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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
Open accessAbstract
Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.
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“The role of the adaptive arm of the immune system, particularly its CD4+ T cell component has become clearer, with multiple different T cell subsets being implicated.(4)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [4]
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“the role of B cells, dendritic cells and natural killer cells has emerged more clearly, broadening the prior narrative of T cell dysregulation that emerged from earlier studies.(4)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [4]
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“published efforts to systematically interrogate severity have, thus far, only involved modest numbers of cases, and unanimously fall short of identifying any convincingly associated genetic variants5,10,11.”
From Locus for severity implicates CNS resilience in progression of multiple sclerosis (2023) · cites this paper as [5]
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“refinement of the associations in the HLA region showed that just four variants are sufficient to account for the risk previously attributed to extended haplotype alleles spanning hundreds of kilobases (kb) and many tens of genes.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [43]
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“the GWAS enrichment studies all point to risk being mediated by gene regulation in CD4+ T cells43”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [43]
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“Several studies have explored the genetic basis of clinical course, age of onset and severity, although no genome‐wide significant associations have been discovered.36, 37, 43, 74, 75, 76, 77”
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“Although these risk variants have been found to reduce the age at onset5, it is notable that they do not appear to have any impact on disease severity6.”
From Locus for severity implicates CNS resilience in progression of multiple sclerosis (2023) · cites this paper as [5]
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“A further expansion of the IMSGC resulted in a collaborative GWAS of 9772 cases and 17 376 controls, again of European descent, in 2011.43 This study replicated 23 of 26 previously identified associations and identified 29 novel risk loci.”
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“it became evident that these loci are strongly enriched for genes acting in T‐cell activation and proliferation pathways.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [43]
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Citations
Cites
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Compston, A., & Coles, A. J. (2008) · The Lancet · doi:10.1016/s0140-6736(08)61620-7 · Cited by 4,699
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162 · cited 1×
“However, even use of all seven top principal components that captured genome-wide effects in our data resulted in an unacceptably high genomic inflation: for example, the genomic control facto”
Variance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817
Risk Alleles for Multiple Sclerosis Identified by a Genomewide Study
(2007) · New England Journal of Medicine · doi:10.1056/nejmoa073493 · Cited by 1,746
Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants
Wellcome Trust Case Control Consortium, & The Australo-Anglo-American Spondylitis Consortium (TASC) (2007) · Nature Genetics · doi:10.1038/ng.2007.17 · Cited by 1,374
Strange, A., Spencer, C. C. A., Band, G., Bellenguez, C., Freeman, C., Pirinen, M., Rautanen, A., Su, Z., Donnelly, P., Capon, F., et al. (2010) · Nature Genetics · doi:10.1038/ng.694 · Cited by 1,056
International MS Genetics Consortium, De Jager, P. L., Jia, X., Wang, J., de Bakker, P. I. W., Ottoboni, L., Aggarwal, N. T., Piccio, L., Raychaudhuri, S., Tran, D., et al. (2009) · Nature Genetics · doi:10.1038/ng.401 · Cited by 800
The Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) (2009) · Nature Genetics · doi:10.1038/ng.396 · Cited by 550
Genome-wide association analysis of susceptibility and clinical phenotype in multiple sclerosis
Baranzini, S. E., Wang, J., Gibson, R. A., Galwey, N., Naegelin, Y., Barkhof, F., Radue, E.-W., Lindberg, R. L. P., Uitdehaag, B. M. G., Johnson, M. R., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddn388 · Cited by 476
Cited by
Sorted by citations
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.11.029 · Cited by 2,425
Immune attack: the role of inflammation in Alzheimer disease
Heppner, F. L., Ransohoff, R. M., & Becher, B. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3880 · Cited by 2,134
Bjornevik, K., Cortese, M., Healy, B. C., Kuhle, J., Mina, M. J., Leng, Y., Elledge, S. J., Niebuhr, D. W., Scher, A. I., Munger, K. L., et al. (2022) · Science · doi:10.1126/science.abj8222 · Cited by 2,049
Microglia and macrophages in brain homeostasis and disease
Li, Q., & Barres, B. A. (2018) · Nature Reviews Immunology · doi:10.1038/nri.2017.125 · Cited by 1,999
How neuroinflammation contributes to neurodegeneration
Ransohoff, R. M. (2016) · Science · doi:10.1126/science.aag2590 · Cited by 1,967
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Farh, K. K.-H., Marson, A., Zhu, J., Kleinewietfeld, M., Housley, W. J., Beik, S., Shoresh, N., Whitton, H., Ryan, R. J. H., Shishkin, A. A., et al. (2015) · Nature · doi:10.1038/nature13835 · Cited by 1,956
Thompson, A. J., Baranzini, S. E., Geurts, J. J. G., Hemmer, B., & Ciccarelli, O. (2018) · The Lancet · doi:10.1016/s0140-6736(18)30481-1 · Cited by 1,979
New genetic loci link adipose and insulin biology to body fat distribution
The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature · doi:10.1038/nature14132 · Cited by 1,580
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Loh, P.-R., Tucker, G., Bulik-Sullivan, B. K., Vilhjálmsson, B. J., Finucane, H. K., Salem, R. M., Chasman, D. I., Ridker, P. M., Neale, B. M., Berger, B., et al. (2015) · Nature Genetics · doi:10.1038/ng.3190 · Cited by 1,507
Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
International Multiple Sclerosis Genetics Consortium, Patsopoulos, N. A., Baranzini, S. E., Santaniello, A., Shoostari, P., Cotsapas, C., Wong, G., Beecham, A. H., James, T., Replogle, J., et al. (2019) · Science · doi:10.1126/science.aav7188 · Cited by 1,471
“In particular, the role of B cells, dendritic cells, and NK cells has emerged more clearly, broadening the prior narrative of T cell dysregulation that emerged from earlier studies (4).”
Sodium chloride drives autoimmune disease by the induction of pathogenic TH17 cells
Kleinewietfeld, M., Manzel, A., Titze, J., Kvakan, H., Yosef, N., Linker, R. A., Muller, D. N., & Hafler, D. A. (2013) · Nature · doi:10.1038/nature11868 · Cited by 1,394
Self-citationAnalysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
International Multiple Sclerosis Genetics Consortium (IMSGC) (2013) · Nature Genetics · doi:10.1038/ng.2770 · Cited by 1,386
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Vilhjálmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindström, S., Ripke, S., Genovese, G., Loh, P.-R., Bhatia, G., Do, R., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.09.001 · Cited by 1,303
Complex genetic signatures in immune cells underlie autoimmunity and inform therapy
Orrù, V., Steri, M., Sidore, C., Marongiu, M., Serra, V., Olla, S., Sole, G., Lai, S., Dei, M., Mulas, A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0684-4 · Cited by 1,246
Self-citationThe Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., Mead, D., Bouman, H., Riveros-Mckay, F., Kostadima, M. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.042 · Cited by 1,224
Human autoimmune diseases: a comprehensive update
Wang, L., Wang, F., & Gershwin, M. E. (2015) · Journal of Internal Medicine · doi:10.1111/joim.12395 · Cited by 1,274
Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis
Olsson, T. P., Barcellos, L. F., & Alfredsson, L. S. (2016) · Nature Reviews Neurology · doi:10.1038/nrneurol.2016.187 · Cited by 1,263
