Diabetes Polygenic Scores Predict Glycemic Indices and Insulin Use in Individuals with Atypical Diabetes
- 1Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA
Abstract
Aims/HypothesisAtypical forms of diabetes often provide diagnostic challenges and are suboptimally treated. We sought to determine whether type 1 and 2 diabetes polygenic scores (PS) would help improve classification of islet autoantibody-negative (IAb-) atypical diabetes cases.
MethodsWe implemented type 1 diabetes PS (T1D PS) and type 2 diabetes PS (T2D PS) in 309 IAb-individuals genome sequencing from the Rare and Atypical Diabetes Network (RADIANT), the largest and most comprehensively phenotyped collection of unsolved and atypical diabetes cases. We performed regression analyses to assess associations between PS, clinical characteristics, and glycemic measures.
ResultsBoth T1D and T2D PS were significantly higher in RADIANT than in ancestry-matched controls from UK Biobank. Both PS were associated with C-peptide measures throughout participant oral glucose tolerance tests (OGTT), although in opposite directions; T1D PS was associated with lower C-peptide measures, while T2D PS was associated with higher measures. Participants with T1D PS above a previously established optimal PS value for differentiating cases and controls (T1D PS GRS2>12.88) had 13-fold higher odds of both insulin deficiency on OGTT and use of both basal and bolus insulin therapy.
Conclusions/InterpretationIndividuals in RADIANT with ambiguous diabetes subtypes displayed genetic enrichment for both type 1 and type 2 diabetes, despite ascertainment to remove standard type 1 and type 2 diabetes. T1D PS identified individuals with an unrecognized "type 1 diabetes-like" phenotype with insulin deficiency and need for intensive insulin in the absence of islet autoantibodies. PS may help identify individuals with atypical diabetes who will ultimately benefit from insulin therapy.
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BibTeX
@misc{gage2026diabetes,
title = {{Diabetes Polygenic Scores Predict Glycemic Indices and Insulin Use in Individuals with Atypical Diabetes}},
author = {S. D. Gage and R. J. Kreienkamp and A. J. Deutsch and E. J. Richards and L. K. Billings and S. J. Cromer and S. A. W. Greeley and I. B. Hirsch and A. Huerta-Chagoya and S. E. Kahn and K. R. Klein and J. M. Mercader and N. Rasouli and M. Rezaei and M. J. Redondo and A. Balasubramanyam and J. C. Florez and L. H. Philipson and J. Flannick and M. S. Udler and RADIANT Study Group},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.01.26364299},
url = {https://www.medrxiv.org/content/10.64898/2026.10.01.26364299v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Diabetes Polygenic Scores Predict Glycemic Indices and Insulin Use in Individuals with Atypical Diabetes
AU - S. D. Gage
AU - R. J. Kreienkamp
AU - A. J. Deutsch
AU - E. J. Richards
AU - L. K. Billings
AU - S. J. Cromer
AU - S. A. W. Greeley
AU - I. B. Hirsch
AU - A. Huerta-Chagoya
AU - S. E. Kahn
AU - K. R. Klein
AU - J. M. Mercader
AU - N. Rasouli
AU - M. Rezaei
AU - M. J. Redondo
AU - A. Balasubramanyam
AU - J. C. Florez
AU - L. H. Philipson
AU - J. Flannick
AU - M. S. Udler
AU - RADIANT Study Group
PY - 2026
DA - 2026/10/01
PB - medRxiv
DO - 10.64898/2026.10.01.26364299
UR - https://www.medrxiv.org/content/10.64898/2026.10.01.26364299v1
AB - Aims/HypothesisAtypical forms of diabetes often provide diagnostic challenges and are suboptimally treated. We sought to determine whether type 1 and 2 diabetes polygenic scores (PS) would help improve classification of islet autoantibody-negative (IAb-) atypical diabetes cases. MethodsWe implemented type 1 diabetes PS (T1D PS) and type 2 diabetes PS (T2D PS) in 309 IAb-individuals genome sequencing from the Rare and Atypical Diabetes Network (RADIANT), the largest and most comprehensively phenotyped collection of unsolved and atypical diabetes cases. We performed regression analyses to assess associations between PS, clinical characteristics, and glycemic measures. ResultsBoth T1D and T2D PS were significantly higher in RADIANT than in ancestry-matched controls from UK Biobank. Both PS were associated with C-peptide measures throughout participant oral glucose tolerance tests (OGTT), although in opposite directions; T1D PS was associated with lower C-peptide measures, while T2D PS was associated with higher measures. Participants with T1D PS above a previously established optimal PS value for differentiating cases and controls (T1D PS GRS2>12.88) had 13-fold higher odds of both insulin deficiency on OGTT and use of both basal and bolus insulin therapy. Conclusions/InterpretationIndividuals in RADIANT with ambiguous diabetes subtypes displayed genetic enrichment for both type 1 and type 2 diabetes, despite ascertainment to remove standard type 1 and type 2 diabetes. T1D PS identified individuals with an unrecognized "type 1 diabetes-like" phenotype with insulin deficiency and need for intensive insulin in the absence of islet autoantibodies. PS may help identify individuals with atypical diabetes who will ultimately benefit from insulin therapy.
ER -