The shape of the glucose response curve during an oral glucose tolerance test heralds β–cell function in a large Chinese population

Cheng, Xinqi; Yang, Na; Li, Yuxiu; Sun, Qi; Qiu, Ling; Xu, Lingling; Ping, Fan; Li, Wei; Zhang, Huabing

doi:10.1186/s12902-019-0446-4

Cited by 20 publications

(25 citation statements)

References 27 publications

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“…The largest range for all of the estimated parameters was found in the NGT group, which could partly be explained due to the data set containing more normo-glycemic individuals (see Table 1 ) resulting in a larger variability. Furthermore, normo-glycemic individuals are also known to be more likely to exhibit bi-phasic responses [ 11 ], raising the variability of responses, and thereby the range of estimated parameters values in this category. In addition, the groupings defined by the ADA criteria only consider the fasting and 2h plasma glucose values while ignoring the insulin levels.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, certain dynamic properties of the glucose response curves e.g. peak time, have been nominated as relevant for pathophysiological characterization [6,[8][9][10][11]. In addition, the post-load glucose and insulin trajectories may be used to derive proxy measures of whole-body and tissue-specific insulin sensitivity to serve as a surrogate to the hyperinsulinemic-euglycemic clamp.…”

Section: Introductionmentioning

confidence: 99%

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Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

et al. 2021

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Plasma glucose and insulin responses following an oral glucose challenge are representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals’ challenge test responses has been shown to underlie the effectiveness of lifestyle intervention. Currently, this heterogeneity is overlooked due to a lack of methods to quantify the interconnected dynamics in the glucose and insulin time-courses. Here, a physiology-based mathematical model of the human glucose-insulin system is personalized to elucidate the heterogeneity in individuals’ responses using a large population of overweight/obese individuals (n = 738) from the DIOGenes study. The personalized models are derived from population level models through a systematic parameter selection pipeline that may be generalized to other biological systems. The resulting personalized models showed a 4-5 fold decrease in discrepancy between measurements and model simulation compared to population level. The estimated model parameters capture relevant features of individuals’ metabolic health such as gastric emptying, endogenous insulin secretion and insulin dependent glucose disposal into tissues, with the latter also showing a significant association with the Insulinogenic index and the Matsuda insulin sensitivity index, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

et al. 2021

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“…Metabolism to diagnostic glucose cut-points, the shape of the glucose response curve during an oral glucose tolerance test (OGTT) has been noted to fall into patterns that reflect differences in underlying β-cell function and metabolic risk. [1][2][3][4][5][6][7][8][9] A biphasic or multiphasic glucose profile, characterized by a rise, fall, and subsequent rise in glucose after an oral glucose challenge, has been associated with better β-cell function and lower glucose concentrations compared with a monophasic pattern (simple rise and fall) in adults [2][3][4][5] and youth [7][8][9] with normal and impaired glucose tolerance. In youth with type 2 diabetes, a third pattern of a glucose that has not yet started to decline within the 2 hours following a glucose load was noted, and this pattern, which we have designated as a continuous rise pattern, was associated with poorer β-cell function and greater risk of progression compared with a monophasic or biphasic pattern.…”

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confidence: 99%

Shape of the OGTT glucose response curve: relationship with β-cell function and differences by sex, race, and BMI in adults with early type 2 diabetes treated with metformin

Utzschneider

Younes

Rasouli

et al. 2021

BMJ Open Diab Res Care

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IntroductionThe shape of the glucose curve during an oral glucose tolerance test (OGTT) reflects β-cell function in populations without diabetes but has not been as well studied in those with diabetes. A monophasic shape has been associated with higher risk of diabetes, while a biphasic pattern has been associated with lower risk. We sought to determine if phenotypic or metabolic characteristics were associated with glucose response curve shape in adults with type 2 diabetes treated with metformin alone.Research design and methodsThis is a cross-sectional analysis of 3108 metformin-treated adults with type 2 diabetes diagnosed <10 years who underwent 2-hour 75 g OGTT at baseline as part of the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE). Insulin sensitivity (homeostasis model of insulin sensitivity, HOMA2-S) and β-cell function (early, late, and total incremental insulin and C peptide responses adjusted for HOMA2-S) were calculated. Glucose curve shape was classified as monophasic, biphasic, or continuous rise.ResultsThe monophasic profile was the most common (67.8% monophasic, 5.5% biphasic, 26.7% continuous rise). The monophasic subgroup was younger, more likely male and white, and had higher body mass index (BMI), while the continuous rise subgroup was more likely female and African American/black. HOMA2-S and fasting glucose did not differ among the subgroups. The biphasic subgroup had the highest early, late, and total insulin and C peptide responses (all p<0.05 vs monophasic and continuous rise). Compared with the monophasic subgroup, the continuous rise subgroup had similar early insulin (p=0.3) and C peptide (p=0.6) responses but lower late insulin (p<0.001) and total insulin (p=0.008) and C peptide (p<0.001) responses.ConclusionsBased on the large multiethnic GRADE cohort, sex, race, age, and BMI were found to be important determinants of the shape of the glucose response curve. A pattern of a continuously rising glucose at 2 hours reflected reduced β-cell function and may portend increased glycemic failure rates.Trial registration numberNCT01794143.

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“…[107][108][109][110] The monophasic and unclassified, compared to the biphasic curve, is associated with lower insulin sensitivity and decreased β-cell function across a range of populations. 117,[119][120][121][122][123][124][125] Moreover, compared to the biphasic curve, the monophasic and unclassified curves were better predictors of prediabetes in individuals at high risk for type 1 diabetes, T2DM, or GDM. 118,[126][127][128] More recently, the shape of the OGTT curve has also been used as a predictor of treatment outcomes.…”

Section: The Ogtt Shape Indexmentioning

confidence: 96%

<p>The Oral Glucose Tolerance Test: 100 Years Later</p>

Jagannathan¹,

Neves²,

Dorcely³

et al. 2020

DMSO

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For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate hyperglycemia (prediabetes). Despite this, there has been a steadfast global consensus of the 2-h PG for defining dysglycemic states during the OGTT. This article reviews the history of the OGTT and recent advances in its application, including the glucose challenge test and mathematical modeling for determining the shape of the glucose curve. Pitfalls of the FPG, 2-h PG during the OGTT, and HbA1c are considered as well. Finally, the associations between the 30-minute and 1-hour plasma glucose (1-h PG) levels derived from the OGTT and incidence of diabetes and its complications will be reviewed. The considerable evidence base supports modifying current screening and diagnostic recommendations with the use of the 1-h PG. Measurement of the 1-h PG level could increase the likelihood of identifying high-risk individuals when the pancreatic ß-cell function is substantially more intact with the added practical advantage of potentially replacing the conventional 2-h OGTT making it more acceptable in the clinical setting.

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The shape of the glucose response curve during an oral glucose tolerance test heralds β–cell function in a large Chinese population

Cited by 20 publications

References 27 publications

Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

Shape of the OGTT glucose response curve: relationship with β-cell function and differences by sex, race, and BMI in adults with early type 2 diabetes treated with metformin

<p>The Oral Glucose Tolerance Test: 100 Years Later</p>

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