Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
Open accessAbstract
Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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Published efforts to systematically interrogate MS severity have only involved modest numbers of cases and have not identified any convincingly associated genetic variants.
“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 [11]
Online Methods, ‘Secondary analyses’ (page unavailable), confirms that this paper performed a case-only analysis of MS severity using MSSS. Our copy does not give the number of cases in that analysis or report whether it identified any convincingly associated variants, so it does not substantiate those parts of the claim. (LLM, conf=0.78)
Experimental — accuracy not yet measuredA targeted ImmunoChip study in 29,300 multiple sclerosis cases and 50,794 unrelated healthy individuals identified 48 new susceptibility variants, bringing the total number of MS risk variants to 110 at 103 discrete loci outside the MHC.
“A further study, this time on a targeted array (the ImmunoChip44) in 29 300 MS cases and 50 794 unrelated healthy individuals, identified 48 new susceptibility variants, bringing the total number of MS risk variants to 110 at 103 discrete loci outside the MHC.45”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [45]
The Abstract reports 48 new susceptibility variants and a total of 110 established variants at 103 non-MHC loci. The case and control totals also match, but only 14,498 cases and 24,091 controls were analysed on the ImmunoChip; the remaining participants contributed previous GWAS data in the replication phase. Thus, the sentence overstates the size of the targeted-array sample. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe vast majority of genome-wide association study loci encode genes obviously active in the immune system, and particularly in the lymphocyte lineage, placing beyond a doubt the nature of multiple sclerosis as autoimmune.
“The vast majority of GWAS loci encode genes obviously active in the immune system,45, 63 and particularly in the lymphocyte lineage,64 placing beyond a doubt the nature of the disease as autoimmune.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [45]
The Gene Ontology passage (page unavailable) reports that a majority of 97 associated variants lie within 50 kb of genes with immunological functions, supporting an immune-system association. It does not establish that a vast majority of GWAS loci encode those genes; the paper also cautions that proximity does not necessarily indicate functional importance. The lymphocyte-lineage clause has a separate citation in the citing sentence. (LLM, conf=0.88)
Experimental — accuracy not yet measuredWhen a fine-mapping approach was applied to 6356 multiple sclerosis cases and 9617 controls from the United Kingdom, it only meaningfully resolved a small subset of associations, with 8/68 loci resolving to fewer than five candidate variants, and from these, a relevant candidate gene was identified in three.
“When applied to 6356 MS cases and 9617 controls from the United Kingdom, this approach only meaningfully resolved a small subset of associations, with 8/68 loci we analysed resolving to fewer than five candidate variants, and from these, we have been able to identify a relevant candidate gene in three.45”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [45]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredSeveral non-genome-wide effects are eventually identified as genome-wide significant, given enough sample size and true effects.
“More importantly, several such effects are eventually identified as genome-wide significant, given enough sample size and true effects.(3)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [3]
The previously reported MS susceptibility list identified 9 communities (81 connected genes out of 307), compared with 13 communities from the 551 prioritized genes.
“This compares to 9 communities that could be identified by the previously reported MS susceptibility list (81 connected genes out of 307; Table S23).(3)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [3]
The Abstract reports MS susceptibility variants and loci, while the Online Methods > Gene Ontology section describes annotating nearby genes; neither reports gene-network communities. Searches for “9 communities,” “81 connected genes out of 307,” and “551 prioritized genes” found no passage supporting the cited comparison. Page numbers were unavailable in our copy. (LLM, conf=0.74)
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- Authors
- International Multiple Sclerosis Genetics Consortium (IMSGC)
- Venue
- Nature Genetics
- Published
- 2013-09-29
- Volume
- 45
- Issue
- 11
- Pages
- 1353-1360
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3832895
- OpenAlex
- W2135403800
- Cited by
- 1,386
- References
- 7
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- en
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- ORBi UMONS (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Zurich Open Repository and Archive (University of Zurich)
- WOS
- Funders
- National Science Foundation
- U.S. Department of Energy
- Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
- Wellcome Trust (095552/Z/11/Z, 085475PELTONEN, 085475DONNELLY, 095552, 068545, 090532, 098051)
- Türkiye Atom Enerjisi Kurumu
- CERN
- Thailand Center of Excellence in Physics
- Infrastructures en Biologie Santé et Agronomie
- Kanton Zürich
- National Institute for Health and Care Research
- Multiple Sclerosis Society
- Deutsche Forschungsgemeinschaft
- Institut National de la Santé et de la Recherche Médicale
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Fundação de Amparo à Pesquisa do Estado de São Paulo
- National Natural Science Foundation of China
- Research Promotion Foundation (SF0690030s09)
- National Science Council
- Russian Foundation for Basic Research
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Bundesministerium für Bildung und Forschung
- Chinese Academy of Sciences
- Austrian Science Fund
- Eidgenössische Technische Hochschule Zürich
- Consejo Nacional de Ciencia y Tecnología
- Ministry of Education and Science of the Russian Federation
- General Secretariat for Research and Technology
- Crohn's and Colitis UK (M11-1)
- Ministry of Business, Innovation and Employment
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Hjärt-Lungfonden
- Joint Institute for Nuclear Research
- Nemzeti Kutatási és Technológiai Hivatal
- Karolinska Institutet
- Knut och Alice Wallenbergs Stiftelse
- Ministry of Education, Science and Technology
- National Science and Technology Development Agency
- Stockholms Läns Landsting
- Vetenskapsrådet
- Narodowym Centrum Nauki
- Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
- Centre National de la Recherche Scientifique
- Universidad Autónoma de San Luis Potosí
- School of Mathematics, Institute for Research in Fundamental Sciences
- Bundesministerium für Wissenschaft und Forschung
- Lietuvos Mokslų Akademija
- Pakistan Atomic Energy Commission
- Federal Agency of Atomic Energy of the Russian Federation
- Istituto Nazionale di Fisica Nucleare
- Board of the Swiss Federal Institutes of Technology
- National Institutes of Health
- Medical Research Council
- Science and Technology Facilities Council
- Fundação para a Ciência e a Tecnologia
- Russian Academy of Sciences
- Secretaría de Estado de Investigación, Desarrollo e Innovación
- European Regional Development Fund
- Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional
- Institut National de Physique Nucléaire et de Physique des Particules
- National Cancer Institute (R01CA104021)
- National Institute of General Medical Sciences (RC2GM093080)
- National Institute of Allergy and Infectious Diseases (R01AI076544)
- National Institute of Neurological Disorders and Stroke (RC2NS070340, R01NS032830, R01NS026799, R01NS049510, R01NS067305, R01NS049477)
- National Institute of Environmental Health Sciences (R01ES017080)
- National Center for Research Resources (UL1RR024975)
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- multiple sclerosis, genetic risk variants, fine mapping, Bayesian fine-mapping, immunochip, genome-wide association study, disease risk loci, immune system process, European ancestry
- MeSH terms
- Chromosome Mapping, Gene Frequency, Genotype, Humans, Multiple Sclerosis, Genetic Variation, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, White People, Genome-Wide Association Study, Genetic Loci
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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