Literature DB >> 21248305

Shape of glucose, insulin, C-peptide curves during a 3-h oral glucose tolerance test: any relationship with the degree of glucose tolerance?

Andrea Tura1, Umberto Morbiducci, Stefano Sbrignadello, Yvonne Winhofer, Giovanni Pacini, Alexandra Kautzky-Willer.   

Abstract

We aimed to analyze the shape of the glucose, insulin, and C-peptide curves during a 3-h oral glucose tolerance test (OGTT). Another aim was defining an index of shape taking into account the whole OGTT pattern. Five-hundred ninety-two OGTT curves were analyzed, mainly from women with former gestational diabetes, with glycemic concentrations characterized by normal glucose tolerance (n = 411), impaired glucose metabolism (n = 134), and Type 2 diabetes (n = 47). Glucose curves were classified according to their shape (monophasic, biphasic, triphasic, and 4/5-phases), and the metabolic condition of the subjects, divided according to the glucose shape stratification, was analyzed. Indices of shape based on the discrete second-order derivative of the curve patterns were also defined. We found that the majority of the glucose curves were monophasic (n = 262). Complex shapes were less frequent but not rare (n = 37 for the 4/5-phases shape, i.e., three peaks). There was a tendency toward the amelioration of the metabolic condition for increasing complexity of the shape, as indicated by lower glucose concentrations, improved insulin sensitivity and β-cell function. The shape index computed on C-peptide, WHOSH(CP) (WHole-Ogtt-SHape-index-C-peptide), showed a progressive increase [monophasic: 0.93 ± 0.04 (dimensionless); 4/5-phases: 1.35 ± 0.14], and it showed properties typical of β-cell function indices. We also found that the type of glucose shape is often associated to similar insulin and C-peptide shape. In conclusion, OGTT curves can be characterized by high variability, and complex OGTT shape is associated with better glucose tolerance. WHOSH(CP) (WHole-Ogtt-SHape-index) may be a powerful index of β-cell function much simpler than model-based indices.

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Year:  2011        PMID: 21248305     DOI: 10.1152/ajpregu.00650.2010

Source DB:  PubMed          Journal:  Am J Physiol Regul Integr Comp Physiol        ISSN: 0363-6119            Impact factor:   3.619


  38 in total

1.  The shape of the glucose concentration curve during an oral glucose tolerance test predicts risk for type 1 diabetes.

Authors:  Heba M Ismail; Ping Xu; Ingrid M Libman; Dorothy J Becker; Jennifer B Marks; Jay S Skyler; Jerry P Palmer; Jay M Sosenko
Journal:  Diabetologia       Date:  2017-09-27       Impact factor: 10.122

2.  Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts.

Authors:  Akram Alyass; Peter Almgren; Mikael Akerlund; Jonathan Dushoff; Bo Isomaa; Peter Nilsson; Tiinamaija Tuomi; Valeriya Lyssenko; Leif Groop; David Meyre
Journal:  Diabetologia       Date:  2014-10-08       Impact factor: 10.122

3.  The Pathological Evolution of Glucose Response Curves During the Progression to Type 1 Diabetes in the TrialNet Pathway to Prevention Study.

Authors:  Heba M Ismail; Mario A Cleves; Ping Xu; Ingrid M Libman; Dorothy J Becker; Jennifer B Marks; Jay S Skyler; Jerry P Palmer; Jay M Sosenko
Journal:  Diabetes Care       Date:  2020-09-08       Impact factor: 19.112

4.  Time to glucose peak during an oral glucose tolerance test identifies prediabetes risk.

Authors:  Stephanie T Chung; Joon Ha; Anthony U Onuzuruike; Kannan Kasturi; Mirella Galvan-De La Cruz; Brianna A Bingham; Rafeal L Baker; Jean N Utumatwishima; Lilian S Mabundo; Madia Ricks; Arthur S Sherman; Anne E Sumner
Journal:  Clin Endocrinol (Oxf)       Date:  2017-08-06       Impact factor: 3.478

5.  Delayed timing of post-challenge peak blood glucose predicts declining beta cell function and worsening glucose tolerance over time: insight from the first year postpartum.

Authors:  Caroline K Kramer; Chang Ye; Anthony J G Hanley; Philip W Connelly; Mathew Sermer; Bernard Zinman; Ravi Retnakaran
Journal:  Diabetologia       Date:  2015-03-12       Impact factor: 10.122

6.  The Shape of the Glucose Response Curve During an Oral Glucose Tolerance Test: Forerunner of Heightened Glycemic Failure Rates and Accelerated Decline in β-Cell Function in TODAY.

Authors:  Silva Arslanian; Laure El Ghormli; Joon Young Kim; Fida Bacha; Christine Chan; Heba M Ismail; Lorraine E Levitt Katz; Lynne Levitsky; Jeanie B Tryggestad; Neil H White
Journal:  Diabetes Care       Date:  2018-11-19       Impact factor: 19.112

7.  Patterns of changes in fasting plasma glucose, hemoglobin A1c and the area under the curve during oral glucose tolerance tests in prediabetic subjects: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients.

Authors:  Shahla Safari; Masoud Amini; Ashraf Aminorroaya; Awat Feizi
Journal:  Acta Diabetol       Date:  2020-10-21       Impact factor: 4.280

8.  Novel Hypoglycemia Phenotype in Congenital Hyperinsulinism Due to Dominant Mutations of Uncoupling Protein 2.

Authors:  Christine T Ferrara; Kara E Boodhansingh; Eleonora Paradies; Giuseppe Fiermonte; Linda J Steinkrauss; Lisa Swartz Topor; Jose Bernardo Quintos; Arupa Ganguly; Diva D De Leon; Ferdinando Palmieri; Charles A Stanley
Journal:  J Clin Endocrinol Metab       Date:  2017-03-01       Impact factor: 5.958

9.  The Shape of the Glucose Response Curve During an Oral Glucose Tolerance Test Heralds Biomarkers of Type 2 Diabetes Risk in Obese Youth.

Authors:  Joon Young Kim; Sara F Michaliszyn; Alexis Nasr; SoJung Lee; Hala Tfayli; Tamara Hannon; Kara S Hughan; Fida Bacha; Silva Arslanian
Journal:  Diabetes Care       Date:  2016-06-12       Impact factor: 19.112

Review 10.  Review of methods for detecting glycemic disorders.

Authors:  Michael Bergman; Muhammad Abdul-Ghani; Ralph A DeFronzo; Melania Manco; Giorgio Sesti; Teresa Vanessa Fiorentino; Antonio Ceriello; Mary Rhee; Lawrence S Phillips; Stephanie Chung; Celeste Cravalho; Ram Jagannathan; Louis Monnier; Claude Colette; David Owens; Cristina Bianchi; Stefano Del Prato; Mariana P Monteiro; João Sérgio Neves; Jose Luiz Medina; Maria Paula Macedo; Rogério Tavares Ribeiro; João Filipe Raposo; Brenda Dorcely; Nouran Ibrahim; Martin Buysschaert
Journal:  Diabetes Res Clin Pract       Date:  2020-06-01       Impact factor: 5.602

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