Evidence map›Paper›PMID 42706366›Full record

ArticleScientific reports2026

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

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

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Li TangDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, China.
Zhigang LinDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, China.
Linmeng ZouDepartment of General Practice, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, China.
Yongmei HuDepartment of General Practice, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, China.
Shan GaoDepartment of General Practice, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, China.
Wen PanHealth Management Center, Hospital of Chengdu Office of People's Government of Xizang Autonomous Region, Chengdu, China.
Ling WeiDepartment of General Practice, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, China. wl1982340@163.com.
Mo ChenDepartment of General Practice, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, China. chenmo_1986@qq.com.ORCID 0009-0002-2049-0783

Funding

Chengdu Medical Research Program, China 2022359Science and Technology Projects of Xizang Autonomous Region XZ202501YD0013Science and Technology Projects of Xizang Autonomous Region, China XZ202301ZY0050G
6 · The paper itself

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.

Indexed as

Arthritis, RheumatoidExosomesMachine LearningMicroRNAsSarcopeniaAgedBiomarkersFemaleGene Regulatory NetworksHumansMaleMiddle AgedTibetBiomarkersMicroRNAsBiomarkersExosomal microRNAHigh-throughput sequencingLow muscle massMachine learningNomogramRheumatoid arthritis

Identifiers

PMID42706366
PMCPMC13550484

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