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已发表论文
MYL1 表达下调成为类风湿关节炎有前景的诊断生物标志物
Authors Yang C, Huang Z , Zheng X, Tang H, Qin W , Liang Y, Chen H, Hao W, Yi D, Lu WW , Chen Y
Received 3 July 2025
Accepted for publication 7 December 2025
Published 18 December 2025 Volume 2025:18 Pages 17693—17714
DOI https://doi.org/10.2147/JIR.S551219
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 6
Editor who approved publication: Dr Ujjwol Risal
Chaoquan Yang,1,* Zhiling Huang,1,* Xifan Zheng,1,* Haojun Tang,1 Wenpeng Qin,1 Yicheng Liang,1 Haidong Chen,1 Wenjun Hao,1 Dan Yi,2 William W Lu,3 Yan Chen1
1Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 2Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People’s Republic of China; 3Department of Orthopedics and Traumatology, The University of Hong Kong, Hong Kong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yan Chen, Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China, Tel/Fax +8607715319091, Email cy003@connect.hku.hk
Purpose: Rheumatoid arthritis (RA) affects millions of people worldwide and causes chronic joint pain with incompletely understood pathogenesis and challenging management. Myosin light chain 1 (MYL1) a muscle regulatory protein, has an unknown role in RA pathogenesis.
Methods: We analyzed transcriptomic data from RA patients and healthy controls in the Gene Expression Omnibus (GEO). Using least absolute shrinkage and selection operator (LASSO) regression and random forest, we identified differentially expressed genes (DEGs). Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC). To explore potential mechanisms, we conducted functional enrichment and immune-infiltration analyses. We further validated MYL1 expression in a rat RA model using qRT-PCR and Western blotting.
Results: We found MYL1 significantly downregulated in RA with high diagnostic value (AUC > 0.8). Enrichment analyses revealed its involvement in muscle structure development, immune regulation, and calcium signaling pathways. CIBERSORT analysis indicated associations with immune cell infiltration, particularly regulatory T cells, activated natural killer (NK) cells, and M1 macrophages. The rat model confirmed reduced MYL1 expression at both mRNA (p < 0.001) and protein (p = 0.009) levels, consistent with human data.
Conclusion: MYL1 is consistently downregulated in RA and may serve as a potential diagnostic biomarker. The results indicate that MYL1 may be involved in the pathological process of RA through calcium signaling, muscle function, and immune cell regulation. However, further clinical and mechanistic studies are warranted.
Keywords: rheumatoid arthritis, myosin light chain 1, machine learning algorithm, immune cells
1Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 2Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People’s Republic of China; 3Department of Orthopedics and Traumatology, The University of Hong Kong, Hong Kong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yan Chen, Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China, Tel/Fax +8607715319091, Email cy003@connect.hku.hk
Purpose: Rheumatoid arthritis (RA) affects millions of people worldwide and causes chronic joint pain with incompletely understood pathogenesis and challenging management. Myosin light chain 1 (MYL1) a muscle regulatory protein, has an unknown role in RA pathogenesis.
Methods: We analyzed transcriptomic data from RA patients and healthy controls in the Gene Expression Omnibus (GEO). Using least absolute shrinkage and selection operator (LASSO) regression and random forest, we identified differentially expressed genes (DEGs). Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC). To explore potential mechanisms, we conducted functional enrichment and immune-infiltration analyses. We further validated MYL1 expression in a rat RA model using qRT-PCR and Western blotting.
Results: We found MYL1 significantly downregulated in RA with high diagnostic value (AUC > 0.8). Enrichment analyses revealed its involvement in muscle structure development, immune regulation, and calcium signaling pathways. CIBERSORT analysis indicated associations with immune cell infiltration, particularly regulatory T cells, activated natural killer (NK) cells, and M1 macrophages. The rat model confirmed reduced MYL1 expression at both mRNA (p < 0.001) and protein (p = 0.009) levels, consistent with human data.
Conclusion: MYL1 is consistently downregulated in RA and may serve as a potential diagnostic biomarker. The results indicate that MYL1 may be involved in the pathological process of RA through calcium signaling, muscle function, and immune cell regulation. However, further clinical and mechanistic studies are warranted.
Keywords: rheumatoid arthritis, myosin light chain 1, machine learning algorithm, immune cells