2016
Power estimation for non-standardized multisite studies
Keshavan A, Paul F, Beyer MK, Zhu AH, Papinutto N, Shinohara RT, Stern W, Amann M, Bakshi R, Bischof A, Carriero A, Comabella M, Crane JC, D'Alfonso S, Demaerel P, Dubois B, Filippi M, Fleischer V, Fontaine B, Gaetano L, Goris A, Graetz C, Gröger A, Groppa S, Hafler DA, Harbo HF, Hemmer B, Jordan K, Kappos L, Kirkish G, Llufriu S, Magon S, Martinelli-Boneschi F, McCauley JL, Montalban X, Mühlau M, Pelletier D, Pattany PM, Pericak-Vance M, Cournu-Rebeix I, Rocca MA, Rovira A, Schlaeger R, Saiz A, Sprenger T, Stecco A, Uitdehaag BMJ, Villoslada P, Wattjes MP, Weiner H, Wuerfel J, Zimmer C, Zipp F, Consortium I, Hauser SL, Oksenberg JR, Henry RG. Power estimation for non-standardized multisite studies. NeuroImage 2016, 134: 281-294. PMID: 27039700, PMCID: PMC5656257, DOI: 10.1016/j.neuroimage.2016.03.051.Peer-Reviewed Original Research
2014
Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data
Pyne S, Lee SX, Wang K, Irish J, Tamayo P, Nazaire MD, Duong T, Ng SK, Hafler D, Levy R, Nolan GP, Mesirov J, McLachlan GJ. Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data. PLOS ONE 2014, 9: e100334. PMID: 24983991, PMCID: PMC4077578, DOI: 10.1371/journal.pone.0100334.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsCluster AnalysisComputational BiologyComputer SimulationFlow CytometryHumansSoftwareConceptsMultivariate probability distributionProbability distributionMultivariate responseJCM modelMultiple experimental conditionsJoint modelingJoint clusteringSimultaneous modelingComputational methodsRegistration of populationTypical experimentModelingNew samplesModelJCMFlow cytometric dataMultiparametric cytometrySystem-level variationApplications
2013
Serum autoantibodies to myelin peptides distinguish acute disseminated encephalomyelitis from relapsing– remitting multiple sclerosis
Van Haren K, Tomooka BH, Kidd BA, Banwell B, Bar-Or A, Chitnis T, Tenembaum SN, Pohl D, Rostasy K, Dale RC, O’Connor K, Hafler DA, Steinman L, Robinson WH. Serum autoantibodies to myelin peptides distinguish acute disseminated encephalomyelitis from relapsing– remitting multiple sclerosis. Multiple Sclerosis Journal 2013, 19: 1726-1733. PMID: 23612879, PMCID: PMC4411183, DOI: 10.1177/1352458513485653.Peer-Reviewed Original ResearchConceptsAcute disseminated encephalomyelitisMyelin basic proteinDisseminated encephalomyelitisMyelin peptidesMultiple sclerosisIgM autoantibodiesIsotype-specific secondary antibodiesPediatric acute disseminated encephalomyelitisRelapsing-remitting multiple sclerosisPediatric multiple sclerosisProteolipid proteinMicroarrays softwareBasic proteinMyelin antigensLaboratory featuresPeptide autoantibodiesMS seraSerum autoantibodiesIgG autoantibodiesAutoantibody biomarkersSerum IgGOligodendrocyte-specific proteinAutoantibody reactivityAdult MSAutoantibodies
2012
Fingolimod for Multiple Sclerosis
Pelletier D, Hafler DA. Fingolimod for Multiple Sclerosis. New England Journal Of Medicine 2012, 366: 339-347. PMID: 22276823, DOI: 10.1056/nejmct1101691.Peer-Reviewed Original Research
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