Consensus cluster analysis of apoptosis-related genes in patients with osteoarthritis and their correlation with immune cell infiltration

Abstract

BackgroundOsteoarthritis (OA) progression involves multiple factors, including cartilage erosion as the basic pathological mechanism of degeneration, and is closely related to chondrocyte apoptosis. To analyze the correlation between apoptosis and OA development, we selected apoptosis genes from the differentially expressed genes (DEGs) between OA and normal samples from the Gene Expression Omnibus (GEO) database, used lasso regression analysis to identify characteristic genes, and performed consensus cluster analysis to further explore the pathogenesis of this disease.MethodsThe Gene expression profile datasets of OA samples, GSE12021 and GSE55235, were downloaded from GEO. The datasets were combined and analyzed for DEGs. Apoptosis-related genes (ARGs) were collected from the GeneCards database and intersected with DEGs for apoptosis-related DEGs (ARDEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to obtain characteristic genes, and a nomogram was constructed based on these genes. A consensus cluster analysis was performed to divide the patients into clusters. The immune characteristics, functional enrichment, and immune infiltration statuses of the clusters were compared. In addition, a protein–protein interaction network of mRNA drugs, mRNA-transcription factors (TFs), and mRNA-miRNAs was constructed.ResultsA total of 95 DEGs were identified, of which 47 were upregulated and 48 were downregulated, and 31 hub genes were selected as ARDEGs. LASSO regression analysis revealed nine characteristic genes: growth differentiation factor 15 (GDF15), NAMPT, TLR7, CXCL2, KLF2, REV3L, KLF9, THBD, and MTHFD2. Clusters A and B were identified, and neutrophil activation and neutrophil activation involved in the immune response were highly enriched in Cluster B, whereas protein repair and purine salvage signal pathways were enriched in Cluster A. The number of activated natural killer cells in Cluster B was significantly higher than that in Cluster A. GDF15 and KLF9 interacted with 193 and 32 TFs, respectively, and CXCL2 and REV3L interacted with 48 and 82 miRNAs, respectively.ConclusionARGs could predict the occurrence of OA and may be related to different degrees of OA progression.

Bioinformatic analysis combined with immune infiltration to explore osteoarthritis biomarkers and drug prediction

“…In addition, NK motif 2D promotes the production of pro-inflammatory effects of Th1 and Th17, causing antigen-induced Guillain-Barré. [ 10 ] The infiltration of these immune cells is an important cause of various inflammatory conditions, so treating OA in terms of immune modulation may also be a new therapeutic target. We will further search for suitable drugs to modulate immune-related targets for the treatment of OA in subsequent research.…”

“…[ 9 ] This implies that one of the factors pertaining to the advancement of arthritis that must be examined is cell death. [ 10 ] This might have something to do with the body’s aberrant general metabolic status, which causes cellular abnormalities in the joints and many fatalities.…”