Evidence map›Paper›PMID 24234648›Full record

SynthesisHuman molecular genetics2014

No evidence for shared genetic basis of common variants in multiple sclerosis and amyotrophic lateral sclerosis.

An Goris, Jessica van Setten, Frank Diekstra, Stephan Ripke, Nikolaos A Patsopoulos, Stephen J Sawcer, International Multiple Sclerosis Genetics Consortium, Michael van Es, Australia and New Zealand MS Genetics Consortium, Peter M Andersen and 23 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Human molecular genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Genetics of Multiple Sclerosis: An Overview and New Directions.Cold Spring Harbor perspectives in medicine · 2018
    Review
  14. Polygenic Epidemiology.Genetic epidemiology · 2016
    Review
  15. Article
  16. Homogeneous case subgroups increase power in genetic association studies.European journal of human genetics : EJHG · 2015
    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

33 authors.

An GorisLaboratory for Neuroimmunology, Experimental Neurology, KU Leuven, Leuven, Belgium.
Jessica van Setten
Frank Diekstra
Stephan Ripke
Nikolaos A Patsopoulos
Stephen J Sawcer
International Multiple Sclerosis Genetics Consortium
Michael van Es
Australia and New Zealand MS Genetics Consortium
Peter M Andersen
Judith Melki
Vincent Meininger
Orla Hardiman
John E Landers
Robert H Brown
Aleksey Shatunov
Nigel Leigh
Ammar Al-Chalabi
Christopher E Shaw
Bryan J Traynor
Adriano Chiò
Gabriella Restagno
Gabriele Mora
Roel A Ophoff
Jorge R Oksenberg
Philip Van Damme
Alastair Compston
Wim Robberecht
Bénédicte Dubois
Leonard H van den Berg
Philip L De Jager
Jan H Veldink
Paul I W de Bakker

Funding

A Haplotype Map for Multiple SclerosisR01NS049477 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HAUSER, STEPHEN L · 2005 to 2014
$15.3M
Genome wide SNP analysis in Amyotrophic Lateral SclerosisZIAAG000933 · NIA · NATIONAL INSTITUTE ON AGING · PI TRAYNOR, BRYAN · 2009 to 2025
$9.8M
Identification of genes causative for familial ALS gene using exome sequencingR01NS073873 · NINDS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LANDERS, JOHN E · 2011 to 2019
$4.6M
Genome wide SNP analysis in Parkinson's diseaseZ01AG000949 · NIA · NATIONAL INSTITUTE ON AGING · PI SINGLETON, ANDREW B · 2006 to 2008
$2.6M
High-Throughput Genomic Approaches to Identify ALS GenesR01NS050557 · NINDS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI BROWN, ROBERT H. · 2005 to 2009
$2.5M
Intramural NIH HHS Z01 AG000949Medical Research Council G0500289Medical Research Council G0501573Medical Research Council G0600974Medical Research Council G0900635Medical Research Council G0900688Medical Research Council G1100695Medical Research Council MC_G1000733NIA NIH HHS Z01-AG000949-02NINDS NIH HHS NS050557NINDS NIH HHS R01 NS049477NINDS NIH HHS R01 NS050557NINDS NIH HHS R01 NS073873Wellcome Trust 089701
6 · The paper itself

Abstract

Genome-wide association studies have been successful in identifying common variants that influence the susceptibility to complex diseases. From these studies, it has emerged that there is substantial overlap in susceptibility loci between diseases. In line with those findings, we hypothesized that shared genetic pathways may exist between multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS). While both diseases may have inflammatory and neurodegenerative features, epidemiological studies have indicated an increased co-occurrence within individuals and families. To this purpose, we combined genome-wide data from 4088 MS patients, 3762 ALS patients and 12 030 healthy control individuals in whom 5 440 446 single-nucleotide polymorphisms (SNPs) were successfully genotyped or imputed. We tested these SNPs for the excess association shared between MS and ALS and also explored whether polygenic models of SNPs below genome-wide significance could explain some of the observed trait variance between diseases. Genome-wide association meta-analysis of SNPs as well as polygenic analyses fails to provide evidence in favor of an overlap in genetic susceptibility between MS and ALS. Hence, our findings do not support a shared genetic background of common risk variants in MS and ALS.

Indexed as

Amyotrophic Lateral SclerosisComorbidityGenetic Predisposition to DiseaseHumansMultiple SclerosisPolymorphism, Single Nucleotide

Identifiers

PMID24234648
PMCPMC3943520

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.