Predictive and integrative models for disease prevention using the UK Biobank Data
Principal Investigator: Dr Dheeraj Bobbili
Approved Research ID: 52446
Approval date: November 20th 2019
Currently, many diseases are diagnosed only after the appearance of clinical symptoms. However, in many cases a timely intervention could prevent or at least delay the disease. One example is hereditary hemochromatosis. The major risk factor is two mutated HFE genes inherited one from each parent. Although, many individuals may not develop the disease, simple lifestyle changes such as reducing the iron rich foods, medication or frequent blood donation could aid in reducing the risk of developing the disease. Such interventions are not hard to implement and may not require much effort from the individuals. Similar steps can be taken for other diseases such as cardiovascular, diabetes etc., Aim of the proposed project is to calculate the risk of an individual for a specific disease by combining different sources of data. Building such disease risk and stratification algorithms requires a significant amount of resources and effort. Hence we believe that a duration of 36 months is required to achieve the aims of this project. It is an ambitious project integrating various sources of information we require a 36 month access to the data. The mission of Megeno and goal of the proposed project is to help the general public in increasing their healthy lifespan. Our proposal will have significant impact on the healthcare system as it is extremely difficult to handle large number of individuals that will be identified to be at risk for several conditions. Hence, the proposed project will help manage such high numbers by allowing individuals to engage in personalized disease prevention.