Genetic Variant Identification May Improve Drug Development

Study finds new technique may improve treatment of diabetes.

A new technique that involves identifying genetic variants may help identify side effects early and reduce investigational drugs from failing in the later stages of clinical trials.

The approach identifies genetic variants that mimic a drug’s action on its intended target and then are checked in large patient cohorts to see if the variants were associated with risk of other conditions, such as cardiovascular disease.

Published in Science Translational Medicine, researchers analyzed genetic variations in DNA encoding drug targets for type 2 diabetes and obesity in nearly 12,000 patients.

Researchers found a variant in the glucose-lowering glucagon-like peptide-1 receptor (GLP1R) gene that seemed to mimic the action of the diabetes drugs. The results were confirmed after testing 40,000 more participants. Next, available genetic data from an international data-sharing consortium was used to study the variant in nearly 62,000 people with coronary disease and more than 160,000 controls.

The results of the study showed that the variant reduced the risk of heart disease.

“This further suggests that human genetics can support the development of new therapies, and can offer insights into their safety profile early in the development process,” said first study author Robert Scott.

Currently long term, large scale, randomized, controlled clinical trials are being conducted to evaluate the cardiovascular safety or GLP1R-agonsits. Additionally, results from a large trial are expected to be released later this month.

“Researching and developing new medicines is a lengthy, expensive and risky journey, and any insights we can gain in to the processes of the body related to disease could help improve our ability to succeed,” said joint senior study author Dawn Waterworth. “By pooling our resources and expertise in collaborations like this one with Cambridge University, we believe there's an opportunity to expand our knowledge of disease biology, which in turn could help reduce the risk of late-stage failures and accelerate the development of innovative new treatments for patients.”