Machine learning identifies plasma-derived exosomal miRNAs associated with low muscle mass in Tibetan patients with rheumatoid arthritis

Sarcopenia poses a significant health burden in aging populations, particularly among patients with rheumatoid arthritis (RA), but current diagnostic approaches face limitations in early detection. This study aims to identify plasma-derived exosomal miRNA features associated with low muscle mass in Tibetan patients with RA. High-throughput sequencing identified 101 candidate dysregulated miRNAs in Tibetan patients with RA and low muscle mass, including 61 upregulated and 40 downregulated miRNAs, using exploratory thresholds of |log2 fold change| ≥ 0.58 and nominal P < 0.05. Most candidates did not remain significant after Benjamini–Hochberg false discovery rate correction; therefore, the broader candidate set was considered exploratory. Machine learning algorithms consistently identified hsa-miR-1294 and hsa-let-7c-5p as candidate miRNA features. Integrated miRNA–mRNA regulatory network analysis retained 50 candidate target genes for the construction of two direction-specific putative interaction networks involving 43 miRNAs. Functional enrichment analysis identified nominally enriched metabolic pathways, including sphingolipid metabolism and oxidative phosphorylation, while immune microenvironment analysis revealed differences in estimated muscle satellite-cell and mast-cell enrichment scores. Internally evaluated miRNA-based and target gene-based nomogram models both showed preliminary apparent discrimination, with an area under the receiver operating characteristic curve of 0.905 in their respective development datasets. Exploratory computational drug screening identified several candidate compounds for future investigation, including deferasirox, acarbose, taxifolin, pterostilbene, and ercalcitriol. This study prioritized hsa-miR-1294 and hsa-let-7c-5p as candidate exosomal miRNA features associated with low muscle mass in Tibetan patients with RA. These findings provide hypothesis-generating evidence for the further evaluation of minimally invasive miRNA features associated with low muscle mass.

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Publication Details

Journal
Scientific Reports
Published
2026-09-06
DOI
https://doi.org/10.1038/s41598-026-68952-2
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
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article

Machine learning identifies plasma-derived exosomal miRNAs associated with low muscle mass in Tibetan patients with rheumatoid arthritis

Shan Gao, Yongmei Hu, Ling Wei, Zhigang Lin et al.
Scientific Reports
Rheumatoid Arthritis Research and Therapies
article

Machine learning identifies plasma-derived exosomal miRNAs associated with low muscle mass in Tibetan patients with rheumatoid arthritis

Shan Gao, Yongmei Hu, Ling Wei, Zhigang Lin, Li Tang, Wen Pan, Mo Chen, Linmeng Zou
article en

Abstract

Sarcopenia poses a significant health burden in aging populations, particularly among patients with rheumatoid arthritis (RA), but current diagnostic approaches face limitations in early detection. This study aims to identify plasma-derived exosomal miRNA features associated with low muscle mass in Tibetan patients with RA. High-throughput sequencing identified 101 candidate dysregulated miRNAs in Tibetan patients with RA and low muscle mass, including 61 upregulated and 40 downregulated miRNAs, using exploratory thresholds of |log2 fold change| ≥ 0.58 and nominal P < 0.05. Most candidates did not remain significant after Benjamini–Hochberg false discovery rate correction; therefore, the broader candidate set was considered exploratory. Machine learning algorithms consistently identified hsa-miR-1294 and hsa-let-7c-5p as candidate miRNA features. Integrated miRNA–mRNA regulatory network analysis retained 50 candidate target genes for the construction of two direction-specific putative interaction networks involving 43 miRNAs. Functional enrichment analysis identified nominally enriched metabolic pathways, including sphingolipid metabolism and oxidative phosphorylation, while immune microenvironment analysis revealed differences in estimated muscle satellite-cell and mast-cell enrichment scores. Internally evaluated miRNA-based and target gene-based nomogram models both showed preliminary apparent discrimination, with an area under the receiver operating characteristic curve of 0.905 in their respective development datasets. Exploratory computational drug screening identified several candidate compounds for future investigation, including deferasirox, acarbose, taxifolin, pterostilbene, and ercalcitriol. This study prioritized hsa-miR-1294 and hsa-let-7c-5p as candidate exosomal miRNA features associated with low muscle mass in Tibetan patients with RA. These findings provide hypothesis-generating evidence for the further evaluation of minimally invasive miRNA features associated with low muscle mass.

Scientific ReportsVol. 16(1)
Sichuan University (CN), West China Hospital of Sichuan University (CN), Tibet Autonomous Region People's Hospital (CN), People's Government of Shaanxi Province (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 10%
Rheumatoid Arthritis Research and Therapies
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