1
|
Tura A, Göbl C, El-Tanani M, Rizzo M. In-silico modelling of insulin secretion and pancreatic beta-cell function for clinical applications: is it worth the effort? FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2024; 5:1452400. [PMID: 39559404 PMCID: PMC11570995 DOI: 10.3389/fcdhc.2024.1452400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Accepted: 08/29/2024] [Indexed: 11/20/2024]
Affiliation(s)
- Andrea Tura
- CNR Institute of Neuroscience, Padova, Italy
| | - Christian Göbl
- Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
- Department of Obstetrics and Gynecology, Medical University of Graz, Graz, Austria
| | - Mohamed El-Tanani
- College of Pharmacy, Ras Al Khaimah Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates
| | - Manfredi Rizzo
- School of Medicine, Mohammed Bin Rashid University, Dubai, United Arab Emirates
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, School of Medicine, University of Palermo, Palermo, Italy
| |
Collapse
|
2
|
Deepa Maheshvare M, Raha S, König M, Pal D. A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell. Front Endocrinol (Lausanne) 2023; 14:1185656. [PMID: 37600713 PMCID: PMC10433753 DOI: 10.3389/fendo.2023.1185656] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/08/2023] [Indexed: 08/22/2023] Open
Abstract
The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic β-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct a novel data-driven kinetic model of GSIS in the pancreatic β-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and β-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and phenomenological equations for insulin secretion coupled to cellular energy state, ATP dynamics and (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the β-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and biphasic insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic β-cell.
Collapse
Affiliation(s)
- M. Deepa Maheshvare
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
| | - Soumyendu Raha
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
| | - Matthias König
- Institute for Biology, Institute for Theoretical Biology, Humboldt-University Berlin, Berlin, Germany
| | - Debnath Pal
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
| |
Collapse
|
3
|
Borri A, De Gaetano A. A quasi-equilibrium reduced model of pancreatic insulin secretion. J Math Biol 2021; 82:25. [PMID: 33649875 DOI: 10.1007/s00285-021-01575-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 07/11/2020] [Accepted: 02/14/2021] [Indexed: 11/24/2022]
Abstract
Much attention has been devoted in the last few decades to mathematical models of insulin secretion, in order to better understand the regulation of glycemia and its derangements. The glucose-insulin homeostatic mechanism is so complex and gives rise to such diverse behavior following perturbations that different models had been published, which reproduced the results of single experiments. More recently, a unifying model of pancreatic insulin secretion was proposed, which is able to account, with a single value of the (meta)parameters, for the wide array of clinically observed behavior. This model explicitly represented the pulsatile nature of the many pancreatic hormone-secreting firing units: the price to pay for its flexibility and performance is the very high dimensionality (hundreds of thousand equations) of the corresponding dynamical system. Clearly, it would be desirable to reduce this model to a much simpler form while retaining its power to reproduce heterogeneous phenomena. The present work reviews the qualitative behavior of this pancreas pulsatile model and offers some insight into its reduction in equilibrium and quasi-equilibrium conditions, also considering single-shot (non-repeated) glucose jumps from an approximately resting condition (such as would occur in standard Intra-Venous bolus dosing of glucose during diabetes diagnostic maneuvers). The resulting quasi-steady-state model can be further endowed with additional lower-order dynamics to also approximate transient behavior. Although a more accurate reduction of the original pulsatile model is left to further investigation, numerical results confirm the biomedical applicability of the formulation already obtained.
Collapse
Affiliation(s)
| | - Andrea De Gaetano
- CNR-IASI Biomathematics Laboratory (BioMatLab), Rome, Italy.,CNR-IRIB (Institute for Biomedical Research and Innovation), Palermo, Italy
| |
Collapse
|
4
|
Chudtong M, Gaetano AD. A mathematical model of food intake. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:1238-1279. [PMID: 33757185 DOI: 10.3934/mbe.2021067] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The metabolic, hormonal and psychological determinants of the feeding behavior in humans are numerous and complex. A plausible model of the initiation, continuation and cessation of meals taking into account the most relevant such determinants would be very useful in simulating food intake over hours to days, thus providing input into existing models of nutrient absorption and metabolism. In the present work, a meal model is proposed, incorporating stomach distension, glycemic variations, ghrelin dynamics, cultural habits and influences on the initiation and continuation of meals, reflecting a combination of hedonic and appetite components. Given a set of parameter values (portraying a single subject), the timing and size of meals are stochastic. The model parameters are calibrated so as to reflect established medical knowledge on data of food intake from the National Health and Nutrition Examination Survey (NHANES) database during years 2015 and 2016.
