Evidence map›Paper›PMID 38298525›Full record

ArticleJournal of inflammation research2024

Identification of m6A-Related Biomarkers in Systemic Lupus Erythematosus: A Bioinformation-Based Analysis.

Yuan Tian, Kang Tao, Shifei Li, Xiaoqiang Chen, Rupeng Wang, Mingwang Zhang, Zhifang Zhai

Open access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
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  7. Biomarkers for systemic lupus erythematosus: A scoping review.Immunity, inflammation and disease · 2024
    Article
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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 4 institutions in 1 country.

Yuan TianDepartment of Dermatology, The First Affiliated Hospital, Army Medical University, Chongqing, People's Republic of China.
Kang TaoDepartment of Dermatology, The First Affiliated Hospital, Army Medical University, Chongqing, People's Republic of China.
Shifei LiDepartment of Dermatology, The First Affiliated Hospital, Army Medical University, Chongqing, People's Republic of China.
Xiaoqiang ChenDepartment of Dermatology, General Hospital of Central Theater Command, Wuhan, People's Republic of China.
Rupeng WangDepartment of Dermatology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, People's Republic of China.
Mingwang ZhangDepartment of Dermatology, The First Affiliated Hospital, Army Medical University, Chongqing, People's Republic of China.
Zhifang ZhaiDepartment of Dermatology, The First Affiliated Hospital, Army Medical University, Chongqing, People's Republic of China.
Army Medical University · CNChongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CNGeneral Hospital of Central Theater Command

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Systemic Lupus Erythematosus (SLE), a prototypical autoimmune disorder, presents a challenge due to the absence of reliable biomarkers for discerning organ-specific damage within SLE. A growing body of evidence underscores the pivotal involvement of N6-methyladenosine (m6A) in the etiology of autoimmune conditions. Methods: The datasets, which primarily encompassed the expression profiles of m6A regulatory genes, were retrieved from the Gene Expression Omnibus (GEO) repository. The optimal model, selected from either Random Forest (RF) or Support Vector Machine (SVM), was employed for the development of a predictive nomogram model. To identify pivotal genes associated with SLE, a comprehensive screening process was conducted utilizing LASSO, SVM-RFE, and RF techniques. Within the realm of SLE susceptibility, Weighted Gene Co-expression Network Analysis (WGCNA) was harnessed to delineate relevant modules and hub genes. Additionally, MeRIP-qPCR assays were performed to elucidate key genes correlated with m6A targets. Furthermore, a Mendelian randomization study was conducted based on genome-wide association studies to assess the causative influence of MMP9 on ischemic stroke (IS), which is not only a severe cerebrovascular event but also a common complication of SLE. Results: Twelve m6A regulatory genes was identified, demonstrating statistical significance ( Conclusion: Our study identified twelve m6A regulators, shedding light on the molecular mechanisms underlying SLE risk genes. Importantly, our analysis established a causal relationship between MMP9, a key m6A-related gene, and ischemic stroke, a common complication of SLE, thereby providing critical insights for presymptomatic diagnostic approaches.

Indexed as

bioinformatic analysism6A regulatory genesMendelian randomizationMMP9N6-methyladenosinesystemic lupus erythematosus

Identifiers

PMID38298525
PMCPMC10829513
OpenAlexW4391280093

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.