1
|
Visentin R, Cobelli C, Sieber J, Dalla Man C. Short- and Long-Term Effects on Glucose Control of Nonadherence to Insulin Therapy in People With Type 2 Diabetes An In Silico Study. J Diabetes Sci Technol 2024; 18:309-317. [PMID: 38284154 DOI: 10.1177/19322968231223936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
BACKGROUND Strict adherence to multiple daily insulin (MDI) therapy is a cornerstone for the achievement of good glucose control in people with advanced type 2 diabetes (T2D). Here, we aim to in silico assess glucose control in T2D subjects with poor adherence to MDI therapy. METHODS We tuned the Padova T2D Simulator, originally describing early-stage T2D physiology, around advanced T2D people. One hundred in silico advanced T2D subjects were generated and equipped with optimal MDI therapy: specifically, basal and bolus insulin amounts and injection times were individualized for each subject by applying titration algorithms that iteratively update insulin dose based on glucose deviation from its target. Then, the effect of nonadhering to MDI therapy was assessed using standard glucose control metrics calculated in two 6-month 3-meal/day in silico scenarios: in Scenario 1, subjects received the optimal basal and prandial insulin bolus at each meal; in Scenario 2, subjects received optimal basal insulin and randomly delayed or skipped the prandial insulin bolus in 3 lunches during working days and 1 dinner during weekends. RESULTS A statistically significant degradation was found in all glucose control outcome metrics in Scenario 2 versus Scenario 1: e.g., percent time above 180 mg/dL increased by 22.2% and glucose management index by 0.2%. CONCLUSIONS Impaired adherence to MDI therapy in T2D leads to glucose control deteriorations in both short and long terms. Interestingly, short-term hyperglycemia seems being contrasted by residual endogenous insulin secretion, which statistically increased by 3-fold after delayed/skipped insulin boluses compared with optimal ones.
Collapse
Affiliation(s)
- Roberto Visentin
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padua, Padua, Italy
| | | | - Chiara Dalla Man
- Department of Information Engineering, University of Padua, Padua, Italy
| |
Collapse
|
2
|
Romeres D, Yadav Y, Ruchi FNU, Carter R, Cobelli C, Basu R, Basu A. Hyperglycemia suppresses Lactate Clearance during Exercise in Type 1 Diabetes. J Clin Endocrinol Metab 2024:dgae005. [PMID: 38174728 DOI: 10.1210/clinem/dgae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/19/2023] [Accepted: 01/02/2024] [Indexed: 01/05/2024]
Abstract
CONTEXT Circulating lactate concentration is an important determinant of exercise tolerance. OBJECTIVE To determine the role of hyperglycemia on lactate metabolism during exercise in type 1 diabetes (T1D). DESIGN Protocol involved compared T1D participants and participants without diabetes (ND) at euglycemia [5.5mM] or hyperglycemia [9.2mM] in random order in T1D and at euglycemia in ND. SETTING Clinical Research Unit, University of Virginia, Charlottesville, VA. PARTICIPANTS 7 T1D and 7 ND. INTERVENTION [1-13C] lactate infusion, exercise at 65% VO2max, euglycemia and hyperglycemia visits. MAIN OUTCOME MEASURE Lactate turnover before, during and after 60 min of exercise at 65% VO2max. RESULTS A two-compartment model with loss only from the peripheral compartment described lactate kinetics. Volume of distribution of the accessible compartment was similar between T1D and ND (p=0.76) and concordant to plasma volume (∼40ml/kg). Circulating lactate concentrations were higher (p<0.001) in T1D participants during exercise at hyperglycemia than euglycemia. Exercise induced lactate appearance did not differ (p=0.13) between hyperglycemia and euglycemia. However, lactate clearance was lower (p=0.03) during hyperglycemia than euglycemia in T1D. There were no differences in any of the above parameters between T1D and ND during euglycemia. CONCLUSIONS Hyperglycemia modulates lactate metabolism during exercise by lowering lactate clearance leading to higher circulating lactate concentrations in T1D. This novel observation implies that exercise during hyperglycemia can lead to higher circulating lactate concentrations thus increasing the likelihood of reaching the lactate threshold sooner in T1D, and has high translational relevance for both providers and recreationally active people with Type 1 diabetes.
Collapse
Affiliation(s)
- Davide Romeres
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Yogesh Yadav
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - F N U Ruchi
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Rickey Carter
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Padova, Italy
| | - Rita Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Ananda Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908
| |
Collapse
|
3
|
Welch AA, Farahani RA, Egan AM, Laurenti MC, Zeini M, Vella M, Bailey KR, Cobelli C, Dalla Man C, Matveyenko A, Vella A. Glucagon-like peptide-1 receptor blockade impairs islet secretion and glucose metabolism in humans. J Clin Invest 2023; 133:e173495. [PMID: 37751301 PMCID: PMC10645389 DOI: 10.1172/jci173495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/12/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUNDProglucagon can be processed to glucagon-like peptide1 (GLP-1) within the islet, but its contribution to islet function in humans remains unknown. We sought to understand whether pancreatic GLP-1 alters islet function in humans and whether this is affected by type 2 diabetes.METHODSWe therefore studied individuals with and without type 2 diabetes on two occasions in random order. On one occasion, exendin 9-39, a competitive antagonist of the GLP-1 Receptor (GLP1R), was infused, while on the other, saline was infused. The tracer dilution technique ([3-3H] glucose) was used to measure glucose turnover during fasting and during a hyperglycemic clamp.RESULTSExendin 9-39 increased fasting glucose concentrations; fasting islet hormone concentrations were unchanged, but inappropriate for the higher fasting glucose observed. In people with type 2 diabetes, fasting glucagon concentrations were markedly elevated and persisted despite hyperglycemia. This impaired suppression of endogenous glucose production by hyperglycemia.CONCLUSIONThese data show that GLP1R blockade impairs islet function, implying that intra-islet GLP1R activation alters islet responses to glucose and does so to a greater degree in people with type 2 diabetes.TRIAL REGISTRATIONThis study was registered at ClinicalTrials.gov NCT04466618.FUNDINGThe study was primarily funded by NIH NIDDK DK126206. AV is supported by DK78646, DK116231 and DK126206. CDM was supported by MIUR (Italian Minister for Education) under the initiative "Departments of Excellence" (Law 232/2016).
Collapse
Affiliation(s)
- Andrew A. Welch
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Rahele A. Farahani
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Aoife M. Egan
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Marcello C. Laurenti
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Maya Zeini
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Max Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Kent R. Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Aleksey Matveyenko
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| |
Collapse
|
4
|
Cobelli C, Kovatchev B. Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility. J Diabetes Sci Technol 2023; 17:1493-1505. [PMID: 37743740 PMCID: PMC10658679 DOI: 10.1177/19322968231195081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Arguably, diabetes mellitus is one of the best quantified human conditions. In the past 50 years, the metabolic monitoring technologies progressed from occasional assessment of average glycemia via HbA1c, through episodic blood glucose readings, to continuous glucose monitoring (CGM) producing data points every few minutes. The high-temporal resolution of CGM data enabled increasingly intensive treatments, from decision support assisting insulin injection or oral medication, to automated closed-loop control, known as the "artificial pancreas." Throughout this progress, mathematical models and computer simulation of the human metabolic system became indispensable for the technological progress of diabetes treatment, enabling every step, from assessment of insulin sensitivity via the now classic Minimal Model of Glucose Kinetics, to in silico trials replacing animal experiments, to automated insulin delivery algorithms. In this review, we follow these developments, beginning with the Minimal Model, which evolved through the years to become large and comprehensive and trigger a paradigm change in the design of diabetes optimization strategies: in 2007, we introduced a sophisticated model of glucose-insulin dynamics and a computer simulator equipped with a "population" of N = 300 in silico "subjects" with type 1 diabetes. In January 2008, in an unprecedented decision, the Food and Drug Administration (FDA) accepted this simulator as a substitute to animal trials for the pre-clinical testing of insulin treatment strategies. This opened the field for rapid and cost-effective development and pre-clinical testing of new treatment approaches, which continues today. Meanwhile, animal experiments for the purpose of designing new insulin treatment algorithms have been abandoned.
Collapse
Affiliation(s)
| | - Boris Kovatchev
- Center for Diabetes Technology,
University of Virginia, Charlottesville, VA, USA
| |
Collapse
|
5
|
Kanaley JA, Porter JW, Winn NC, Lastra G, Chockalingam A, Pettit-Mee RJ, Petroski GF, Cobelli C, Schiavon M, Parks EJ. Temporal optimization of exercise to lower fasting glucose levels. J Physiol 2023:10.1113/JP285069. [PMID: 37732475 PMCID: PMC10954586 DOI: 10.1113/jp285069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/30/2023] [Indexed: 09/22/2023] Open
Abstract
Exercise stimulates glucose uptake and increases insulin sensitivity acutely. Temporally optimizing exercise timing may minimize the nocturnal rise in glucose levels. This study examined the effect of exercise timing on evening and overnight glucose concentrations in individuals who were non-obese with normal fasting glucose levels (Non-Ob; n = 18) and individuals with obesity (OB) with impaired fasting glucose levels (OB+IFG) and without (n = 16 and n = 18, respectively). Subjects were studied on three occasions (no exercise (NOEX)), morning exercise (AMEX; 0700 h) and evening exercise (PMEX; 2000 h). The evening meal was provided (1800 h) and blood samples were taken from 1740 to 0700 h and morning endogenous glucose production (EGP) was measured. Glucose and insulin concentrations increased with the dinner meal with peak concentrations being higher in OB+IFG than in OB and Non-Ob (P = 0.04). In OB+IFG, evening glucose concentrations rose above baseline levels at about 2300 h, with the glucose concentrations staying somewhat lower with AMEX and PMEX until ∼0500 h than with NOEX. In OB+IFG, insulin concentrations decreased following the dinner meal and waned throughout the night, despite the rising glucose concentrations. In the OB and Non-Ob individuals following the dinner meal, no increase in glucose concentrations occurred in the evening period and insulin levels mirrored this. No difference was observed in the morning fasting glucose levels between study days or between groups. Regardless of time of day, exercise delays the evening rise in glucose concentrations in adults with OB+IFG but does not lower morning fasting glucose levels or improve the synchrony between glucose and insulin concentrations. KEY POINTS: Insulin resistance and type 2 diabetes have been linked to disturbances of the core clock, and glucose tolerance demonstrates a diurnal rhythm in healthy humans with better glucose tolerance in the morning than in the afternoon and evening. Skeletal muscle is a primary site for insulin resistance in people with impaired glucose tolerance. In individuals with obesity and impaired fasting glucose levels (OB+IFG), following a dinner meal, glucose concentrations started to rise and continues throughout the night, resulting in elevated glucose levels, while concomitantly, insulin levels are waning. Exercise, regardless of the time of day, suppressed the rise in glucose levels in OB+IFG for many hours during the night but did not lower morning fasting glucose levels. Morning exercise was not quite as effective as evening exercise.
Collapse
Affiliation(s)
- Jill A Kanaley
- Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, Missouri, USA
| | - J W Porter
- Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, Missouri, USA
| | - N C Winn
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, USA
| | - G Lastra
- Department of Endocrinology, Internal Medicine, University of Missouri, Columbia, Missouri, USA
| | - A Chockalingam
- Department of Cardiology, University of Missouri, Columbia, Missouri, USA
| | - R J Pettit-Mee
- Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, Missouri, USA
| | - G F Petroski
- Office of Medical Research, Biostatistics Unit, University of Missouri, Columbia, Missouri, USA
| | - C Cobelli
- Department of Women's and Children's Health, University of Padova, Padova, Italy
| | - M Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - E J Parks
- Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, Missouri, USA
| |
Collapse
|
6
|
Taylor R, Barnes A, Hollingsworth K, Irvine K, Solovyova A, Clark L, Kelly T, Martin-Ruiz C, Romeres D, Koulman A, Meek C, Jenkins B, Cobelli C, Holman R. Aetiology of Type 2 diabetes in people with a 'normal' body mass index: testing the personal fat threshold hypothesis. Clin Sci (Lond) 2023; 137:1333-1346. [PMID: 37593846 PMCID: PMC10472166 DOI: 10.1042/cs20230586] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 08/19/2023]
Abstract
Weight loss in overweight or obese individuals with Type 2 diabetes (T2D) can normalize hepatic fat metabolism, decrease fatty acid oversupply to β cells and restore normoglycaemia. One in six people has BMI <27 kg/m2 at diagnosis, and their T2D is assumed to have different aetiology. The Personal Fat Threshold hypothesis postulated differing individual thresholds for lipid overspill and adverse effects on β-cell function. To test this hypothesis, people with Type 2 diabetes and body mass index <27kg/m2 (n = 20) underwent repeated 5% weight loss cycles. Metabolic assessments were carried out at stable weight after each cycle and after 12 months. To determine how closely metabolic features returned to normal, 20 matched normoglycemic controls were studied once. Between baseline and 12 months: BMI fell (mean ± SD), 24.8 ± 0.4 to 22.5 ± 0.4 kg/m2 (P<0.0001) (controls: 21.5 ± 0.5); total body fat, 32.1 ± 1.5 to 27.6 ± 1.8% (P<0.0001) (24.6 ± 1.5). Liver fat content and fat export fell to normal as did fasting plasma insulin. Post-meal insulin secretion increased but remained subnormal. Sustained diabetes remission (HbA1c < 48 mmol/mol off all glucose-lowering agents) was achieved by 70% (14/20) by initial weight loss of 6.5 (5.5-10.2)%. Correction of concealed excess intra-hepatic fat reduced hepatic fat export, with recovery of β-cell function, glycaemic improvement in all and return to a non-diabetic metabolic state in the majority of this group with BMI <27 kg/m2 as previously demonstrated for overweight or obese groups. The data confirm the Personal Fat Threshold hypothesis: aetiology of Type 2 diabetes does not depend on BMI. This pathophysiological insight has major implications for management.
