Our research seeks to explore the complex associations between environmental factors, biomarkers, lifestyle, and multi-omics on osteoarthritis risk. We aim to understand how these multifaceted elements interact and contribute to the onset and structural progression of osteoarthritis. Additionally, we will examine the potential mediating role of systemic inflammation, metabolic dysregulation, and epigenetic modification in the context of obesity, which often coexist with osteoarthritis and further complicate the clinical landscape. By creating predictive models that integrate environmental exposures, biological signatures, lifestyle, and multi-omics, we hope to improve early detection and prevention strategies for osteoarthritis and identify potential therapeutic targets to optimise patient outcomes.
The multifactorial nature of osteoarthritis risk is increasingly recognised, with adiposity, physical inactivity, diet, and genetic susceptibility all contributing to cartilage degradation and subchondral bone changes. However, the interplay between these factors and their cumulative impact on disease initiation and progression remains unclear. Advances in high-throughput biomarker profiling, metabolomics, and radiomics now offer new tools for assessing osteoarthritis risk, yet their integration into predictive algorithms and clinical practice is still limited. Moreover, common comorbidities such as obesity, metabolic syndrome further modulate osteoarthritis risk, yet the mechanisms through which they interact with molecular pathways are not fully understood. Developing predictive frameworks that combine environmental factors, biomarkers, lifestyle, and multi-omics data is therefore essential to refine risk stratification, guide targeted interventions and ultimately reduce the global burden of osteoarthritis.
