Quantitative estimation of disposition index from postprandial glucose data across the spectrum of glucose tolerance
The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI...
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Published in | American journal of physiology: endocrinology and metabolism Vol. 329; no. 2; pp. E355 - E367 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
01.08.2025
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Subjects | |
Online Access | Get full text |
ISSN | 0193-1849 1522-1555 1522-1555 |
DOI | 10.1152/ajpendo.00407.2024 |
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Abstract | The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI G ) was developed and validated against a reference. DI G can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices.
Disposition index (DI), defined as the product of insulin sensitivity and β-cell responsivity, is the best measure of β-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical dataset with mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, whereas the second consisted of 62 individuals with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin, and C-peptide concentrations were used to estimate the reference DI from the OMM (DI MM ), whereas glucose data only were used to calculate the proposed DI (DI G ). DI G was well correlated with DI MM in both the clinical and simulated datasets ( R between 0.88 and 0.79, P < 0.001), and exhibited the same between-visit or between-group pattern. DI G can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess β-cell function in real-life conditions using CGM.
NEW & NOTEWORTHY The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI G ) was developed and validated against a reference. DI G can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices. |
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AbstractList | Disposition Index (DI), defined as the product of insulin sensitivity and beta-cell responsivity, is the best measure of beta-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals, raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM).
To do so, we used data from two clinical mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, while the second consisted of 62 individuals, with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin and C-peptide concentrations were used to estimate the reference DI from the OMM (
DI
MM
), while glucose data only were used to calculate the proposed DI (
DI
G
).
DI
G
was well correlated with
DI
MM
in both the clinical and simulated datasets (R between 0.88 and 0.79, p<0.001), and exhibited the same between-visit or between-group pattern.
DI
G
can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess beta-cell function in real-life conditions using CGM.
The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying Disposition Index (DI), a key metric of beta-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (
DI
G
) was developed and validated against reference.
DI
G
can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices. The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI G ) was developed and validated against a reference. DI G can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices. Disposition index (DI), defined as the product of insulin sensitivity and β-cell responsivity, is the best measure of β-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical dataset with mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, whereas the second consisted of 62 individuals with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin, and C-peptide concentrations were used to estimate the reference DI from the OMM (DI MM ), whereas glucose data only were used to calculate the proposed DI (DI G ). DI G was well correlated with DI MM in both the clinical and simulated datasets ( R between 0.88 and 0.79, P < 0.001), and exhibited the same between-visit or between-group pattern. DI G can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess β-cell function in real-life conditions using CGM. NEW & NOTEWORTHY The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI G ) was developed and validated against a reference. DI G can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices. Disposition index (DI), defined as the product of insulin sensitivity and β-cell responsivity, is the best measure of β-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical dataset with mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, whereas the second consisted of 62 individuals with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin, and C-peptide concentrations were used to estimate the reference DI from the OMM (DI ), whereas glucose data only were used to calculate the proposed DI (DI ). DI was well correlated with DI in both the clinical and simulated datasets ( between 0.88 and 0.79, < 0.001), and exhibited the same between-visit or between-group pattern. DI can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess β-cell function in real-life conditions using CGM. The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric of β-cell function usually assessed in research settings, in outpatients. A method for DI estimation from postprandial glucose data only (DI ) was developed and validated against a reference. DI can be used to assess therapy effectiveness and degree of glucose tolerance in