2019
Multiple 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 variants
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
2013
Network-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
2011
Pervasive 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 polymorphismsA knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility
Bush WS, McCauley JL, DeJager PL, Dudek SM, Hafler DA, Gibson RA, Matthews PM, Kappos L, Naegelin Y, Polman CH, Hauser SL, Oksenberg J, Haines JL, Ritchie MD. A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility. Genes & Immunity 2011, 12: 335-340. PMID: 21346779, PMCID: PMC3136581, DOI: 10.1038/gene.2011.3.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGene-gene interactionsCytoskeleton regulatory proteinsCytoskeletal regulationGenetic architectureGene clusterInteraction analysisSingle-locus analysisGWAS dataRegulatory proteinsBiological contextRelated genesAssociation studiesSusceptibility lociWeak main effectsPhospholipase CGenetic effectsΒ isoformsComplex diseasesBiological mechanismsNeurodegenerative mechanismsNew genetic effectsEpistasisACTN1Genes