2016
Solving Immunology?
Vodovotz Y, Xia A, Read EL, Bassaganya-Riera J, Hafler DA, Sontag E, Wang J, Tsang JS, Day JD, Kleinstein SH, Butte AJ, Altman MC, Hammond R, Sealfon SC. Solving Immunology? Trends In Immunology 2016, 38: 116-127. PMID: 27986392, PMCID: PMC5695553, DOI: 10.1016/j.it.2016.11.006.Peer-Reviewed Original ResearchMultiple 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 functionProgression
2015
Integrative analysis of 111 reference human epigenomes
Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller M, Amin V, Whitaker J, Schultz M, Ward L, Sarkar A, Quon G, Sandstrom R, Eaton M, Wu Y, Pfenning A, Wang X, ClaussnitzerYaping Liu M, Coarfa C, Alan Harris R, Shoresh N, Epstein C, Gjoneska E, Leung D, Xie W, David Hawkins R, Lister R, Hong C, Gascard P, Mungall A, Moore R, Chuah E, Tam A, Canfield T, Scott Hansen R, Kaul R, Sabo P, Bansal M, Carles A, Dixon J, Farh K, Feizi S, Karlic R, Kim A, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer T, Neph S, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari R, Siebenthall K, Sinnott-Armstrong N, Stevens M, Thurman R, Wu J, Zhang B, Zhou X, Abdennur N, Adli M, Akerman M, Barrera L, Antosiewicz-Bourget J, Ballinger T, Barnes M, Bates D, Bell R, Bennett D, Bianco K, Bock C, Boyle P, Brinchmann J, Caballero-Campo P, Camahort R, Carrasco-Alfonso M, Charnecki T, Chen H, Chen Z, Cheng J, Cho S, Chu A, Chung W, Cowan C, Athena Deng Q, Deshpande V, Diegel M, Ding B, Durham T, Echipare L, Edsall L, Flowers D, Genbacev-Krtolica O, Gifford C, Gillespie S, Giste E, Glass I, Gnirke A, Gormley M, Gu H, Gu J, Hafler D, Hangauer M, Hariharan M, Hatan M, Haugen E, He Y, Heimfeld S, Herlofsen S, Hou Z, Humbert R, Issner R, Jackson A, Jia H, Jiang P, Johnson A, Kadlecek T, Kamoh B, Kapidzic M, Kent J, Kim A, Kleinewietfeld M, Klugman S, Krishnan J, Kuan S, Kutyavin T, Lee A, Lee K, Li J, Li N, Li Y, Ligon K, Lin S, Lin Y, Liu J, Liu Y, Luckey C, Ma Y, Maire C, Marson A, Mattick J, Mayo M, McMaster M, Metsky H, Mikkelsen T, Miller D, Miri M, Mukame E, Nagarajan R, Neri F, Nery J, Nguyen T, O’Geen H, Paithankar S, Papayannopoulou T, Pelizzola M, Plettner P, Propson N, Raghuraman S, Raney B, Raubitschek A, Reynolds A, Richards H, Riehle K, Rinaudo P, Robinson J, Rockweiler N, Rosen E, Rynes E, Schein J, Sears R, Sejnowski T, Shafer A, Shen L, Shoemaker R, Sigaroudinia M, Slukvin I, Stehling-Sun S, Stewart R, Subramanian S, Suknuntha K, Swanson S, Tian S, Tilden H, Tsai L, Urich M, Vaughn I, Vierstra J, Vong S, Wagner U, Wang H, Wang T, Wang Y, Weiss A, Whitton H, Wildberg A, Witt H, Won K, Xie M, Xing X, Xu I, Xuan Z, Ye Z, Yen C, Yu P, Zhang X, Zhang X, Zhao J, Zhou Y, Zhu J, Zhu Y, Ziegler S, Beaudet A, Boyer L, De Jager P, Farnham P, Fisher S, Haussler D, Jones S, Li W, Marra M, McManus M, Sunyaev S, Thomson J, Tlsty T, Tsai L, Wang W, Waterland R, Zhang M, Chadwick L, Bernstein B, Costello J, Ecker J, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos J, Wang T, Kellis M. Integrative analysis of 111 reference human epigenomes. Nature 2015, 518: 317-330. PMID: 25693563, PMCID: PMC4530010, DOI: 10.1038/nature14248.Peer-Reviewed Original ResearchConceptsHuman epigenomeHuman diseasesIntegrative analysisReference human genome sequenceDiverse human traitsRoadmap Epigenomics ConsortiumHuman genome sequenceHistone modification patternsRelevant cell typesEpigenomic informationEpigenomic marksDNA accessibilityRegulatory modulesGene regulationEpigenomic studiesGenome sequenceDNA methylationGenetic variationRegulatory elementsCellular differentiationMolecular basisModification patternsEpigenomeHuman traitsCell types
2014
Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells
Lee MN, Ye C, Villani AC, Raj T, Li W, Eisenhaure TM, Imboywa SH, Chipendo PI, Ran FA, Slowikowski K, Ward LD, Raddassi K, McCabe C, Lee MH, Frohlich IY, Hafler DA, Kellis M, Raychaudhuri S, Zhang F, Stranger BE, Benoist CO, De Jager PL, Regev A, Hacohen N. Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells. Science 2014, 343: 1246980. PMID: 24604203, PMCID: PMC4124741, DOI: 10.1126/science.1246980.Peer-Reviewed Original ResearchMeSH KeywordsAdultAutoimmune DiseasesCommunicable DiseasesDendritic CellsEscherichia coliFemaleGene-Environment InteractionGenetic LociGenome-Wide Association StudyHEK293 CellsHost-Pathogen InteractionsHumansInfluenza A virusInterferon Regulatory Factor-7Interferon-betaLipopolysaccharidesMaleMiddle AgedPolymorphism, Single NucleotideQuantitative Trait LociSTAT Transcription FactorsTranscriptomeYoung AdultConceptsGenetic variationPathogen-responsive genesHuman genetic variationGenetic variantsIRF transcription factorsCommon genetic variantsType I IFN inductionFunctional annotationExpression responsesTranscription factorsI IFN inductionCausal variantsPathogen sensingEnvironmental stimuliComplex diseasesCommon variantsCommon allelesIFN inductionComputational approachVariantsCellsInductionGenesInterindividual variationSTAT
2010
Genetic variation in the IL7RA/IL7 pathway increases multiple sclerosis susceptibility
Zuvich RL, McCauley JL, Oksenberg JR, Sawcer SJ, De Jager PL, International Multiple Sclerosis Genetics Consortium, Aubin C, Cross AH, Piccio L, Aggarwal NT, Evans D, Hafler DA, Compston A, Hauser SL, Pericak-Vance MA, Haines JL. Genetic variation in the IL7RA/IL7 pathway increases multiple sclerosis susceptibility. Human Genetics 2010, 127: 525-535. PMID: 20112030, PMCID: PMC2854871, DOI: 10.1007/s00439-010-0789-4.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsGene regionCase-control data setsPutative functional relationshipsNovel gene regionsIndependent case-control data setDense SNP mapReceptor alpha-chain geneIllumina Infinium BeadChipExperiment-wise significanceNovel associationsAlpha chain geneGenetic architectureComplex traitsStrong genetic componentGenetic variationSNP mapInfinium BeadChipAffordable genotypingBiological pathwaysGenesGenetic componentChain geneTYK2 geneNumerous family studiesChapter 3 Uncovering the Genetic Architecture of Multiple Sclerosis
De Jager P, Hafler D. Chapter 3 Uncovering the Genetic Architecture of Multiple Sclerosis. Blue Books Of Neurology 2010, 35: 43-56. DOI: 10.1016/b978-1-4160-6068-0.00003-6.Peer-Reviewed Original ResearchGenetic architectureSusceptibility lociWhole-genome association scansCommon human diseasesMajor histocompatibility complexMultiple sclerosis geneticsCommon genetic variationAssociation scanHuman genomeGenetic variationSingle locusHuman diseasesLociFirst glimpseCurrent discoveriesHistocompatibility complexGenotyped subjectsGenetic susceptibilityGenomeRapid progressHuman leukocyte antigenGeneticsHapMapConvergence of resourcesMultiple sclerosis
2003
Genetic analysis of multiple sclerosis
Walsh EC, Guschwan-McMahon S, Daly MJ, Hafler DA, Rioux JD. Genetic analysis of multiple sclerosis. Journal Of Autoimmunity 2003, 21: 111-116. PMID: 12935779, DOI: 10.1016/s0896-8411(03)00094-5.Peer-Reviewed Original ResearchConceptsComplementary genetic approachesComplex diseasesHuman genomeGenetic variationGenetic approachesSuch lociGenetic analysisSignificant genetic contributionGenetic variantsGenetic contributionAdditional statistical powerRecent important advancesGenetic causeModest effectLociMeta-analytical approachCTLA-4 variantsGenomeGenetic riskVariantsImportant advancesStatistical powerFuture studiesMS resultsAdvances