Pathological mechanisms in progressive multiple sclerosis
Mahad, D., Trapp, B. D., & Lassmann, H. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70256-x · Cited by 1,198
Kelley, D. R., Snoek, J., & Rinn, J. L. (2016) · Genome Research · doi:10.1101/gr.200535.115 · Cited by 1,048
Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.037 · Cited by 1,046
Innate immunity in the central nervous system
Ransohoff, R. M., & Brown, M. A. (2012) · Journal of Clinical Investigation · doi:10.1172/jci58644 · Cited by 1,034
Advantages and pitfalls in the application of mixed-model association methods
Yang, J., Zaitlen, N. A., Goddard, M. E., Visscher, P. M., & Price, A. L. (2014) · Nature Genetics · doi:10.1038/ng.2876 · Cited by 981
Clonally expanded B cells in multiple sclerosis bind EBV EBNA1 and GlialCAM
Lanz, T. V., Brewer, R. C., Ho, P. P., Moon, J.-S., Jude, K. M., Fernandez, D., Fernandes, R. A., Gomez, A. M., Nadj, G.-S., Bartley, C. M., et al. (2022) · Nature · doi:10.1038/s41586-022-04432-7 · Cited by 908
Zheng, J., Erzurumluoglu, A. M., Elsworth, B. L., Kemp, J. P., Howe, L., Haycock, P. C., Hemani, G., Tansey, K., Laurin, C., Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium, et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw613 · Cited by 869
Cortés, A., Hadler, J., Robinson, P. C., Leo, P., Cremin, K., Pryce, K., Harris, J., Bradbury, L. A., Kenna, T., Yang, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2667 · Cited by 872
Miyake, S., Kim, S., Suda, W., Oshima, K., Nakamura, M., Matsuoka, T., Chihara, N., Tomita, A., Sato, W., Kim, S.-W., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0137429 · Cited by 809
Annotation-free quantification of RNA splicing using LeafCutter
Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics · doi:10.1038/s41588-017-0004-9 · Cited by 765
Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression
Fairfax, B. P., Humburg, P., Makino, S., Naranbhai, V., Wong, D., Lau, E., Jostins, L., Plant, K., Andrews, R., McGee, C., et al. (2014) · Science · doi:10.1126/science.1246949 · Cited by 764
Myelin in the Central Nervous System: Structure, Function, and Pathology
Stadelmann, C., Timmler, S., Barrantes‐Freer, A., & Simons, M. (2019) · Physiological Reviews · doi:10.1152/physrev.00031.2018 · Cited by 799
Cytokine networks in neuroinflammation
Becher, B., Spath, S., & Goverman, J. M. (2016) · Nature reviews. Immunology · doi:10.1038/nri.2016.123 · Cited by 707
Pathogenic Mechanisms Associated With Different Clinical Courses of Multiple Sclerosis
Lassmann, H. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2018.03116 · Cited by 711
B cell depletion therapies in autoimmune disease: advances and mechanistic insights
Lee, D. S. W., Rojas, O. L., & Gommerman, J. L. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-00092-2 · Cited by 684
Winkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S. H., Czajkowski, J., Esko, T., Fall, T., Kilpeläinen, T. O., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005378 · Cited by 681
RNA splicing is a primary link between genetic variation and disease
Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science · doi:10.1126/science.aad9417 · Cited by 660
Regenerating CNS myelin — from mechanisms to experimental medicines
Franklin, R. J. M., & ffrench-Constant, C. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.136 · Cited by 647
Imputing Amino Acid Polymorphisms in Human Leukocyte Antigens
Jia, X., Han, B., Önengüt-Gümüşcü, S., Chen, W., CONCANNON, P. J., Rich, S. S., Raychaudhuri, S., & de Bakker, P. I. W. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064683 · Cited by 650
Paternoster, L., Kemp, J. P., Zheng, J., Smith, G. D., Relton, C. L., Evans, D. M., McArdle, W. L., Henderson, A. J., Standl, M., Tiesler, C. M. T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3424 · Cited by 620
Genome-wide genetic data on ~500,000 UK Biobank participantsPreprint
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/166298 · Cited by 622
Lemke, G. (2013) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a009076 · Cited by 598
