Research Question
The human eye not only represents a vital sensory organ but also acts as a crucial interface linking systemic health with genetic and environmental factors. Despite its significance, existing approaches to understanding the relationship between genetic predisposition, environmental exposures, and ocular health remain insufficient. Our research aims to bridge this gap by developing models that can predict the onset and progression of ocular and systemic diseases with high accuracy.
Objective
1.To establish multifaceted risk models that integrate multi-omic data with environmental factors, providing a comprehensive understanding of risk determinants for ocular and systemic diseases.
2.To develop advanced AI-driven diagnostic frameworks that leverage medical imaging, genetic data, and environmental inputs for enhanced prediction of disease outcomes.
Scientific Rationale
Recent advancements in non-invasive imaging techniques have allowed for a deeper understanding of how eye health is interconnected with overall bodily functions. Structures such as the cornea, retina, and lens offer direct insights into systemic conditions like cardiovascular diseases, neurodegenerative disorders, and metabolic conditions. Despite these advances, there is a notable lack of comprehensive studies combining genetic data, systemic biomarkers, and environmental factors to predict the onset of eye-related and broader systemic diseases. Current predictive models do not adequately account for the intricate interplay between genetics, epigenetics, environmental exposures, and clinical biomarkers. Using the extensive resources available through the UK Biobank, our research will focus on addressing these gaps by creating multimodal models that integrate genetic risk scores, lifestyle factors, and environmental influences. By understanding how these elements converge in disease pathways, we aim to improve both risk stratification and disease prognosis.