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

Area of Science:

• Biochemistry
• Genetics
• Immunology

Background:

• Osteoarthritis (OA) is a prevalent degenerative joint disease with largely unknown causes.
• The role of Zinc Finger Protein 652 (ZNF652), a known transcription factor, in OA pathogenesis remains uninvestigated.

Purpose of the Study:

• To investigate the potential role of ZNF652 in osteoarthritis.
• To identify ZNF652 as a potential diagnostic and therapeutic target for OA.

Main Methods:

• Transcriptome data from OA patients and healthy individuals were analyzed to identify differentially expressed genes (DEGs) using machine learning.
• The diagnostic accuracy of DEGs was assessed via Receiver Operating Characteristic (ROC) curve analysis.
• ZNF652 expression was validated in OA rat cartilage using qRT-PCR and Western blotting.

Main Results:

• ZNF652 was identified as a significant DEG with high diagnostic value for OA.
• Enrichment analyses indicated ZNF652's involvement in nitric oxide anabolism, macrophage proliferation, immune response, and PI3K/Akt and MAPK signaling pathways.
• Validation confirmed significantly increased ZNF652 expression in OA cartilage.

Conclusions:

• ZNF652 is implicated in OA pathogenesis and shows potential as a diagnostic and therapeutic target.
• ZNF652's mechanism involves regulating nitric oxide, macrophage activity, signaling pathways, and immune cell functions in OA.
• Further clinical validation and mechanistic studies are warranted.