Role of the innate and adaptive immune responses in the course of multiple sclerosis
Hemmer, B., Kerschensteiner, M., & Korn, T. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70305-9 · Cited by 629
Single-cell genomics unveils critical regulators of Th17 cell pathogenicity
Gaublomme, J. T., Yosef, N., Lee, Y., Gertner, R. S., Yang, L. V., Wu, C., Pandolfi, P. P., Mak, T., Satija, R., Shalek, A. K., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.009 · Cited by 575
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
Zhou, J., Theesfeld, C. L., Yao, K., Chen, K. M., Wong, A. K., & Troyanskaya, O. G. (2018) · Nature Genetics · doi:10.1038/s41588-018-0160-6 · Cited by 559
Common brain disorders are associated with heritable patterns of apparent aging of the brain
Kaufmann, T., van der Meer, D., Doan, N. T., Schwarz, E., Lund, M. J., Agartz, I., Alnæs, D., Barch, D. M., Baur‐Streubel, R., Bertolino, A., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0471-7 · Cited by 575
The fine-scale genetic structure of the British population
Leslie, S., WINNEY, B. J., Hellenthal, G., Davison, D., Boumertit, A., Day, T., Hutnik, K., Røyrvik, E. C., Cunliffe, B. W., Lawson, D. J., et al. (2015) · Nature · doi:10.1038/nature14230 · Cited by 572
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544
for UK Primary Sjögren's Syndrome Registry, Lessard, C. J., Li, H., Adrianto, I., Ice, J. A., Rasmussen, A., Grundahl, K. M., Kelly, J. A., Dozmorov, M. G., Miceli‐Richard, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2792 · Cited by 542
Sex and gender issues in multiple sclerosis
Harbo, H. F., Gold, R., & Tintoré, M. (2013) · Therapeutic Advances in Neurological Disorders · doi:10.1177/1756285613488434 · Cited by 529
The Role of IL-17 and related cytokines in inflammatory autoimmune diseases
Kuwabara, T., Ishikawa, F., Kondo, M., & Kakiuchi, T. (2017) · Mediators of Inflammation · doi:10.1155/2017/3908061 · Cited by 519
The epidemiology of multiple sclerosis
Goodin, D. S. (2016) · Handbook of clinical neurology · doi:10.1016/b978-0-12-802973-2.00011-2 · Cited by 517
TAM Receptor Signaling in Immune Homeostasis
Rothlin, C. V., Silva, E. A. C., Bosurgi, L., & Ghosh, S. (2015) · Annual Review of Immunology · doi:10.1146/annurev-immunol-032414-112103 · Cited by 531
A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis
Mechelli, R., Umeton, R., Policano, C., Annibali, V., Coarelli, G., Ricigliano, V. A. G., Vittori, D., Fornasiero, A., Buscarinu, M. C., Romano, S., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063300 · Cited by 513
Memory B Cells Activate Brain-Homing, Autoreactive CD4+ T Cells in Multiple Sclerosis
Jelčić, I., Nimer, F. A., Wang, J., Lentsch, V., Planas, R., Jelčić, I., Madjovski, A., Ruhrmann, S., Faigle, W., Frauenknecht, K. B. M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.011 · Cited by 532
Miller, D. H., Chard, D., & Ciccarelli, O. (2012) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70274-5 · Cited by 535
TNF and its receptors in the CNS: The essential, the desirable and the deleterious effects
Probert, L. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.06.038 · Cited by 523
Nylander, A., & Hafler, D. A. (2012) · Journal of Clinical Investigation · doi:10.1172/jci58649 · Cited by 495
Self-citationEpstein–Barr virus and multiple sclerosis
Soldan, S. S., & Lieberman, P. M. (2022) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00770-5 · Cited by 536
The TIGIT/CD226 Axis Regulates Human T Cell Function
Lozano, E., Dominguez‐Villar, M., Kuchroo, V. K., & Hafler, D. A. (2012) · The Journal of Immunology · doi:10.4049/jimmunol.1103627 · Cited by 488
Will the real multiple sclerosis please stand up?
Stys, P. K., Zamponi, G. W., van Minnen, J., & Geurts, J. J. G. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3275 · Cited by 475
Human microglial state dynamics in Alzheimer’s disease progression
Sun, N., Victor, M. B., Park, Y. P., Xiong, X., Scannail, A. N., Leary, N., Prosper, S., Viswanathan, S., Luna, X., Boix, C. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.037 · Cited by 462
