Identifying early signs of metabolic dysfunction is crucial for preventing and delaying type 2 diabetes mellitus. As such, glucose challenge tests that assess fasting and postprandial glucose, insulin, and C-peptide metabolism, such as oral glucose tolerance tests (OGTT), mixed meal tests (MMT), intravenous glucose tolerance tests (IVGTT), and continuous glucose monitoring (CGM) have been widely used to assess risks for type 2 diabetes and prediabetes. While simple mathematical indices (e.g., insulinogenic index (IGI), oral disposition index, HOMA-IR, and Matsuda index) are widely used in clinical research and epidemiological studies, more complex mathematical models of OGTT, MMT, and IVGTT are emerging as sensitive and precise markers for beta-cell function and insulin sensitivity. More recently, CGM-derived metabolic parameters, including mean amplitude of glycemic excursions (MAGE), are pragmatic alternatives to assess metabolic risk and status. For utilization across the lifespan, measures must be robust and versatile with universal applicability including in pubertal youth and those with extreme insulin resistance.
Recently, measures such as the shape of glucose profiles and time to glucose peak during OGTTs have been developed to predict future glucose abnormality. These novel markers utilize qualitative features to predict diabetes and diabetes risk, as compared to conventional estimates. However, comparable measures are needed to describe other aspects of metabolic function and interpret MMT, IVGTT, and CGM data. Therefore, the development of new measures for quantifying data from glucose challenge tests and CGM is necessary to support clinical practice and promote scientific understanding. Given the variability in metabolic responses associated with age, sex, and race/ethnicity, models must be tested in a wide range of patient populations.
The goals of this Research Topic are to highlight new and emerging metabolic estimates of glucose challenge tests and CGM with the potential for advancing the field of diabetes risk prediction and assessment especially in diverse populations.
The articles (original research or reviews) in this Research Topic should address the following sub-topics:
1. Novel metabolic markers or model parameters of glucose challenge tests, especially models that include diverse populations, women, and children.
• Markers for assessment of insulin resistance and secretion
• Markers that improve diabetes screening, diabetes progression and/or treatment
• Understanding how models may be affected by extreme insulin resistance
• Models with high discrimination in prediabetes
• Models for evaluating insulin resistance/ secretion in the clinical setting
2. Metabolic estimates of CGM for the screening/ monitoring of diabetes.
3. Influence of diet and macronutrient intake on metabolic parameters of glucose challenge tests.
Identifying early signs of metabolic dysfunction is crucial for preventing and delaying type 2 diabetes mellitus. As such, glucose challenge tests that assess fasting and postprandial glucose, insulin, and C-peptide metabolism, such as oral glucose tolerance tests (OGTT), mixed meal tests (MMT), intravenous glucose tolerance tests (IVGTT), and continuous glucose monitoring (CGM) have been widely used to assess risks for type 2 diabetes and prediabetes. While simple mathematical indices (e.g., insulinogenic index (IGI), oral disposition index, HOMA-IR, and Matsuda index) are widely used in clinical research and epidemiological studies, more complex mathematical models of OGTT, MMT, and IVGTT are emerging as sensitive and precise markers for beta-cell function and insulin sensitivity. More recently, CGM-derived metabolic parameters, including mean amplitude of glycemic excursions (MAGE), are pragmatic alternatives to assess metabolic risk and status. For utilization across the lifespan, measures must be robust and versatile with universal applicability including in pubertal youth and those with extreme insulin resistance.
Recently, measures such as the shape of glucose profiles and time to glucose peak during OGTTs have been developed to predict future glucose abnormality. These novel markers utilize qualitative features to predict diabetes and diabetes risk, as compared to conventional estimates. However, comparable measures are needed to describe other aspects of metabolic function and interpret MMT, IVGTT, and CGM data. Therefore, the development of new measures for quantifying data from glucose challenge tests and CGM is necessary to support clinical practice and promote scientific understanding. Given the variability in metabolic responses associated with age, sex, and race/ethnicity, models must be tested in a wide range of patient populations.
The goals of this Research Topic are to highlight new and emerging metabolic estimates of glucose challenge tests and CGM with the potential for advancing the field of diabetes risk prediction and assessment especially in diverse populations.
The articles (original research or reviews) in this Research Topic should address the following sub-topics:
1. Novel metabolic markers or model parameters of glucose challenge tests, especially models that include diverse populations, women, and children.
• Markers for assessment of insulin resistance and secretion
• Markers that improve diabetes screening, diabetes progression and/or treatment
• Understanding how models may be affected by extreme insulin resistance
• Models with high discrimination in prediabetes
• Models for evaluating insulin resistance/ secretion in the clinical setting
2. Metabolic estimates of CGM for the screening/ monitoring of diabetes.
3. Influence of diet and macronutrient intake on metabolic parameters of glucose challenge tests.
