Evidence map›Paper›PMID 38590521›Full record

ArticleFrontiers in immunology2024

Iron metabolism disorder and multiple sclerosis: a comprehensive analysis.

Chao Tang, Jiaxin Yang, Chaomin Zhu, Yaqi Ding, Sushuang Yang, Bingyang Xu, Dian He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
10.9field-weighted citation impact, top 1% 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

18 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Review
  3. Cell death in multiple sclerosis.Cell death and differentiation · 2026
    Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

7 authors at 1 institution in 1 country.

Chao Tang *Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Jiaxin Yang *School of Clinical Medicine, Guizhou Medical University, Guiyang, Guizhou, China.
Chaomin Zhu *School of Clinical Medicine, Guizhou Medical University, Guiyang, Guizhou, China.
Yaqi DingDepartment of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Sushuang YangDepartment of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Bingyang XuSchool of Clinical Medicine, Guizhou Medical University, Guiyang, Guizhou, China.
Dian HeDepartment of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Guiyang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system. Currently, the pathological mechanisms of MS are not fully understood, but research has suggested that iron metabolism disorder may be associated with the onset and clinical manifestations of MS. Methods and materials: The study utilized publicly available databases and bioinformatics techniques for gene expression data analysis, including differential expression analysis, weighted correlation network analysis, gene enrichment analysis, and construction of logistic regression models. Subsequently, Mendelian randomization was used to assess the causal relationship between different iron metabolism markers and MS. Results: This study identified IREB2, LAMP2, ISCU, ATP6V1G1, ATP13A2, and SKP1 as genes associated with multiple sclerosis (MS) and iron metabolism, establishing their multi-gene diagnostic value for MS with an AUC of 0.83. Additionally, Mendelian randomization analysis revealed a potential causal relationship between transferrin saturation and MS (p=2.22E-02; OR 95%CI=0.86 (0.75, 0.98)), as well as serum transferrin and MS (p=2.18E-04; OR 95%CI=1.22 (1.10, 1.36)). Conclusion: This study comprehensively explored the relationship between iron metabolism and MS through integrated bioinformatics analysis and Mendelian randomization methods. The findings provide important insights for further research into the role of iron metabolism disorder in the pathogenesis of MS and offer crucial theoretical support for the treatment of MS.

Indexed as

Iron Metabolism DisordersMultiple SclerosisGenes, RegulatorHumansIronTransferrinsIronTransferrinsbioinformatic analysiscausal relationshipiron metabolismMendelian randomizationmultiple sclerosis

Identifiers

PMID38590521
PMCPMC11000231
OpenAlexW4393054021

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.