Screening of Biomarkers for Osteoarthritis and Establishment of a Multidimensional Data Based Early Diagnostic Method

Osteoarthritis (OA), the most common degenerative joint disease worldwide, is witnessing an increasingly severe epidemiological trend in China driven by population aging and shifts in lifestyle. According to the Global Burden of Disease (GBD) data, the number of OA patients in China has risen from 26.1 million in 1990 to 61.2 million in 2019, ranking first globally, and is projected to exceed 200 million by 2044. The prevalence of OA increases markedly with age, affecting over 50% of individuals aged 65 years and older. Women exhibit a higher incidence than men, especially after menopause, and tend to suffer from more severe structural lesions and clinical symptoms. The knee joint is the most frequently affected site, followed by the hands, hips and other joints.

OA not only causes pain, loss of joint function and impaired quality of life, but also represents the leading cause of disability in the population aged over 60. In 2019, the age-standardized disability-adjusted life years (DALYs) of OA in China reached 224.78 per 100,000 population, a 9.4% increase compared with 1990. Notably, the disease burden of knee and hip OA related to elevated body mass index (BMI) has increased substantially in males, and the growth rate of DALYs attributable to high BMI is higher for hip OA than for knee OA. Meanwhile, the disease burden of hand OA is also on the rise among females.

Major risk factors for OA include advanced age, obesity, joint injury and occupational strain such as sedentary behavior and repetitive weight-bearing activities. Since the reform and opening-up, China has achieved rapid economic development and a remarkable extension in life expectancy. By the end of 2024, the population aged 65 and above had reached 220 million, accounting for 15.6% of the total population; life expectancy is expected to reach 81.3 years by 2035. In parallel, behavioral risk factors closely linked to OA, including a sedentary lifestyle, insufficient physical activity, unhealthy dietary patterns, elevated BMI, smoking and alcohol consumption, have become increasingly prevalent. Under the combined effect of population aging and unhealthy lifestyles, the incidence, prevalence and overall disease burden of OA are predicted to climb continuously. This places a heavy burden on the healthcare system and poses a major challenge to the achievement of the Healthy China Initiative.

Current clinical management of OA is confronted with two core bottlenecks. First, there is a scarcity of early diagnostic biomarkers and individualized prediction tools. Most patients seek medical care only after obvious symptoms emerge, by which time irreversible structural damage to joints has already developed. Second, OA is a highly heterogeneous disease. The pathogenesis of OA at different anatomical sites (knee, hip, hand, etc.) involves the complex interaction of multiple factors including mechanical overload, low-grade inflammation and metabolic disorders. Consequently, there are currently no effective therapies capable of reversing disease progression, and clinical interventions remain limited to symptomatic relief.

Accordingly, the establishment of a specialized OA cohort is of critical importance. By systematically collecting high-risk factors, clinical phenotypes, imaging findings, biological specimens (blood, synovial fluid, joint tissue, etc.) and multi-omics data, the specialized cohort will facilitate precision prevention and treatment of OA in the following aspects: 1. Identification of novel biomarkers for early diagnosis and prognostic evaluation; 2. Construction of artificial intelligence-assisted individualized diagnosis and prediction models, which integrate multidimensional data to realize early disease warning, progression risk stratification and treatment response prediction.