Collapse
Affiliation(s)
- Roy Taylor
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Alison C. Barnes
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Kieren G. Hollingsworth
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Keaton M. Irvine
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | | | - Lucy Clark
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Tara Kelly
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Carmen Martin-Ruiz
- BioScreening Core Facility, Campus for Ageing and Vitality, Faculty of Medical Sciences, Newcastle University, U.K
| | - Davide Romeres
- Department of Endocrinology, University of Virginia, Charlottesville, VA, U.S.A
| | - Albert Koulman
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Box 289, Cambridge Biomedical Campus, Cambridge, U.K
| | - Claire M. Meek
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Box 289, Cambridge Biomedical Campus, Cambridge, U.K
- Wolfson Diabetes and Endocrine Centre, Cambridge Universities NHS Foundation Trust, Cambridge, U.K
| | - Benjamin Jenkins
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Box 289, Cambridge Biomedical Campus, Cambridge, U.K
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Italy
| | - Rury R. Holman
- Diabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
| |
Collapse
|
7
|
Bonet J, Yadav Y, Miles J, Basu A, Cobelli C, Basu R, Dalla Man C. A new oral model of free fatty acid kinetics to assess lipolysis in subjects with and without type 2 diabetes. Am J Physiol Endocrinol Metab 2023; 325:E163-E170. [PMID: 37378622 PMCID: PMC10393336 DOI: 10.1152/ajpendo.00091.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 06/02/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023]
Abstract
Assessing free fatty acids (FFAs) kinetics and the role of insulin and glucose on FFA lipolysis and disposal may improve our understanding of the pathogenesis of type 2 diabetes (T2D). Some models have been proposed to describe FFA kinetics during an intravenous glucose tolerance test and only one during an oral glucose tolerance test. Here, we propose a model of FFA kinetics during a meal tolerance test and use it to assess possible differences in postprandial lipolysis in individuals with type 2 diabetes (T2D) and individuals with obesity without type 2 diabetes (ND). We studied 18 obese ND and 16 T2D undergoing three meal tolerance tests (MTT) on three occasions (breakfast, lunch, and dinner). We used plasma glucose, insulin, and FFA concentrations collected at breakfast to test a battery of models and selected the best one based on physiological plausibility, ability to fit the data, precision of parameter estimates, and the Akaike parsimony criterion. The best model assumes that the postprandial suppression of FFA lipolysis is proportional to the above basal insulin, while FFA disposal is proportional to FFA concentration. It was used to compare FFA kinetics in ND and T2D along the day. The maximum lipolysis suppression occurred significantly earlier in ND than T2D (39 ± 6 min vs. 102 ± 13 min, 36 ± 4 min vs. 78 ± 11 min, and 38 ± 6 min vs. 84 ± 13 min, P < 0.01, at breakfast, lunch, and dinner, respectively), making lipolysis significantly lower in ND than T2D. This is mainly attributable to the lower insulin concentration in the second group. This novel FFA model allows to assess lipolysis and insulin antilipolytic effect in postprandial conditions.NEW & NOTEWORTHY In this study, we propose a new mathematical model able to quantify postprandial FFA kinetics and adipose tissue insulin sensitivity in both subjects with obesity without type 2 diabetes (ND) and subjects with type 2 diabetes (T2D). Results show that the slower postprandial suppression of lipolysis in T2D contributes to the higher free fatty acid (FFA) concentration that, in turn, may contribute to hyperglycemia.
Collapse
Affiliation(s)
- J. Bonet
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Y. Yadav
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - J. Miles
- University of Kansas Medical Center, Kansas City, Kansas, United States
| | - A. Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - C. Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - R. Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - C. Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
8
|
Ballardini G, Tamadon I, Guarnera D, Al-Haddad H, Iacovacci V, Mariottini F, Ricciardi S, Cucini A, Libera AD, Vistoli F, Menciassi A, Dario P, Cobelli C, Ricotti L. Controlling and powering a fully implantable artificial pancreas refillable by ingestible pills. Annu Int Conf IEEE Eng Med Biol Soc 2023; 2023:1-7. [PMID: 38083764 DOI: 10.1109/embc40787.2023.10340006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Over the past decade, there has been a growing interest in the development of an artificial pancreas for intraperitoneal insulin delivery. Intraperitoneal implantable pumps guarantee more physiological glycemic control than subcutaneous wearable ones, for the treatment of type 1 diabetes. In this work, a fully implantable artificial pancreas refillable by ingestible pills is presented. In particular, solutions enabling the communication between the implanted pump and external user interfaces and novel control algorithms to intraperitoneally release an adequate amount of insulin based on glycemic data are shown. In addition, the powering and the wireless battery recharging are addressed. Specifically, the design and optimization of a customized transcutaneous energy transfer with two independent wireless channels are presented. The system was tested in terms of recharging efficacy, possible temperature rise within the body, during the recharging process and reliability of the wireless connection in the air and in the presence of ex vivo tissues.Clinical Relevance- This work aims to improve the control, battery recharging, and wireless communication of a fully implantable artificial pancreas for type 1 diabetes treatment.
Collapse
|
9
|
Schembri Wismayer D, Laurenti MC, Song Y, Egan AM, Welch AA, Bailey KR, Cobelli C, Dalla Man C, Jensen MD, Vella A. Effects of overnight fasting milieu on indices of β-cell function and glucose metabolism in subjects without diabetes. Am J Physiol Endocrinol Metab 2023. [PMID: 37285600 PMCID: PMC10393375 DOI: 10.1152/ajpendo.00043.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 06/06/2023] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Elevated fasting free fatty acids (FFA) are associated with Impaired Glucose Tolerance (IGT) and decreased β-cell function (quantified as Disposition Index (DI)). We sought to examine how changes in fasting FFA and glucose alter islet function. METHODS We studied 10 subjects with Normal Fasting Glucose (NFG) and Normal Glucose Tolerance (NGT) on 2 occasions. On one occasion, Intralipid® and glucose were infused overnight to mimic conditions present in IFG/IGT. In addition, we studied 7 subjects with IFG/IGT on 2 occasions. On one occasion insulin was infused to lower overnight FFA and glucose concentrations to those observed in people with NFG/NGT. The following morning, a labeled mixed meal was used to measure postprandial glucose metabolism and β-cell function. RESULTS Elevation of overnight fasting FFA and glucose in NFG/NGT did not alter peak or integrated glucose concentrations (2.0 ± 0.1 vs 2.0 ± 0.1 Mol per 5 h, Saline vs. Intralipid® / glucose, p = 0.55). While overall β-cell function quantified by the Disposition Index was unchanged, the dynamic component of β-cell responsivity (fd) was decreased by Intralipid® and glucose infusion (9 ± 1 vs. 16 ± 3 10-9, p = 0.02). In people with IFG/IGT, insulin did not alter postprandial glucose concentrations or indices of β-cell function. Endogenous glucose production and glucose disappearance was also unchanged in both groups. CONCLUSIONS We conclude that acute, overnight changes in FFA and glucose concentrations do not alter islet function or glucose metabolism in prediabetes.
Collapse
Grants
- DK TR000135 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
- DK78646 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
- DK116231 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
- DK126206 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
- DK40484 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
- DK45343 HHS | NIH | NIDDK | Division of Diabetes, Endocrinology, and Metabolic Diseases (DEM)
Collapse
Affiliation(s)
- Daniel Schembri Wismayer
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| | - Marcello C Laurenti
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States
| | - Yilin Song
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| | - Andrew A Welch
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Michael D Jensen
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| | - Adrian Vella
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States
| |
Collapse
|
10
|
Dalla Libera A, Toffanin C, Drecogna M, Galderisi A, Pillonetto G, Cobelli C. In silico design and validation of a time-varying PID controller for an artificial pancreas with intraperitoneal insulin delivery and glucose sensing. APL Bioeng 2023; 7:026105. [PMID: 37229215 PMCID: PMC10205143 DOI: 10.1063/5.0145446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023] Open
Abstract
Type 1 diabetes (T1D) is a chronic autoimmune disease featured by the loss of beta cell function and the need for lifetime insulin replacement. Over the recent decade, the use of automated insulin delivery systems (AID) has shifted the paradigm of treatment: the availability of continuous subcutaneous (SC) glucose sensors to guide SC insulin delivery through a control algorithm has allowed, for the first time, to reduce the daily burden of the disease as well as to abate the risk for hypoglycemia. AID use is still limited by individual acceptance, local availability, coverage, and expertise. A major drawback of SC insulin delivery is the need for meal announcement and the peripheral hyperinsulinemia that, over time, contributes to macrovascular complications. Inpatient trials using intraperitoneal (IP) insulin pumps have demonstrated that glycemic control can be improved without meal announcement due to the faster insulin delivery through the peritoneal space. This calls for novel control algorithms able to account for the specificities of IP insulin kinetics. Recently, our group described a two-compartment model of IP insulin kinetics demonstrating that the peritoneal space acts as a virtual compartment and IP insulin delivery is virtually intraportal (intrahepatic), thus closely mimicking the physiology of insulin secretion. The FDA-accepted T1D simulator for SC insulin delivery and sensing has been updated for IP insulin delivery and sensing. Herein, we design and validate-in silico-a time-varying proportional integrative derivative controller to guide IP insulin delivery in a fully closed-loop mode without meal announcement.
Collapse
Affiliation(s)
- Alberto Dalla Libera
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
| | - Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Martina Drecogna
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
| | | | - Gianluigi Pillonetto
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
| |
Collapse
|
11
|
Galderisi A, Evans-Molina C, Martino M, Caprio S, Cobelli C, Moran A. β-Cell Function and Insulin Sensitivity in Youth With Early Type 1 Diabetes From a 2-Hour 7-Sample OGTT. J Clin Endocrinol Metab 2023; 108:1376-1386. [PMID: 36546354 PMCID: PMC10188312 DOI: 10.1210/clinem/dgac740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
CONTEXT The oral minimal model is a widely accepted noninvasive tool to quantify both β-cell responsiveness and insulin sensitivity (SI) from glucose, C-peptide, and insulin concentrations during a 3-hour 9-point oral glucose tolerance test (OGTT). OBJECTIVE Here, we aimed to validate a 2-hour 7-point protocol against the 3-hour OGTT and to test how variation in early sampling frequency impacts estimates of β-cell responsiveness and SI. METHODS We conducted a secondary analysis on 15 lean youth with stage 1 type 1 diabetes (T1D; ≥ 2 islet autoantibodies with no dysglycemia) who underwent a 3-hour 9-point OGTT. The oral minimal model was used to quantitate β-cell responsiveness (φtotal) and insulin sensitivity (SI), allowing assessment of β-cell function by the disposition index (DI = φtotal × SI). Seven- and 5-point 2-hour OGTT protocols were tested against the 3-hour 9-point gold standard to determine agreement between estimates of φtotal and its dynamic and static components, SI, and DI across different sampling strategies. RESULTS The 2-hour estimates for the disposition index exhibited a strong correlation with 3-hour measures (r = 0.975; P < .001) with similar results for β-cell responsiveness and SI (r = 0.997 and r = 0.982; P < .001, respectively). The agreement of the 3 estimates between the 7-point 2-hour and 9-point 3-hour protocols fell within the 95% CI on the Bland-Altman grid with a median difference of 16.9% (-35.3 to 32.5), 0.2% (-0.6 to 1.3), and 14.9% (-1.4 to 28.3) for DI, φtotal, and SI. Conversely, the 5-point protocol did not provide reliable estimates of φ dynamic and static components. CONCLUSION The 2-hour 7-point OGTT is reliable in individuals with stage 1 T1D for assessment of β-cell responsiveness, SI, and DI. Incorporation of these analyses into current 2-hour diabetes staging and monitoring OGTTs offers the potential to more accurately quantify risk of progression in the early stages of T1D.
Collapse
Affiliation(s)
- Alfonso Galderisi
- Department of Woman and Child's Health, University of Padova,
35128 Padua, Italy
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana
University, Indianapolis, Indiana 46202, USA
| | - Mariangela Martino
- Department of Woman and Child's Health, University of Padova,
35128 Padua, Italy
| | - Sonia Caprio
- Department of Pediatrics, Yale University, New
Haven, Connecticut 06520, USA
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova,
35128 Padua, Italy
| | - Antoinette Moran
- Department of Pediatrics, University of Minnesota,
Minneapolis, Minnesota 55454, USA
| |
Collapse
|
12
|
Farahani RA, Egan AM, Welch AA, Laurenti MC, Cobelli C, Dalla Man C, Vella A. The Effect of Glucagon-Like Peptide 1 Receptor Blockade on Glucagon-Induced Stimulation of Insulin Secretion. Diabetes 2023; 72:449-454. [PMID: 36562995 PMCID: PMC10260388 DOI: 10.2337/db22-0709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]
Abstract
Data from transgenic rodent models suggest that glucagon acts as an insulin secretagogue by signaling through the glucagon-like peptide 1 receptor (GLP-1R) present on β-cells. However, its net contribution to physiologic insulin secretion in humans is unknown. To address this question, we studied individuals without diabetes in two separate experiments. Each subject was studied on two occasions in random order. In the first experiment, during a hyperglycemic clamp, glucagon was infused at 0.4 ng/kg/min, increasing by 0.2 ng/kg/min every hour for 5 h. On one day, exendin-9,39 (300 pmol/kg/min) was infused to block GLP-1R, while on the other, saline was infused. The insulin secretion rate (ISR) was calculated by nonparametric deconvolution from plasma concentrations of C-peptide. Endogenous glucose production and glucose disappearance were measured using the tracer-dilution technique. Glucagon concentrations, by design, did not differ between study days. Integrated ISR was lower during exendin-9,39 infusion (213 ± 26 vs. 191 ± 22 nmol/5 h, saline vs. exendin-9,39, respectively; P = 0.02). In the separate experiment, exendin-9,39 infusion, compared with saline infusion, also decreased the β-cell secretory response to a 1-mg glucagon bolus. These data show that, in humans without diabetes, glucagon partially stimulates the β-cell through GLP-1R.
