Identification of ion channel-related genes as diagnostic markers and potential therapeutic targets for osteoarthritis through bioinformatics and machine learning-based approaches

Abstract

Background

Osteoarthritis (OA) is a debilitating joint disorder characterized by the progressive degeneration of articular cartilage. Although the role of ion channels in OA pathogenesis is increasingly recognized, diagnostic markers and targeted therapies remain limited.

Methods

In this study, we analyzed the GSE48556 dataset to identify differentially expressed ion channel-related genes (DEGs) in OA and normal controls. We employed machine learning algorithms, least absolute shrinkage and selection operator(LASSO), and support vector machine recursive feature elimination(SVM-RFE) to select potential diagnostic markers. Then the gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential diagnostic markers’ involvement in biological pathways. Finally, weighted gene co-expression network analysis (WGCNA) was used to identify key genes associated with OA.

Results

We identified a total of 47 DEGs, with the majority involved in transient receptor potential (TRP) pathways. Seven genes (CHRNA4, GABRE, HTR3B, KCNG2, KCNJ2, LRRC8C, and TRPM5) were identified as the best characteristic genes for distinguishing OA from healthy samples. We performed clustering analysis and identified two distinct subtypes of OA, C1, and C2, with differential gene expression and immune cell infiltration profiles. Then we identified three key genes (PPP1R3D, ZNF101, and LOC651309) associated with OA. We constructed a prediction model using these genes and validated it using the GSE46750 dataset, demonstrating reasonable accuracy and specificity.

Conclusions

Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer potential diagnostic markers and therapeutic targets for the treatment of OA.

CLINICAL SIGNIFICANCE

• As society ages, the incidence of knee osteoarthritis continues to rise, bringing with it a series of social impacts and medical pressure. Despite the increasing recognition of the role of ion channels in the pathogenesis of OA, diagnostic markers and targeted therapies remain limited.

• This study investigated the role of TRP as possible diagnostic tools for OA.

• Seven TRP-related genes were identified as the best traits to distinguish OA from healthy samples, and then we constructed and validated risk scores for three key genes (PPP1R3D, ZNF101, and LOC651309) relevant to OA ion channel gene modules.

• Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer a reference for further clinical diagnosis.

Keywords:

• Osteoarthritis
• transient receptor potential
• ion channel
• immune cell infiltration
• diagnostic markers
• bioinformatics

Authors’ contributions

All authors contributed to the study conception and design. Conceptualization, Liu Yongming and Xiong Yizhe.; methodology, Liu Yongming.; software, Liu Yongming; validation, Xiong Yizhe, Wang Yupeng and Qian Zhikai; formal analysis, Xiong Yizhe.; investigation, Yin Mengyuan.; resources, Qian Zhikai; data curation, Yin Mengyuan.; writing—original draft preparation, Liu Yongming; writing—review and editing, Wang Xiang; visualization, Du Guoqing; supervision, Zhan Hongsheng.; project administration, Wang Xiang; funding acquisition, Du Guoqing, and Zhan Hongsheng. All authors have read and agreed to the published version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s). The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This research was funded by the National Natural Science Foundation of China (82174403, 82074466, 82374488); the Summit Plateau Team Project in Traumatology of Shanghai University of TCM, Shanghai Chronic Musculoskeletal Disease Clinical Medical Research Center (20MC1920600); Clinical study of traditional Chinese medicine manipulation in the treatment of the Frozen Shoulder (22Y21920200); Shanghai clinical specialty “traditional Chinese medicine orthopaedic traumatology” (shslczdzk03901); the second-round construction project of the National Traditional Chinese Medicine Academic School Inheritance Studio “Shi’s Traumatology Department”; the innovation team of “Research and Transformation of Chronic Musculoskeletal Diseases” in Shanghai’s high-level local universities (Shanghai Education Commission [2022] No. 3); “Shanghai School of Traditional Chinese Medicine Inheritance” Extension Plan” (ZY(2021-2023)-0209-02), Zhan Hongsheng National Famous Veteran Traditional Chinese Medicine Expert Inheritance Studio Construction Project (2022-75).