Droplet digital PCR to detect beta cell death in Type 1 diabetes
A new equipment grant will help Dr Kathleen Gillespie and her team buy a ‘droplet digital PCR machine’ – a piece of new technology that will improve the sensitivity of tests to detect the death of beta cells. This could be a vital tool for ongoing studies to predict and prevent Type 1 diabetes.
Background to research
Type 1 diabetes occurs when the immune system attacks and kills insulin-producing beta cells in the pancreas. Dr Kathleen Gillespie and her team at the University of Bristol have developed tests that use genetic and immune markers to help predict when someone will develop Type 1 diabetes. However, these tests have so far not been effective for monitoring the impact of new Type 1 diabetes therapies in clinical trials. To do this more effectively they need a way to directly measure the death of beta cells. Recent studies have identified an insulin DNA sequence that exists only in beta cells and not in other cells of the body, and can be detected in the blood. Dr Gillespie’s team have developed a test that measures this DNA, but they want to make it more sensitive, so that it can accurately detect the death of individual beta cells.
A Diabetes UK equipment grant will help the researchers in Bristol buy a ‘droplet digital PCR machine’ – a piece of new technology that will improve the sensitivity of tests to detect the death of beta cells. The equipment will be used in many different studies of Type 1 diabetes and allow the researchers to detect very precisely how many insulin-producing cells are present, right down to the level of a single beta cell. The researchers will trial their new test using this equipment and adjust its design if necessary. If this is successful, they will move on to testing blood from people newly diagnosed with Type 1 diabetes from diagnosis onwards, as well as from people at risk.
Potential benefit to people with diabetes
The test developed as part of this work will allow researchers to test the blood of people at risk of Type 1 diabetes and people who have been recently diagnosed and follow them up to see how their islet cells change over time. Ultimately, it could become an essential tool for improving the effectiveness of ongoing studies to predict and prevent Type 1 diabetes.