Oral diseases are common, multifactorial conditions influenced by both genetic susceptibility and modifiable lifestyle factors such as smoking, alcohol consumption, dietary habits, oral hygiene, and metabolic health. While the role of lifestyle in oral health is well established, inter-individual variation in disease risk suggests that gene-lifestyle interactions may contribute significantly to disease onset and progression. This project aims to investigate whether genetic variants modify the effects of lifestyle factors on the risk and clinical outcomes of oral diseases. The specific objectives are: (1) to identify genetic variants that interact with lifestyle exposures in influencing oral disease incidence; (2) to examine gene-lifestyle interactions associated with adverse oral health outcomes using self-reported oral health data and hospital-based diagnoses; and (3) to evaluate whether incorporating gene-lifestyle interactions improves oral disease risk prediction models. Utilizing the UK Biobank’s comprehensive dataset, including genome-wide genotyping, detailed lifestyle and dietary assessments, and linked hospital and cancer registry records, we will conduct genome-wide interaction studies and apply machine learning approaches to detect and validate meaningful interactions. Despite the absence of clinical dental examinations, the available self-reported and hospital-based data provide robust endpoints for analysis. This research will enhance our understanding of how genetic predisposition interacts with lifestyle to influence oral disease risk, with potential applications in precision oral health prevention and risk stratification.
