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

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 indi...

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Published inPloS one Vol. 5; no. 12; p. e14194
Main Authors Herzberg-Schäfer, Silke A, Staiger, Harald, Heni, Martin, Ketterer, Caroline, Guthoff, Martina, Kantartzis, Konstantinos, Machicao, Fausto, Stefan, Norbert, Häring, Hans-Ulrich, Fritsche, Andreas
Format Journal Article
LanguageEnglish
Published Public Library of Science 02.12.2010
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Summary: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 [beta]-cell dysfunction. 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[less than or equal to]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).sub.Insulin(0-30) /AUC.sub.Glucose(0-30) as the best-ranked index to detect SNP-dependent differences in insulin release. Moreover, AUC.sub.Insulin(0-30) /AUC.sub.Glucose(0-30), corrected insulin response (CIR), AUC.sub.C-Peptide(0-30) /AUC.sub.Glucose(0-30), AUC.sub.C-Peptide(0-120) /AUC.sub.Glucose(0-120), two different formulas for the incremental insulin response from 0-30 min, i.e., the insulinogenic indices (IGI).sub.2 and IGI.sub.1, and insulin 30 min were significantly higher-ranked than homeostasis model assessment of [beta]-cell function (HOMA-B; p<0.05). AUC.sub.C-Peptide(0-120) /AUC.sub.Glucose(0-120) was best-ranked for the detection of SNPs involved in incretin-stimulated insulin secretion. In all analyses, HOMA-[beta] displayed the highest rank sums and, thus, scored last. With AUC.sub.Insulin(0-30) /AUC.sub.Glucose(0-30), CIR, AUC.sub.C-Peptide(0-30) /AUC.sub.Glucose(0-30), AUC.sub.C-Peptide(0-120) /AUC.sub.Glucose(0-120), IGI.sub.2, IGI.sub.1, and insulin 30 min, dynamic measures of insulin secretion based on early insulin and C-peptide responses to oral glucose represent measures which are more appropriate to assess genetically determined [beta]-cell dysfunction than fasting measures, i.e., HOMA-B. Genes predominantly influencing the incretin axis may possibly be best detected by AUC.sub.C-Peptide(0-120) /AUC.sub.Glucose(0-120).
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0014194