Continuous glucose monitoring evidence of celiac disease in type 1 diabetes
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Author(s) • • • • • • •
Jessica L. Ruiz
Lisa A. Asaro
Allison S. Bernique
Elizabeth Healey
Jocelyn A. Silvester
David Wypij
Michael S.D. Agus
Christina M. Astley
Date Issued
September 25, 2025
Journal
Journal of Pediatric Endocrinology and Metabolism
Publisher
Walter de Gruyter GmbH
Citation
Ruiz, Jessica L., Asaro, Lisa A., Bernique, Allison S., Healey, Elizabeth, Silvester, Jocelyn A., Wypij, David, Agus, Michael S.D. and Astley, Christina M.. "Continuous glucose monitoring evidence of celiac disease in type 1 diabetes" Journal of Pediatric Endocrinology and Metabolism, vol. 38, no. 11, 2025, pp. 1126-1134.
Version
Final published version
Abstract
Objectives
Quantitative glycemic metrics are needed to identify undiagnosed celiac disease in type 1 diabetes and reduce delays in celiac diagnosis. Celiac enteropathy drives malabsorption that increases the risk of prandial insulin-glucose mismatch and hypoglycemia. We assessed if children with type 1 diabetes and celiac disease have lower post-prandial glucose levels preceding celiac diagnosis vs. those without celiac disease, leveraging continuous glucose monitoring (CGM) data and a computational meal annotation algorithm.
Methods
In this retrospective cohort study, children with type 1 diabetes <12 months duration using CGM, positive celiac serologies and biopsy confirmed celiac disease (n=16) were matched 1-to-4 to those with negative celiac serologies (n=60). Meals were computationally annotated in the 30-day window before serologies. Differences in post-prandial trough glucose and other prandial glycemic outcomes were assessed via mixed models.
Results
Undiagnosed celiac disease was associated with a lower glucose rise from meal start to peak vs. no celiac disease (−8.9 %, 95 % CI, −14.9–−2.5 %, p=0.009) and, during the first meal of the day, a lower fall from peak to trough (−9.3 %, 95 % CI, −16.5 %–−1.5 %, p=0.02). There was no significant association between celiac disease and trough glucose, meal hypoglycemia or time hypoglycemic.
Conclusions
Computational analysis revealed that blunted prandial glycemic trajectories, not hypoglycemia, are associated with undiagnosed celiac disease in children with type 1 diabetes using CGM. These findings challenge current guidelines, and future studies should validate and integrate these glycemic biomarkers into a CGM-based model for real-time prediction of celiac disease in type 1 diabetes.
MIT Department
Harvard-MIT Program in Health Sciences and Technology
Broad Institute of MIT and Harvard
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DOI of Published Version
https://doi.org/10.1515/jpem-2025-0302