A Bibliometric and Knowledge Map Analysis of Osteoarthritis Signaling Pathways from 2012 to 2022

Background: Osteoarthritis(OA) is one of the most common joint diseases, and signaling pathways play an essential role in the occurrence and development of OA, so it is significant to study OA with signaling pathways as an entry point. Purpose: This study aims to visualize and map the knowledge of OA-related signaling pathway research between 2012 and 2022, summarise and analyze the current research status and potential development trends in the domain, and provide a reference for future OA-related research. Methods: Retrieve relevant literature from the Web of Science database and use VOSviwer and CiteSpace software to visualize authors, institutions, country distribution, references, and keywords. The results are interpreted and analyzed in conjunction with the results obtained. Results: According to the search strategy, a total of 4894 articles were published between January 2012 and January 2022; during these ten years, the number of reports increased annually, and the research became further intensive; through this analysis, it was found that China is the most prolific country in this field; The institution with the most articles was Xi'an Jiaotong University from China, and the most prolific author was Tang Chih Hsin; Among the cited references, the reports of Glyn-Jones S and Hunter DJ were ranked first and second respectively. In the keyword analysis, cartilage and expression were the popular keywords; Animal model, akt, and platelet-rich plasma had the highest centrality; Burst analysis revealed pi3k, senescence, Ampk, and exosomes had received more attention in recent years of research. Conclusion: This study analyzes and summarizes the current research status and development trend of relevant signaling pathways in OA from the perspective of bibliometric and visual analysis, which can help researchers to keep track of hot topics and conduct more in-depth exploration of research hotspots and frontier knowledge areas.