WGCNA and machine learning identify autophagy and senescence signature genes in osteoarthritis chondrocytes

Abstract

BACKGROUND: Autophagy and senescence are considered important factors in the pathogenesis of osteoarthritis, but their specific regulatory mechanisms remain unclear. OBJECTIVE: To screen autophagy- and senescence-related genes in osteoarthritis through bioinformatics analysis combined with machine learning methods, providing new molecular targets for early diagnosis and treatment of osteoarthritis. METHODS: Osteoarthritis-related datasets (including GSE51588, GSE169077, and GSE114007) were downloaded from the GEO database. Differential expression analysis, weighted gene co-expression network analysis, and functional enrichment analysis were performed to screen autophagy- and senescence-related genes in osteoarthritis. LASSO regression, random forest (RF), and support vector machine (SVM) were used to further screen potential core genes, and receiver operating characteristic curve analysis was used to evaluate the diagnostic value of core genes. Based on the GSE51588 dataset, the CIBERSORT algorithm was used to analyze the proportions of immune cell types such as T cell subsets, B cells, and macrophages in osteoarthritis and healthy control knee cartilage specimens. The expression of ubiquitin-conjugating enzyme E2I, ribosomal protein S6 kinase 1, interleukin-2 receptor beta chain, YEATS protein family member 4, histone H4 variant, and Toll-like receptor 3 was detected in the external validation set GSE114007. Clinical knee cartilage specimens from 5 osteoarthritis patients and 5 healthy controls were collected, and RT-qPCR was used to detect the mRNA expression of these genes. RESULTS AND CONCLUSION: (1) A total of 26 autophagy- and senescence-related differentially expressed genes were obtained. Functional enrichment analysis showed that these genes were mainly involved in biological processes such as cellular homeostasis, immune regulation, and cell death, and played important roles in multiple signaling pathways. Six key genes were screened by machine learning: ubiquitin-conjugating enzyme E2I, ribosomal protein S6 kinase 1, interleukin-2 receptor beta chain, YEATS protein family member 4, histone H4 variant, and Toll-like receptor 3. The area under the receiver operating characteristic curve (AUC) values of these genes were all greater than 0.8, indicating high diagnostic performance. Immune infiltration analysis showed that the infiltration of plasma cells, resting CD4 memory T cells, resting NK cells, monocytes, M2 macrophages, eosinophils, and neutrophils was significantly decreased in the osteoarthritis group, while the infiltration of follicular helper T cells, gamma delta T cells, activated NK cells, M1 macrophages, and resting dendritic cells was significantly increased. (2) In the external validation set, the expression of ubiquitin-conjugating enzyme E2I, interleukin-2 receptor beta chain, and Toll-like receptor 3 was higher in the osteoarthritis group than in the healthy control group (P < 0.05), while there was no significant difference in the expression of histone H4 variant, YEATS protein family member 4, and ribosomal protein S6 kinase 1 between the two groups (P > 0.05). In clinical samples, the mRNA expression of ribosomal protein S6 kinase 1, interleukin-2 receptor beta chain, YEATS protein family member 4, histone H4 variant, and Toll-like receptor 3 was higher in the osteoarthritis group than in the healthy control group (P < 0.05), while there was no significant difference in the expression of ubiquitin-conjugating enzyme E2I mRNA between the two groups (P > 0.05). (3) These results indicate that Toll-like receptor 3 and interleukin-2 receptor beta chain can serve as key genes for autophagy and senescence in osteoarthritis chondrocytes, and may become diagnostic molecular markers and potential therapeutic targets for osteoarthritis.

1. Introduction

Osteoarthritis is a common chronic degenerative joint disease that primarily affects the elderly population. With the global aging population, the prevalence and disability rate of osteoarthritis continue to rise, making it one of the leading causes of functional impairment and reduced quality of life worldwide [1-2]. Osteoarthritis is characterized by degeneration of articular cartilage, subchondral bone sclerosis, synovial inflammation, and osteophyte formation [3], with clinical manifestations including persistent joint pain, stiffness, limited mobility, and in severe cases, disability [4-5]. The pathogenesis of osteoarthritis is not fully understood; traditionally, it was considered to be mainly caused by mechanical wear, but recent studies have found that inflammation, cellular senescence, and autophagy dysfunction also play important roles in the development and progression of osteoarthritis [6]. Therefore, in-depth exploration of the pathogenesis of osteoarthritis and identification of potential molecular markers and therapeutic targets have become research priorities to delay disease progression and improve patient prognosis.

Chondrocyte senescence plays a key role in the development and progression of osteoarthritis [7]. Cellular senescence is characterized by permanent cell cycle arrest and increased secretion of pro-inflammatory molecules. The senescence-associated secretory phenotype (SASP) refers to the various pro-inflammatory cytokines, matrix metalloproteinases, and growth factors secreted by senescent cells, which can alter the local microenvironment, promote cartilage degradation and inflammatory responses, and thereby drive the progression of osteoarthritis [8-9]. Autophagy is an intracellular self-degradation mechanism that maintains cellular homeostasis by clearing damaged organelles and proteins [10]. In osteoarthritis, autophagy plays a crucial role in maintaining articular cartilage homeostasis and repairing damaged chondrocytes [3,11]. Studies have shown that autophagy is a double-edged sword: moderate autophagy can maintain cellular homeostasis by clearing damaged organelles and abnormal proteins, while excessive activation may exacerbate pathological processes. The accumulation of senescent cells in osteoarthritis has been proven to be a key factor leading to tissue dysfunction and aggravated inflammatory responses. However, how to precisely regulate autophagy activity in pathological conditions and balance its protective clearance and potential destructive effects remains a core challenge in osteoarthritis treatment research.