Literature DB >> 36271244

SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function.

Bernhard O Boehm1,2,3, Nihal Thomas4, Johannes W Dietrich5,6,7,8, Riddhi Dasgupta4, Shajith Anoop4, Felix Jebasingh4, Mathews E Kurian4, Mercy Inbakumari4.   

Abstract

Modelling insulin-glucose homeostasis may provide novel functional insights. In particular, simple models are clinically useful if they yield diagnostic methods. Examples include the homeostasis model assessment (HOMA) and the quantitative insulin sensitivity check index (QUICKI). However, limitations of these approaches have been criticised. Moreover, recent advances in physiological and biochemical research prompt further refinement in this area. We have developed a nonlinear model based on fundamental physiological motifs, including saturation kinetics, non-competitive inhibition, and pharmacokinetics. This model explains the evolution of insulin and glucose concentrations from perturbation to steady-state. Additionally, it lays the foundation of a structure parameter inference approach (SPINA), providing novel biomarkers of carbohydrate homeostasis, namely the secretory capacity of beta-cells (SPINA-GBeta) and insulin receptor gain (SPINA-GR). These markers correlate with central parameters of glucose metabolism, including average glucose infusion rate in hyperinsulinemic glucose clamp studies, response to oral glucose tolerance testing and HbA1c. Moreover, they mirror multiple measures of body composition. Compared to normal controls, SPINA-GR is significantly reduced in subjects with diabetes and prediabetes. The new model explains important physiological phenomena of insulin-glucose homeostasis. Clinical validation suggests that it may provide an efficient biomarker panel for screening purposes and clinical research.
© 2022. The Author(s).

Entities:  

Year:  2022        PMID: 36271244     DOI: 10.1038/s41598-022-22531-3

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.996


  35 in total

Review 1.  Insulin resistance in obesity and polycystic ovary syndrome: systematic review and meta-analysis of observational studies.

Authors:  Samira Behboudi-Gandevani; Fahimeh Ramezani Tehrani; Marzieh Rostami Dovom; Maryam Farahmand; Mahnaz Bahri Khomami; Mahsa Noroozzadeh; Ali Kabir; Fereidoun Azizi
Journal:  Gynecol Endocrinol       Date:  2016-01-06       Impact factor: 2.260

2.  Fasting plasma glucose is a stronger predictor of diabetes than triglyceride-glucose index, triglycerides/high-density lipoprotein cholesterol, and homeostasis model assessment of insulin resistance: Tehran Lipid and Glucose Study.

Authors:  Maryam Tohidi; Aidin Baghbani-Oskouei; Noushin Sadat Ahanchi; Fereidoun Azizi; Farzad Hadaegh
Journal:  Acta Diabetol       Date:  2018-07-31       Impact factor: 4.280

3.  Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

Authors:  A Katz; S S Nambi; K Mather; A D Baron; D A Follmann; G Sullivan; M J Quon
Journal:  J Clin Endocrinol Metab       Date:  2000-07       Impact factor: 5.958

4.  Effectiveness of artificial pancreas in the non-adult population: A systematic review and network meta-analysis.

Authors:  Vasilios Karageorgiou; Theodoros G Papaioannou; Ioannis Bellos; Krystallenia Alexandraki; Nikolaos Tentolouris; Christodoulos Stefanadis; George P Chrousos; Dimitrios Tousoulis
Journal:  Metabolism       Date:  2018-10-12       Impact factor: 8.694

5.  Diabetes: Models, Signals, and Control.

Authors:  Claudio Cobelli; Chiara Dalla Man; Giovanni Sparacino; Lalo Magni; Giuseppe De Nicolao; Boris P Kovatchev
Journal:  IEEE Rev Biomed Eng       Date:  2009-01-01

6.  Limitation of the homeostasis model assessment to predict insulin resistance and beta-cell dysfunction in older people.

Authors:  Annette M Chang; Marla J Smith; Cathie J Bloem; Andrzej T Galecki; Jeffrey B Halter; Mark A Supiano
Journal:  J Clin Endocrinol Metab       Date:  2005-11-29       Impact factor: 5.958

Review 7.  Methods of measuring insulin sensitivity.

Authors:  Kimberly K Trout; Carol Homko; Nancy C Tkacs
Journal:  Biol Res Nurs       Date:  2007-04       Impact factor: 2.522

8.  Metabolic syndrome in polycystic ovary syndrome: a systematic review, meta-analysis and meta-regression.

Authors:  S S Lim; N S Kakoly; J W J Tan; G Fitzgerald; M Bahri Khomami; A E Joham; S D Cooray; M L Misso; R J Norman; C L Harrison; S Ranasinha; H J Teede; L J Moran
Journal:  Obes Rev       Date:  2018-10-19       Impact factor: 9.213

9.  Toward Better Understanding of Insulin Therapy by Translation of a PK-PD Model to Visualize Insulin and Glucose Action Profiles.

Authors:  Karen Schneck; Lai San Tham; Ali Ertekin; Jesus Reviriego
Journal:  J Clin Pharmacol       Date:  2018-10-19       Impact factor: 3.126

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