South Asians have a 2- to 3-fold higher risk of type 2 diabetes and coronary heart disease than White Europeans but may exhibit lower all-cause and cancer mortality (1,2). The reasons for these disparities remain unclear. Omics data-covering metabolomics, proteomics, and whole-genome sequencing-offer a robust lens to uncover the biological mechanisms behind these differences.
Data Sources
1. South Asia Biobank – ~100,000 South Asian participants in the UK, with up to 20 years of follow-up on lifestyle, environment, sociodemographic, clinical markers, genetics, and metabolomics (3).
2. UK Biobank – A large dataset including White Europeans and ~8,000 South Asians, with over 15 years of follow-up.
Research Questions
1. Which lifestyle, genetic, and omics factors best predict cardiovascular disease, type 2 diabetes, cancer, and all-cause mortality etc.?
2. How do these risk profiles differ between South Asians and White Europeans?
3. Can these findings be generalized or adapted to guide disease prevention in other ethnic groups?
Objectives
1. Integrate data from both cohorts to enhance statistical power and capture a broad range of genetic, environmental, and lifestyle factors.
2. Identify and validate key risk factors (e.g., lifestyle, polygenic risk scores, metabolic, and proteomic profiles) associated with disease in each ethnic group.
3. Compare risk factor contributions between South Asians and White Europeans to uncover the main drivers of observed health disparities.
Expected Impact
By clarifying how various risk factors shape disease trajectories, this research will inform targeted prevention strategies and personalized clinical interventions. Although focused on South Asians and White Europeans, insights gained may extend to other populations and guide broader public health measures.
References
1. Gholap N, et al. Primary Care Diabetes. 2011;5(2):45-56.
2. Bhopal RS, et al. PLoS Med. 2018;15(3):e1002515.
3. https://www.sabiobank.org/
