Scientific Rationale:
Affective, anxiety, and trauma-related disorders are leading causes of disability with complex, heterogeneous etiologies. Current research is often fragmented, failing to capture the interplay of risk factors over time. A critical gap exists in understanding the longitudinal trajectories of these conditions. This project will leverage the UK Biobank’s unique multimodal data to build an integrative biopsychosocial model, aiming to uncover the mechanisms that drive illness and resilience.
Research Questions:
1. How do genetic predispositions, environmental factors, and lifestyle behaviors (e.g., sleep, activity) interact to shape the developmental trajectories of these disorders?
2. What are the core biological mechanisms, including physiological and neurobiological pathways, that mediate these risk trajectories?
3. Can we synthesize these high-dimensional, multi-modal data to accurately predict an individual’s risk and identify novel, modifiable targets for intervention?
Objectives:
1. To Map Longitudinal Trajectories: We will integrate genetic data (Polygenic Risk Scores), health records, and objective lifestyle measures from accelerometry to identify and characterize distinct temporal patterns of risk and symptoms.
2. To Investigate Biological Mechanisms: We will analyze biochemical markers (from blood/urine assays) to probe the role of mediating physiological pathways (e.g., inflammation). This provides the foundation for future investigation into neurobiological substrates.
3. To Develop Predictive and Interventional Models: We will employ machine learning algorithms to build robust, integrative models that predict individual risk. The ultimate goal is to pinpoint the most impactful and modifiable targets for personalized interventions.