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利用机器学习鉴定ZNF652作为骨关节炎的诊断和治疗靶点

Identification of ZNF652 as a Diagnostic and Therapeutic Target in Osteoarthritis Using Machine Learning.

作者信息

Chen Yeping, Liang Rongyuan, Zheng Xifan, Fang Dalang, Lu William W, Chen Yan

机构信息

Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.

Department of Thyroid and Breast Surgery, Affiliated Hospital of Youjiang Medical College of Nationalities, Baise, Guangxi, People's Republic of China.

出版信息

J Inflamm Res. 2024 Dec 2;17:10141-10161. doi: 10.2147/JIR.S488841. eCollection 2024.

Abstract

PURPOSE

Osteoarthritis (OA) is the most common degenerative joint disease. However, its etiology remains largely unknown. Zinc Finger Protein 652 (ZNF652) is a transcription factor implicated in various biological processes. Nevertheless, its role in OA has not been elucidated.

METHODS

The search term "osteoarthritis" was utilized to procure transcriptome data relating to OA patients and healthy people from the Gene Expression Omnibus (GEO) database. Then a screening process was initiated to identify differentially expressed genes (DEGs). The DEGs were discerned using three distinct machine learning methods. The accuracy of these DEGs in diagnosing OA was evaluated using the Receiver Operating Characteristic (ROC) Curve. A competitive endogenous RNA (ceRNA) visualization network was established to delve into potential regulatory targets. The ZNF652 expression was confirmed in the cartilage of OA rats using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting (WB) and analyzed using an independent -test.

RESULTS

ZNF652 was identified as a DEG and exhibited the highest diagnostic value for OA according to the ROC analysis. The GO and KEGG enrichment analyses suggest that ZNF652 plays a vital role in OA development through processes including nitric oxide anabolism, macrophage proliferation, immune response, and the PI3K/Akt and the MAPK signaling pathways. The increased expression of ZNF652 in OA was validated in qRT-PCR (1.193 ± 0.005 vs 1.000 ± 0.005, p < 0.001) and WB (0.981 ± 0.055 vs 0.856 ± 0.026, p = 0.012) analysis.

CONCLUSION

ZNF652 was found to be related to OA pathogenesis and can potentially serve as a diagnostic and therapeutic target of OA. The underlying mechanism is that ZNF652 was related to nitric oxide anabolism, macrophage proliferation, various signaling pathways, and immune cells and their functions in OA. Nevertheless, the findings need to be confirmed in clinical trials and the molecular mechanism requires further study.

摘要

目的

骨关节炎(OA)是最常见的退行性关节疾病。然而,其病因在很大程度上仍不清楚。锌指蛋白652(ZNF652)是一种参与多种生物学过程的转录因子。然而,其在OA中的作用尚未阐明。

方法

利用搜索词“骨关节炎”从基因表达综合数据库(GEO)中获取与OA患者和健康人相关的转录组数据。然后启动筛选过程以鉴定差异表达基因(DEG)。使用三种不同的机器学习方法识别DEG。使用受试者工作特征(ROC)曲线评估这些DEG在诊断OA中的准确性。建立竞争性内源性RNA(ceRNA)可视化网络以深入研究潜在的调控靶点。使用定量逆转录聚合酶链反应(qRT-PCR)和蛋白质免疫印迹法(WB)在OA大鼠软骨中证实ZNF652的表达,并使用独立样本t检验进行分析。

结果

根据ROC分析,ZNF652被鉴定为DEG,并且对OA表现出最高的诊断价值。基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析表明,ZNF652通过一氧化氮合成代谢、巨噬细胞增殖、免疫反应以及PI3K/Akt和丝裂原活化蛋白激酶(MAPK)信号通路等过程在OA发展中起重要作用。qRT-PCR(1.193±0.005对1.000±0.005,p<0.001)和WB(0.981±0.055对0.856±0.026,p = 0.012)分析验证了OA中ZNF652表达的增加。

结论

发现ZNF652与OA发病机制相关,并且可能作为OA的诊断和治疗靶点。潜在机制是ZNF652与一氧化氮合成代谢、巨噬细胞增殖、各种信号通路以及OA中的免疫细胞及其功能有关。然而,这些发现需要在临床试验中得到证实,并且分子机制需要进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f78a/11624598/55a618b409ef/JIR-17-10141-g0001.jpg

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