Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Genetic analysis of multiple sclerosis.

Emily C Walsh1, Sheila Guschwan-McMahon, Mark J Daly

  • 1Whitehead Institute for Biomedical Research, Center for Genome Research, One Kendall Square, Cambridge, MA 02141, USA.

Journal of Autoimmunity
|August 26, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identification of a Novel Genetic Variant Responsible for Familial Atrial Fibrillation.

The Canadian journal of cardiology·2026
Same author

Exome sequencing directly implicates 68 genes in inflammatory bowel disease.

medRxiv : the preprint server for health sciences·2026
Same author

Reproducible detection of antigen-specific T cells and Tregs via standardized and automated activation-induced marker assay workflows.

Cell reports methods·2026
Same author

Empiric azithromycin alters the upper respiratory microbiome and resistome without anti-inflammatory benefit in COVID-19.

Nature microbiology·2026
Same author

HLA class I signal peptide variation predicts strength of NKG2A<sup>+</sup> NK cell response to missing-self and risk of human disease.

Nature immunology·2026
Same author

Author Correction: Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors.

Communications medicine·2026
Same journal

Neonatal total parenteral nutrition and the risk of childhood autoimmune diseases: A nationwide population-based study of 2.3 million children.

Journal of autoimmunity·2026
Same journal

Targeting autoreactive B cells in rheumatoid arthritis through MHC class I-presented BCR-derived neo-epitopes.

Journal of autoimmunity·2026
Same journal

Intermittent fasting ameliorates Sjögren's syndrome-related dry eye through a preponderant bile acid-Akkermansia homeostasis establishment.

Journal of autoimmunity·2026
Same journal

High-intensity immunosuppression versus modern standard care in poor-prognosis diffuse cutaneous systemic sclerosis: A propensity-matched study.

Journal of autoimmunity·2026
Same journal

Efficacy, safety, and tolerability of treatments for interstitial lung disease associated with rtoid arthritis: A systematic review and network meta-analysis.

Journal of autoimmunity·2026
Same journal

Celiac disease plasma cells recognize the active form of transglutaminase 2 with and without bound substrate.

Journal of autoimmunity·2026
See all related articles

Multiple sclerosis (MS) genetics involves many small-effect variants. Meta-analysis helps detect these subtle genetic factors, improving our understanding of MS susceptibility.

Area of Science:

  • Genetics
  • Immunology
  • Neurology

Background:

  • Multiple sclerosis (MS) is a complex neurological autoimmune disease with a substantial genetic component.
  • Genetic risk in MS arises from numerous variants, each with a minor individual effect.
  • Identifying these low-effect genetic loci presents a significant challenge in MS research.

Purpose of the Study:

  • To review genetic approaches for identifying MS susceptibility loci.
  • To highlight the utility of meta-analytical methods in detecting modest genetic effects.
  • To explore the role of specific variants, such as CTLA-4, in MS etiology.

Main Methods:

  • Review of linkage and association studies in multiple sclerosis genetics.
  • Application of meta-analytical approaches to increase statistical power for locus detection.

Related Experiment Videos

  • Evaluation of the association between a CTLA-4 variant and MS risk.

    • Main Results:

    • Challenges exist in identifying multiple low-effect genetic variants contributing to MS.
    • Meta-analysis offers enhanced statistical power crucial for detecting such variants.
    • The study evaluated the association of a CTLA-4 variant with MS using meta-analysis.

    Conclusions:

    • Understanding the complex genetic architecture of MS requires advanced statistical methods.
    • Meta-analysis is a powerful tool for dissecting the genetic basis of complex diseases like MS.
    • Advances in human genome variation studies will further illuminate the genetic causes of MS.