Collapse
Affiliation(s)
- Rahele A. Farahani
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN
| | - Aoife M. Egan
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN
| | - Andrew A. Welch
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN
| | - Marcello C. Laurenti
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN
| | - Claudio Cobelli
- Department of Women’s and Children’s Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN
| |
Collapse
|
13
|
Phillip M, Nimri R, Bergenstal RM, Barnard-Kelly K, Danne T, Hovorka R, Kovatchev BP, Messer LH, Parkin CG, Ambler-Osborn L, Amiel SA, Bally L, Beck RW, Biester S, Biester T, Blanchette JE, Bosi E, Boughton CK, Breton MD, Brown SA, Buckingham BA, Cai A, Carlson AL, Castle JR, Choudhary P, Close KL, Cobelli C, Criego AB, Davis E, de Beaufort C, de Bock MI, DeSalvo DJ, DeVries JH, Dovc K, Doyle FJ, Ekhlaspour L, Shvalb NF, Forlenza GP, Gallen G, Garg SK, Gershenoff DC, Gonder-Frederick LA, Haidar A, Hartnell S, Heinemann L, Heller S, Hirsch IB, Hood KK, Isaacs D, Klonoff DC, Kordonouri O, Kowalski A, Laffel L, Lawton J, Lal RA, Leelarathna L, Maahs DM, Murphy HR, Nørgaard K, O’Neal D, Oser S, Oser T, Renard E, Riddell MC, Rodbard D, Russell SJ, Schatz DA, Shah VN, Sherr JL, Simonson GD, Wadwa RP, Ward C, Weinzimer SA, Wilmot EG, Battelino T. Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice. Endocr Rev 2023; 44:254-280. [PMID: 36066457 PMCID: PMC9985411 DOI: 10.1210/endrev/bnac022] [Citation(s) in RCA: 79] [Impact Index Per Article: 79.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/22/2022] [Indexed: 02/06/2023]
Abstract
The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.
Collapse
Affiliation(s)
- Moshe Phillip
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Revital Nimri
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Richard M Bergenstal
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | | | - Thomas Danne
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Boris P Kovatchev
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Laurel H Messer
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | | | | | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Roy W Beck
- Jaeb Center for Health Research Foundation, Inc., Tampa, FL 33647, USA
| | - Sarah Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Torben Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Julia E Blanchette
- College of Nursing, University of Utah, Salt Lake City, UT 84112, USA
- Center for Diabetes and Obesity, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Hospital and San Raffaele Vita Salute University, Milan, Italy
| | - Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Marc D Breton
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Sue A Brown
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Division of Endocrinology, University of Virginia, Charlottesville, VA 22903, USA
| | - Bruce A Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Albert Cai
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Anders L Carlson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Jessica R Castle
- Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Pratik Choudhary
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Kelly L Close
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - Amy B Criego
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Elizabeth Davis
- Telethon Kids Institute, University of Western Australia, Perth Children’s Hospital, Perth, Australia
| | - Carine de Beaufort
- Diabetes & Endocrine Care Clinique Pédiatrique DECCP/Centre Hospitalier Luxembourg, and Faculty of Sciences, Technology and Medicine, University of Luxembourg, Esch sur Alzette, GD Luxembourg/Department of Paediatrics, UZ-VUB, Brussels, Belgium
| | - Martin I de Bock
- Department of Paediatrics, University of Otago, Christchurch, New Zealand
| | - Daniel J DeSalvo
- Division of Pediatric Diabetes and Endocrinology, Baylor College of Medicine, Texas Children’s Hospital, Houston, TX 77598, USA
| | - J Hans DeVries
- Amsterdam UMC, University of Amsterdam, Internal Medicine, Amsterdam, The Netherlands
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Laya Ekhlaspour
- Lucile Packard Children’s Hospital—Pediatric Endocrinology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Naama Fisch Shvalb
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
| | - Gregory P Forlenza
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Satish K Garg
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Dana C Gershenoff
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Linda A Gonder-Frederick
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Ahmad Haidar
- Department of Biomedical Engineering, McGill University, Montreal, Canada
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Simon Heller
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Irl B Hirsch
- Department of Medicine, University of Washington Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Korey K Hood
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Diana Isaacs
- Cleveland Clinic, Endocrinology and Metabolism Institute, Cleveland, OH 44106, USA
| | - David C Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA 94010, USA
| | - Olga Kordonouri
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | | | - Lori Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Julia Lawton
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Rayhan A Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lalantha Leelarathna
- Manchester University Hospitals NHS Foundation Trust/University of Manchester, Manchester, UK
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Helen R Murphy
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Kirsten Nørgaard
- Steno Diabetes Center Copenhagen and Department of Clinical Medicine, University of Copenhagen, Gentofte, Denmark
| | - David O’Neal
- Department of Medicine and Department of Endocrinology, St Vincent’s Hospital Melbourne, University of Melbourne, Melbourne, Australia
| | - Sean Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tamara Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, and Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Michael C Riddell
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, Canada
| | - David Rodbard
- Biomedical Informatics Consultants LLC, Potomac, MD, USA
| | - Steven J Russell
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Desmond A Schatz
- Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL 02114, USA
| | - Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Gregg D Simonson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - R Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Candice Ward
- Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Emma G Wilmot
- Department of Diabetes & Endocrinology, University Hospitals of Derby and Burton NHS Trust, Derby, UK
- Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Nottingham, England, UK
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| |
Collapse
|
14
|
Yadav Y, Romeres D, Cobelli C, Dalla Man C, Carter R, Basu A, Basu R. Impaired Diurnal Pattern of Meal Tolerance and Insulin Sensitivity in Type 2 Diabetes: Implications for Therapy. Diabetes 2023; 72:223-232. [PMID: 36346619 PMCID: PMC9871193 DOI: 10.2337/db22-0238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 11/03/2022] [Indexed: 11/09/2022]
Abstract
To assess the diurnal patterns of postprandial glucose tolerance and insulin sensitivity, 19 subjects with type 2 diabetes (8 women; 60 ± 11 years; BMI 32 ± 5 kg/m2) and 19 anthropometrically matched subjects with no diabetes (ND; 11 women; 53 ± 12 years; BMI 29 ± 5 kg/m2) were studied during breakfast (B), lunch (L), and dinner (D) with identical mixed meals (75 g carbohydrates) on 3 consecutive days in a randomized Latin square design. Three stable isotopes of glucose were ustilized to estimate meal fluxes, and mathematical models were used in estimating indices of insulin action and β-cell function. Postmeal glucose excursions were higher at D versus B and at D versus L in type 2 diabetes (P < 0.05), while in ND they were higher at D versus B (P = 0.025) and at L versus B (P = 0.04). The insulin area under the curve was highest at B compared with L and D in type 2 diabetes, while no differences were observed in ND. Disposition index (DI) was higher at B than at L (P < 0.01) and at D (P < 0.001) in ND subjects, whereas DI was low with unchanging pattern across B-L-D in individuals with type 2 diabetes. Furthermore, between-meal differences in β-cell responsivity to glucose (F) and insulin sensitivity (SI) were concurrent with changes in the DI within groups. Fasting and postmeal glucose, insulin, and C-peptide concentrations, along with estimates of endogenous glucose production (EGP), Rd, SI, F, hepatic extraction of insulin, insulin secretion rate, extracted insulin, and DI, were altered in type 2 diabetes compared with ND (P < 0.011 for all). The data show a diurnal pattern of postprandial glucose tolerance in overweight otherwise glucose-tolerant ND individuals that differs from overweight individuals with type 2 diabetes. The results not only provide valuable insight into management strategies for better glycemic control in people with type 2 diabetes, but also improved understanding of daytime glucose metabolism in overweight individuals without impaired glucose tolerance or overt diabetes.
Collapse
Affiliation(s)
- Yogesh Yadav
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA
| | - Davide Romeres
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Rickey Carter
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL
| | - Ananda Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA
| | - Rita Basu
- Division of Endocrinology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA
| |
Collapse
|
15
|
Kohlenberg JD, Laurenti MC, Egan AM, Wismayer DS, Bailey KR, Cobelli C, Man CD, Vella A. Differential contribution of alpha and beta cell dysfunction to impaired fasting glucose and impaired glucose tolerance. Diabetologia 2023; 66:201-212. [PMID: 36112169 PMCID: PMC9742343 DOI: 10.1007/s00125-022-05794-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/02/2022] [Indexed: 12/14/2022]
Abstract
AIMS/HYPOTHESIS People with isolated impaired fasting glucose (IFG) have normal beta cell function. We hypothesised that an increased glucose threshold for beta cell secretion explains IFG. METHODS We used graded glucose infusion to examine the relationship of insulin secretion rate (ISR) and glucagon secretion rate (GSR) with rising glucose. We studied 39 non-diabetic individuals (53 ± 2 years, BMI 30 ± 1 kg/m2), categorised by fasting glucose and glucose tolerance status. After an overnight fast, a variable insulin infusion was used to maintain glucose at ~4.44 mmol/l (07:00 to 08:30 hours). At 09:00 hours, graded glucose infusion commenced at 1 mg kg-1 min-1 and doubled every 60 min until 13:00 hours. GSR and ISR were calculated by nonparametric deconvolution from concentrations of glucagon and C-peptide, respectively. RESULTS The relationship of ISR with glucose was linear and the threshold for insulin secretion in isolated IFG did not differ from that in people with normal fasting glucose and normal glucose tolerance. GSR exhibited a single-exponential relationship with glucose that could be characterised by G50, the change in glucose necessary to suppress GSR by 50%. G50 was increased in IFG compared with normal fasting glucose regardless of the presence of impaired or normal glucose tolerance. CONCLUSIONS/INTERPRETATION These data show that, in non-diabetic humans, alpha cell dysfunction contributes to the pathogenesis of IFG independently of defects in insulin secretion. We also describe a new index that quantifies the suppression of glucagon secretion by glucose.
Collapse
Affiliation(s)
- Jacob D Kohlenberg
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Marcello C Laurenti
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Daniel Schembri Wismayer
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Claudio Cobelli
- Department of Women's and Children's Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA.
| |
Collapse
|
16
|
Cobelli C, Dalla Man C. Response to Comment on "Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical Trials". J Diabetes Sci Technol 2022; 16:1346-1347. [PMID: 34839748 PMCID: PMC9445347 DOI: 10.1177/19322968211060069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Claudio Cobelli
- Department of Woman’s and Child’s Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
17
|
Abstract
Several models have been proposed to describe the glucose system at whole-body, organ/tissue and cellular level, designed to measure non-accessible parameters (minimal models), to simulate system behavior and run in silico clinical trials (maximal models). Here, we will review the authors' work, by putting it into a concise historical background. We will discuss first the parametric portrait provided by the oral minimal models-building on the classical intravenous glucose tolerance test minimal models-to measure otherwise non-accessible key parameters like insulin sensitivity and beta-cell responsivity from a physiological oral test, the mixed meal or the oral glucose tolerance tests, and what can be gained by adding a tracer to the oral glucose dose. These models were used in various pathophysiological studies, which we will briefly review. A deeper understanding of insulin sensitivity can be gained by measuring insulin action in the skeletal muscle. This requires the use of isotopic tracers: both the classical multiple-tracer dilution and the positron emission tomography techniques are discussed, which quantitate the effect of insulin on the individual steps of glucose metabolism, that is, bidirectional transport plasma-interstitium, and phosphorylation. Finally, we will present a cellular model of insulin secretion that, using a multiscale modeling approach, highlights the relations between minimal model indices and subcellular secretory events. In terms of maximal models, we will move from a parametric to a flux portrait of the system by discussing the triple tracer meal protocol implemented with the tracer-to-tracee clamp technique. This allows to arrive at quasi-model independent measurement of glucose rate of appearance (Ra), endogenous glucose production (EGP), and glucose rate of disappearance (Rd). Both the fast absorbing simple carbs and the slow absorbing complex carbs are discussed. This rich data base has allowed us to build the UVA/Padova Type 1 diabetes and the Padova Type 2 diabetes large scale simulators. In particular, the UVA/Padova Type 1 simulator proved to be a very useful tool to safely and effectively test in silico closed-loop control algorithms for an artificial pancreas (AP). This was the first and unique simulator of the glucose system accepted by the U.S. Food and Drug Administration as a substitute to animal trials for in silico testing AP algorithms. Recent uses of the simulator have looked at glucose sensors for non-adjunctive use and new insulin molecules.
Collapse
Affiliation(s)
- Claudio Cobelli
- Department of Woman and Child’s Health University of Padova, Padova, Italy
- Claudio Cobelli, PhD, Department of Woman and Child’s Health, University of Padova, Via N. Giustiniani, 3, Padova 35128, Italy.
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
18
|
Visentin R, Cobelli C, Dalla Man C. A software interface for in silico testing of type 2 diabetes treatments. Comput Methods Programs Biomed 2022; 223:106973. [PMID: 35792365 DOI: 10.1016/j.cmpb.2022.106973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 06/09/2022] [Accepted: 06/21/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE The increasing incidence of diabetes continuously stimulates the research on new antidiabetic drugs. Computer simulation can save time and costs, alleviating the need of animal trials and providing useful information for optimal experiment design and drug dosing. We recently presented a type 2 diabetes (T2D) simulator as tool for in silico testing of new molecules and guiding treatment optimization. Here we present a user-friendly interface aimed to increase the usability of the simulator. METHOD The simulator, based on a large-scale glucose, insulin, and C-peptide model and equipped with 100 virtual subjects well describing system dynamics in a real T2D population, is extended to incorporate pharmacokinetics/pharmacodynamics (PK/PD) of a drug of interest. A graphical interface is developed on top of the simulator, allowing an easy design of in silico experiments: specifically, it is possible to select the population size to test, design the experiment (crossover or parallel), its duration and the sampling grid, choose glucose and insulin doses, and define treatment PK/PD and dose administered. The simulator also provides the outcome metrics requested by the user, and performs statistical comparisons among treatments and/or placebo. RESULTS To illustrate the potential of the simulator, we provided a case study using metformin and liraglutide. Literature-based PK/PD models of metformin and liraglutide have been incorporated in the simulator, by modulating key drug-sensitive model parameters. An in silico placebo-controlled trial has been done by simulating a three-arm meal tolerance test with subjects receiving placebo, metformin 850 mg, liraglutide 1.80 mg, respectively. The obtained results are in agreement with the clinical evidences, in terms of main glucose, insulin, and C-peptide outcome metrics. CONCLUSIONS We developed a user-friendly software interface for the T2D simulator to support the design and test of new antidiabetic drugs and treatments. This increases the simulator usability, making it suitable also for users who have low experience with computer programming.
