时间1
骨关节炎
转录组
下调和上调
软骨细胞
医学
细胞外基质
软骨
癌症研究
微阵列分析技术
生物信息学
基因
生物
基因表达
细胞生物学
病理
遗传学
解剖
替代医学
作者
Zhenyu Gao,Guoqing Yan,Linchong Su,Sanshan He,Jiao‐e Sheng,Qingchao Wu,Xia Huang,Yufang Dai
标识
DOI:10.1111/1756-185x.70083
摘要
Osteoarthritis is a systemic disease that primarily damages articular cartilage and also affects the synovium, ligaments, and bone tissues. The key mechanisms involved are chondrocyte death and degradation of the extracellular matrix. This study aims to identify differentially expressed genes (DEGs) associated with ferroptosis and investigate their roles in the development of osteoarthritis. We used several methods, such as transcriptomic data analysis, gene enrichment analysis, protein-protein interaction network construction, animal model experiments, and immune cell infiltration analysis. Our examination of the GSE114007 dataset uncovered 2614 DEGs, including 1300 that were upregulated and 1314 that were downregulated. From these, we identified eight ferroptosis-related DEGs (FRGs-DEGs). Functional enrichment analysis showed that these genes are significant for cellular migration and tissue remodeling. They are particularly involved in the HIF-1 and PPAR signaling pathways. Additionally, our immune cell infiltration analysis indicated an increase in M0 and M2 macrophages in osteoarthritis samples, while levels of eosinophils and memory B cells were notably decreased. The receiver operating characteristic curve analysis identified GJA1, TIMP Metallopeptidase Inhibitor 1 (TIMP1), and DPP4 as potential biomarkers for osteoarthritis diagnosis, with area under the curve of 0.91, 0.85, and 0.83, respectively. Moreover, RT-qPCR validation in an osteoarthritis rat model confirmed the upregulation of TIMP1, supporting our bioinformatics results. In summary, our study identifies key FRGs-DEGs and their potential roles in osteoarthritis. This research provides new insights into the disease's molecular mechanisms and suggests innovative therapeutic targets for clinical intervention. Future research should aim to include larger patient cohorts and clinical validation to improve the applicability of these findings.
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