller D, Hafler D. High salt induces pathogenic Th17 cells and exacerbates autoimmune diseases (60.13). The Journal Of Immunology 2012, 188: 60.13-60.13. DOI: 10.4049/jimmunol.188.supp.60.13.Peer-Reviewed Original ResearchPathogenic Th17 cellsExperimental autoimmune encephalomyelitisEnvironmental risk factorsTh17 cellsAutoimmune diseasesRisk factorsMultiple sclerosisHigh-salt dietHelper T cellsGenetic risk factorsExacerbated inductionAutoimmune encephalomyelitisSalt dietSalt intakeCardiovascular diseaseT cellsSun exposureSevere formDiseaseGenetic factorsDietCertain pathogensInduction of murineInductionPivotal role
2011
Genome-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 subjectsPervasive Sharing of Genetic Effects in Autoimmune Disease
Cotsapas C, Voight BF, Rossin E, Lage K, Neale BM, Wallace C, Abecasis GR, Barrett JC, Behrens T, Cho J, De Jager PL, Elder JT, Graham RR, Gregersen P, Klareskog L, Siminovitch KA, van Heel DA, Wijmenga C, Worthington J, Todd JA, Hafler DA, Rich SS, Daly MJ, . Pervasive Sharing of Genetic Effects in Autoimmune Disease. PLOS Genetics 2011, 7: e1002254. PMID: 21852963, PMCID: PMC3154137, DOI: 10.1371/journal.pgen.1002254.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsSystemic lupus erythematosusImmune-mediated diseasesType 1 diabetesGenetic risk factorsMajor histocompatibility locusCommon autoimmuneCommon single nucleotide polymorphismsLupus erythematosusCrohn's diseaseRheumatoid arthritisClinical evidenceMultiple sclerosisAutoimmune diseasesRisk single nucleotide polymorphismsCeliac diseaseInflammatory diseasesRisk factorsMeta-AnalysisDisease riskDiseaseHistocompatibility locusUnderlying mechanismGenetic associationNucleotide polymorphisms
2010
Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals
Briggs FB, Bartlett SE, Goldstein BA, Wang J, McCauley JL, Zuvich RL, De Jager PL, Rioux JD, Ivinson AJ, Compston A, Hafler DA, Hauser SL, Oksenberg JR, Sawcer SJ, Pericak-Vance MA, Haines JL, Consortium I, Barcellos L. Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals. Human Molecular Genetics 2010, 19: 4286-4295. PMID: 20699326, PMCID: PMC2951862, DOI: 10.1093/hmg/ddq328.Peer-Reviewed Original ResearchConceptsMultiple sclerosisMS casesHealthy controlsCRHR1 variantsCorticotrophin-releasing hormone receptor 1Primary genetic risk factorAdrenal (HPA) axis genesHPA axis regulationGenetic risk factorsHormone receptor 1European ancestryMS pathogenesisSystem involvementRisk factorsUnivariate analysisAxis regulationReceptor 1Axis genesStrong associationCRHR1Lines of evidenceSclerosisDiscovery datasetImportant predictorFurther investigation
2009
Integration of genetic risk factors into a clinical algorithm for multiple sclerosis susceptibility: a weighted genetic risk score
De Jager PL, Chibnik LB, Cui J, Reischl J, Lehr S, Simon KC, Aubin C, Bauer D, Heubach JF, Sandbrink R, Tyblova M, Lelkova P, the steering committees of the BENEFIT B, Havrdova E, Pohl C, Horakova D, Ascherio A, Hafler D, Karlson E. Integration of genetic risk factors into a clinical algorithm for multiple sclerosis susceptibility: a weighted genetic risk score. The Lancet Neurology 2009, 8: 1111-1119. PMID: 19879194, PMCID: PMC3099419, DOI: 10.1016/s1474-4422(09)70275-3.Peer-Reviewed Original ResearchConceptsWeighted genetic risk scoreEpstein-Barr virusHealth Study IMultiple sclerosisC-statisticRisk factorsGenetic risk scoreImmune responseRisk scoreNurses' Health Study IDiagnosis of MSNon-genetic risk factorsHigh-risk individualsMultiple sclerosis susceptibilityEnvironmental risk factorsGenetic risk factorsNHS cohortDerivation cohortTherapeutic trialsMS riskProspective studyClinical algorithmImportant clinical applicationsHigher oddsSusceptibility loci
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
2007
Risk Alleles for Multiple Sclerosis Identified by a Genomewide Study
Hafler D, Compston A, Sawcer S, Lander E, Daly M, De Jager P, de Bakker P, Gabriel S, Mirel D, Ivinson A, Pericak-Vance M, Gregory S, Rioux J, McCauley J, Haines J, Barcellos L, Cree B, Oksenberg J, Hauser S. Risk Alleles for Multiple Sclerosis Identified by a Genomewide Study. New England Journal Of Medicine 2007, 357: 851-862. PMID: 17660530, DOI: 10.1056/nejmoa073493.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAllelesFemaleGenetic Predisposition to DiseaseGenome, HumanHLA-DR alpha-ChainsHLA-DR AntigensHumansInterleukin-2 Receptor alpha SubunitInterleukin-7 Receptor alpha SubunitLinkage DisequilibriumMaleMiddle AgedMultiple SclerosisMutationOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideRisk FactorsConceptsMultiple sclerosisReceptor alpha geneSingle nucleotide polymorphismsControl subjectsCase subjectsInterleukin-7 receptor alpha geneHeritable risk factorsAlpha geneRisk factorsFamily triosSclerosisRisk allelesHLA lociHLA-DRA locusTransmission disequilibrium testStringent P valueP-valueEffect sizeSignificant heritable componentInterleukin-2 receptor alpha geneNonsynonymous single nucleotide polymorphismsGenomewide association studiesMultiple single nucleotide polymorphismsSubjectsAssociation