Collapse
Affiliation(s)
- Roberto Visentin
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy.
| |
Collapse
|
19
|
Xu NY, Nguyen KT, DuBord AY, Pickup J, Sherr JL, Teymourian H, Cengiz E, Ginsberg BH, Cobelli C, Ahn D, Bellazzi R, Bequette BW, Gandrud Pickett L, Parks L, Spanakis EK, Masharani U, Akturk HK, Melish JS, Kim S, Kang GE, Klonoff DC. Diabetes Technology Meeting 2021. J Diabetes Sci Technol 2022; 16:1016-1056. [PMID: 35499170 PMCID: PMC9264449 DOI: 10.1177/19322968221090279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 4 to November 6, 2021. This meeting brought together speakers to discuss various developments within the field of diabetes technology. Meeting topics included blood glucose monitoring, continuous glucose monitoring, novel sensors, direct-to-consumer telehealth, metrics for glycemia, software for diabetes, regulation of diabetes technology, diabetes data science, artificial pancreas, novel insulins, insulin delivery, skin trauma, metabesity, precision diabetes, diversity in diabetes technology, use of diabetes technology in pregnancy, and green diabetes. A live demonstration on a mobile app to monitor diabetic foot wounds was presented.
Collapse
Affiliation(s)
- Nicole Y. Xu
- Diabetes Technology Society,
Burlingame, CA, USA
| | | | | | | | | | | | - Eda Cengiz
- University of California, San
Francisco, San Francisco, CA, USA
| | | | | | - David Ahn
- Mary & Dick Allen Diabetes Center
at Hoag, Newport Beach, CA, USA
| | | | | | | | - Linda Parks
- University of California, San
Francisco, San Francisco, CA, USA
| | - Elias K. Spanakis
- Baltimore VA Medical Center,
Baltimore, MD, USA
- University of Maryland, Baltimore,
MD, USA
| | - Umesh Masharani
- University of California, San
Francisco, San Francisco, CA, USA
| | - Halis K. Akturk
- Barbara Davis Center for Diabetes,
University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Sarah Kim
- University of California, San
Francisco, San Francisco, CA, USA
| | - Gu Eon Kang
- The University of Texas at Dallas,
Richardson, TX, USA
| | - David C. Klonoff
- Diabetes Research Institute,
Mills-Peninsula Medical Center, San Mateo, CA, USA
| |
Collapse
|
20
|
Laurenti MC, Arora P, Dalla Man C, Andrews JC, Rizza RA, Matveyenko A, Bailey KR, Cobelli C, Vella A. The relationship between insulin and glucagon concentrations in non-diabetic humans. Physiol Rep 2022; 10:e15380. [PMID: 35822422 PMCID: PMC9277417 DOI: 10.14814/phy2.15380] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/13/2022] [Accepted: 06/17/2022] [Indexed: 06/02/2023] Open
Abstract
Abnormal postprandial suppression of glucagon in Type 2 diabetes (T2DM) has been attributed to impaired insulin secretion. Prior work suggests that insulin and glucagon show an inverse coordinated relationship. However, dysregulation of α-cell function in prediabetes occurs early and independently of changes in β-cells, which suggests insulin having a less significant role on glucagon control. We therefore, sought to examine whether hepatic vein hormone concentrations provide evidence to further support the modulation of glucagon secretion by insulin. As part of a series of experiments to measure the effect of diabetes-associated genetic variation in TCF7L2 on islet cell function, hepatic vein insulin and glucagon concentrations were measured at 2-minute intervals during fasting and a hyperglycemic clamp. The experiment was performed on 29 nondiabetic subjects (age = 46 ± 2 years, BMI 28 ± 1 Kg/m2 ) and enabled post-hoc analysis, using Cross-Correlation and Cross-Approximate Entropy (Cross-ApEn) to evaluate the interaction of insulin and glucose. Mean insulin concentrations rose from fasting (33 ± 4 vs. 146 ± 12 pmol/L, p < 0.01) while glucagon was suppressed (96 ± 8 vs. 62 ± 5 ng/L, p < 0.01) during the clamp. Cross-ApEn was used to measure pattern reproducibility in the two hormones using glucagon as control mechanism (0.78 ± 0.03 vs. 0.76 ± 0.03, fasting vs. hyperglycemia) and using insulin as a control mechanism (0.78 ± 0.02 vs. 0.76 ± 0.03, fasting vs. hyperglycemia). Values did not differ between the two scenarios. Cross-correlation analysis demonstrated a small in-phase coordination between insulin and glucagon concentrations during fasting, which inverted during hyperglycemia. This data suggests that the interaction between the two hormones is not driven by either. On a minute-to-minute basis, direct control and secretion of glucagon is not mediated (or restrained) by insulin.
Collapse
Affiliation(s)
- Marcello C. Laurenti
- Division of Endocrinology, Diabetes & MetabolismEndocrine Research Unit, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical SciencesRochesterMinnesotaUSA
| | - Praveer Arora
- Division of Endocrinology, Diabetes & MetabolismEndocrine Research Unit, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| | - Chiara Dalla Man
- Department of Information EngineeringUniversity of PadovaPadovaItaly
| | - James C. Andrews
- Vascular and Interventional Radiology, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| | - Robert A. Rizza
- Division of Endocrinology, Diabetes & MetabolismEndocrine Research Unit, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| | - Aleksey Matveyenko
- Division of Endocrinology, Diabetes & MetabolismEndocrine Research Unit, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| | - Kent R. Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| | - Claudio Cobelli
- Department of Woman and Child's HealthUniversity of PadovaPadovaItaly
| | - Adrian Vella
- Division of Endocrinology, Diabetes & MetabolismEndocrine Research Unit, Mayo Clinic, College of Medicine and ScienceRochesterMinnesotaUSA
| |
Collapse
|
21
|
Bisiacco M, Pillonetto G, Cobelli C. Closed-form expressions and nonparametric estimation of COVID-19 infection rate. Automatica (Oxf) 2022; 140:110265. [PMID: 35400084 PMCID: PMC8976198 DOI: 10.1016/j.automatica.2022.110265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/05/2021] [Accepted: 01/13/2022] [Indexed: 06/14/2023]
Abstract
Quantitative assessment of the infection rate of a virus is key to monitor the evolution of an epidemic. However, such variable is not accessible to direct measurement and its estimation requires the solution of a difficult inverse problem. In particular, being the result not only of biological but also of social factors, the transmission dynamics can vary significantly in time. This makes questionable the use of parametric models which could be unable to capture their full complexity. In this paper we exploit compartmental models which include important COVID-19 peculiarities (like the presence of asymptomatic individuals) and allow the infection rate to assume any continuous-time profile. We show that these models are universal, i.e. capable to reproduce exactly any epidemic evolution, and extract from them closed-form expressions of the infection rate time-course. Building upon such expressions, we then design a regularized estimator able to reconstruct COVID-19 transmission dynamics in continuous-time. Using real data collected in Italy, our technique proves to be an useful tool to monitor COVID-19 transmission dynamics and to predict and assess the effect of lockdown restrictions.
Collapse
Affiliation(s)
- Mauro Bisiacco
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
- Consiglio Superiore di Sanità, Italian Ministry of Health, Italy
| |
Collapse
|
22
|
Yadav Y, Dunagan K, Khot R, Venkatesh SK, Port J, Galderisi A, Cobelli C, Wegner C, Basu A, Carter R, Basu R. Inhibition of 11β-Hydroxysteroid dehydrogenase-1 with AZD4017 in patients with nonalcoholic steatohepatitis or nonalcoholic fatty liver disease: A randomized, double-blind, placebo-controlled, phase II study. Diabetes Obes Metab 2022; 24:881-890. [PMID: 35014156 PMCID: PMC9135169 DOI: 10.1111/dom.14646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 11/29/2022]
Abstract
AIM To evaluate whether short-term treatment with a selective 11β-Hydroxysteroid dehydrogenase-1 (11β-HSD1) inhibitor, AZD4017, would block hepatic cortisol production and thereby decrease hepatic fat in patients with nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH), with or without type 2 diabetes (T2D). MATERIALS AND METHODS This was a randomized, double-blind, placebo-controlled, phase 2 study conducted at two sites. Key inclusion criteria were the presence of NAFLD or NASH on magnetic resonance imaging (MRI) or recent biopsy positive for NASH. Enrolled patients were randomly assigned (1:1) to AZD4017 or placebo for 12 weeks. Primary outcomes were between-group differences in mean change from baseline to week 12 in liver fat fraction (LFF) and conversion of 13 C cortisone to 13 C cortisol in the liver. RESULTS A total of 93 patients were randomized; 85 patients completed treatment. The mean (standard deviation [SD]) change in LFF was -0.667 (5.246) and 0.139 (4.323) in the AZD4017 and placebo groups (P = 0.441). For patients with NASH and T2D, the mean (SD) change in LFF was significantly improved in the AZD4017 versus the placebo group (-1.087 [5.374] vs. 1.675 [3.318]; P = 0.033). Conversion of 13 C cortisone to 13 C cortisol was blocked in all patients in the AZD4017 group. There were no significant between-group differences (AZD4017 vs. placebo) in changes in fibrosis, weight, levels of liver enzymes or lipids, or insulin sensitivity. CONCLUSION Although the study did not meet one of the primary outcomes, AZD4017 blocked the conversion of 13 C cortisone to 13 C cortisol in the liver in all patients who received the drug. In patients with NASH and T2D, AZD4017 improved liver steatosis versus placebo.
Collapse
Affiliation(s)
- Yogesh Yadav
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Kelly Dunagan
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Rachita Khot
- Division of Body Imaging, Department of Radiology and Medical ImagingUniversity of VirginiaCharlottesvilleVirginiaUSA
| | | | - John Port
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Alfonso Galderisi
- Department of Woman and Child's healthUniversity of PadovaPadovaVenetoItaly
| | - Claudio Cobelli
- Department of Woman and Child's healthUniversity of PadovaPadovaVenetoItaly
| | - Craig Wegner
- Retired from Emerging & Open Innovations Unit, IMED Biotech UnitAstraZenecaUSA
| | - Ananda Basu
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Rickey Carter
- Department of Quantitative Health SciencesMayo ClinicJacksonvilleFloridaUSA
| | - Rita Basu
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| |
Collapse
|
23
|
Adams JD, Egan AM, Laurenti MC, Schembri Wismayer D, Bailey KR, Cobelli C, Dalla Man C, Vella A. The Effect of Diabetes-Associated Variation in TCF7L2 on Postprandial Glucose Metabolism When Glucagon and Insulin Concentrations Are Matched. Metab Syndr Relat Disord 2022; 20:329-335. [PMID: 35442800 PMCID: PMC9419949 DOI: 10.1089/met.2021.0136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Background: The rs7903146 variant in the TCF7L2 gene is associated with defects in postprandial insulin and glucagon secretion and increased risk of type 2 diabetes. However, it is unclear if this variant has effects on glucose metabolism that are independent of islet function. Methods: We studied 54 nondiabetic subjects on two occasions where endogenous hormone secretion was inhibited by somatostatin. Twenty-nine subjects were homozygous for the diabetes-associated allele (TT) and 25 for the diabetes-protective allele (CC) at rs7903146, but otherwise matched for anthropometric characteristics. On 1 day, glucagon infused at a rate of 0.65 ng/kg/min, and at 0 min prevented a fall in glucagon (nonsuppressed day). On the contrary, infusion commenced at 120 min to create a transient fall in glucagon (suppressed day). Subjects received glucose (labeled with [3-3H]-glucose) infused to mimic the systemic appearance of oral glucose. Insulin was infused to mimic a prandial insulin response. Endogenous glucose production (EGP) was measured using the tracer dilution technique. Results: Lack of glucagon suppression increased postchallenge glucose concentrations and impaired EGP suppression. However, in the presence of matched insulin and glucagon concentrations, genetic variation in TCF7L2 did not alter glucose metabolism. Conclusion: These data suggest that genetic variation in TCF7L2 alters glucose metabolism through changes in islet hormone secretion.
Collapse
Affiliation(s)
- Jon D Adams
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Marcello C Laurenti
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Daniel Schembri Wismayer
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Claudio Cobelli
- Department of Woman and Child's Health and University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| |
Collapse
|
24
|
Lo Presti J, Galderisi A, Doyle FJ, Zisser HC, Dassau E, Renard E, Toffanin C, Cobelli C. Intraperitoneal Insulin Delivery: Evidence of a Physiological Route for Artificial Pancreas From Compartmental Modeling. J Diabetes Sci Technol 2022; 17:751-756. [PMID: 35144503 DOI: 10.1177/19322968221076559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Intraperitoneal insulin delivery has proven to safely overcome a major limit of subcutaneous delivery-meal announcement-and has been able to optimize glycemic control in adults under controlled experimental conditions. In addition, intraperitoneal delivery avoids peripheral hyperinsulinemia resulting from the subcutaneous route and restores a physiological liver gradient. METHODS Relying on a unique data set of intraperitoneal closed-loop insulin delivery obtained with a Model Predictive Controller (MPC), we develop a compartmental model of intraperitoneal insulin kinetics, which, once included in the UVa/Padova T1D simulator, will facilitate the investigation of various control strategies, for example, the simpler Proportional Integral Derivative controller versus MPC. RESULTS Intraperitoneal insulin kinetics can be described with a 2-compartment model including liver and plasma. CONCLUSION Intraperitoneal insulin transit is fast enough to render irrelevant the addition of a peritoneal compartment, proving the peritoneum being a virtual-not actual-transit space for insulin delivery.
Collapse
Affiliation(s)
- Jorge Lo Presti
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
| | - Alfonso Galderisi
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
- Hôpital Necker-Enfants Malades, Paris, France
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Howard C Zisser
- Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, Montpellier, France
| | - Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Claudio Cobelli
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
| |
Collapse
|
25
|
Simha V, Lanza IR, Dasari S, Klaus KA, Le Brasseur N, Vuckovic I, Laurenti MC, Cobelli C, Port JD, Nair KS. Impaired Muscle Mitochondrial Function in Familial Partial Lipodystrophy. J Clin Endocrinol Metab 2022; 107:346-362. [PMID: 34614176 PMCID: PMC8764358 DOI: 10.1210/clinem/dgab725] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Indexed: 01/04/2023]
Abstract
CONTEXT Familial partial lipodystrophy (FPL), Dunnigan variety is characterized by skeletal muscle hypertrophy and insulin resistance besides fat loss from the extremities. The cause for the muscle hypertrophy and its functional consequences is not known. OBJECTIVE To compare muscle strength and endurance, besides muscle protein synthesis rate between subjects with FPL and matched controls (n = 6 in each group). In addition, we studied skeletal muscle mitochondrial function and gene expression pattern to help understand the mechanisms for the observed differences. METHODS Body composition by dual-energy X-ray absorptiometry, insulin sensitivity by minimal modelling, assessment of peak muscle strength and fatigue, skeletal muscle biopsy and calculation of muscle protein synthesis rate, mitochondrial respirometry, skeletal muscle transcriptome, proteome, and gene set enrichment analysis. RESULTS Despite increased muscularity, FPL subjects did not demonstrate increased muscle strength but had earlier fatigue on chest press exercise. Decreased mitochondrial state 3 respiration in the presence of fatty acid substrate was noted, concurrent to elevated muscle lactate and decreased long-chain acylcarnitine. Based on gene transcriptome, there was significant downregulation of many critical metabolic pathways involved in mitochondrial biogenesis and function. Moreover, the overall pattern of gene expression was indicative of accelerated aging in FPL subjects. A lower muscle protein synthesis and downregulation of gene transcripts involved in muscle protein catabolism was observed. CONCLUSION Increased muscularity in FPL is not due to increased muscle protein synthesis and is likely due to reduced muscle protein degradation. Impaired mitochondrial function and altered gene expression likely explain the metabolic abnormalities and skeletal muscle dysfunction in FPL subjects.