Role of “Western Diet” in Inflammatory Autoimmune Diseases
Manzel, A., Müller, D. N., Hafler, D. A., Erdman, S. E., Linker, R. A., & Kleinewietfeld, M. (2013) · Current Allergy and Asthma Reports · doi:10.1007/s11882-013-0404-6 · Cited by 477
Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study
Mokry, L. E., Ross, S., Ahmad, O. S., Forgetta, V., Smith, G. D., Leong, A., Greenwood, C. M. T., Thanassoulis, G., & Richards, J. B. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001866 · Cited by 445
Integrated single cell analysis of blood and cerebrospinal fluid leukocytes in multiple sclerosis
Schafflick, D., Xu, C. A., Hartlehnert, M., Cole, M. B., Schulte‐Mecklenbeck, A., Lautwein, T., Wolbert, J., Heming, M., Meuth, S. G., Kuhlmann, T., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-14118-w · Cited by 457
Korte, A., Vilhjálmsson, B. J., Segura, V., Platt, A., Long, Q., & Nordborg, M. (2012) · Nature Genetics · doi:10.1038/ng.2376 · Cited by 453
T cells become licensed in the lung to enter the central nervous system
Odoardi, F., Sie, C., Streyl, K., Ulaganathan, V. K., Schläger, C., Lodygin, D., Heckelsmiller, K., Nietfeld, W., Ellwart, J. W., Klinkert, W. E. F., et al. (2012) · Nature · doi:10.1038/nature11337 · Cited by 453
Long‐term evolution of multiple sclerosis disability in the treatment era
Cree, B., Gourraud, P., Oksenberg, J. R., Bevan, C. J., Crabtree‐Hartman, E., Gelfand, J. M., Goodin, D. S., Graves, J., Green, A., Mowry, E. M., et al. (2016) · Annals of Neurology · doi:10.1002/ana.24747 · Cited by 440
Bioactive Lipids and Chronic Inflammation: Managing the Fire Within
Chiurchiù, V., Leuti, A., & Maccarrone, M. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00038 · Cited by 427
The immunogenetics of multiple sclerosis: A comprehensive review
Hollenbach, J. A., & Oksenberg, J. R. (2015) · Journal of Autoimmunity · doi:10.1016/j.jaut.2015.06.010 · Cited by 423
Molnarfi, N., Schulze‐Topphoff, U., Weber, M. S., Patarroyo, J. C., Prod’homme, T., Varrin‐Doyer, M., Shetty, A., Linington, C., Slavin, A., Hidalgo, J., et al. (2013) · The Journal of Experimental Medicine · doi:10.1084/jem.20130699 · Cited by 422
Class II HLA interactions modulate genetic risk for multiple sclerosis
the International Multiple Sclerosis Genetics Consortium (2015) · Nature Genetics · doi:10.1038/ng.3395 · Cited by 418
Multiple Sclerosis: Current and Emerging Disease-Modifying Therapies and Treatment Strategies
Wingerchuk, D. M., & Carter, J. L. (2014) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2013.11.002 · Cited by 416
Exploring the origins of grey matter damage in multiple sclerosis
Calabrese, M., Magliozzi, R., Ciccarelli, O., Geurts, J. J. G., Reynolds, R., & Martin, R. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3900 · Cited by 414
Self-citationBACH2 represses effector programs to stabilize Treg-mediated immune homeostasis
Roychoudhuri, R., Hirahara, K., Mousavi, K., Clever, D. C., Klebanoff, C. A., Bonelli, M. M., Sciumè, G., Zare, H., Vahedi, G., Dema, B., et al. (2013) · Nature · doi:10.1038/nature12199 · Cited by 412
Sawcer, S. J., Franklin, R. J. M., & Ban, M. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70041-9 · Cited by 432
The UK-PSCSC Consortium, Liu, J. Z., The International IBD Genetics Consortium, The International PSC Study Group, Hov, J. R., Folseraas, T., Ellinghaus, E., Rushbrook, S. M., Doncheva, N. T., Andreassen, O. A., et al. (2013) · Nature Genetics · doi:10.1038/ng.2616 · Cited by 391
TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis
Gregory, A., Dendrou, C. A., Attfield, K. E., Haghikia, A., Xifara, D. K., Butter, F., Poschmann, G., Kaur, G., Lambert, L., Leach, O. A., et al. (2012) · Nature · doi:10.1038/nature11307 · Cited by 395
Kiryluk, K., Li, Y., Sanna‐Cherchi, S., Rohanizadegan, M., Suzuki, H., Eitner, F., Snyder, H. J., Choi, M., Hou, P., Scolari, F., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002765 · Cited by 382
Overexpression of the Cytokine BAFF and Autoimmunity Risk
Steri, M., Orrù, V., Idda, M. L., Pitzalis, M., Pala, M., Zara, I., Sidore, C., Faà, V., Floris, M., Deiana, M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1610528 · Cited by 382
