Evidence map›Paper›PMID 25071715›Full record

ReviewFrontiers in neurology2014

Recent advances and future challenges in the genetics of multiple sclerosis.

Christina M Lill

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in neurology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

22 citing papers in PubMed, 49 citations in OpenAlex.

  1. Article
  2. Copy number variations across the blood-brain barrier in multiple sclerosis.Annals of clinical and translational neurology · 2022
    Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Replication study of GWAS risk loci in Greek multiple sclerosis patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2019
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  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

1 author at 1 institution in 1 country.

Christina M LillNeuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics , Berlin , Germany ; Focus Program Translational Neuroscience, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz , Mainz , Germany.
Max Planck Society · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is the most common auto-inflammatory disease of the central nervous system, affecting more than 2 million individuals worldwide. It is a genetically complex disease, in which a substantial part of a person's liability to develop MS is caused by a combination of multiple genetic and non-genetic (e.g., environmental) risk factors. Increasing this complexity, many of the involved risk factors likely interact in an intricate and hitherto ill-defined fashion. Despite these complexities, and owing greatly to the advent and application of large-scale genome-wide association studies, our understanding of the genetic factors underlying MS etiology has begun to gain unprecedented momentum. In this perspective, I will summarize some recent advances and outline future challenges in MS genetics research.

Indexed as

autoimmune diseaseepigeneticsgenome-wide association studyheritabilityimmunogeneticsmultiple sclerosisrare variants

Identifiers

PMID25071715
PMCPMC4094909
OpenAlexW2103502637

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.