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抗 MDA5 自身抗体阳性和阴性特发性炎性肌病患者炎症相关蛋白谱的共有特征与独特差异
Authors Zhang Y , Hu W, Li T, Pan Z, Sun J, He Y, Guan W, Zhang L, Lian C, Liu S, Zhang P
Received 23 December 2024
Accepted for publication 24 April 2025
Published 7 May 2025 Volume 2025:18 Pages 6009—6024
DOI http://doi.org/10.2147/JIR.S509777
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Chaim Putterman
Yusheng Zhang, Wenlu Hu, Tianqi Li, Zhou Pan, Jinlei Sun, Yujie He, Wenjuan Guan, Lijuan Zhang, Chaofeng Lian, Shengyun Liu, Panpan Zhang
Department of Rheumatology and Clinical Immunology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
Correspondence: Panpan Zhang, Department of Rheumatology and Clinical Immunology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China, Email panpanzhang2016@163.com Shengyun Liu, Department of Rheumatology and Clinical Immunology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China, Email fccliusy2@zzu.edu.cn
Purpose: Due to the heterogeneous nature of the diseases, treatment efficacy and prognosis vary for idiopathic inflammatory myopathy (IIM) patients with different myositis specific autoantibodies (MSAs). This study aimed to investigate the inflammation-related protein profiling of IIM patients with different MSAs. In addition, the shared and distinctive inflammation-related protein profiling in IIM with/without anti-MDA5 autoantibodies.
Methods: Seventy-seven patients with IIM of different MSAs and 53 gender/age matched healthy controls (HCs) were enrolled in this study. Ninety-two inflammation-related proteins were detected by Olink proteomics. We identified differentially expressed proteins (DEPs), and performed gene set enrichment analysis and KEGG pathway analysis. In addition, correlation between DEPs and serological parameters were performed. The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning was used to screen biomarkers related to anti-MDA5+ DM.
Results: Compared with HCs, 36 inflammation-related proteins were identified as DEPs. The top 10 DEPs were CXCL10, CXCL11, CXCL9, CXCL8, S100A12, IL-6, CCL2, CCL8, IL-10 and CCL3. The inflammation-related proteins and cytokine-cytokine receptor interaction pathway were more strikingly expressed in patients with anti-MDA5+ DM patients than in anti-MDA5- IIM patients. In addition, multiple DEPs correlated with serum ferritin, KL-6, muscle enzymes. For the first time, we established that a multi-factor panel comprising CX3CL1, IL-17C, IL-18R1, CCL20, and TNF (AUC = 0.824) serves as a highly efficient diagnostic biomarker for anti-MDA5+ DM.
Conclusion: Plasma profiling revealed that inflammation and inflammatory pathways were extremely elevated in patients with IIM, especially in patients with anti-MDA5 autoantibodies. The shared and distinctive inflammation-related protein signature was demonstrated in patients with/without anti-MDA5 autoantibodies. The expression of CX3CL1 was significantly higher in anti-MDA5+ DM than in patients without anti-MDA5 autoantibodies. In addition, CX3CL1 correlated with ESR, serum ferritin, CK enzymes and disease activity, indicating that CX3CL1 participated in inflammation status of anti-MDA5+ DM.
Keywords: idiopathic inflammatory myopathy, anti-MDA5+ dermatomyositis, myositis specific autoantibodies, inflammation-related biomarkers, CX3CL1