Literature DB >> 1895955

Understanding "insulin resistance": both glucose resistance and insulin resistance are required to model human diabetes.

A S Rudenski1, D R Matthews, J C Levy, R C Turner.   

Abstract

A mathematical model of normal glucose/insulin homoeostasis has been based on the known, experimentally determined responses of the liver and periphery to different glucose/insulin concentrations. Different defects of glucose resistance and insulin resistance have been applied to the model to investigate the degree to which these abnormalities could successfully predict the range of fasting glucose and insulin values found in normal, obese, and diabetic subjects. Modeling glucose resistance or insulin resistance at the liver or the periphery alone did not increase the plasma glucose to levels observed in diabetes, even when associated with marked deficiency of beta-cell function. A defect of either glucose resistance or insulin resistance affecting both periphery and liver allowed a wider range of basal glucose and insulin concentration values, but resulted in unphysiologically low hepatic glucose output: with modeling insulin resistance, hyperglycemia suppressed glucose output, whereas with glucose resistance, raised insulin levels suppressed hepatic glucose output. A wide range of glucose and insulin values, with appropriate basal hepatic glucose output, could only be modeled by insulin resistance at both the liver and periphery with additional glucose resistance at the liver. The modeling results are in accord with investigative studies that suggest secondary hepatic and peripheral glucose resistance in response to hyperglycemia. Modeling provides a systematic means of examining the likely effect of different putative defects in a complex physiological system.

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Year:  1991        PMID: 1895955     DOI: 10.1016/0026-0495(91)90065-5

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  22 in total

1.  Predicting impaired glucose metabolism in women with polycystic ovary syndrome by decision tree modelling.

Authors:  M Möhlig; A Flöter; J Spranger; M O Weickert; T Schill; H W Schlösser; G Brabant; A F H Pfeiffer; J Selbig; C Schöfl
Journal:  Diabetologia       Date:  2006-09-14       Impact factor: 10.122

2.  Assessment of insulin sensitivity in glucokinase-deficient subjects.

Authors:  K Clément; M E Pueyo; M Vaxillaire; B Rakotoambinina; F Thuillier; P Passa; P Froguel; J J Robert; G Velho
Journal:  Diabetologia       Date:  1996-01       Impact factor: 10.122

3.  Is metabolic syndrome a discrete entity in the general population? Evidence from the Caerphilly and Speedwell population studies.

Authors:  J W Yarnell; C C Patterson; D Bainton; P M Sweetnam
Journal:  Heart       Date:  1998-03       Impact factor: 5.994

4.  Relationship between serum circulating insulin-like growth factor-1 and liver fat in the United States.

Authors:  Shauna S Runchey; Edward J Boyko; George N Ioannou; Kristina M Utzschneider
Journal:  J Gastroenterol Hepatol       Date:  2014-03       Impact factor: 4.029

5.  Association between serum lipids, glucose tolerance, and insulin sensitivity during 12 months of celiprolol treatment.

Authors:  K Malminiemi
Journal:  Cardiovasc Drugs Ther       Date:  1995-04       Impact factor: 3.727

6.  Methodology for quantifying fasting glucose homeostasis in type 2 diabetes: observed variability and lability.

Authors:  Nathan R Hill; Apostolos Tsapas; Peter Hindmarsh; David R Matthews
Journal:  J Diabetes Sci Technol       Date:  2013-05-01

7.  Insulin sensitivity and secretory status of a healthy malay population.

Authors:  Abu Kholdun Al-Mahmood; Aziz Al-Safi Ismail; Faridah Abdul Rashid; Wan Mohamad Wan Bebakar
Journal:  Malays J Med Sci       Date:  2006-07

8.  Effect of low- and high-glycemic load on circulating incretins in a randomized clinical trial.

Authors:  Shauna S Runchey; Liisa M Valsta; Yvonne Schwarz; Chiachi Wang; Xiaoling Song; Johanna W Lampe; Marian L Neuhouser
Journal:  Metabolism       Date:  2012-09-07       Impact factor: 8.694

9.  Glycemic load effect on fasting and post-prandial serum glucose, insulin, IGF-1 and IGFBP-3 in a randomized, controlled feeding study.

Authors:  S S Runchey; M N Pollak; L M Valsta; G D Coronado; Y Schwarz; K L Breymeyer; C Wang; C-Y Wang; J W Lampe; M L Neuhouser
Journal:  Eur J Clin Nutr       Date:  2012-08-15       Impact factor: 4.016

10.  Sleep apnea predicts distinct alterations in glucose homeostasis and biomarkers in obese adults with normal and impaired glucose metabolism.

Authors:  Maria Pallayova; Kimberley E Steele; Thomas H Magnuson; Michael A Schweitzer; Nathan R Hill; Shannon Bevans-Fonti; Alan R Schwartz
Journal:  Cardiovasc Diabetol       Date:  2010-12-01       Impact factor: 9.951

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