Evaluation of fasting state-/oral glucose tolerance test-derived measures of insulin release for the detection of genetically impaired β-cell function.
<h4>Background</h4>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) f...
Guardado en:
| Autores principales: | , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Public Library of Science (PLoS)
2010
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/1e925f5541b4403ebc670dc385267669 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | <h4>Background</h4>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.<h4>Methodology/principal findings</h4>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))/AUC(Glucose(0-30)) as the best-ranked index to detect SNP-dependent differences in insulin release. Moreover, AUC(Insulin(0-30))/AUC(Glucose(0-30)), corrected insulin response (CIR), AUC(C-Peptide(0-30))/AUC(Glucose(0-30)), AUC(C-Peptide(0-120))/AUC(Glucose(0-120)), two different formulas for the incremental insulin response from 0-30 min, i.e., the insulinogenic indices (IGI)(2) and IGI(1), and insulin 30 min were significantly higher-ranked than homeostasis model assessment of β-cell function (HOMA-B; p<0.05). AUC(C-Peptide(0-120))/AUC(Glucose(0-120)) was best-ranked for the detection of SNPs involved in incretin-stimulated insulin secretion. In all analyses, HOMA-β displayed the highest rank sums and, thus, scored last.<h4>Conclusions/significance</h4>With AUC(Insulin(0-30))/AUC(Glucose(0-30),) CIR, AUC(C-Peptide(0-30))/AUC(Glucose(0-30)), AUC(C-Peptide(0-120))/AUC(Glucose(0-120)), IGI(2), IGI(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 β-cell dysfunction than fasting measures, i.e., HOMA-B. Genes predominantly influencing the incretin axis may possibly be best detected by AUC(C-Peptide(0-120))/AUC(Glucose(0-120)). |
|---|