This study aims to unravel the complex interplay of genetic susceptibility, environmental exposures, and behavioral patterns in the development and progression of immune-mediated inflammatory skin diseases (IMISDs), such as psoriasis and atopic dermatitis. Leveraging UK Biobank’s unparalleled multimodal data resource, we will systematically address three critical gaps in current research: (1) how non-genetic factors modify inherited disease risks, (2) the biological pathways mediating these interactions, and (3) strategies for personalized prevention.
Phase 1: Multidimensional Data Integration
We will harmonize UK Biobank’s core datasets:
Genetic profiles: Genome-wide genotyping data to identify disease-associated variants and construct polygenic risk scores.
Environmental exposures: Geospatial air quality metrics (NO2, PM2.5), ultraviolet radiation indices, and residential history records.
Behavioral/lifestyle factors: Longitudinal questionnaire data on smoking, sleep patterns, stress levels, and dietary habits.
Clinical endpoints: Hospital diagnoses (ICD-10 codes), imaging data, and plasma biomarkers.
Phase 2: Mechanistic Modeling
Advanced analytical approaches will be employed:
Interaction detection: Machine learning to identify high-risk subgroups where environmental/behavioral exposures amplify genetic predisposition.
Pathway analysis: Mendelian randomization and structural equation modeling to disentangle causal relationships between exposures, immune dysregulation , and clinical outcomes.
