Evidence map›Paper›PMID 40636121›Full record

ArticleFrontiers in immunology2025

Identification and validation of CKAP2 as a novel biomarker in the development and progression of rheumatoid arthritis.

Qiongbing Zheng, Youmian Lan, Jiexin Chen, Ling Lin

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

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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

4 citing papers in PubMed.

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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

4 authors.

Qiongbing Zheng *Department of Rheumatology and Immunology, First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Youmian Lan *Department of Endocrinology and Metabolism, First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Jiexin Chen *Department of Rheumatology and Immunology, First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Ling LinDepartment of Rheumatology and Immunology, First Affiliated Hospital of Shantou University Medical College, Shantou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Rheumatoid arthritis (RA) is a common chronic joint disease. However, many patients exhibit inadequate responses to treatment due to disease heterogeneity. Identifying novel biomarkers for RA is crucial for advancing molecular diagnosis and identifying potential therapeutic targets. Methods: Synovial tissue transcriptome data from RA patients and healthy controls were obtained from the GEO database. Differentially expressed gene (DEG) analysis, functional enrichment analysis, and weighted gene co-expression network analysis (WGCNA) identified key gene modules in RA. Machine learning algorithms were used to identify hub genes, followed by immune infiltration analysis and gene set variation analysis (GSVA). Mendelian randomization (MR) analysis explored the causal relationship between hub genes and RA. Clinical synovial tissue samples were used to validate CKAP2 expression via quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemistry (IHC). The potential role of CKAP2 in the pathogenesis of RA was investigated through CCK-8 assay, wound healing assay, transwell migration assay and transwell invasion assay. Results: A total of 242 DEGs were identified between 20 RA patients and 17 healthy controls. Six gene modules were recognized, with the "turquoise" module associated with RA (cor = 0.39, Conclusion:

Indexed as

Arthritis, RheumatoidBiomarkersCell MovementDisease ProgressionFemaleGene Expression ProfilingGene Regulatory NetworksHumansMaleSynovial MembraneTranscriptomeBiomarkersbioinformatics analysisCKAP2fibroblast-like synoviocytesmachine learningmendelian randomizationrheumatoid arthritis

Identifiers

PMID40636121
PMCPMC12238030

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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.