New Genetic Test Predicts Type 1 Diabetes Risk More Accurately in Non-European Populations

Polygenic scores are tests that estimate a person's genetic risk for developing type 1 diabetes by looking at many genetic variations across the genome. For decades, however, most of these tests were developed using data from people of European ancestry. This matters because genetic variation differs across populations, meaning a test optimized for one group may not work as well for another.

This limitation has left people of non-European ancestry with less accurate genetic risk predictions—a disparity that undercuts efforts to provide equitable, personalized medicine to all communities.

Scientists evaluated seven different polygenic scores for type 1 diabetes in large patient databases that included people of diverse ancestry. They tested how well each score could correctly identify who had type 1 diabetes and who did not, using a statistical measure called the area under the curve (AUC).

Two scores stood out in initial testing: T1D GRS2 and T1D MAPS. Researchers then examined these two more closely across five medical biobanks, analyzing data from nearly 2,800 people with type 1 diabetes and over 546,000 controls.

The results showed that T1D MAPS performed about as well as T1D GRS2 in European ancestry populations. But in non-European populations, T1D MAPS performed significantly better—showing notably improved discrimination in identifying who was at risk.

This improvement came from using genetic data from people of multiple ancestries when building the T1D MAPS score, a multi-ancestry approach that better captures genetic variation across different populations.

More accurate genetic risk prediction tools benefit everyone. For families of diverse backgrounds, a better test could mean earlier identification of relatives at risk for type 1 diabetes, potentially opening doors to screening and early intervention programs.

These findings underscore the importance of including diverse populations in genetic research. As genetic tools become more widely used in clinical practice, ensuring they work fairly across all communities is essential to precision medicine and health equity.

Source: medRxiv : the preprint server for health sciences. Evidence type: PubMed indexed literature. Type1Cure is an information and intelligence hub, not a medical advice service. This article summarizes published research and does not provide diagnosis, treatment, or personal medical guidance. Always talk to your own care team before changing anything about your Type 1 diabetes management.