Collapse
MESH Headings
- Absorptiometry, Photon
- Adult
- Aged
- Female
- Gene Expression Profiling
- Humans
- Lipodystrophy, Familial Partial/genetics
- Lipodystrophy, Familial Partial/metabolism
- Lipodystrophy, Familial Partial/pathology
- Lipodystrophy, Familial Partial/physiopathology
- Male
- Middle Aged
- Mitochondria, Muscle/metabolism
- Mitochondria, Muscle/pathology
- Muscle Strength/physiology
- Muscle, Skeletal/cytology
- Muscle, Skeletal/pathology
- Muscle, Skeletal/physiopathology
- Physical Endurance/physiology
- Proteolysis
- Young Adult
Collapse
Affiliation(s)
- Vinaya Simha
- Divisions of Endocrinology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ian R Lanza
- Divisions of Endocrinology, Mayo Clinic, Rochester, MN 55905, USA
| | - Surendra Dasari
- Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Nathan Le Brasseur
- Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN 55905, USA
| | - Ivan Vuckovic
- Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - John D Port
- Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | |
Collapse
|
26
|
Adams JD, Egan AM, Laurenti MC, Schembri Wismayer D, Bailey KR, Cobelli C, Dalla Man C, Vella A. Insulin secretion and action and the response of endogenous glucose production to a lack of glucagon suppression in nondiabetic subjects. Am J Physiol Endocrinol Metab 2021; 321:E728-E736. [PMID: 34658253 PMCID: PMC8782666 DOI: 10.1152/ajpendo.00284.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Type 2 diabetes is a disease characterized by impaired insulin secretion and defective glucagon suppression in the postprandial period. We examined the effect of impaired glucagon suppression on glucose concentrations and endogenous glucose production (EGP) at different degrees of insulin secretory impairment. The contribution of anthropometric characteristics, peripheral, and hepatic insulin action to this variability was also examined. To do so, we studied 54 nondiabetic subjects on two occasions in which endogenous hormone secretion was inhibited by somatostatin, with glucagon infused at a rate of 0.65 ng/kg/min, at 0 min to prevent a fall in glucagon (nonsuppressed day) or at 120 min to create a transient fall in glucagon (suppressed day). Subjects received glucose (labeled with [3-3H]-glucose) infused to mimic the systemic appearance of 50-g oral glucose. Insulin was infused to mimic a prandial insulin response in 18 subjects, another 18 received 80% of the dose, and the remaining 18 received 60%. EGP was measured using the tracer-dilution technique. Decreased prandial insulin resulted in greater % increase in peak glucose but not in integrated glucose concentrations attributable to nonsuppressed glucagon. The % change in integrated EGP was unaffected by insulin dose. Multivariate regression analysis, adjusted for age, sex, weight, and insulin dose, did not show a relationship between the EGP response to impaired suppression of glucagon and insulin action as measured at the time of screening by oral glucose tolerance. A similar analysis for hepatic insulin action also did not show a relationship with the EGP response. These data indicate that the effect of impaired glucagon suppression on EGP is independent of anthropometric characteristics and insulin action.NEW & NOTEWORTHY In prediabetes, anthropometric characteristics as well as insulin action do not alter the hepatic response to glucagon. The postprandial suppression or lack of suppression of glucagon secretion is an important factor governing postprandial glucose tolerance independent of insulin secretion.
Collapse
Affiliation(s)
- Jon D Adams
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota
- Department of Health and Human Performance, College of Charleston, Charleston, South Carolina
| | - Aoife M Egan
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Marcello C Laurenti
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Daniel Schembri Wismayer
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota
| |
Collapse
|
27
|
Schiavon M, Cobelli C, Dalla Man C. Modeling Intraperitoneal Insulin Absorption in Patients with Type 1 Diabetes. Metabolites 2021; 11:metabo11090600. [PMID: 34564415 PMCID: PMC8465342 DOI: 10.3390/metabo11090600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/27/2021] [Accepted: 09/01/2021] [Indexed: 11/16/2022] Open
Abstract
Standard insulin therapy to treat type 1 diabetes (T1D) consists of exogenous insulin administration through the subcutaneous (SC) tissue. Despite recent advances in insulin formulations, the SC route still suffers from delays and large inter/intra-subject variability that limiting optimal glucose control. Intraperitoneal (IP) insulin administration, despite its higher invasiveness, was shown to represent a valid alternative to the SC one. To date, no mathematical model describing the absorption and distribution of insulin after IP administration is available. Here, we aim to fill this gap by using data from eight patients with T1D, treated by implanted IP pump, studied in a hospitalized setting, with frequent measurements of plasma insulin and glucose concentration. A battery of models describing insulin kinetics after IP administration were tested. Model comparison and selection were performed based on model ability to predict the data, precision of parameters and parsimony criteria. The selected model assumed that the insulin absorption from the IP space was described by a linear, two-compartment model, coupled with a two-compartment model of whole-body insulin kinetics with hepatic insulin extraction controlled by hepatic insulin. Future developments include model incorporation into the UVa/Padova T1D Simulator for testing open- and closed-loop therapies with IP insulin administration.
Collapse
Affiliation(s)
- Michele Schiavon
- Department of Information Engineering, University of Padova, 35131 Padova, Italy;
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, 35128 Padova, Italy;
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, 35131 Padova, Italy;
- Correspondence:
| |
Collapse
|
28
|
Galderisi A, Moran A, Evans-Molina C, Martino M, Santoro N, Caprio S, Cobelli C. Early Impairment of Insulin Sensitivity, β-Cell Responsiveness, and Insulin Clearance in Youth with Stage 1 Type 1 Diabetes. J Clin Endocrinol Metab 2021; 106:2660-2669. [PMID: 34000022 PMCID: PMC8372628 DOI: 10.1210/clinem/dgab344] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Indexed: 01/10/2023]
Abstract
CONTEXT Clinical onset of type 1 diabetes (Stage 3 T1D) is preceded by a presymptomatic phase characterized by multiple islet autoantibodies with normal glucose tolerance (Stage 1 T1D). OBJECTIVE The aim was to explore the metabolic phenotypes of β-cell function and insulin sensitivity and clearance in normoglycemic youth with Stage 1 T1D and compare them with healthy nonrelated peers during a 3-hour oral glucose tolerance test (OGTT). METHODS Twenty-eight lean youth, 14 with ≥2 islet autoantibodies (cases) and 14 healthy controls underwent a 3-hour 9-point OGTT with measurement of glucose, C-peptide, and insulin. The oral minimal model was used to quantitate β-cell responsiveness (φtotal) and insulin sensitivity (SI), allowing assessment of β-cell function by the disposition index (DI=φtotal×SI). Fasting insulin clearance (CL0) was calculated as the ratio between the fasting insulin secretion rate (ISR) and plasma insulin levels (ISR0/I0), while postload clearance (CL180) was estimated by the ratio of AUC of ISR over the plasma insulin AUC for the 3-hour OGTT (ISRAUC/IAUC). Participants with impaired fasting glucose, impaired glucose tolerance, or any OGTT glucose concentration ≥200 mg/dL were excluded. RESULTS Cases (10.5 years [8, 15]) exhibited reduced DI (P < .001) due to a simultaneous reduction in both φtotal (P < 0.001) and SI (P = .008) compared with controls (11.5 years [10.4, 14.9]). CL0 and CL180 were lower in cases than in controls (P = .005 and P = .019). CONCLUSION Presymptomatic Stage 1 T1D in youth is associated with reduced insulin sensitivity and lower β-cell responsiveness, and the presence of blunted insulin clearance.
Collapse
Affiliation(s)
- Alfonso Galderisi
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
- Department of Pediatrics, Yale University, New Haven, CT, USA
- Correspondence: Alfonso Galderisi, MD, PhD, Department of Woman and Child’s Health, University of Padova, Via N. Giustiniani, 3, 35128 Padova, Italy.
| | - Antoinette Moran
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana University, Bloomington, IN, USA
| | - Mariangela Martino
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - Nicola Santoro
- Department of Pediatrics, Yale University, New Haven, CT, USA
- Department of Medicine and Health Sciences “V. Tiberio,” University of Molise, Campobasso, Italy
| | - Sonia Caprio
- Department of Pediatrics, Yale University, New Haven, CT, USA
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| |
Collapse
|
29
|
Schiavon M, Visentin R, Göbel B, Riz M, Cobelli C, Klabunde T, Dalla Man C. Improved postprandial glucose metabolism in type 2 diabetes by the dual glucagon-like peptide-1/glucagon receptor agonist SAR425899 in comparison with liraglutide. Diabetes Obes Metab 2021; 23:1795-1805. [PMID: 33822469 PMCID: PMC8359969 DOI: 10.1111/dom.14394] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/16/2021] [Accepted: 03/28/2021] [Indexed: 12/15/2022]
Abstract
AIM To gain further insights into the efficacy of SAR425899, a dual glucagon-like peptide-1/glucagon receptor agonist, by providing direct comparison with the glucagon-like peptide-1 receptor agonist, liraglutide, in terms of key outcomes of glucose metabolism. RESEARCH DESIGN AND METHODS Seventy overweight to obese subjects with type 2 diabetes (T2D) were randomized to receive once-daily subcutaneous administrations of SAR425899 (0.12, 0.16 or 0.20 mg), liraglutide (1.80 mg) or placebo for 26 weeks. Mixed meal tolerance tests were conducted at baseline (BSL) and at the end of treatment (EOT). Metabolic indices of insulin action and secretion were assessed via Homeostasis Model Assessment (HOMA2) and oral minimal model (OMM) methods. RESULTS From BSL to EOT (median [25th, 75th] percentile), HOMA2 quantified a significant improvement in basal insulin action in liraglutide (35% [21%, 74%]), while secretion enhanced both in SAR425899 (125% [63%, 228%]) and liraglutide (73% [43%, 147%]). OMM quantified, both in SAR425899 and liraglutide, a significant improvement in insulin sensitivity (203% [58%, 440%] and 36% [21%, 197%]), basal beta-cell responsiveness (67% [34%, 112%] and 40% [16%, 59%]), and above-basal beta-cell responsiveness (139% [64%, 261%] and 69% [-15%, 120%]). A significant delay in glucose absorption was highlighted in SAR425899 (37% [52%,18%]). CONCLUSIONS SAR425899 and liraglutide improved postprandial glucose control in overweight to obese subjects with T2D. A significantly higher enhancement in beta-cell function was shown by SAR425899 than liraglutide.
Collapse
Affiliation(s)
- Michele Schiavon
- Department of Information EngineeringUniversity of PadovaPadovaItaly
| | - Roberto Visentin
- Department of Information EngineeringUniversity of PadovaPadovaItaly
| | - Britta Göbel
- R&D Data & Data ScienceSanofi‐Aventis Deutschland GmbHFrankfurt am MainGermany
| | - Michela Riz
- R&D Data & Data ScienceSanofi‐Aventis Deutschland GmbHFrankfurt am MainGermany
| | - Claudio Cobelli
- Department of Information EngineeringUniversity of PadovaPadovaItaly
| | - Thomas Klabunde
- R&D Data & Data ScienceSanofi‐Aventis Deutschland GmbHFrankfurt am MainGermany
| | - Chiara Dalla Man
- Department of Information EngineeringUniversity of PadovaPadovaItaly
| |
Collapse
|
30
|
Romeres D, Schiavon M, Basu A, Cobelli C, Basu R, Dalla Man C. Exercise effect on insulin-dependent and insulin-independent glucose utilization in healthy individuals and individuals with type 1 diabetes: a modeling study. Am J Physiol Endocrinol Metab 2021; 321:E122-E129. [PMID: 33998292 PMCID: PMC8321821 DOI: 10.1152/ajpendo.00084.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Exercise effects (EE) on whole body glucose rate of disappearance (Rd) occur through insulin-independent (IIRd) and insulin-dependent (IDRd) mechanisms. Quantifying these processes in vivo would allow a better understanding of the physiology of glucose regulation. This is of particular importance in individuals with type 1 diabetes (T1D) since such a knowledge may help to improve glucose management. However, such a model is still lacking. Here, we analyzed data from six T1D and six nondiabetic (ND) subjects undergoing a labeled glucose clamp study during, before, and after a 60-min exercise session at 65% V̇o2max on three randomized visits: euglycemia-low insulin, euglycemia-high insulin, and hyperglycemia-low insulin. We tested a set of models, all sharing a single-compartment description of glucose kinetics, but differing in how exercise is assumed to modulate glucose disposal. Model selection was based on parsimony criteria. The best model assumed an exercise-induced immediate effect on IIRd and a delayed effect on IDRd. It predicted that exercise increases IIRd, compared with rest, by 66%-82% and 67%-97% in T1D and ND, respectively, not significantly different between the two groups. Conversely, the exercise effect on IDRd ranged between 81% and 155% in T1D and it was significantly higher than ND, which ranged between 10% and 40%. The exaggerated effect observed in IDRd can explain the higher hypoglycemia risk related to individuals with T1D. This novel exercise model could help in informing safe and effective glucose management during and after exercise in individuals with T1D.NEW & NOTEWORTHY Here, we present a new mathematical model describing the effect of moderate physical activity on insulin-mediated and noninsulin-mediated glucose disposal in subjects with and without diabetes. We believe that this represents a step-forward in the knowledge of type 1 diabetes pathophysiology, and an useful tool to design safe and effective insulin-therapies.