Collapse
Affiliation(s)
- Mantana Chudtong
- Department of Mathematics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Center of Excellence in Mathematics, the Commission on Higher Education, Si Ayutthaya Rd., Bangkok 10400, Thailand
| | - Andrea De Gaetano
- Department of Mathematics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Consiglio Nazionale delle Ricerche, Istituto per la Ricerca e l'Innovazione Biomedica (CNR-IRIB), Palermo, Italy
- Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica "A. Ruberti" (CNR-IASI), Rome, Italy
| |
Collapse
|
5
|
Mari A, Tura A, Grespan E, Bizzotto R. Mathematical Modeling for the Physiological and Clinical Investigation of Glucose Homeostasis and Diabetes. Front Physiol 2020; 11:575789. [PMID: 33324238 PMCID: PMC7723974 DOI: 10.3389/fphys.2020.575789] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 11/04/2020] [Indexed: 12/21/2022] Open
Abstract
Mathematical modeling in the field of glucose metabolism has a longstanding tradition. The use of models is motivated by several reasons. Models have been used for calculating parameters of physiological interest from experimental data indirectly, to provide an unambiguous quantitative representation of pathophysiological mechanisms, to determine indices of clinical usefulness from simple experimental tests. With the growing societal impact of type 2 diabetes, which involves the disturbance of the glucose homeostasis system, development and use of models in this area have increased. Following the approaches of physiological and clinical investigation, the focus of the models has spanned from representations of whole body processes to those of cells, i.e., from in vivo to in vitro research. Model-based approaches for linking in vivo to in vitro research have been proposed, as well as multiscale models merging the two areas. The success and impact of models has been variable. Two kinds of models have received remarkable interest: those widely used in clinical applications, e.g., for the assessment of insulin sensitivity and β-cell function and some models representing specific aspects of the glucose homeostasis system, which have become iconic for their efficacy in describing clearly and compactly key physiological processes, such as insulin secretion from the pancreatic β cells. Models are inevitably simplified and approximate representations of a physiological system. Key to their success is an appropriate balance between adherence to reality, comprehensibility, interpretative value and practical usefulness. This has been achieved with a variety of approaches. Although many models concerning the glucose homeostasis system have been proposed, research in this area still needs to address numerous issues and tackle new opportunities. The mathematical representation of the glucose homeostasis processes is only partial, also because some mechanisms are still only partially understood. For in vitro research, mathematical models still need to develop their potential. This review illustrates the problems, approaches and contribution of mathematical modeling to the physiological and clinical investigation of glucose homeostasis and diabetes, focusing on the most relevant and stimulating models.
Collapse
Affiliation(s)
- Andrea Mari
- Institute of Neuroscience, National Research Council, Padua, Italy
| | - Andrea Tura
- Institute of Neuroscience, National Research Council, Padua, Italy
| | - Eleonora Grespan
- Institute of Neuroscience, National Research Council, Padua, Italy
| | - Roberto Bizzotto
- Institute of Neuroscience, National Research Council, Padua, Italy
| |
Collapse
|
6
|
De Gaetano A, Hardy TA. A novel fast-slow model of diabetes progression: Insights into mechanisms of response to the interventions in the Diabetes Prevention Program. PLoS One 2019; 14:e0222833. [PMID: 31600232 PMCID: PMC6786566 DOI: 10.1371/journal.pone.0222833] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 09/09/2019] [Indexed: 12/22/2022] Open
Abstract
Several models for the long-term development of T2DM already exist, focusing on the dynamics of the interaction between glycemia, insulinemia and β-cell mass. Current models consider representative (fasting or daily average) glycemia and insulinemia as characterizing the compensation state of the subject at some instant in slow time. This implies that only these representative levels can be followed through time and that the role of fast glycemic oscillations is neglected. An improved model (DPM15) for the long-term progression of T2DM is proposed, introducing separate peripheral and hepatic (liver and kidney) insulin actions. The DPM15 model no longer uses near-equilibrium approximation to separate fast and slow time scales, but rather describes, at each step in slow time, a complete day in the life of the virtual subject in fast time. The model can thus represent both fasting and postprandial glycemic levels and describe the effect of interventions acting on insulin-enhanced tissue glucose disposal or on insulin-inhibited hepatic glucose output, as well as on insulin secretion and β-cell replicating ability. The model can simulate long-term variations of commonly used clinical indices (HOMA-B, HOMA-IR, insulinogenic index) as well as of Oral Glucose Tolerance or Euglycemic Hyperinsulinemic Clamp test results. The model has been calibrated against observational data from the Diabetes Prevention Program study: it shows good adaptation to observations as a function of very plausible values of the parameters describing the effect of such interventions as Placebo, Intensive LifeStyle and Metformin administration.
