Research Questions: Can integrating genetic, protein, and metabolic data with clinical information improve the prediction of who will develop major non-communicable diseases (NCDs) like heart disease, diabetes, chronic lung disease, and common cancers? Furthermore, in people already diagnosed, can these molecular data identify who is at highest risk of mortality?
Objectives: This project aims to: 1) Develop and validate integrated risk models for the incidence of cardiovascular disease, type 2 diabetes, chronic obstructive pulmonary disease, and common cancers (e.g., lung, breast, prostate ). 2) Identify protein and metabolite biomarkers in the blood that are associated with survival after an NCD diagnosis. 3) Explore the biological pathways these biomarkers are involved in to better understand disease mechanisms.
Scientific Rationale: NCDs, including cancers, are a leading global health burden. While lifestyle factors are important, current tools to predict who will get sick or have a poor outcome are imperfect. The UK Biobank, with its vast collection of health data, genetic information, and new molecular measurements (proteomics and metabolomics) from hundreds of thousands of participants, provides a unique opportunity to discover novel biomarkers across a spectrum of major diseases. By combining these different types of data using advanced statistical methods, we hope to create a more complete picture of disease risk and progression, moving towards more personalised healthcare.