Collapse
Affiliation(s)
- Davide Romeres
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Michele Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ananda Basu
- Division of Endocrinology, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, Padova, Italy
| | - Rita Basu
- Division of Endocrinology, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
31
|
Egan AM, Laurenti MC, Hurtado Andrade MD, Dalla Man C, Cobelli C, Bailey KR, Vella A. Limitations of the fasting proinsulin to insulin ratio as a measure of β-cell health in people with and without impaired glucose tolerance. Eur J Clin Invest 2021; 51:e13469. [PMID: 33289929 PMCID: PMC8169515 DOI: 10.1111/eci.13469] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/02/2020] [Accepted: 12/04/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The fasting proinsulin to insulin ratio is elevated in people with type 2 diabetes and has been suggested as a marker of β-cell health. However, its utility in discriminating between individuals with varying degrees of β-cell dysfunction is unclear. Proinsulin has a very different half-life to insulin and unlike insulin does not undergo hepatic extraction prior to reaching the systemic circulation. Given these limitations, we sought to examine the relationship between fasting and postprandial concentrations of β-cell polypeptides (proinsulin, insulin and C-peptide) in people with normal and impaired glucose tolerance in differing metabolic environments. DESIGN Subjects were studied on two occasions in random order while undergoing an oral challenge. During one study day, free fatty acids were elevated (to induce insulin resistance) by infusion of Intralipid with heparin. Proinsulin to insulin and proinsulin to C-peptide ratios were calculated for the 0-, 30-, 60- and 240-minute time points. Insulin action (Si) and β-cell responsivity (Φ) indices were calculated using the oral minimal model. RESULTS The fasting proinsulin to c-peptide or fasting proinsulin to insulin ratios did not differ between groups and did not predict subsequent β-cell responsivity to glucose during the glycerol or Intralipid study days in either group. CONCLUSIONS Among nondiabetic individuals, the fasting proinsulin to insulin ratio is not a useful marker of β-cell function.
Collapse
Affiliation(s)
- Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic, Rochester, MN, USA
| | - Marcello C Laurenti
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic, Rochester, MN, USA
| | | | - Chiara Dalla Man
- Department of Information Engineering, Università degli Studi di Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Information Engineering, Università degli Studi di Padova, Padova, Italy
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Adrian Vella
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
32
|
Laurenti MC, Dalla Man C, Varghese RT, Andrews JC, Jones JG, Barosa C, Rizza RA, Matveyenko A, De Nicolao G, Bailey KR, Cobelli C, Vella A. Insulin Pulse Characteristics and Insulin Action in Non-diabetic Humans. J Clin Endocrinol Metab 2021; 106:1702-1709. [PMID: 33606017 PMCID: PMC8344841 DOI: 10.1210/clinem/dgab100] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Indexed: 01/05/2023]
Abstract
OBJECTIVE Pulsatile insulin secretion is impaired in diseases such as type 2 diabetes that are characterized by insulin resistance. This has led to the suggestion that changes in insulin pulsatility directly impair insulin signaling. We sought to examine the effects of pulse characteristics on insulin action in humans, hypothesizing that a decrease in pulse amplitude or frequency is associated with impaired hepatic insulin action. METHODS We studied 29 nondiabetic subjects on two occasions. On 1 occasion, hepatic and peripheral insulin action was measured using a euglycemic clamp. The deuterated water method was used to estimate the contribution of gluconeogenesis to endogenous glucose production. On a separate study day, we utilized nonparametric stochastic deconvolution of frequently sampled peripheral C-peptide concentrations during fasting to reconstruct portal insulin secretion. In addition to measuring basal and pulsatile insulin secretion, we used approximate entropy to measure orderliness and Fourier transform to measure the average, and the dispersion of, insulin pulse frequencies. RESULTS In univariate analysis, basal insulin secretion (R2 = 0.16) and insulin pulse amplitude (R2 = 0.09) correlated weakly with insulin-induced suppression of gluconeogenesis. However, after adjustment for age, sex, and weight, these associations were no longer significant. The other pulse characteristics also did not correlate with the ability of insulin to suppress endogenous glucose production (and gluconeogenesis) or to stimulate glucose disappearance. CONCLUSIONS Overall, our data demonstrate that insulin pulse characteristics, considered independently of other factors, do not correlate with measures of hepatic and peripheral insulin sensitivity in nondiabetic humans.
Collapse
Affiliation(s)
- Marcello C Laurenti
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, MN, USA
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ron T Varghese
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, MN, USA
| | - James C Andrews
- Vascular and Interventional Radiology, Mayo Clinic, Rochester, MN, USA
| | - John G Jones
- Center for Neurosciences, University of Coimbra, Coimbra, Portugal
| | - Cristina Barosa
- Center for Neurosciences, University of Coimbra, Coimbra, Portugal
| | - Robert A Rizza
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, MN, USA
| | - Aleksey Matveyenko
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, MN, USA
- Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Giuseppe De Nicolao
- Department of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, MN, USA
- Correspondence: Adrian Vella MD, Endocrine Research Unit, Mayo Clinic College of Medicine, 200 First ST SW, 5–194 Joseph, Rochester, MN 55905, USA.
| |
Collapse
|
33
|
Pillonetto G, Bisiacco M, Palù G, Cobelli C. Tracking the time course of reproduction number and lockdown's effect on human behaviour during SARS-CoV-2 epidemic: nonparametric estimation. Sci Rep 2021; 11:9772. [PMID: 33963235 PMCID: PMC8105401 DOI: 10.1038/s41598-021-89014-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 04/14/2021] [Indexed: 01/10/2023] Open
Abstract
Understanding the SARS-CoV-2 dynamics has been subject of intense research in the last months. In particular, accurate modeling of lockdown effects on human behaviour and epidemic evolution is a key issue in order e.g. to inform health-care decisions on emergency management. In this regard, the compartmental and spatial models so far proposed use parametric descriptions of the contact rate, often assuming a time-invariant effect of the lockdown. In this paper we show that these assumptions may lead to erroneous evaluations on the ongoing pandemic. Thus, we develop a new class of nonparametric compartmental models able to describe how the impact of the lockdown varies in time. Our estimation strategy does not require significant Bayes prior information and exploits regularization theory. Hospitalized data are mapped into an infinite-dimensional space, hence obtaining a function which takes into account also how social distancing measures and people's growing awareness of infection's risk evolves as time progresses. This also permits to reconstruct a continuous-time profile of SARS-CoV-2 reproduction number with a resolution never reached before in the literature. When applied to data collected in Lombardy, the most affected Italian region, our model illustrates how people behaviour changed during the restrictions and its importance to contain the epidemic. Results also indicate that, at the end of the lockdown, around [Formula: see text] of people in Lombardy and [Formula: see text] in Italy was affected by SARS-CoV-2, with the fatality rate being 1.14%. Then, we discuss how the situation evolved after the end of the lockdown showing that the reproduction number dangerously increased in the summer, due to holiday relax, reaching values larger than one on August 1, 2020. Finally, we also document how Italy faced the second wave of infection in the last part of 2020. Since several countries still observe a growing epidemic and others could be subject to other waves, the proposed reproduction number tracking methodology can be of great help to health care authorities to prevent SARS-CoV-2 diffusion or to assess the impact of lockdown restrictions on human behaviour to contain the spread.
Collapse
Affiliation(s)
- G Pillonetto
- Department of Information Engineering, University of Padova, Padova, Italy.
| | - M Bisiacco
- Department of Information Engineering, University of Padova, Padova, Italy
| | - G Palù
- Department of Molecular Medicine, Professor Emeritus, University of Padova, Padova, Italy
- Member of the Scientific Technical Committee, Italian Ministry of Health, Rome, Italy
| | - C Cobelli
- Member of Consiglio Superiore di Sanità, Italian Ministry of Health, Rome, Italy
- Dipartimento di Salute della Donna e del Bambino, Professor Emeritus, University of Padova, Padova, Italy
| |
Collapse
|
34
|
Visentin R, Cobelli C, Dalla Man C. The Padova Type 2 Diabetes Simulator from Triple-Tracer Single-Meal Studies: In Silico Trials Also Possible in Rare but Not-So-Rare Individuals. Diabetes Technol Ther 2020; 22:892-903. [PMID: 32324063 DOI: 10.1089/dia.2020.0110] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background:In silico trials in type 2 diabetes (T2D) would be useful for testing diabetes treatments and accelerating the development of new antidiabetic drugs. In this study, we present a T2D simulator able to reproduce the variability observed in a T2D population. The simulator also allows to safely experiment on virtual subjects with severe (and possibly rare) pathological conditions. Methods: A meal simulation model of glucose, insulin, and C-peptide systems, made of 15 differential equations and 39 parameters, has been identified using a system decomposition and forcing function Bayesian strategy on data of 51 T2D subjects undergoing a single triple-tracer mixed meal. One hundred T2D in silico subjects have been generated from the joint distribution of estimated model parameters. A case study is presented to illustrate the simulator use for testing a virtual drug (improving insulin action and secretion) in a subpopulation of rare, extremely impaired, T2D subjects. Results: The model well fitted T2D data and parameters were estimated with precision. Simulated plasma glucose, insulin, and C-peptide well matched the data (e.g., median [25th-75th percentile] glucose area under the curves of 6.9 [6.1-8.5] 104 mg/dL·min in silico vs. 7.0 [5.6-8.2] 104 mg/dL·min in vivo). The potential use of the simulator was shown in a case study, in which the (virtual) antidiabetic drug dose was optimized for very insulin-resistant T2D subjects. Conclusions: We have developed a T2D simulator that captures the behavior of T2D population during a meal, both in terms of average and intersubject variability. The simulator represents a cost-effective way to test new antidiabetic drugs, before moving to human trials.
Collapse
Affiliation(s)
- Roberto Visentin
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
35
|
Bynoe K, Unwin N, Taylor C, Murphy MM, Bartholomew L, Greenidge A, Abed M, Jeyaseelan S, Cobelli C, Dalla Man C, Taylor R. Inducing remission of Type 2 diabetes in the Caribbean: findings from a mixed methods feasibility study of a low-calorie liquid diet-based intervention in Barbados. Diabet Med 2020; 37:1816-1824. [PMID: 31365159 DOI: 10.1111/dme.14096] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/29/2019] [Indexed: 01/04/2023]
Abstract
AIM In a high proportion of people with recently diagnosed Type 2 diabetes, a short (2-3-month) low-calorie diet is able to restore normal glucose and insulin metabolism. The aim of this study was to determine the feasibility of this approach in Barbados. METHODS Twenty-five individuals with Type 2 diabetes diagnosed within past 6 years, not on insulin, BMI ≥ 27 kg/m2 were recruited. Hypoglycaemic medication was stopped on commencement of the 8-week liquid (760 calorie) diet. Insulin response was assessed in meal tests at baseline, 8 weeks and 8 months. Semi-structured interviews, analysed thematically, explored participants' experiences. 'Responders' were those with fasting plasma glucose (FPG) < 7 mmol/l at 8 weeks. RESULTS Ten men and 15 women (mean age 48, range 26-68 years) participated. Mean (sd) BMI was 34.2 kg/m2 (6.0); FPG 9.2 mmol/l (2.2). Mean weight loss at 8 weeks and 8 months was 10.1 kg [95% confidence interval (CI) 8.1, 12.0] and 8.2 kg (95% CI 5.8, 10.6); FPG was lower by 2.2 mmol/l (95% CI 1.2, 3.2) and 1.7 mmol/l (95% CI 0.8, 2.7) respectively. Nine of 11 (82%) of those who lost ≥ 10 kg were 'responders' compared with 6 of 14 (43%) who lost < 10 kg (P = 0.048). The 30-min insulin increment was higher in responders at baseline and follow-up (P ≤ 0.01). A food culture based on starchy foods and pressures to eat large amounts at social events were among the challenges identified by participants. CONCLUSIONS The feasibility of this approach to weight loss and diabetes remission in a predominantly black population in Barbados was demonstrated.
Collapse
Affiliation(s)
- K Bynoe
- George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, University of the West Indies, Barbados
| | - N Unwin
- George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, University of the West Indies, Barbados
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - C Taylor
- Department of Medicine, University of the West Indies, Barbados
| | - M M Murphy
- Public Health Group, Faculty of Medical Sciences, University of Padova, Italy
| | - L Bartholomew
- Public Health Group, Faculty of Medical Sciences, University of Padova, Italy
| | - A Greenidge
- George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, University of the West Indies, Barbados
| | - M Abed
- George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, University of the West Indies, Barbados
| | - S Jeyaseelan
- George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, University of the West Indies, Barbados
| | - C Cobelli
- Department of Information Engineering, University of Padova, Italy
| | - C Dalla Man
- Department of Information Engineering, University of Padova, Italy
| | - R Taylor
- Newcastle Magnetic Resonance Centre, Newcastle University, Newcastle, UK
| |
Collapse
|
36
|
Romeres D, Olson K, Carter R, Cobelli C, Dalla Man C, Basu A, Basu R. Hyperglycemia But Not Hyperinsulinemia Is Favorable for Exercise in Type 1 Diabetes: A Pilot Study. Diabetes Care 2020; 43:2176-2182. [PMID: 32661106 PMCID: PMC7440891 DOI: 10.2337/dc20-0611] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 06/09/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To distinguish the effects of hyperglycemia and hyperinsulinemia on exercise-induced increases in Rd and endogenous glucose production (EGP) in type 1 diabetes. RESEARCH DESIGN AND METHODS We studied six participants without diabetes and six participants with type 1 diabetes on three visits in random order for the following: euglycemia, low insulin (EuLoI); euglycemia, high insulin (EuHiI); and hyperglycemia, low insulin (HyLoI). Glucose fluxes were measured using [6,6-2H2] glucose before, during, and after 60 min of exercise. RESULTS Rd increased (P < 0.01) with exercise within groups, while peak Rd during exercise was lower (P < 0.01) in participants with type 1 diabetes than participants without diabetes during all visits. In type 1 diabetes participants, EGP increased (P < 0.001) with exercise during EuLoI and HyLoI but not during EuHiI. This demonstrates that hyperinsulinemia, but not hyperglycemia, blunts the compensatory exercise-induced increase in EGP in type 1 diabetes. CONCLUSIONS The data from this pilot study indicate that 1) exercise-induced compensatory increase in EGP was inhibited in participants with type 1 diabetes with hyperinsulinemia but not with hyperglycemia; 2) in contrast, in participants without diabetes, exercise-induced increase in EGP was inhibited only during combined hyperinsulinemia and hyperglycemia. Taken together, these results suggest that low insulin coupled with euglycemia or modest hyperglycemia appear to be the most favorable milieu for type 1 diabetes during exercise.
