Skin diseases are highly prevalent, often chronic, and frequently co-occur with systemic conditions such as cardiovascular disease, inflammatory bowel disease, and various malignancies. Approximately 30% of patients with skin disorders present at least one comorbidity, and their risk of cancer-related comorbidities is estimated to be two to five times higher than the general population. However, the underlying mechanisms remain poorly understood. This study aims to address three key questions: (1) What modifiable and genetic factors are associated with the onset of skin diseases and related comorbidities? (2) How do genetic predispositions interact with environmental triggers in influencing disease progression? (3) What shared biological mechanisms underlie these comorbidities?
To answer these questions, we will leverage the UK Biobank’s large-scale, multidimensional dataset-encompassing genetic, environmental, lifestyle, and clinical information-to identify key risk factors and infer causal relationships. We will apply advanced epidemiological and statistical methods, including Cox regression, GWAS, Mendelian randomization, and machine learning, to explore associations, interactions, and disease trajectories. This integrated approach will help uncover the complex interplay between genes and environment in skin disease etiology and comorbidity development. The findings are expected to provide a robust scientific foundation for early prevention, precise risk stratification, and the development of personalized intervention strategies, thereby improving patient outcomes and supporting public health efforts.