Continuous glucose monitoring evidence of celiac disease in type 1 diabetes.

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.