Abstract
BACKGROUND: The study of chronic gouty arthritis (CGA) is limited by the absence of animal models that faithfully mimic its chronic progression. Existing models fail to capture the transition from acute flares to chronic joint damage, highlighting the need for a more representative model. METHODS: A novel CGA model was established in SD rats using a combined strategy. Chronic hyperuricemia was induced via a diet containing 2% potassium oxonate and 12% yeast. This was supplemented with twice-weekly gavage of hypoxanthine to simulate acute uric acid fluctuations, followed by intra-articular injections of monosodium urate (MSU) crystals into the ankle and plantar region. This protocol lasted 10 weeks. Rats were divided into control, model, and allopurinol treatment groups. Evaluations included serum uric acid monitoring, joint swelling and inflammation scores, hindlimb hanging tests, histopathology, micro-CT, and inflammatory cytokine assays. RESULTS: The model group exhibited sustained hyperuricemia with acute fluctuations, persistent joint swelling, significantly elevated inflammation scores (P<0.0001), and reduced hanging time (P<0.0001), indicating chronic pain and functional impairment. Histology revealed synovial hyperplasia, inflammatory cell infiltration, and cartilage damage. Micro-CT confirmed significant bone erosion, evidenced by an increased bone surface/bone volume ratio (P<0.001). Serum levels of IL-1β, TNF-α, and IL-6 were significantly elevated. Allopurinol treatment effectively lowered uric acid and alleviated joint swelling and bone erosion. CONCLUSION: This study successfully established and systematically characterized the phenotypic features of a CGA rat model that integrates chronic hyperuricemia, acute uric acid fluctuations, and local MSU crystal deposition. Phenotypically, this model recapitulates the core features of human CGA, including joint swelling, bone erosion, and functional impairment, thereby providing an experimental platform for investigating chronic joint damage induced by multiple interacting factors.