non-insulin-treated individuals, paving the way for its quantification in real-life conditions from CGM devices. Disposition Index (DI), defined as the product of insulin sensitivity and beta-cell responsivity, is the best measure of beta-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals, raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, while the second consisted of 62 individuals, with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin and C-peptide concentrations were used to estimate the reference DI from the OMM (DIMM), while glucose data only were used to calculate the proposed DI (DIG). DIG was well correlated with DIMM in both the clinical and simulated datasets (R between 0.88 and 0.79, p<0.001), and exhibited the same between-visit or between-group pattern. DIG can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess beta-cell function in real-life conditions using CGM.Disposition Index (DI), defined as the product of insulin sensitivity and beta-cell responsivity, is the best measure of beta-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals, raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, while the second consisted of 62 individuals, with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin and C-peptide concentrations were used to estimate the reference DI from the OMM (DIMM), while glucose data only were used to calculate the proposed DI (DIG). DIG was well correlated with DIMM in both the clinical and simulated datasets (R between 0.88 and 0.79, p<0.001), and exhibited the same between-visit or between-group pattern. DIG can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess beta-cell function in real-life conditions using CGM. |
Author | Vella, Adrian Dalla Man, Chiara Schiavon, Michele |
AuthorAffiliation | 1 Department of Information Engineering, University of Padova, Padova, Italy 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation, Rochester, MN, USA |
AuthorAffiliation_xml | – name: 1 Department of Information Engineering, University of Padova, Padova, Italy – name: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation, Rochester, MN, USA |
Author_xml | – sequence: 1 givenname: Michele orcidid: 0000-0003-0590-2399 surname: Schiavon fullname: Schiavon, Michele – sequence: 2 givenname: Adrian orcidid: 0000-0001-6493-7837 surname: Vella fullname: Vella, Adrian – sequence: 3 givenname: Chiara orcidid: 0000-0002-4908-0596 surname: Dalla Man fullname: Dalla Man, Chiara |
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Cites_doi | 10.1089/dia.2024.0197 10.2337/db06-1272 10.1152/ajpendo.00421.2006 10.1177/1932296814559746 10.1089/dia.2015.0119 10.2337/dc17-1600 10.1152/ajpendo.90842.2008 10.1089/dia.2017.0248 10.2337/diacare.29.02.06.dc05-1963 10.1089/dia.2017.0024 10.1111/dom.14949 10.2337/dc06-1331 10.1177/19322968241242487 10.2337/diabetes.42.11.1663 10.2337/dc08-1512 10.1152/ajpendo.2001.281.4.E693 10.1089/dia.2022.0397 10.2337/dc13-1120 10.1089/15209150050194332 10.1152/ajpendo.1979.236.6.E667 10.1038/oby.2008.307 10.2337/dc08-1826 10.1109/TBME.2015.2505507 10.1177/19322968251333441 10.2337/diabetes.50.1.150 10.3389/fendo.2021.611253 10.1089/dia.2021.0212 10.1210/jc.2015-2081 10.1109/10.995680 10.1210/jcem-51-3-520 10.1002/oby.23503 10.1152/ajpendo.00473.2004 10.2337/db13-1198 10.1111/dom.14418 10.1089/dia.2020.0110 10.1152/ajpendo.90340.2008 10.1172/JCI113011 10.1016/S0140-6736(18)30297-6 10.2337/diabetes.54.11.3265 10.1007/s11517-014-1226-y 10.2337/dc17-1188 10.1172/jci110398 10.2337/dc16-2482 10.2337/ds20-0069 10.2337/diabetes.41.3.368 10.7326/M16-2855 10.1210/clinem/dgab857 |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 MS developed the method, performed the analysis, contributed to the discussion and wrote the manuscript. CDM developed the method, supervised the analysis, contributed to the discussion and edited the manuscript. AV designed and conducted the clinical study, contributed to the discussion and critically revised the manuscript. CDM is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors have read and agreed to the published version of the manuscript. Author Contributions |
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Snippet | The advent of continuous glucose monitoring (CGM) in non-insulin-treated individuals raises the possibility of quantifying disposition index (DI), a key metric... Disposition index (DI), defined as the product of insulin sensitivity and β-cell responsivity, is the best measure of β-cell function. This is usually assessed... Disposition Index (DI), defined as the product of insulin sensitivity and beta-cell responsivity, is the best measure of beta-cell function. This is usually... |
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SubjectTerms | Adult Aged Blood Glucose - analysis Blood Glucose - metabolism Blood Glucose Self-Monitoring C-Peptide - blood Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - drug therapy Diabetes Mellitus, Type 2 - metabolism Dipeptidyl-Peptidase IV Inhibitors - therapeutic use Female Glucose Intolerance - blood Glucose Tolerance Test Humans Insulin - blood Insulin Resistance - physiology Insulin-Secreting Cells - metabolism Male Middle Aged Postprandial Period - physiology |
Title | Quantitative estimation of disposition index from postprandial glucose data across the spectrum of glucose tolerance |
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