Animal models of multiple sclerosis: the good, the bad and the bottom line
Ransohoff, R. M. (2012) · Nature Neuroscience · doi:10.1038/nn.3168 · Cited by 379
Neuroinflammation: Microglia and T Cells Get Ready to Tango
Schetters, S. T. T., Gómez‐Nicola, D., García-Vallejo, J. J., & van Kooyk, Y. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01905 · Cited by 400
The impact of the gut microbiome on extra-intestinal autoimmune diseases
Miyauchi, E., Shimokawa, C., Steimle, A., Desai, M. S., & Ohno, H. (2022) · Nature reviews. Immunology · doi:10.1038/s41577-022-00727-y · Cited by 384
Super-enhancers delineate disease-associated regulatory nodes in T cells
Vahedi, G., Kanno, Y., Furumoto, Y., Jiang, K., Parker, S. C. J., Erdos, M. R., Davis, S. R., Roychoudhuri, R., Restifo, N. P., Gadina, M., et al. (2015) · Nature · doi:10.1038/nature14154 · Cited by 369
Autophagy in the renewal, differentiation and homeostasis of immune cells
Clarke, A. J., & Simon, A. K. (2019) · Nature Reviews Immunology · doi:10.1038/s41577-018-0095-2 · Cited by 361
Lauc, G., Huffman, J. E., Pučić‐Baković, M., Zgaga, L., Adamczyk, B., Mužinić, A., Novokmet, M., Polašek, O., Gornik, O., Krištić, J., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003225 · Cited by 366
The Expanding Landscape of Alternative Splicing Variation in Human Populations
Park, E., Pan, Z., Zhang, Z., Lin, L., & Xing, Y. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.11.002 · Cited by 385
The Role of Astrocytes in Multiple Sclerosis
Ponath, G. D., Park, C., & Pitt, D. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00217 · Cited by 378
Genome-wide pleiotropy between Parkinson disease and autoimmune diseases
Witoelar, A., Jansen, I. E., Wang, Y., Desikan, R. S., Gibbs, J. R., Blauwendraat, C., Thompson, W. K., Hernandez, D. G., Djurovic, S., Schork, A. J., et al. (2017) · JAMA Neurology · doi:10.1001/jamaneurol.2017.0469 · Cited by 352
Bayesian weighted Mendelian randomization for causal inference based on summary statistics
Zhao, J., Ming, J., Hu, X., Chen, G., Liu, J., & Yang, C. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz749 · Cited by 355
An update on immunopathogenesis, diagnosis, and treatment of multiple sclerosis
Garg, N., & Smith, T. W. (2015) · Brain and Behavior · doi:10.1002/brb3.362 · Cited by 398
B cells in autoimmune and neurodegenerative central nervous system diseases
Sabatino, J. J., Pröbstel, A., & Zamvil, S. S. (2019) · Nature reviews. Neuroscience · doi:10.1038/s41583-019-0233-2 · Cited by 361
The Immune Response in Multiple Sclerosis
Murúa, S. R., Farez, M., & Quintana, F. J. (2021) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-052920-040318 · Cited by 378
Environmental and genetic risk factors for MS: an integrated review
Waubant, E. L., Lucas, R. M., Mowry, E. M., Graves, J., Olsson, T. P., Alfredsson, L. S., & Langer-Gould, A. M. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50862 · Cited by 368
Population genomics of the Viking world
Margaryan, A., Lawson, D. J., Sikora, M., Racimo, F., Rasmussen, S., Moltke, I., Cassidy, L. M., Jørsboe, E., Ingason, A., Pedersen, M. W., et al. (2020) · Nature · doi:10.1038/s41586-020-2688-8 · Cited by 354
Noble, J. A., & Erlich, H. A. (2012) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a007732 · Cited by 335
SYK coordinates neuroprotective microglial responses in neurodegenerative disease
Ennerfelt, H., Frost, E. L., Shapiro, D. A., Holliday, C., Zengeler, K. E., Voithofer, G., Bolte, A. C., Lammert, C. R., Kulas, J. A., Ulland, T. K., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.030 · Cited by 297
Review: The role of vitamin D in nervous system health and disease
DeLuca, G. C., Kimball, S., Kolasinski, J., Ramagopalan, S. V., & Ebers, G. C. (2013) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12020 · Cited by 340
Ma, W., Gilligan, B. M., Yuan, J. D., & Li, T. (2016) · Journal of Hematology & Oncology · doi:10.1186/s13045-016-0277-y · Cited by 333
Metadata
- Authors
