Evidence map›Paper›PMID 27058221›Full record

ReviewCurrent opinion in neurology2016

Multiple sclerosis: genetics, biomarkers, treatments.

Pierre-Paul Axisa, David A Hafler

Open access · greenAbstract readReview
In one paragraph

Review in Current opinion in neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% of its field
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

62 citing papers in PubMed, 1 synthesis or guideline pooled it, 111 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Circular RNAs in Immune-Related Diseases.Advances in experimental medicine and biology · 2025
    Review
  17. Review
  18. Review
  19. Review
  20. Current use of fluid biomarkers as outcome measures in Multiple Sclerosis (MS): a review of ongoing pharmacological clinical trials.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
    Review

2 more citing papers are in PubMed but not listed here.

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

2 authors at 2 institutions in 3 countries.

Pierre-Paul AxisaaDepartments of Neurology and Immunobiology, Yale School of Medicine, New Haven, Connecticut, USA bCentre National de la Recherche Scientifique, U5282 cCentre de Physiopathologie Toulouse-Purpan, Université Toulouse 3 dINSERM, U1043, Toulouse, France eBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
David A Hafler
Broad Institute · USYale University · US

Funding

Role of Negative Costimulation in Regulation of AutoimmunityP01AI039671 · NIAID · YALE UNIVERSITY · PI David A. Hafler · 1996 to 2026
$51.7M
TCR recognition of MHC class II peptide compexes in multiple sclerosisP01AI045757 · NIAID · DANA-FARBER CANCER INSTITUTE · PI KUCHROO, VIJAY K., LOVE, JOHN CHRISTOPHER · 1999 to 2017
$22.8M
Gene Expression and Regulatory Networks in Human LeukocytesRC2GM093080 · NIGMS · HARVARD MEDICAL SCHOOL · PI BENOIST, CHRISTOPHE O., MATHIS, DIANE J · 2009 to 2010
$7.3M
Regulatory T Cells in Autoimmune DiseaseU19AI070352 · NIAID · YALE UNIVERSITY · PI HAFLER, DAVID A. · 2006 to 2011
$5.9M
Treatment of Autoimmune Disease by Costimulatory Signal*U19AI046130 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI KHOURY, SAMIA J. · 1999 to 2007
$5.6M
Exploring the consequences of the TNFRSF1A susceptibility allele for MSR01NS067305 · NINDS · BRIGHAM AND WOMEN'S HOSPITAL · PI DE JAGER, PHILIP L · 2009 to 2011
$1.2M
Sodium Chloride Induced Dysregulation of CD4+CD25+ Regulatory T Cells in PatientsF31NS086434 · NINDS · YALE UNIVERSITY · PI HERNANDEZ, AMANDA · 2013 to 2014
$74k
NIAID NIH HHS P01 AI039671NIAID NIH HHS P01 AI045757NIAID NIH HHS U19 AI046130NIAID NIH HHS U19 AI070352NIGMS NIH HHS RC2 GM093080NINDS NIH HHS F31 NS086434NINDS NIH HHS R01 NS067305
6 · The paper itself

Abstract

purpose of reviewWe discuss new paradigms for understanding the immunopathology of multiple sclerosis through the recent development of high throughput genetic analysis, emergence of numerous candidate biomarkers, and the broadening of the treatment arsenal. RECENT

findingsThe recent use of genome wide association studies provide new tools for a better understanding of multiple sclerosis etiology. Genome-wide association studies have identified many genes implicated in immune regulation and the next step will be to elucidate how those genetic variations influence immune cell function to drive disease development and progression. Furthermore, patient care has seen the emergence of new biomarkers for monitoring disease progression and response to treatment. Finally, the introduction of numerous immunomodulatory treatments will likely improve clinical outcome of multiple sclerosis patients in the future. SUMMARY: Breakthroughs in the field of multiple sclerosis have led to a better understanding of the physiopathology of the disease, follow up, and treatment of the patients that develop relapsing remitting multiple sclerosis. The next challenge for multiple sclerosis will be to press forward to model and decipher multiple sclerosis progression, which will help both to develop therapeutics and generate knowledge about mechanisms of neurodegeneration.

Indexed as

BiomarkersDisease ProgressionGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansImmunologic FactorsMultiple SclerosisBiomarkersImmunologic Factors

Identifiers

PMID27058221
PMCPMC7882195
OpenAlexW2338575860

What OpenQuestion holds

Textmetadata
LicenceTDM
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.