{"title":"Identification of mitophagy-related biomarkers in osteoarthritis.","authors":"Shiqiang Ruan, Dongxu Tang, Yanfei Luo, Hao Song","doi":"10.1002/ame2.12416","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":93869,"journal":{"name":"Animal models and experimental medicine","volume":" ","pages":"781-792"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11680475/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Animal models and experimental medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/ame2.12416","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Background: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
背景: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。有丝分裂在 OA 中发挥着重要作用;然而,有丝分裂在 OA 免疫系统中的作用尚不明确:本研究采用差异分析法和富集分析法鉴定在OA中表达差异的有丝分裂相关基因(MRGs),以及参与OA的功能通路。随后,采用 RF 和 LASSO 两种机器学习方法筛选出具有诊断价值的 MRGs,并构建了提名图。同时,通过免疫渗透分析探讨了有丝分裂与OA免疫反应之间的关系:结果:在OA中发现了43个不同的MRGs,其中6个MRGs(GABARAPL2、PARL、GABARAPL1、JUN、RRAS和SNX7)与OA诊断相关。ROC分析结果表明,这6个MRGs对OA的诊断具有很高的预测准确性。在免疫浸润分析中,我们发现 OA 中显著不同的免疫细胞的丰度大多上调。此外,与诊断相关的MRGs的表达与OA中免疫细胞丰度的变化相关:本研究表明,六种 MRGs 可用作诊断生物标记物。结论:本研究表明,六种 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,有丝分裂可能通过调节免疫细胞影响 OA 的免疫微环境,最终导致 OA 的恶化。