Collapse
Affiliation(s)
- Davide Romeres
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Karen Olson
- Division of Endocrinology, Center of Diabetes Technology, University of Virginia School of Medicine, Charlottesville, VA
| | - Rickey Carter
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ananda Basu
- Division of Endocrinology, Center of Diabetes Technology, University of Virginia School of Medicine, Charlottesville, VA
| | - Rita Basu
- Division of Endocrinology, Center of Diabetes Technology, University of Virginia School of Medicine, Charlottesville, VA
| |
Collapse
|
37
|
Schiavon M, Visentin R, Giegerich C, Sieber J, Dalla Man C, Cobelli C, Klabunde T. In Silico Head-to-Head Comparison of Insulin Glargine 300 U/mL and Insulin Degludec 100 U/mL in Type 1 Diabetes. Diabetes Technol Ther 2020; 22:553-561. [PMID: 32125178 PMCID: PMC7407002 DOI: 10.1089/dia.2020.0027] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background: Second-generation long-acting insulin glargine 300 U/mL (Gla-300) and degludec 100 U/mL (Deg-100) provide novel basal insulin therapies for the treatment of type 1 diabetes (T1D). Both offer a flatter pharmacokinetic (PK) profile than the previous generation of long-acting insulins, thus improving glycemic control while reducing hypoglycemic events. This work describes an in silico head-to-head comparison of the two basal insulins on 24-h glucose profiles and was used to guide the design of a clinical trial. Materials and Methods: The Universities of Virginia (UVA)/Padova T1D simulator describes the intra-/interday variability of glucose-insulin dynamics and thus provides a robust bench-test for assessing glucose control for basal insulin therapies. A PK model describing subcutaneous absorption of Deg-100, in addition to the one already available for Gla-300, has been developed based on T1D clinical data and incorporated into the simulator. One hundred in silico T1D subjects received a basal insulin dose (Gla-300 or Deg-100) for 12 weeks (8 weeks uptitration, 4 weeks stable dosing) by morning or evening administration in a basal/bolus regimen. The virtual patients were uptitrated to their individual doses with two different titration rules. Results: The last 2-week simulated continuous glucose monitoring data were used to calculate various outcome metrics for both basal insulin treatments, with primary outcome being the percent time in glucose target (70-140 mg/dL). The simulations show no statistically significant difference for Gla-300 versus Deg-100 in the main endpoints. Conclusions: This work suggests comparable glucose control using either Gla-300 or Deg-100 and was used to guide the design of a clinical trial intended to compare second-generation long-acting insulin analogues.
Collapse
Affiliation(s)
- Michele Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Roberto Visentin
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Clemens Giegerich
- Translational Disease Modeling, R&D Digital and Data Sciences, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Jochen Sieber
- Medical Affairs Diabetes Care EMEA, Becton, Dickinson and Company
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Thomas Klabunde
- Translational Disease Modeling, R&D Digital and Data Sciences, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
- Address correspondence to: Thomas Klabunde, PhD, Translational Disease Modeling, R&D Digital and Data Sciences, Sanofi-Aventis Deutschland GmbH, Industriepark Hochst, Frankfurt am Main D-65926, Germany
| |
Collapse
|
38
|
Fabris C, Heinemann L, Beck R, Cobelli C, Kovatchev B. Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in Individuals with Type 1 Diabetes: Is Time In Range All We Need? Diabetes Technol Ther 2020; 22:501-508. [PMID: 32459124 PMCID: PMC7336887 DOI: 10.1089/dia.2020.0236] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Objective: To bridge the gap between laboratory-measured hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM)-derived time in target range (TIR), introducing TIR-driven estimated A1c (eA1c). Methods: Data from Protocol 1 (training data set) and Protocol 3 (testing data set) of the International Diabetes Closed-Loop Trial were used. Training data included 3 months of CGM recordings from 125 individuals with type 1 diabetes, and HbA1c at 3 months; testing data included 9 months of CGM recordings from 168 individuals, and HbA1c at 3, 6, and 9 months. Hemoglobin glycation was modeled by a first-order differential equation driven by TIR. Three model parameters were estimated in the training data set and fixed thereafter. A fourth parameter was estimated in the testing data set, to individualize the model by calibration with month 3 HbA1c. The accuracy of eA1c was assessed on months 6 and 9 HbA1c. Results: eA1c was tracked for each individual in the testing data set for 6 months after calibration. Mean absolute differences between HbA1c and eA1c 3- and 6-month postcalibration were 0.25% and 0.24%; Pearson's correlation coefficients were 0.93 and 0.93; percentages of eA1c within 10% from reference HbA1c were 97.6% and 96.3%, respectively. Conclusions: HbA1c and TIR are reflections of the same underlying process of glycemic fluctuation. Using a model individualized with one HbA1c measurement, TIR provides an accurate approximation of HbA1c for at least 6 months, reflecting blood glucose fluctuations and nonglycemic biological factors. Thus, eA1c is an intermediate metric that mathematically adjusts a CGM-based assessment of glycemic control to individual glycation rates.
Collapse
Affiliation(s)
- Chiara Fabris
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA
- Address correspondence to: Chiara Fabris, PhD, Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, 560 Ray C Hunt Drive, Charlottesville, VA 22903, USA
| | | | - Roy Beck
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Boris Kovatchev
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA
| |
Collapse
|
39
|
Laurenti MC, Dalla Man C, Varghese RT, Andrews JC, Rizza RA, Matveyenko A, De Nicolao G, Cobelli C, Vella A. Diabetes-associated genetic variation in TCF7L2 alters pulsatile insulin secretion in humans. JCI Insight 2020; 5:136136. [PMID: 32182220 DOI: 10.1172/jci.insight.136136] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 03/05/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUNDMetabolic disorders such as type 2 diabetes have been associated with a decrease in insulin pulse frequency and amplitude. We hypothesized that the T allele at rs7903146 in TCF7L2, previously associated with β cell dysfunction, would be associated with changes in these insulin pulse characteristics.METHODSTwenty-nine nondiabetic subjects (age 46 ± 2, BMI 28 ± 1 kg/m2) participated in this study. Of these, 16 were homozygous for the C allele at rs7903146 and 13 were homozygous for the T allele. Deconvolution of peripheral C-peptide concentrations allowed the reconstruction of portal insulin secretion over time. These data were used for subsequent analyses. Pulse orderliness was assessed by approximate entropy (ApEn), and the dispersion of insulin pulses was measured by a frequency dispersion index (FDI) after a Fast Fourier Transform (FFT) of individual insulin secretion rates.RESULTSDuring fasting conditions, the CC genotype group exhibited decreased pulse disorderliness compared with the TT genotype group (1.10 ± 0.03 vs. 1.19 ± 0.04, P = 0.03). FDI decreased in response to hyperglycemia in the CC genotype group, perhaps reflecting less entrainment of insulin secretion during fasting.CONCLUSIONDiabetes-associated variation in TCF7L2 is associated with decreased orderliness and pulse dispersion, unchanged by hyperglycemia. Quantification of ApEn and FDI could represent novel markers of β cell health.FUNDINGThis work was funded by US NIH (DK78646, DK116231), University of Padova research grant CPDA145405, and Mayo Clinic General Clinical Research Center (UL1 TR000135).
Collapse
Affiliation(s)
- Marcello C Laurenti
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, Minnesota, USA
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ron T Varghese
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Robert A Rizza
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, Minnesota, USA
| | - Aleksey Matveyenko
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, Minnesota, USA.,Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
| | - Giuseppe De Nicolao
- Department of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
40
|
Visentin R, Schiavon M, Göbel B, Riz M, Cobelli C, Klabunde T, Dalla Man C. Dual glucagon-like peptide-1 receptor/glucagon receptor agonist SAR425899 improves beta-cell function in type 2 diabetes. Diabetes Obes Metab 2020; 22:640-647. [PMID: 31808298 DOI: 10.1111/dom.13939] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 12/02/2019] [Accepted: 12/02/2019] [Indexed: 12/15/2022]
Abstract
AIM To evaluate the change in insulin sensitivity, β-cell function and glucose absorption after 28 days of treatment with high and low doses of SAR425899, a novel dual glucagon-like peptide-1 receptor/glucagon receptor agonist, versus placebo. MATERIALS AND METHODS Thirty-six overweight to obese subjects with type 2 diabetes were randomized to receive daily subcutaneous administrations of low-dose SAR425899 (0.03, 0.06 and 0.09 mg) and high-dose SAR425899 (0.06, 0.12 and 0.18 mg) or placebo for 28 days; dose escalation occurred after days 7 and 14. Mixed meal tolerance tests were conducted before treatment (day -1) and on days 1 and 28. Oral glucose and C-peptide minimal models were used to quantify metabolic indices of insulin sensitivity, β-cell responsiveness and glucose absorption. RESULTS With low-dose SAR425899, high-dose SAR425899 and placebo, β-cell function from day -1 to day 28 increased by 163%, 95% and 23%, respectively. The change in area under the curve for the rate of meal glucose appearance between 0 and 120 minutes was -32%, -20% and 8%, respectively. CONCLUSIONS After 28 days of treatment, SAR425899 improved postprandial glucose control by significantly enhancing β-cell function and slowing glucose absorption rate.
Collapse
Affiliation(s)
- Roberto Visentin
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Michele Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Britta Göbel
- Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Michela Riz
- Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| |
Collapse
|
41
|
Adams JD, Dalla Man C, Laurenti MC, Andrade MDH, Cobelli C, Rizza RA, Bailey KR, Vella A. Fasting glucagon concentrations are associated with longitudinal decline of β-cell function in non-diabetic humans. Metabolism 2020; 105:154175. [PMID: 32045582 PMCID: PMC7093233 DOI: 10.1016/j.metabol.2020.154175] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 02/05/2020] [Accepted: 02/07/2020] [Indexed: 01/31/2023]
Abstract
PURPOSE Abnormal glucagon concentrations are a feature of prediabetes but it is uncertain if α-cell dysfunction contributes to a longitudinal decline in β-cell function. We therefore sought to determine if a decline in β-cell function is associated with a higher nadir glucagon in the postprandial period or with higher fasting glucagon. METHODS This was a longitudinal study in which 73 non-diabetic subjects were studied on 2 occasions 6.6 ± 0.3 years apart using a 2-hour, 7-sample oral glucose tolerance test. Disposition Index (DI) was calculated using the oral minimal model applied to the measurements of glucose, insulin, C-peptide concentrations during the studies. We subsequently examined the relationship of glucagon concentrations at baseline with change in DI (used as a measure of β-cell function) after adjusting for changes in weight and the baseline value of DI. RESULTS After adjusting for covariates, nadir postprandial glucagon concentrations were not associated with changes in β-cell function as quantified by DI. On the other hand, fasting glucagon concentrations during the baseline study were inversely correlated with longitudinal changes in DI. CONCLUSIONS Defects in α-cell function, manifest as elevated fasting glucagon, are associated with a subsequent decline in β-cell function. It remains to be ascertained if abnormal α-cell function contributes directly to loss of β-cell secretory capacity in the pathogenesis of type 2 diabetes.
Collapse
Affiliation(s)
- Jon D Adams
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Marcello C Laurenti
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - M Daniela Hurtado Andrade
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Robert A Rizza
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Kent R Bailey
- Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA.
| |
Collapse
|
42
|
Toffanin C, Kozak M, Sumnik Z, Cobelli C, Petruzelkova L. In Silico Trials of an Open-Source Android-Based Artificial Pancreas: A New Paradigm to Test Safety and Efficacy of Do-It-Yourself Systems. Diabetes Technol Ther 2020; 22:112-120. [PMID: 31769699 DOI: 10.1089/dia.2019.0375] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Objective: Safety data on Do-It-Yourself Artificial Pancreas Systems are missing. The most widespread in Europe is the AndroidAPS implementation of the OpenAPS algorithm. We used the UVA/Padova Type 1 Diabetes Simulator to in silico test safety and efficacy of this algorithm in different scenarios. Methods: We tested five configurations of the AndroidAPS algorithm differing in aggressiveness and patient's interaction with the system. All configurations were tested with insulin sensitivity variation of ±30%. The most promising configurations were tested in real-life scenarios: over- and underestimated bolus by 50%, bolus delivered 15 min before meal, and late bolus delivered 15 min after meal. Continuous Glucose Monitoring (CGM) time in ranges (TIRs) metrics were used to assess the glycemic control. Results: In silico testing showed that open-source closed-loop system AndroidAPS works effectively and safely. The best results were reached if AndroidAPS algorithm worked with microboluses and when half of calculated bolus was issued (mean glycemia 131 mg/dL, SD 27 mg/dL, TIR 91%, time between 54 and 70 mg/dL <1%, and low blood glucose index even <1). The meal bolus over- and underestimation as well as late bolus did not affect the TIR and, importantly, the time between 54 and 70 mg/dL. Conclusion: In silico testing proved that AndroidAPS implementation of the OpenAPS algorithm is safe and effective, and it showed a great potential to be tested in prospective home setting study.
