Although aging has traditionally been viewed as the most important risk factor for osteoarthritis (OA), an increasing amount of epidemiological evidence has highlighted the association between metabolic abnormalities and OA, particularly in younger individuals. Metabolic abnormalities, such as obesity and type II diabetes, are strongly linked to OA, and they affect both weight-bearing and non-weight-bearing joints, thus suggesting that the pathogenesis of OA is more complicated than the mechanical stress induced by overweight. This review aims to explore the recent advances in research on the relationship between metabolic abnormalities and OA risk, including the impact of abnormal glucose and lipid metabolism, the potential pathogenesis and targeted therapeutic strategies.

Temporomandibular joint (TMJ) osteoarthritis (OA) is a type of TMJ disorders with clinical symptoms of pain, movement limitation, cartilage degeneration and joint dysfunction. This review article is aiming to summarize recent findings on signaling pathways involved in TMJ OA development and progression. Most recent findings in TMJ OA studies have been reviewed and cited. TMJ OA is caused by inflammation, abnormal mechanical loading and genetic abnormalities. The molecular mechanisms related to TMJ OA have been determined using different genetic mouse models. Recent studies demonstrated that several signaling pathways are involved in TMJ OA pathology, including Wnt/β-catenin, TGF-β and BMP, Indian Hedgehog, FGF, NF-κB, and Notch pathways, which are summarized in this review article. Alterations of these signaling pathways lead to the pathological changes in TMJ tissues, affecting cartilage matrix degradation, catabolic metabolism and chondrocyte apoptosis. Multiple signaling pathways were involved in the pathological process of TMJ OA. New therapeutic strategies, such as stem cell application, gene editing and other techniques may be utilized for TMJ OA treatment. TMJ OA is a most important subtype of TMJ disorders and may lead to substantial joint pain, dysfunction, dental malocclusion, and reduced health-related quality of life. This review article summarized current findings of signaling pathways involved in TMJ OA, including Wnt/β-catenin, TGF-β and BMP, Indian Hedgehog, FGF, NF-κB, and Notch pathways, to better understand the pathological mechanisms of TMJ OA and define the molecular targets for TMJ OA treatment.

Osteoarthritis (OA) is a degenerative joint disease with significant clinical and societal impact. Traditional diagnostic methods, including subjective clinical assessments and imaging techniques such as X-rays and MRIs, are often limited in their ability to detect early-stage OA or capture subtle joint changes. These limitations result in delayed diagnoses and inconsistent outcomes. Additionally, the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets, making it difficult to identify key molecular mechanisms and biomarkers. Recent advancements in artificial intelligence (AI) offer transformative potential to address these challenges. This review systematically explores the integration of AI into OA research, focusing on applications such as AI-driven early screening and risk prediction from electronic health records (EHR), automated grading and morphological analysis of imaging data, and biomarker discovery through multi-omics integration. By consolidating progress across clinical, imaging, and omics domains, this review provides a comprehensive perspective on how AI is reshaping OA research. The findings have the potential to drive innovations in personalized medicine and targeted interventions, addressing longstanding challenges in OA diagnosis and management.

Osteoarthritis (OA) is a painful degenerative joint disease and is the leading cause of chronic disability among elderly individuals. To improve the quality of life for patients with OA, the primary goal for OA treatment is to relieve the pain. During OA progression, nerve ingrowth was observed in synovial tissue and articular cartilage. These abnormal neonatal nerves act as nociceptors to detect OA pain signals. The molecular mechanisms for transmitting OA pain in the joint tissues to the central nerve system (CNS) is currently unknown. MicroRNA miR-204 has been demonstrated to maintain the homeostasis of joint tissues and have chondro-protective effect on OA pathogenesis. However, the role of miR-204 in OA pain has not been determined. In this study, we investigated interactions between chondrocytes and neural cells and evaluated the effect and mechanism of miR-204 delivered by exosome in the treatment of OA pain in an experimental OA mouse model. Our findings demonstrated that miR-204 could protect OA pain by inhibition of SP1- LDL Receptor Related Protein 1 (LRP1) signaling and blocking neuro-cartilage interaction in the joint. Our studies defined novel molecular targets for the treatment of OA pain.