Ruan Shiqiang, Tang Dongxu, Luo Yanfei, Song Hao
Department of Orthopaedics Surgery, the First People's Hospital of Zunyi City (The Third Affiliated Hospital of Zunyi Medical University), Zunyi, China.
Animal Model Exp Med. 2024 Dec;7(6):781-792. doi: 10.1002/ame2.12416. Epub 2024 May 8.
Osteoarthritis (OA) is a common joint disease, and existing drugs cannot cure OA, so there is an urgent need to identify new targets. Mitophagy plays an important role in OA; however, the role of mitophagy in the OA immune system is not yet clear.
In this study, differential analysis and enrichment analysis were used to identify mitophagy-related genes (MRGs) with differential expression in OA and the functional pathways involved in OA. Subsequently, two machine learning methods, RF and LASSO, were used to screen MRGs with diagnostic value and construct nomograms. At the same time, the relationship between mitophagy and OA immune response was explored by immunoinfiltration analysis.
Forty-three differentially MRGs were identified in OA, of which six MRGs (GABARAPL2, PARL, GABARAPL1, JUN, RRAS, and SNX7) were associated with the diagnosis of OA. The ROC analysis results show that these 6 MRGs have high predictive accuracy in the diagnosis of OA. In immune infiltration analysis, we found that the abundance of significantly different immune cells in OA was mostly upregulated. In addition, the expression of diagnostic-related MRGs is correlated with changes in the abundance of immune cells in OA.
This study demonstrates that six MRGs can be used as diagnostic biomarkers. The expression of diagnostic-related MRGs is correlated with changes in the abundance of immune cells in OA. At the same time, mitophagy may affect the immune microenvironment of OA by regulating immune cells, ultimately leading to the progression of OA.
骨关节炎（OA）是一种常见的关节疾病，现有药物无法治愈OA，因此迫切需要确定新的靶点。线粒体自噬在OA中起重要作用；然而，线粒体自噬在OA免疫系统中的作用尚不清楚。
在本研究中，采用差异分析和富集分析来鉴定OA中差异表达的线粒体自噬相关基因（MRGs）以及OA涉及的功能途径。随后，使用随机森林（RF）和套索（LASSO）两种机器学习方法筛选具有诊断价值的MRGs并构建列线图。同时，通过免疫浸润分析探讨线粒体自噬与OA免疫反应之间的关系。
在OA中鉴定出43个差异MRGs，其中6个MRGs（GABARAPL2、PARL、GABARAPL1、JUN、RRAS和SNX7）与OA的诊断相关。ROC分析结果表明，这6个MRGs在OA诊断中具有较高的预测准确性。在免疫浸润分析中，我们发现OA中显著不同的免疫细胞丰度大多上调。此外，诊断相关MRGs的表达与OA中免疫细胞丰度的变化相关。
本研究表明，6个MRGs可作为诊断生物标志物。诊断相关MRGs的表达与OA中免疫细胞丰度的变化相关。同时，线粒体自噬可能通过调节免疫细胞影响OA的免疫微环境，最终导致OA的进展。
