Screening and validation of key genes associated with osteoarthritis.

Abstract

Background: Osteoarthritis is recognized as a common geriatric condition characterized by irregular chronic pain. Its prevalence is steadily increasing, posing significant challenges to global public health, while some studies indicate a trend towards younger individuals being affected. This condition severely impacts patients' quality of life.

Methods: Using the Gene Expression Omnibus (GEO) database, we downloaded datasets GSE114007, GSE169077, and GSE206848. We utilized R software to screen and confirm differentially expressed genes (DEGs) related to the development of osteoarthritis. A cross-analysis of the three datasets was conducted, with the least overlapping dataset, GSE206848, selected as the validation set. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the DEGs from GSE114007 and GSE169077. Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to identify modules closely associated with osteoarthritis, and genes from these intersecting modules were entered into the STRING database to construct Protein-Protein Interaction Networks. The top ten genes by connectivity were identified and validated using GSE206848. Key genes were identified and preliminarily validated using Quantitative Real-Time PCR (QPCR). Subsequent validation of related genes was carried out through Western Blot (WB) analysis.

Results: Differentially expressed genes were identified from the GSE114007 and GSE169077 datasets and validated in the GSE206848 dataset, with ANGPTL4 selected as the key gene. QPCR results indicated a significant difference in ANGPTL4 expression levels between normal and osteoarthritic chondrocytes. Western Blot analysis confirmed a significant difference in ANGPTL4 protein expression between normal and osteoarthritic chondrocytes.

Conclusion: Based on the experimental findings, ANGPTL4 appears to be a potential key gene in osteoarthritis.