Collapse
Affiliation(s)
- Andrea De Gaetano
- CNR-IASI BioMatLab (Italian National Research Council - Institute of Analysis, Systems and Computer Science - Biomathematics Laboratory), Rome, Italy
| | - Thomas Andrew Hardy
- Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana, United States of America
| |
Collapse
|
7
|
De Gaetano A, Gaz C, Panunzi S. Consistency of compact and extended models of glucose-insulin homeostasis: The role of variable pancreatic reserve. PLoS One 2019; 14:e0211331. [PMID: 30768604 PMCID: PMC6377092 DOI: 10.1371/journal.pone.0211331] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 01/11/2019] [Indexed: 01/16/2023] Open
Abstract
Published compact and extended models of the glucose-insulin physiologic control system are compared, in order to understand why a specific functional form of the compact model proved to be necessary for a satisfactory representation of acute perturbation experiments such as the Intra Venous Glucose Tolerance Test (IVGTT). A spectrum of IVGTT’s of virtual subjects ranging from normal to IFG to IGT to frank T2DM were simulated using an extended model incorporating the population-of-controllers paradigm originally hypothesized by Grodsky, and proven to be able to capture a wide array of experimental results from heterogeneous perturbation procedures. The simulated IVGTT’s were then fitted with the Single-Delay Model (SDM), a compact model with only six free parameters, previously shown to be very effective in delivering precise estimates of insulin sensitivity and secretion during an IVGTT. Comparison of the generating, extended-model parameter values with the obtained compact model estimates shows that the functional form of the nonlinear insulin-secretion term, empirically found to be necessary for the compact model to satisfactorily fit clinical observations, captures the pancreatic reserve level of the simulated virtual patients. This result supports the validity of the compact model as a meaningful analysis tool for the clinical assessment of insulin sensitivity.
Collapse
Affiliation(s)
- Andrea De Gaetano
- CNR-IASI BioMatLab, Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica, Laboratorio di Biomatematica (Italian National Research Council - Institute for System Analysis and Computer Science - Biomathematics Laboratory), UCSC Largo A. Gemelli 8, Rome, Italy
| | - Claudio Gaz
- CNR-IASI BioMatLab, Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica, Laboratorio di Biomatematica (Italian National Research Council - Institute for System Analysis and Computer Science - Biomathematics Laboratory), UCSC Largo A. Gemelli 8, Rome, Italy
- Sapienza Università di Roma, Dipartimento di Ingegneria Informatica, Automatica e Gestionale (DIAG) (Department of Computer, Control and Management Engineering), Via Ariosto 25, Rome, Italy
- * E-mail: ,
| | - Simona Panunzi
- CNR-IASI BioMatLab, Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica, Laboratorio di Biomatematica (Italian National Research Council - Institute for System Analysis and Computer Science - Biomathematics Laboratory), UCSC Largo A. Gemelli 8, Rome, Italy
| |
Collapse
|
8
|
KANG HYUK, HAN KYUNGREEM, GOH SEGUN, CHOI MOOYOUNG. COEXISTENCE OF THREE OSCILLATORY MODES OF INSULIN SECRETION: MATHEMATICAL MODELING AND RELEVANCE TO GLUCOSE REGULATION. J BIOL SYST 2017. [DOI: 10.1142/s0218339017500188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Insulin secretion in pancreatic [Formula: see text]-cells exhibits three oscillatory modes with distinct period ranges, called fast, slow, and ultradian modes. To unveil the mechanism underlying such oscillatory behaviors and their roles in blood glucose regulation, we propose a combined model for the glucose–insulin regulation system, incorporating both the cell-level insulin secretion mechanism and inter-organ interactions in the blood glucose regulation. Special emphasis is placed on the identification of the mechanism of the slow oscillation and its role associated with the whole-body glucose regulation. Via extensive numerical simulations, we obtain macroscopic behaviors of the three types of insulin/glucose oscillations in the whole-body as well as microscopic behaviors of the membrane potential and the calcium concentration in the [Formula: see text]-cell. Finally, optimal regulatory strategies for the blood glucose level are discussed on the basis of the quantitative information obtained from the mathematical modeling and numerical simulations.
