Evidence map›Paper›PMID 39318236›Full record

ReviewGlia2025

Towards an integrated approach for understanding glia in Amyotrophic Lateral Sclerosis.

Stanislaw Majewski, Pierre Klein, Séverine Boillée, Benjamin E Clarke, Rickie Patani

Abstract readReview
In one paragraph

Review in Glia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. 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

5 authors.

Stanislaw MajewskiDepartment of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London, UK.
Pierre KleinDepartment of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London, UK.
Séverine BoilléeSorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital de la Pitié-Salpêtrière, Paris, France.
Benjamin E ClarkeDepartment of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0001-5775-352X
Rickie PataniDepartment of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0002-3825-7675

Funding

Medical Research Council MR/S006591/1
6 · The paper itself

Abstract

Substantial advances in technology are permitting a high resolution understanding of the salience of glia, and have helped us to transcend decades of predominantly neuron-centric research. In particular, recent advances in 'omic' technologies have enabled unique insights into glial biology, shedding light on the cellular and molecular aspects of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Here, we review studies using omic techniques to attempt to understand the role of glia in ALS across different model systems and post mortem tissue. We also address caveats that should be considered when interpreting such studies, and how some of these may be mitigated through either using a multi-omic approach and/or careful low throughput, high fidelity orthogonal validation with particular emphasis on functional validation. Finally, we consider emerging technologies and their potential relevance in deepening our understanding of glia in ALS.

Indexed as

Amyotrophic Lateral SclerosisNeurogliaAnimalsHumansALSastrocytegliamicrogliamultiomicsoligodendrocyteomics

Identifiers

PMID39318236
PMCPMC11784848

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.