Hormone research in paediatrics · 2026
T1D GRS: A Tool for Identifying Children and Adolescents with Monogenic Diabetes.
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Dobiasova Zuzana, Skopkova Martina, Karhanek Miloslav, Gregus Filip, Sabo Miroslav, Huckova Miroslava, Lobotkova Denisa, Podolakova Kristina, Jancova Emilia, Barak Lubomir, Gasperikova Daniela, Stanik Juraj
Аннотация
INTRODUCTION: Diagnosing monogenic diabetes is important as it enables gene-tailored treatment. In children and adolescents, monogenic diabetes must primarily be differentiated from type 1 diabetes. People with type 1 and monogenic diabetes have different genetic risks for type 1 diabetes. This study evaluates the effectiveness of the Type 1 Diabetes Genetic Risk Score (T1D GRS) as a tool to prioritise children with newly diagnosed hyperglycaemia for monogenic diabetes genetic testing.
METHODS: The T1D GRS2 and 10 SNP GRSs were assessed in 808 children and adolescents with newly diagnosed hyperglycaemia, 165 patients with monogenic diabetes, and 24 healthy individuals. Genetic testing was performed in all autoantibody-negative cases and cases with clinically unclassified diabetes. The usefulness of T1D GRS in prioritisation for genetic testing was evaluated retrospectively.
RESULTS: The ROC analysis showed very good discrimination of type 1 diabetes cases by T1D GRS2 with AUC 0.919 (95% CI: 0.898-0.941) and the optimal cut-off 11.818. Applying T1D GRS2 alongside negative autoantibodies tripled the pick-up rate and increased specificity from 92.9% to 98.8%, with only a slight reduction in sensitivity (from 77.8% to 72.2%) compared with autoantibody testing alone. Most monogenic diabetes cases missed by this prioritisation had low levels of a single autoantibody and likely represented false-positive results in autoantibody testing. While these monogenic cases that were not prioritised by GRS2 and autoantibodies were diagnosed based on clinical phenotype, two HNF1B-MODY cases were identified solely thanks to their low GRS2 scores.
CONCLUSIONS: Combining T1D GRS with autoantibody testing improves the efficiency of genetic testing by reducing unnecessary investigations while maintaining high sensitivity. When combined with clinical evaluation, this approach enables earlier and more targeted identification of candidates for monogenic diabetes testing.
METHODS: The T1D GRS2 and 10 SNP GRSs were assessed in 808 children and adolescents with newly diagnosed hyperglycaemia, 165 patients with monogenic diabetes, and 24 healthy individuals. Genetic testing was performed in all autoantibody-negative cases and cases with clinically unclassified diabetes. The usefulness of T1D GRS in prioritisation for genetic testing was evaluated retrospectively.
RESULTS: The ROC analysis showed very good discrimination of type 1 diabetes cases by T1D GRS2 with AUC 0.919 (95% CI: 0.898-0.941) and the optimal cut-off 11.818. Applying T1D GRS2 alongside negative autoantibodies tripled the pick-up rate and increased specificity from 92.9% to 98.8%, with only a slight reduction in sensitivity (from 77.8% to 72.2%) compared with autoantibody testing alone. Most monogenic diabetes cases missed by this prioritisation had low levels of a single autoantibody and likely represented false-positive results in autoantibody testing. While these monogenic cases that were not prioritised by GRS2 and autoantibodies were diagnosed based on clinical phenotype, two HNF1B-MODY cases were identified solely thanks to their low GRS2 scores.
CONCLUSIONS: Combining T1D GRS with autoantibody testing improves the efficiency of genetic testing by reducing unnecessary investigations while maintaining high sensitivity. When combined with clinical evaluation, this approach enables earlier and more targeted identification of candidates for monogenic diabetes testing.