Evidence map›Paper›PMID 27540591›Full record

ArticleNeurology. Genetics2016

Multiple sclerosis risk loci and disease severity in 7,125 individuals from 10 studies.

Michaela F George, Farren B S Briggs, Xiaorong Shao, Milena A Gianfrancesco, Ingrid Kockum, Hanne F Harbo, Elisabeth G Celius, Steffan D Bos, Anna Hedström, Ling Shen and 24 more

Abstract read
In one paragraph

Article in Neurology. Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Immune-Related Gene Variants as Modifiers of Multiple Sclerosis Severity.International journal of molecular sciences · 2026
    Article
  5. Review
  6. Article
  7. Article
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  9. Article
  10. Review
  11. Review
  12. Article
  13. Observational
  14. Observational
  15. Single nucleotide variants around the connective tissue growth factor (CTGF/CCN2) gene and their association with multiple sclerosis risk, disability scores, and rate of disease progression.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022
    Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors.

Michaela F GeorgeAuthor affiliations are listed at the end of the article.
Farren B S BriggsAuthor affiliations are listed at the end of the article.
Xiaorong ShaoAuthor affiliations are listed at the end of the article.
Milena A GianfrancescoAuthor affiliations are listed at the end of the article.
Ingrid KockumAuthor affiliations are listed at the end of the article.
Hanne F HarboAuthor affiliations are listed at the end of the article.
Elisabeth G CeliusAuthor affiliations are listed at the end of the article.
Steffan D BosAuthor affiliations are listed at the end of the article.
Anna HedströmAuthor affiliations are listed at the end of the article.
Ling ShenAuthor affiliations are listed at the end of the article.
Allan BernsteinAuthor affiliations are listed at the end of the article.
Lars AlfredssonAuthor affiliations are listed at the end of the article.
Jan HillertAuthor affiliations are listed at the end of the article.
Tomas OlssonAuthor affiliations are listed at the end of the article.
Nikolaos A PatsopoulosAuthor affiliations are listed at the end of the article.
Philip L De JagerAuthor affiliations are listed at the end of the article.
Annette B OturaiAuthor affiliations are listed at the end of the article.
Helle B SøndergaardAuthor affiliations are listed at the end of the article.
Finn SellebjergAuthor affiliations are listed at the end of the article.
Per S SorensenAuthor affiliations are listed at the end of the article.
Refujia GomezAuthor affiliations are listed at the end of the article.
Stacy J CaillierAuthor affiliations are listed at the end of the article.
Bruce A C CreeAuthor affiliations are listed at the end of the article.
Jorge R OksenbergAuthor affiliations are listed at the end of the article.
Stephen L HauserAuthor affiliations are listed at the end of the article.
Sandra D'AlfonsoAuthor affiliations are listed at the end of the article.
Maurizio A LeoneAuthor affiliations are listed at the end of the article.
Filippo Martinelli BoneschiAuthor affiliations are listed at the end of the article.
Melissa SorosinaAuthor affiliations are listed at the end of the article.
Ingrid van der MeiAuthor affiliations are listed at the end of the article.
Bruce V TaylorAuthor affiliations are listed at the end of the article.
Yuan ZhouAuthor affiliations are listed at the end of the article.
Catherine SchaeferAuthor affiliations are listed at the end of the article.
Lisa F BarcellosAuthor affiliations are listed at the end of the article.

Funding

A Haplotype Map for Multiple SclerosisR01NS049477 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HAUSER, STEPHEN L · 2005 to 2014
$15.3M
GENE LINKAGE STUDY OF MULTIPLE SCLEROSIS SIBLING PAIRSR01NS026799 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HAUSER, STEPHEN L, OKSENBERG, JORGE R. · 1989 to 2018
$6.8M
The Identification of Risk Factors for the Complex MS PhenotypeR01AI076544 · NIAID · UNIVERSITY OF CALIFORNIA BERKELEY · PI BARCELLOS, LISA F · 2008 to 2012
$3.6M
Novel Strategies to Identify GxE Contributions to MS PathogenesisR01ES017080 · NIEHS · UNIVERSITY OF CALIFORNIA BERKELEY · PI BARCELLOS, LISA F · 2011 to 2015
$3.0M
Genetic and non-genetic risk factors in MSR01NS049510 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI BARCELLOS, LISA F · 2005 to 2009
$2.7M
NIAID NIH HHS R01 AI076544NIEHS NIH HHS R01 ES017080NINDS NIH HHS R01 NS026799NINDS NIH HHS R01 NS049477NINDS NIH HHS R01 NS049510
6 · The paper itself

Abstract

objectiveWe investigated the association between 52 risk variants identified through genome-wide association studies and disease severity in multiple sclerosis (MS).

methodsTen unique MS case data sets were analyzed. The Multiple Sclerosis Severity Score (MSSS) was calculated using the Expanded Disability Status Scale at study entry and disease duration. MSSS was considered as a continuous variable and as 2 dichotomous variables (median and extreme ends; MSSS of ≤5 vs >5 and MSSS of <2.5 vs ≥7.5, respectively). Single nucleotide polymorphisms (SNPs) were examined individually and as both combined weighted genetic risk score (wGRS) and unweighted genetic risk score (GRS) for association with disease severity. Random-effects meta-analyses were conducted and adjusted for cohort, sex, age at onset, and HLA-DRB1*15:01.

resultsA total of 7,125 MS cases were analyzed. The wGRS and GRS were not strongly associated with disease severity after accounting for cohort, sex, age at onset, and HLA-DRB1*15:01. After restricting analyses to cases with disease duration ≥10 years, associations were null (p value ≥0.05). No SNP was associated with disease severity after adjusting for multiple testing.

conclusionsThe largest meta-analysis of established MS genetic risk variants and disease severity, to date, was performed. Results suggest that the investigated MS genetic risk variants are not associated with MSSS, even after controlling for potential confounders. Further research in large cohorts is needed to identify genetic determinants of disease severity using sensitive clinical and MRI measures, which are critical to understanding disease mechanisms and guiding development of effective treatments.

Identifiers

PMID27540591
PMCPMC4974846

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.