Combining genetic and phenotypic data in type 2 diabetes to deduce a genetic risk score
Principal Investigator:
Dr Ramesh Menon
Approved Research ID:
42406
Approval date:
January 28th 2019
Lay summary
Genome-wide association studies are useful in identifying genetic variants associated with human complex diseases. Polygenic risk score summarizes weights of multiple genetic loci associated with the disease. The goal of PRS is to stratify patients into risk categories based on their genetic mutations. Here, by utilizing the UKBiobank data, we aim to understand this relationship and to derive a polygenic risk score in diabetes, and the relationships between various traits/clinical observations and their associated risks. This new knowledge will lead to the development of new diagnosis, prevention and hopefully the identification of potential therapeutic targets, and improve the health of an aging population.