Evaluation of Fasting State-/Oral Glucose Tolerance Test-Derived Measures of Insulin Release for the Detection of Genetically Impaired β-Cell Function

Background: To date, fasting state- and different oral glucose tolerance test (OGTT)-derived measures are used to estimate insulin release with reasonable effort in large human cohorts required, e.g., for genetic studies. Here, we evaluated twelve common (or recently introduced) fasting state-/OGTT-derived indices for their suitability to detect genetically determined β-cell dysfunction. Methodology/Principal Findings: A cohort of 1364 White European individuals at increased risk for type 2 diabetes was characterized by OGTT with glucose, insulin, and C-peptide measurements and genotyped for single nucleotide polymorphisms (SNPs) known to affect glucose- and incretin-stimulated insulin secretion. One fasting state- and eleven OGTT-derived indices were calculated and statistically evaluated. After adjustment for confounding variables, all tested SNPs were significantly associated with at least two insulin secretion measures (p≤0.05). The indices were ranked according to their associations' statistical power, and the ranks an index obtained for its associations with all the tested SNPs (or a subset) were summed up resulting in a final ranking. This approach revealed area under the curve (AUC)Insulin(0-30)/AUCGlucose(0-30) as the best-ranked index to detect SNP-dependent differences in insulin release. Moreover, AUCInsulin(0-30)/AUCGlucose(0-30), corrected insulin response (CIR), AUCC-Peptide(0-30)/AUCGlucose(0-30), AUCC-Peptide(0-120)/AUCGlucose(0-120), two different formulas for the incremental insulin response from 0–30 min, i.e., the insulinogenic indices (IGI)2 and IGI1, and insulin 30 min were significantly higher-ranked than homeostasis model assessment of β-cell function (HOMA-B; p