Approved Research

A machine-learning based PRS model predicting risk of developing diabetic nephropathy and hypertension in diabetes patients

Lay summary

The diabetic and hypertensive-related nephropathy is a serious life-threatening condition. Catching the condition early and taking actions in advance can help slow down or even stop the progression of these diseases. Diabetic DN and hypertension are affected by many genetic changes, and non-genetic features frequently mentioned as social and environmental factors. A polygenic risk score is a score that can estimate a person's risk for developing a disease based on their genetics or DNA. This is often displayed in a way that tells how at risk a person is for a specific condition. The proposed study is to investigate these changes and factors to understand the role that genetic and environmental factors play in developing diabetic DN and hypertension across different populations. The expected value of this study is to produce a novel scoring system to predict the risk of developing diabetic DN and hypertension in diabetes patients, based on the total number of changes and other information that is related to this condition. Our goal is to provide an accurate risk assessment tool that can help diabetes patients to manage their personal risk for developing diabetic DN and hypertension. The proposed duration of this study is 2 or 3 years.