Osteoarthritis (OA) and osteoporosis (OP) are both degenerative diseases that are related to age and more common in older women [1]. OA can affect the entire synovial joint, typically manifesting as articular cartilage damage, subchondral bone degeneration, synovial and tissue vascular proliferation, and reduced tendon and ligament stability [2, 3]. Articular cartilage undertakes joint load transfer and buffers and protects subchondral bone by virtue of its unique mechanical properties. With the influence of factors such as age and mechanical overload, its structure and mechanical properties change, resulting in progressive degeneration of joint tissue [4]. OA can cause cartilage structure damage, increase joint friction, reduce bearing capacity, and accelerate cartilage degradation [5]. In the process of joint degeneration, the imbalance of trace element homeostasis can regulate oxidative stress, inflammatory response, and apoptosis, and participate in cartilage tissue injury and joint degeneration [6]. OP is primarily characterized by impaired bone strength and deterioration of bone tissue [7–9]. Studies have found that OA can cause morning stiffness, joint swelling and even deformity, joint pain, and tenderness [10], and OP can increase the risk of fracture [11]. Traditionally, OP and OA are considered to be two independent and inversely related diseases. OP can reduce the incidence of OA (including knee OA and hip OA) [12, 13]. However, more and more evidence shows that OP and OA comorbidity is not a simple superposition of two diseases. They share multiple risk factors, including oxidative stress, inflammation, and apoptosis, and there is a causal relationship between them [14]. The essence is the disorder of the osteochondral unit, with the destruction of the subchondral bone microenvironment as the core [15]. OP and OA comorbidity is common in postmenopausal women with estrogen deficiency. Estrogen deficiency is the core common driving factor of OP and OA comorbidity, which can integrate and activate inflammation, oxidative stress, and apoptosis pathways, resulting in the overall damage of the osteochondral unit [16]. With aging, the risk of OP and OA comorbidity significantly rises, reducing the quality of life of patients and increasing the economic burden [12]. Therefore, OP and OA comorbidity cannot be simply treated according to the diagnosis and treatment principles of isolated OP or OA, but constitutes a unique and important clinical and scientific problem, which is worthy of further study.

In recent years, OP and OA comorbidity has attracted increasing attention in the medical community and has emerged as a key research focus. Although its clinical significance has been recognized, at present, this field focuses more on the interpretation of a single pathway or local pathological mechanism and lacks a systematic quantitative analysis of the overall research pattern, hot spot evolution, and frontier direction in this field. For example, the pathogenesis, pathological location, diagnosis, and treatment of comorbidity need further investigation. Therefore, it is of great significance to sort out the results of research in the field of OP and OA comorbidity, which is conducive to the future development of this field. Bibliometric visualization can objectively reveal the research hotspots and evolution trends in this field and provide a reference for the optimization of diagnosis and treatment strategies for OP and OA comorbidity patients.

The flowchart for literature screening is shown in Figure 1. This paper used Web of Science (Core Collection) as the data source, SCI-E and SSCI as the indexes, and the search formula was TS= ((“osteoporosis” OR “porosis” OR “OP”) AND (“osteoarthritis” OR “osteoarthrosis” OR “OA”)). The search period was 2005-01-01–2025-12-31, and the literature types were Article and Review. A total of 3,167 articles were retrieved. The screening language was English, and the literature types Early Access, Proceedings Paper, Book Chapters, and duplicate literature were excluded. And 3,031 articles were selected. After CiteSpace deduplication, 10 articles marked as 2026 by Web of Science were found. Because the research time had been exceeded, they were manually excluded. Finally, 3,021 articles were retrieved and exported in plain text format, and the retrieval data are documented in Supplementary material 1 and Supplementary material 2. Sensitivity analysis was carried out under the same database and CiteSpace parameters, and only comorbidity-related search terms were added to the search formula (Supplementary material 3). A total of 304 valid articles were obtained by the restricted search. The keyword clustering results no longer show clusters of stem cells and subchondral bone. The reason is that a strict search will rule out literature that only studies the pathological mechanism of OP or OA. Therefore, this study used a relatively broad search strategy to carry out the main analysis to show the complete research landscape. No full‑text‑based topic screening was performed on the main dataset, and the restricted dataset is only used for robustness evaluation.

The method used in this study was bibliometrics. Bibliometrics is a statistical analysis that describes or displays relationships among published information, such as books, documents, and other publications [17]. Since 1958, bibliometrics has gradually become a core research method for research groups across various fields worldwide [18]. In this study, CiteSpace (version 7.0.1) and VOSviewer (version 1.6.20) were used to analyze the retrieved literature. CiteSpace provides detailed literature and clear research results, serving as an important reference for scholars to deepen their understanding of research progress in this field, promote academic exchange, and grasp research trends [19]. CiteSpace is primarily used for co-citation analysis, generating a timeline diagram, and detecting burst words within a time slice [20]. VOSviewer can use citation data to generate a network diagram of authors, countries, journals, and related entities, and to construct a keyword correlation map based on co-occurrence data analysis [21]. In this study, CiteSpace was used to analyze keywords. The Time Slice was set to 2005–2025. #Years Per Slice was set to 1 year. Term Source was set to select the Title, Abstract, Author Keywords (DE), and Keyword Plus (ID). The Node Type was the keyword, and the selection criterion was g-index (k = 2).

