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Approved Research

A Polygenetic Risk Score Based Analysis of Gene-Drug Interactions Increasing Type Two Diabetes Risk.

Principal Investigator: Mr Jacob Armitage
Approved Research ID: 94215
Approval date: January 11th 2023

Lay summary

It has been shown through many population studies that Statin usage causes an increased risk of developing type two diabetes. Since Statins have been shown to be safe and effective at lowering the risk of cardiovascular disease, they will remain a widely used first line therapy for many people. Therefore, it is clinically relevant to understand the underlying mechanisms of this risk so both preventive and therapeutic actions can be taken.

To explore this risk, we propose to use polygenic risk scores - which describe someone's genetic predisposition for acquiring a certain disease. Overall, we want to see if those that have a higher genetic risk for certain diseases like diabetes or high cholesterol, have a higher than expected risk of developing new onset type two diabetes when taking Statins.

We have three main aims in this project, the first is to create a model to predict the risk of new onset type 2 diabetes using polygenic risk scores and other factors such as age, BMI and Statin usage. The second is to use this model to test for greater than expected diabetes risk in those taking Statins who have a high polygenetic risk score. And finally, if an interaction exists, test for interactions between single genetic variants that make up the polygenic risk score and Statin usage.

The results of this study may be able to identify what groups are at greater risk for increased diabetes susceptibility related to Statin usage and by what biological pathways this increased risk operates through. Having knowledge of what groups are at a higher risk may enable preventative measures to be taken to reduce this risk. Additionally, knowing what biological pathways this increased risk may be working through could provide insights into therapeutic actions that may be taken to mitigate risk.

This project will take approximately 2 years to complete.