Integration of genetic, biochemical and life style data to generate composite health scores for individuals of Indian ancestry
Approved Research ID: 81481
Approval date: February 15th 2022
Scientific rationale: Integration of genetic data with biochemical and lifestyle data holds great promise in identifying at-risk individuals, early intervention to guide them towards healthier lifestyles and in better treatment management. Machine learning algorithms are now widely used in combining and analyzing this growing quantity of data. The algorithms not only help in selecting the factors that best discriminate patients from normal individuals but also help in generating risk scores for various diseases. These risk scores can be used by clinicians to stratify the patients and to make precise treatment decisions. Also, combining the risk scores from multiple diseases helps to comprehend general health risk of individuals. But there are no large scale genetic studies done on Indian population to understand the genetic variations associated with diseases in this population. So, along with our in-house database, we would like to utilize the power of UK Biobank to identify the most-significant genetic variations in Indian population, and to build algorithms that can generate comprehensive health scores.
Aims: 1) identify genetic determinants of various diseases in Indian population, and generate disease-specific risk scores as the combined effect of all the genetic variants; 3) integrate the genetic risk scores with biochemical, demographic and lifestyle data to generate sex-specific and disease-specific risk scores; 4) combine the risk scores from multiple diseases to develop a composite health score that will enable patient stratification and help in suggesting preventive measures; 5) identify genetic differences between Indian population and other populations
Project duration: Project will be completed in 3 years (36 months)
Health impact: The research will be useful to identify the genetic determinants of various diseases in Indian population. It will guide clinicians in identifying individuals at greater risk of disease, in suggesting preventive measures and in treatment choices. It will help to translate genetic research to clinical practice. It will facilitate further collaborative projects in healthcare domain. It will also enable further research to discover genetic differences across populations. It will bring huge opportunity to improvise Indian health care system.