Proof-of-concept Application of Continuous Glucose Monitoring Data Analytics to Identify Diabetes Glucotypes

Area of Science:

• Endocrinology
• Genetics
• Metabolism

Background:

• Monogenic diabetes, specifically Hepatocyte Nuclear Factor 1-alpha gene mutations (HNF1A-MODY), presents a distinct clinical profile.
• Type 1 diabetes (T1D) is the most common form of diabetes in younger individuals, characterized by autoimmune destruction of pancreatic beta cells.

Purpose of the Study:

• To investigate if HNF1A-MODY exhibits a unique continuous glucose monitoring (CGM) glucotype compared to T1D.
• To explore the potential of CGM metrics for differentiating diabetes phenotypes.

Main Methods:

• Continuous glucose monitoring (CGM) data from 5 HNF1A-MODY patients and 115 T1D patients were analyzed.
• Key glucose variability metrics, including hourly between-day coefficient of variation (CV_{b_1h}), were calculated for both groups.

Main Results:

• HNF1A-MODY cohort demonstrated significantly lower minimum (11.3 ± 4.4% vs 18.0 ± 4.9%, P=.02) and maximum (33.9 ± 5.0% vs 50.3 ± 10%, P<.001) CV_{b_1h} compared to T1D.
• All HNF1A-MODY subjects had %CV_{b_1h} ≤ 17.3% (min) and ≤ 37.1% (max), thresholds met by only 12 T1D patients (P<.001).

Conclusions:

• HNF1A-MODY is characterized by reduced hourly, between-day glucose variability.
• CGM-derived metrics show promise for screening atypical diabetes phenotypes within the T1D population.