Phenotypes Associated With Zones Defined by Area Under the Curve Glucose and C-peptide in a Population With Islet Autoantibodies

Author:

Sosenko Jay M.1ORCID,Cuthbertson David2,Sims Emily K.3ORCID,Ismail Heba M.3ORCID,Nathan Brandon M.4ORCID,Jacobsen Laura M.5ORCID,Atkinson Mark A.56ORCID,Evans-Molina Carmella7ORCID,Herold Kevan C.8ORCID,Skyler Jay S.1ORCID,Redondo Maria J.9ORCID,

Affiliation:

1. 1Division of Endocrinology, Diabetes, and Metabolism, and Diabetes Research Institute, University of Miami, Miami, FL

2. 2Department of Pediatrics, Morsani College of Medicine, University of South Florida, Tampa, FL

3. 3Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics, Indiana University, Indianapolis, IN

4. 4Division of Pediatric Endocrinology, Department of Pediatrics, University of Minnesota School of Medicine, Minneapolis, MN

5. 5Department of Pediatrics, College of Medicine, The University of Florida, Gainesville, FL

6. 6Department of Pathology, College of Medicine, The University of Florida, Gainesville, FL

7. 7Division of Endocrinology, Department of Medicine, Indiana University, Indianapolis, IN

8. 8Department of Immunobiology, Yale University School of Medicine, New Haven, CT

9. 9Texas Children’s Hospital, Baylor College of Medicine, Houston, TX

Abstract

OBJECTIVE Metabolic zones were developed to characterize heterogeneity of individuals with islet autoantibodies. RESEARCH DESIGN AND METHODS Baseline 2-h oral glucose tolerance test data from 6,620 TrialNet Pathway to Prevention Study (TNPTP) autoantibody-positive participants (relatives of individuals with type 1 diabetes) were used to form 25 zones from five area under the curve glucose (AUCGLU) rows and five area under the curve C-peptide (AUCPEP) columns. Zone phenotypes were developed from demographic, metabolic, autoantibody, HLA, and risk data. RESULTS As AUCGLU increased, changes of glucose and C-peptide response curves (from mean glucose and mean C-peptide values at 30, 60, 90, and 120 min) were similar within the five AUCPEP columns. Among the zones, 5-year risk for type 1 diabetes was highly correlated with islet antigen 2 antibody prevalence (r = 0.96, P < 0.001). Disease risk decreased markedly in the highest AUCGLU row as AUCPEP increased (0.88–0.41; P < 0.001 from lowest AUCPEP column to highest AUCPEP column). AUCGLU correlated appreciably less with Index60 (an indicator of insulin secretion) in the highest AUCPEP column (r = 0.33) than in other columns (r ≥ 0.78). AUCGLU was positively related to “fasting glucose × fasting insulin” and to “fasting glucose × fasting C-peptide” (indicators of insulin resistance) before and after adjustments for Index60 (P < 0.001). CONCLUSIONS Phenotypes of 25 zones formed from AUCGLU and AUCPEP were used to gain insights into type 1 diabetes heterogeneity. Zones were used to examine GCRC changes with increasing AUCGLU, associations between risk and autoantibody prevalence, the dependence of glucose as a predictor of risk according to C-peptide, and glucose heterogeneity from contributions of insulin secretion and insulin resistance.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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