- The International Multiple Sclerosis Genetics Consortium & The Wellcome Trust Case Control Consortium 2
- Venue
- Nature
- Published
- 2011-08
- Volume
- 476
- Issue
- 7359
- Pages
- 214-219
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3182531
- OpenAlex
- W2040547343
- Cited by
- 2,697
- References
- 26
- Citations by year
- 2026: 72 · 2025: 101 · 2024: 112 · 2023: 111 · 2022: 136 · 2021: 155 · 2020: 167 · 2019: 173 · 2018: 178 · 2017: 215 · 2016: 220 · 2015: 273 · 2014: 244 · 2013: 279 · 2012: 223
- FWCI
- 175.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Keele Research Repository (Keele University) (submittedVersion, cc-by)
- PEARL (University of Plymouth) (submittedVersion)
- eCite Digital Repository (University of Tasmania) (submittedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Murdoch University Research Portal (submittedVersion)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by-nc-sa)
- HAL (submittedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Figshare (submittedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Site cant be reached (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Griffith Research Online (submittedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Faculty of Health; Institute of Health and Biomedical Innovation
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Susan G. Komen for the Cure
- Biogen
- Kaiser Permanente
- Children's Hospital of Philadelphia
- Fondazione CRT
- Fondation pour l'Aide à la Recherche sur la Sclérose en Plaques
- Institute of Clinical and Translational Sciences
- Scleroseforeningen
- Helsingin ja Uudenmaan Sairaanhoitopiiri
- Wellcome Trust (085475/Z/08/Z, 068545/Z/02), 085475, G0000934, 075491, 068545, 075491/Z/04,, 090532, 085475/B/08/Z, 084702)
- National Institute for Health and Care Research (G0000934, NF-SI-0507-10379, PDA/02/06/016)
- Parkinson's UK (G0909, J‐0804)
- Multiple Sclerosis Society (898/08)
- Multiple Sclerosis Australia
- Deutsche Forschungsgemeinschaft
- Agence Nationale de la Recherche (ANR-10-INBS-0001)
- Institut National de la Santé et de la Recherche Médicale
- Forskningsrådet för Arbetsliv och Socialvetenskap
- Academy of Finland
- Fonds Wetenschappelijk Onderzoek
- Ministero della Salute (502/92, D.lgs 502/92)
- Hjärnfonden
- Knut och Alice Wallenbergs Stiftelse
- Stockholms Läns Landsting (562183)
- Norges Forskningsråd
- Regione Piemonte (502/92)
- Haukeland Universitetssjukehus
- Vlaamse regering
- National Institutes of Health (5r01ns019142-03, G0000934, 075491/Z/04, 068545/Z/02, UL1TR000448, NS43559, NS19142, RR024992, CA104021, NS049477)
- U.S. Public Health Service (K23N/S048869)
- Medical Research Council (MC_EX_G0800860, 068545/Z/02, G0000934)
- National Health and Medical Research Council (G0000934)
- Helmholtz Zentrum München
- National Cancer Institute (R01CA104021, CA104021)
- National Institute of Allergy and Infectious Diseases (AI076544, R01AI076544)
- Fogarty International Center (K01TW009996)
- National Institute of Neurological Disorders and Stroke (NS067305, NS26799, NS 43559, NS032830, NS049477, NS19142, R01NS032830, R01NS043559, R01NS026799, R01NS049510, R01NS067305, NS049510, R01NS049477)
- National Center for Research Resources (RR020092, C06RR020092, RR-024992, UL1RR024992)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Clinical Neurology › Multiple Sclerosis Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Immunology and Microbiology › Immunology › Psoriasis: Treatment and Pathogenesis
- Keywords
- multiple sclerosis, genetic susceptibility, genome-wide association study, major histocompatibility complex, T helper cell differentiation, cell-mediated immunity, neuroinflammation, neurodegeneration, pathogenesis, genetic susceptibility loci
- MeSH terms
- Alleles, Cell Differentiation, Europe, T-Lymphocytes, Helper-Inducer, HLA-DR Antigens, Humans, Immunity, Cellular, Major Histocompatibility Complex, Multiple Sclerosis, HLA-A Antigens, Genome, Human, Sample Size, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study, HLA-DRB1 Chains
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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