Collapse
Affiliation(s)
- Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Milos Kozak
- CLOSED LOOP Systems, Prague, Czech Republic, Prague, Czech Republic
| | - Zdenek Sumnik
- Department of Paediatrics, Motol University Hospital, 2nd Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Lenka Petruzelkova
- Department of Paediatrics, Motol University Hospital, 2nd Faculty of Medicine, Charles University, Prague, Czech Republic
| |
Collapse
|
43
|
Galderisi A, Tricò D, Dalla Man C, Santoro N, Pierpont B, Groop L, Cobelli C, Caprio S. Metabolic and Genetic Determinants of Glucose Shape After Oral Challenge in Obese Youths: A Longitudinal Study. J Clin Endocrinol Metab 2020; 105:5714814. [PMID: 31972003 PMCID: PMC6977541 DOI: 10.1210/clinem/dgz207] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 11/15/2019] [Indexed: 02/08/2023]
Abstract
CONTEXT The time-to-glucose-peak following the oral glucose tolerance test (OGTT) is a highly reproducible marker for diabetes risk. In obese youths, we lack evidence for the mechanisms underlying the effects of the TCF7L2 rs7903146 variant on glucose peak. METHODS We analyzed the metabolic phenotype and the genotype for the TCF7L2 rs7903146 in 630 obese youths with normal (NGT) and impaired (IGT) glucose tolerance. Participants underwent a 3-hour, 9-point OGTT to estimate, using the oral minimal model, the disposition index (DI), the static (φstatic) and dynamic (φdynamic) components β-cell responsiveness and insulin sensitivity (SI). In a subgroup (n = 241) longitudinally followed for 2 years, we estimated the effect of time-to-glucose-peak on glucose tolerance change. RESULTS Participants were grouped into early (<30 minutes) and late (≥30 minutes) glucose peakers. A delayed glucose peak was featured by a decline in φstatic (P < .001) in the absence of a difference in φdynamic. The prevalence of T-risk allele for TCF7L2 rs7903146 variant significantly increased in the late peak group. A lower DI was correlated with higher glucose concentration at 1 and 2 hours, whereas SI was inversely associated with 1-hour glucose. Glucose peak <30 minutes was protective toward worsening of glucose tolerance overtime (odds ratio 0.35 [0.15-0.82]; P = .015), with no subjects progressing to NGT or persisting IGT, in contrast to the 40% of progressor in those with late glucose peak. CONCLUSION The prevalence of T-risk allele for the TCF7L2 rs7903146 prevailed in the late time-to-glucose peak group, which in turn is associated with impaired β-cell responsiveness to glucose (φ), thereby predisposing to prediabetes and diabetes in obese youths.
Collapse
Affiliation(s)
- Alfonso Galderisi
- Department of Pediatrics, Pediatrics Endocrinology and Diabetes Section, Yale School of Medicine, New Haven, Connecticut
- Department of Woman’s and Child’s Health, University of Padova, Padova, Italy
- Correspondence and Reprint Requests: Sonia Caprio, MD, Division of Pediatric Endocrinology, Department of Pediatrics, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520. E-mail:
| | - Domenico Tricò
- Institute of Life Sciences, Sant’Anna School of Advanced Studies, Pisa, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Nicola Santoro
- Department of Pediatrics, Pediatrics Endocrinology and Diabetes Section, Yale School of Medicine, New Haven, Connecticut
| | - Bridget Pierpont
- Department of Pediatrics, Pediatrics Endocrinology and Diabetes Section, Yale School of Medicine, New Haven, Connecticut
| | - Leif Groop
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Sonia Caprio
- Department of Pediatrics, Pediatrics Endocrinology and Diabetes Section, Yale School of Medicine, New Haven, Connecticut
| |
Collapse
|
44
|
Abstract
BACKGROUND The objective of this research is to show the effectiveness of individualized hypoglycemia predictive alerts (IHPAs) based on patient-tailored glucose-insulin models (PTMs) for different subjects. Interpatient variability calls for PTMs that have been identified from data collected in free-living conditions during a one-month trial. METHODS A new impulse-response (IR) identification technique has been applied to free-living data in order to identify PTMs that are able to predict the future glucose trends and prevent hypoglycemia events. Impulse response has been applied to seven patients with type 1 diabetes (T1D) of the University of Amsterdam Medical Centre. Individualized hypoglycemia predictive alert has been designed for each patient thanks to the good prediction capabilities of PTMs. RESULTS The PTMs performance is evaluated in terms of index of fitting (FIT), coefficient of determination, and Pearson's correlation coefficient with a population FIT of 63.74%. The IHPAs are evaluated on seven patients with T1D with the aim of predicting in advance (between 45 and 10 minutes) the unavoidable hypoglycemia events; these systems show better performance in terms of sensitivity, precision, and accuracy with respect to previously published results. CONCLUSION The proposed work shows the successful results obtained applying the IR to an entire set of patients, participants of a one-month trial. Individualized hypoglycemia predictive alerts are evaluated in terms of hypoglycemia prevention: the use of a PTM allows to detect 84.67% of the hypoglycemia events occurred during a one-month trial on average with less than 0.4% of false alarms. The promising prediction capabilities of PTMs can be a key ingredient for new generations of individualized model predictive control for artificial pancreas.
Collapse
Affiliation(s)
- Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy
- Chiara Toffanin, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 3, Pavia, Lombardy 27100, Italy.
| | - Eleonora Maria Aiello
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Italy
| | - Lalo Magni
- Department of Civil Engineering and Architecture, University of Pavia, Italy
| |
Collapse
|
45
|
Smushkin G, Sathananthan A, Man CD, Camilleri M, Cobelli C, Rizza RA, Vella A. Letter to the Editor: "Defects in GLP-1 Response to an Oral Challenge Do Not Play a Significant Role in the Pathogenesis of Prediabetes". J Clin Endocrinol Metab 2019; 104:5106-5107. [PMID: 31074786 DOI: 10.1210/jc.2019-00904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 05/06/2019] [Indexed: 02/13/2023]
Affiliation(s)
- Galina Smushkin
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota
| | - Airani Sathananthan
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Michael Camilleri
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Claudio Cobelli
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Robert A Rizza
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota
| | - Adrian Vella
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota
| |
Collapse
|
46
|
Visentin R, Schiavon M, Giegerich C, Klabunde T, Man CD, Cobelli C. Incorporating Long-Acting Insulin Glargine Into the UVA/Padova Type 1 Diabetes Simulator for In Silico Testing of MDI Therapies. IEEE Trans Biomed Eng 2019; 66:2889-2896. [DOI: 10.1109/tbme.2019.2897851] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
47
|
Basu R, Schiavon M, Petterson XM, Hinshaw L, Slama M, Carter R, Man CD, Cobelli C, Basu A. A novel natural tracer method to measure complex carbohydrate metabolism. Am J Physiol Endocrinol Metab 2019; 317:E483-E493. [PMID: 31265327 PMCID: PMC6766609 DOI: 10.1152/ajpendo.00133.2019] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and β-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 μM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 μM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 μM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and β-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and β-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.
Collapse
Affiliation(s)
- Rita Basu
- Division of Endocrinology, University of Virginia, Charlottesville, Virginia
| | - Michele Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Xuan-Mai Petterson
- Endocrine Research Unit, Division of Endocrinology and Metabolism, Mayo Clinic, Rochester, Minnesota
| | - Ling Hinshaw
- Endocrine Research Unit, Division of Endocrinology and Metabolism, Mayo Clinic, Rochester, Minnesota
| | - Michael Slama
- Endocrine Research Unit, Division of Endocrinology and Metabolism, Mayo Clinic, Rochester, Minnesota
| | - Rickey Carter
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, Florida
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ananda Basu
- Division of Endocrinology, University of Virginia, Charlottesville, Virginia
| |
Collapse
|
48
|
Battelino T, Danne T, Bergenstal RM, Amiel SA, Beck R, Biester T, Bosi E, Buckingham BA, Cefalu WT, Close KL, Cobelli C, Dassau E, DeVries JH, Donaghue KC, Dovc K, Doyle FJ, Garg S, Grunberger G, Heller S, Heinemann L, Hirsch IB, Hovorka R, Jia W, Kordonouri O, Kovatchev B, Kowalski A, Laffel L, Levine B, Mayorov A, Mathieu C, Murphy HR, Nimri R, Nørgaard K, Parkin CG, Renard E, Rodbard D, Saboo B, Schatz D, Stoner K, Urakami T, Weinzimer SA, Phillip M. Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range. Diabetes Care 2019. [PMID: 31177185 DOI: 10.2337/dci19‐0028] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Collapse
Affiliation(s)
- Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Slovenia
| | - Thomas Danne
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | | | | | - Roy Beck
- Jaeb Center for Health Research, Tampa, FL
| | - Torben Biester
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Bruce A Buckingham
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford Medical Center, Stanford, CA
| | | | - Kelly L Close
- Close Concerns and The diaTribe Foundation, San Francisco, CA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - J Hans DeVries
- Profil, Neuss, Germany
- Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Kim C Donaghue
- Children's Hospital at Westmead, University of Sydney, Sydney, Australia
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Slovenia
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Satish Garg
- University of Colorado Denver and Barbara Davis Center for Diabetes, Aurora, CO
| | | | - Simon Heller
- Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, U.K
| | | | - Irl B Hirsch
- Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, and Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Weiping Jia
- Department of Endocrinology & Metabolism, Shanghai Clinical Center of Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Olga Kordonouri
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | - Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | | | - Lori Laffel
- Pediatric, Adolescent and Young Adult Section and Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, MA
| | - Brian Levine
- Close Concerns and The diaTribe Foundation, San Francisco, CA
| | | | - Chantal Mathieu
- Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium
| | - Helen R Murphy
- Norwich Medical School, University of East Anglia, Norwich, U.K
| | - Revital Nimri
- Jesse Z and Sara Lea Shafer Institute of Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | | | | | - Eric Renard
- Department of Endocrinology, Diabetes, and Nutrition, Montpellier University Hospital; Institute of Functional Genomics, University of Montpellier; and INSERM Clinical Investigation Centre, Montpellier, France
| | | | | | - Desmond Schatz
- Pediatric Endocrinology, University of Florida, Gainesville, FL
| | | | - Tatsuiko Urakami
- Department of Pediatrics, Nihon University School of Medicine, Tokyo, Japan
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Moshe Phillip
- Jesse Z and Sara Lea Shafer Institute of Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
49
|
Battelino T, Danne T, Bergenstal RM, Amiel SA, Beck R, Biester T, Bosi E, Buckingham BA, Cefalu WT, Close KL, Cobelli C, Dassau E, DeVries JH, Donaghue KC, Dovc K, Doyle FJ, Garg S, Grunberger G, Heller S, Heinemann L, Hirsch IB, Hovorka R, Jia W, Kordonouri O, Kovatchev B, Kowalski A, Laffel L, Levine B, Mayorov A, Mathieu C, Murphy HR, Nimri R, Nørgaard K, Parkin CG, Renard E, Rodbard D, Saboo B, Schatz D, Stoner K, Urakami T, Weinzimer SA, Phillip M. Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range. Diabetes Care 2019; 42:1593-1603. [PMID: 31177185 PMCID: PMC6973648 DOI: 10.2337/dci19-0028] [Citation(s) in RCA: 1789] [Impact Index Per Article: 357.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Collapse
Affiliation(s)
- Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Slovenia
| | - Thomas Danne
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | | | | | - Roy Beck
- Jaeb Center for Health Research, Tampa, FL
| | - Torben Biester
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Bruce A Buckingham
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford Medical Center, Stanford, CA
| | | | - Kelly L Close
- Close Concerns and The diaTribe Foundation, San Francisco, CA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - J Hans DeVries
- Profil, Neuss, Germany.,Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Kim C Donaghue
- Children's Hospital at Westmead, University of Sydney, Sydney, Australia
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Slovenia
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Satish Garg
- University of Colorado Denver and Barbara Davis Center for Diabetes, Aurora, CO
| | | | - Simon Heller
- Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, U.K
| | | | - Irl B Hirsch
- Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, and Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Weiping Jia
- Department of Endocrinology & Metabolism, Shanghai Clinical Center of Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Olga Kordonouri
- Diabetes Centre for Children and Adolescents, Kinder- und Jugendkrankenhaus Auf der Bult, Hannover, Germany
| | - Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | | | - Lori Laffel
- Pediatric, Adolescent and Young Adult Section and Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, MA
| | - Brian Levine
- Close Concerns and The diaTribe Foundation, San Francisco, CA
| | | | - Chantal Mathieu
- Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium
| | - Helen R Murphy
- Norwich Medical School, University of East Anglia, Norwich, U.K
| | - Revital Nimri
- Jesse Z and Sara Lea Shafer Institute of Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | | | | | - Eric Renard
- Department of Endocrinology, Diabetes, and Nutrition, Montpellier University Hospital; Institute of Functional Genomics, University of Montpellier; and INSERM Clinical Investigation Centre, Montpellier, France
| | | | | | - Desmond Schatz
- Pediatric Endocrinology, University of Florida, Gainesville, FL
| | | | - Tatsuiko Urakami
- Department of Pediatrics, Nihon University School of Medicine, Tokyo, Japan
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Moshe Phillip
- Jesse Z and Sara Lea Shafer Institute of Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
50
|
Schiavon M, Visentin R, Giegerich C, Klabunde T, Cobelli C, Dalla Man C. Modeling Subcutaneous Absorption of Long-Acting Insulin Glargine in Type 1 Diabetes. IEEE Trans Biomed Eng 2019; 67:624-631. [PMID: 31150327 DOI: 10.1109/tbme.2019.2919250] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Subcutaneous (sc) administration of long-acting insulin analogs is often employed in multiple daily injection (MDI) therapy of type 1 diabetes (T1D) to cover patient's basal insulin needs. Among these, insulin glargine 100 U/mL (Gla-100) and 300 U/mL (Gla-300) are formulations indicated for once daily sc administration in MDI therapy of T1D. A few semi-mechanistic models of sc absorption of insulin glargine have been proposed in the literature, but were not quantitatively assessed on a large dataset. The aim of this paper is to propose a model of sc absorption of insulin glargine able to describe the data and provide precise model parameters estimates with a clear physiological interpretation. METHODS Three candidate models were identified on a total of 47 and 77 insulin profiles of T1D subjects receiving a single or repeated sc administration of Gla-100 or Gla-300, respectively. Model comparison and selection were performed on the basis of their ability to describe the data and numerical identifiability. RESULTS The most parsimonious model is linear two-compartment and accounts for the insulin distribution between the two compartments after sc administration through parameter k. Between the two formulations, we report a lower fraction of insulin in the first versus second compartment (k = 86% versus 94% in Gla-100 versus Gla-300, p < 0.05), a lower dissolution rate from the first to the second compartment ([Formula: see text] versus 0.0008 min-1 in Gla-100 versus Gla-300, p << 0.001), and a similar rate of insulin absorption from the second compartment to plasma ([Formula: see text] versus 0.0016 min-1 in Gla-100 versus Gla-300, p = NS), in accordance with the mechanisms of insulin glargine protraction. CONCLUSIONS The proposed model is able to both accurately describe plasma insulin data after sc administration and precisely estimate physiologically plausible parameters. SIGNIFICANCE The model can be incorporated in simulation platforms potentially usable for optimizing basal insulin treatment strategies.
Collapse
|