In this study, CiteSpace and VOSviewer were used to systematically and comprehensively analyze the literature on OP and OA comorbidity. Over the past 20 years, the number of publications in this field has increased steadily. In 2025, it exceeded 300 for the first time, indicating that this field has received more and more academic attention and is a very promising field. At present, many countries around the world are carrying out research on the relationship between OP and OA comorbidity. Although China has published the largest number of publications, the research influence still needs to be improved. Therefore, it is necessary to strengthen academic research and establish academic cooperation with other countries. Universities are the main research institutions, but there is a lack of cooperation between these institutions and authors. Therefore, international exchanges and cooperation among institutions, authors, and countries should be strengthened to improve research quality and promote the generalizability of research results.

According to keyword clustering and timeline analysis, stem cells and subchondral bone are long-term research hotspots in this field. There is evidence that subchondral bone, as the core structure of the osteochondral unit, not only undertakes the function of mechanical conduction, but also regulates the differentiation fate of bone marrow MSCs by constructing a local microenvironment. The plasticity of cell fate regulated by the subchondral bone microenvironment is the key mechanism of OP and OA comorbidity [15]. Studies have found that OP is characterized by trabecular bone remodeling and absorption, while OA is characterized by articular cartilage and subchondral bone remodeling. The integrity of articular cartilage function mainly depends on the mechanical properties of subchondral bone [28, 29]. Subchondral bone not only provides mechanical support for joints but also maintains joint health by promoting material exchange between bone and cartilage. OP and OA comorbidity is a special type of OA characterized by a significant decrease in subchondral BMD [30]. Another experiment used mice with OA and OP to demonstrate that the coexistence of OP in OA mice can increase the activity of subchondral bone cells, thereby exacerbating the pathological process of OA in calcified cartilage and subchondral trabecular bone [31]. MSCs are a main focus in stem cell research. MSCs are a class of fibroblast-like cells with self-renewal and multi-directional differentiation potential. They can migrate to the injured site and promote tissue repair by secreting anti-inflammatory factors and growth factors. Therefore, MSC-derived extracellular vesicles are safe for the treatment of comorbidities, are easy to store and manage, and promote fracture healing and bone tissue regeneration for bone‑joint‑related disorders [32, 33].

MSCs, oxidative stress, inflammation, apoptosis, and cells have become the main research directions. The inflammatory response also contributes to the comorbidity of OP and OA. Among them, osteopontin (OPN) is an important inflammatory factor. Its high expression may lead to bone erosion and cartilage degradation in OA and is closely associated with pain and pathological changes in OP. Decreased OPN activity may increase the risk of fracture in OP patients, especially postmenopausal women [34]. On the one hand, oxidative stress interacts with factors such as cell aging, mitochondrial dysfunction, and metabolic disorders to jointly promote the progressive destruction of OA joint structure and increase bone fragility in OP patients [35]. On the other hand, it can also activate apoptosis, induce apoptosis of bone and cartilage cells, reduce bone regeneration ability, and aggravate bone mass loss [16].

Although important progress has been made in the field of OP and OA comorbidity, there are still many challenges in this field. 1) The association between OA and OP is non-linear, variable, and affected by many factors. The complete pathological process of comorbidity cannot be explained only based on systemic bone loss. 2) There is a lack of ideal animal models for comorbidity, and it is difficult to reproduce the real pathological process of OA and OP comorbidity. 3) The role of key signaling pathways is affected by the environment, and the conclusions obtained under certain conditions cannot be extended to all comorbidity scenarios [15]. 4) The clinical symptoms of OP and OA comorbidity overlap, the imaging manifestations are complex, and the risk factors and cellular and molecular pathways are shared, which makes the differential diagnosis of the disease and the clinical evaluation and management difficult [16]. These challenges are also the main research directions in the future.

In the future, researchers should focus on the pathogenesis and treatment of OP and OA comorbidity, clarify the relationship between MSC-related comorbidity treatment and BMD, inflammation, and oxidative stress, and build an extensive international exchange and cooperation network to benefit patients with the comorbidity.

There are still some limitations in this study. First, this study analyzed only English-language literature in the Web of Science database, potentially overlooking relevant studies published in other databases (such as PubMed and Scopus) or in non-English journals. Secondly, this study used CiteSpace and VOSviewer for analysis. Both require researchers to manually adjust parameters, which may introduce subjective bias into the results. Thirdly, the analysis primarily focused on quantitative metrics (such as publication volume and citation counts), making it difficult to distinguish research quality. Fourth, the retrieval formula of this study is relatively broad, and the comorbidity theme is not strictly limited, which leads to a certain degree of deviation in the dataset, and some literature that only studies OP or OA alone is included. At the same time, a small number of non-target disease-related literature, such as rheumatoid arthritis, were included, and there was data noise. Finally, this study is subject to time-lag bias, which naturally favors older publications and may underrepresent the impact of recent creative work.