Project summary
Type 2 diabetes is complex and some people’s risk of it is harder to spot. A key hidden factor is where fat is stored in the body, not simply how much there is. Genetics play a major role in this, but we still don’t fully understand how certain genetic changes cause fat to be stored in harmful places, like around vital organs. Dr Kashyap Amratlal Patel and their PhD student are investigating these genetic clues so we can better identify people with this hidden risk, enabling earlier and more personalised support to prevent type 2.
Background to research
Type 2 diabetes is a complex condition and it develops for a range of reasons, including genetics, age, ethnicity and sleep. While body weight does influence risk, the condition affects people of many different sizes.
Research shows that it’s not just body weight that matters, but also where the body stores fat. Some people store it more safely under the skin. While others store more fat in and around internal organs like the liver and pancreas. This can interfere with how these organs work to control blood sugar levels, raising the risk of type 2 diabetes.
Genes have a big influence on where fat is stored in the body, but we still don’t know exactly which genetic changes drive different fat storage patterns. And we currently don’t have a simple, reliable way to identify people with hidden higher-risk body fat patterns. This is particularly important for people with lower body weights, whose risk of type 2 might not be picked up by current risk checks.
Research aims
Dr Kashyap Amratlal Patel and their PhD student want to understand the genetic causes of harmful fat storage patterns and make it easier for doctors to identify people who have this hidden risk.
To do this, they will analyse large health and genetic datasets from people with and without type 2 diabetes, using existing information from major population studies like the UK Biobank. This includes information like complete DNA sequences, health records, and body scans showing where fat is stored in the body.
They will compare genetic patterns in people with different fat storage profiles to identify certain genetic variations that might drive more harmful fat storage. They will then combine simple clinical info like sex, BMI, and routine blood tests to develop a calculator that estimates the likelihood that someone has a high-risk fat storage pattern. Helping clinicians identify people who might otherwise be missed.
Potential benefit to people with diabetes
Because type 2 diabetes risk can look different from person to person, some people may not be picked up early enough to get the right support they need to reduce their risk.
This research aims to change that by improving how we identify people who have a higher risk of type 2 diabetes because of genetically driven body fat distribution. Earlier identification could allow people to access tailored support sooner, helping to reduce their risk of developing type 2 diabetes or related complications.
In the long run, understanding the biology behind these fat storage patterns could also support the development of new approaches to prevention and risk‑reduction, alongside informing future type 2 treatments.
