Causes & What We Know/August 13, 2026/2 min read

Genetic Risk Scores for Type 1 Diabetes: Why Ancestry Matters

Scientists are improving tests that predict Type 1 diabetes risk by considering genetic variation across different populations. Better tools could help identify at-risk individuals worldwide, not just in European ancestry groups.

PubMed indexed literature

Evidence label explains the kind of source behind this article (for example peer-reviewed literature vs community video). It is not medical advice.

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Key takeaways

Polygenic scores combine information from many genetic variants to estimate Type 1 diabetes risk, with strong accuracy in some populations
Current genetic risk tests work best in people of European ancestry because most research has focused there
The HLA genes—which vary widely around the world—are especially important for Type 1 diabetes risk prediction
New research including diverse populations and improved technology are making genetic risk scores more useful across different ancestry groups

How Genetic Risk Scores Work

Type 1 diabetes runs in families and has strong genetic roots. Scientists have identified thousands of genetic variants linked to Type 1 diabetes risk scattered across the human genome. A polygenic score combines information from many of these variants into a single measure that can estimate an individual's genetic risk.

These scores can be quite powerful at predicting who might develop Type 1 diabetes. However, their accuracy depends on something crucial: the populations included in the research used to develop them.

The Ancestry Gap in Genetic Research

Most existing polygenic scores for Type 1 diabetes perform best in people of European ancestry. This is not because other ancestry groups have different biology—it reflects a real gap in genetic research. People of European descent have been overrepresented in genome studies, while many other populations have been understudied.

This matters because genetic variation differs around the world. A score trained primarily on European genetic data may miss important risk factors or misread signals in other populations.

The HLA Challenge

One reason ancestry affects score accuracy is the HLA system—genes that play a central role in Type 1 diabetes risk. HLA variants are especially diverse globally, varying significantly between populations. Capturing this diversity accurately requires understanding which HLA alleles are common and risky in different parts of the world.

Building Better, Broader Tools

Researchers are now working to improve polygenic scores by including more diverse populations in their studies. Recent large-scale genome research that spans multiple ancestry groups has expanded our knowledge of Type 1 diabetes genetic risk.

Advanced computational techniques are also helping scientists read HLA genes more precisely at high resolution, capturing the full complexity of this important genetic region. These approaches promise polygenic scores that work more reliably across different populations worldwide.

Evidence label

Source: Diabetologia. 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.

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.

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