ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1585895
This article is part of the Research TopicNovel Biomarkers for Early Diagnosis, involved in Autoimmune and Autoinflammatory DiseasesView all 10 articles
Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis
Provisionally accepted- 1Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
- 2The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, China
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Background: Rheumatoid arthritis (RA) is an autoimmune inflammatory disease. The mechanism by which telomeres were involved in the development of RA remains unclear. This study aimed to investigate the relationship between RA and telomeres.In this study, we identified differentially expressed genes (DEGs) between RA and control samples by analyzing transcriptome data from a public database.Candidate genes were determined through the intersection of DEGs and telomererelated genes. Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. Besides, a nomogram model was employed to predict the diagnostic ability of biomarkers for RA. Subsequently, the potential mechanisms of these biomarkers in RA were further explored using gene set enrichment analysis (GSEA), subcellular localization, chromosome localization, immune infiltration, functional analysis, molecular regulatory networks, drug prediction, and molecular docking. Additionally, the expression of biomarkers between RA and control samples was validated through in vitro experiments.Results: ABCC4, S100A8, VAMP2, PIM2, and ISG20 were identified as biomarkers.These biomarkers demonstrated excellent diagnostic ability for RA through a nomogram. Most of the biomarkers were found to be enriched in processes related to allograft rejection and the cell cycle. Subcellular and chromosomal localization analyses indicated that ABCC4 is localized to the plasma membrane, ISG20 to the mitochondria, PIM2 and S100A8 to the cytoplasm, and VAMP2 to the nucleus.Additionally, nine differential immune cells were identified between RA and control samples, with a strong correlation observed between the biomarkers and activated CD4 memory T cells. S100A8, PIM2, and VAMP2 exhibited high similarity to other biomarkers. Furthermore, three transcription factors (TFs), 121 microRNAs (miRNAs), and six long non-coding RNAs (lncRNAs) were identified as targeted biomarkers. Five drugs-methotrexate, adefovir, furosemide, azathioprine, and cefmetazole-were also identified as targeted biomarkers. Notably, ABCC4 interacted with all five drugs and exhibited the strongest binding energy with methotrexate. The results of the in vitro experiments were consistent with those obtained from the bioinformatics analysis.This study identified five biomarkers-ABCC4, S100A8, VAMP2, PIM2, and ISG20-and offered new insights into potential therapeutic strategies for RA.
Keywords: Rheumatoid arthritis, Autoimmune Diseases, telomeres, biomarkers, Bioinformatics analysis, In vitro experiment
Received: 01 Mar 2025; Accepted: 28 Apr 2025.
Copyright: © 2025 Feng, Bai, He, Wang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Hao Wang, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
Wei Zhang, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
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