Collapse
Affiliation(s)
- HYUK KANG
- National Institute for Mathematical Sciences, Daejeon 34047, Korea
| | - KYUNGREEM HAN
- Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - SEGUN GOH
- Department of Physics and Center for Theoretical Physics, Seoul National University, Seoul 151-747, Korea
| | - MOOYOUNG CHOI
- Department of Physics and Center for Theoretical Physics, Seoul National University, Seoul 151-747, Korea
| |
Collapse
|
9
|
Huard B, Bridgewater A, Angelova M. Mathematical investigation of diabetically impaired ultradian oscillations in the glucose-insulin regulation. J Theor Biol 2017; 418:66-76. [PMID: 28130099 DOI: 10.1016/j.jtbi.2017.01.039] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Revised: 01/16/2017] [Accepted: 01/22/2017] [Indexed: 11/17/2022]
Abstract
We study the effect of diabetic deficiencies on the production of an oscillatory ultradian regime using a deterministic nonlinear model which incorporates two physiological delays. It is shown that insulin resistance impairs the production of oscillations by dampening the ultradian cycles. Four strategies for restoring healthy regulation are explored. Through the introduction of an instantaneous glucose-dependent insulin response, explicit conditions for the existence of periodic solutions in the linearised model are formulated, significantly reducing the complexity of identifying an oscillatory regime. The model is thus shown to be suitable for representing the effect of diabetes on the oscillatory regulation and for investigating pathways to reinstating a physiological healthy regime.
Collapse
Affiliation(s)
- B Huard
- Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
| | - A Bridgewater
- Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - M Angelova
- Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK; School of Information Technology, Deakin University, Burwood Vic 3125, Australia
| |
Collapse
|
10
|
Hsu MC, Wang ME, Jiang YF, Liu HC, Chen YC, Chiu CH. Long-term feeding of high-fat plus high-fructose diet induces isolated impaired glucose tolerance and skeletal muscle insulin resistance in miniature pigs. Diabetol Metab Syndr 2017; 9:81. [PMID: 29046729 PMCID: PMC5640912 DOI: 10.1186/s13098-017-0281-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 10/06/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND During the prediabetic development, the changes in β-cell function and tissue-specific insulin resistance have been described. However, there are conflicting views in insulin secretory capacity between early clinical observation and recent proposed mathematical model. On the basis of digestive and metabolic similarities with humans, swine have great potential as an animal model to investigate the progressive mechanisms of prediabetes. The aim of this study was to investigate the insulin secretory response and tissue-specific insulin resistance in a dietary-induced prediabetic porcine model. METHODS Adult male Taiwan Lee-Sung miniature pigs were randomized into two groups: (1) low-fat diet and (2) high-fat plus high-fructose diet (HFHF; 20.9% crude fat and 17.8% fructose). During the 12-month dietary intervention, body weights and blood glucose levels were measured monthly. Intravenous glucose tolerance test was used for measuring glucose tolerance and insulin secretory capacity. At the end of the experiment, liver and soleus muscle specimens were collected for ex vivo insulin sensitivity testing. RESULTS The results showed that the HFHF group had obesity, hyperinsulinemia, and dyslipidemia, but normal fasting glucose levels. The HFHF pigs exhibited enhanced first- and second-phase insulin secretion and high 2-h postload glucose levels in intravenous glucose tolerance test. Furthermore, the skeletal muscle specimens from the HFHF group were desensitized to insulin stimulation as shown by the lack of AKT Ser473 phosphorylation; however, the liver specimens remained a normal response. CONCLUSIONS In conclusion, the HFHF diet-fed pigs developed isolated impaired glucose tolerance corresponding to prediabetes with an intense insulin secretory response and skeletal muscle insulin resistance.
Collapse
Affiliation(s)
- Meng-Chieh Hsu
- Laboratory of Animal Physiology, Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
| | - Mu-En Wang
- Laboratory of Animal Physiology, Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
| | - Yi-Fan Jiang
- Laboratory of Animal Physiology, Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
- Graduate Institute of Molecular and Comparative Pathobiology, School of Veterinary Medicine, National Taiwan University, No. 1, Sec. 4, Rooservelt Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
| | - Hung-Chang Liu
- Department of Thoracic Surgery, Mackay Memorial Hospital, No. 92, Sec. 2, Chung-Shan North Rd., Zhongshan Dist., Taipei, 104 Taiwan, Republic of China
| | - Yi-Chen Chen
- Laboratory of Animal Physiology, Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
| | - Chih-Hsien Chiu
- Laboratory of Animal Physiology, Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei, 106 Taiwan, Republic of China
| |
Collapse
|