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

Author:

Steenkamp Devin W12ORCID,Cheney Michael C12,Ju Zhihui12,Rodbard David3,Wolpert Howard A12

Affiliation:

1. Department of Medicine, Section of Endocrinology, Diabetes and Nutrition, Boston University Chobanian & Avedisian School of Medicine , Boston, MA , USA

2. Boston Medical Center , Boston, MA , USA

3. Biomedical Informatics Consultants LLC , Potomac, MD , USA

Abstract

AbstractBackgroundIn this proof-of-concept study, we evaluated if monogenic diabetes resulting from mutations of the HNF-1α gene (HNF1A-MODY) has a distinctive continuous glucose monitoring (CGM) glucotype, in comparison to type 1 diabetes (T1D).MethodsUsing CGM data from 5 subjects with HNF1A-MODY and 115 subjects with T1D, we calculated multiple glucose metrics, including measures of within- and between-day variability (such as coefficient variation for each hour [CVb_1h]).ResultsThe MODY and T1D cohorts had minimum CVb_1h of 11.3 ± 4.4 and 18.0 ± 4.9, respectively (P = .02) and maximum CVb_1h of 33.9 ± 5.0 and 50.3 ± 10, respectively (P < .001). All subjects with HNF1A-MODY had a minimum %CVb_1h ≤ 17.3% and maximum %CVb_1h ≤ 37.1%. In contrast, only 12 of 115 subjects with T1D had both a minimum and maximum %CVb_1h below these thresholds (P < .001).ConclusionHNF1A- MODY is characterized by a low hourly, between-day glucose variability. CGM-derived glucose metrics may have potential applicability for screening for atypical diabetes phenotypes in the T1D population.

Publisher

The Endocrine Society

Subject

Endocrinology, Diabetes and Metabolism

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