NEFA minimal model parameters estimated from the oral glucose tolerance test and the meal tolerance test

Abstract

The kinetics of nonesterified fatty acid (NEFA) metabolism in humans requires quantification to facilitate understanding of diseases like type 1 and 2 diabetes, metabolic syndrome, and obesity, and the mechanisms underpinning various interventions. Oral glucose tolerance tests (OGTT) and glucose meal tolerance tests (MTT) are potentially useful procedures for enabling quantification of NEFA kinetics because they both cause transitory, but substantial, declines and then rebounds in plasma NEFA concentrations in response to physiologically relevant increases in plasma glucose. The Boston MINIMAL model of NEFA kinetics was developed to analyze data from the intravenous glucose tolerance test (IVGTT), but in this work, we present for the first time its application to modeling NEFA data from both OGTT and MTT studies. This model enables estimation of SFFA (micromol.l(-1).min(-1)) (a parameter describing the maximum rate of lipolysis), and KFFA (%/min) (a parameter related to NEFA oxidation rate). The model could well describe the trajectories of NEFA concentrations following an OGTT (R2 in excess of 0.97) but was not as successful with the MTT (R2>0.65). Model parameters derived from analysis of OGTT and MTT data were well identified with coefficients of variation generally less than 15%. Type 2 diabetes, body mass index, and dietary treatment (high-fat vs. high-glycemic-index diets) were all shown to have significant effects on model parameters. Modeling plasma NEFA concentrations over 24 h has helped to identify and quantify the extent that periprandial NEFA peaks and nocturnal elevation in plasma NEFA can be accounted for by our model.

Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss‐mediated metabolic improvements

“…The postprandial metabolism of glucose and nonesterified fatty acids (NEFAs) is an example of this effect, with glucose and incretin hormones leading to insulin output that inhibits lipolysis, proteolysis, and gluconeogenesis, while promoting glycogen and lipid storage. The suppression of NEFA plasma levels caused by insulin has been used for modeling these insulindependent processes, also revealing metabolic changes in subjects with insulin resistance or type 2 diabetes (12)(13)(14)(15). NEFA levels are increased in plasma samples of obese and diabetic patients and have long been associated with metabolic syndrome and insulin resistance (16)(17)(18)(19)(20).…”

Personalized Oxycodone Dosing: Using Pharmacogenetic Testing and Clinical Pharmacokinetics to Reduce Toxicity Risk and Increase Effectiveness

“…Figure shows the plasma OC concentration‐time profiles digitally extracted from the publication by Samer and coworkers [34] for CYP2D6 EM, UM, and PM phenotypes. This approach has been successfully used to study the dynamic relationship between glucose, insulin and non‐esterified fatty acids [35,36]. Subjects received a dose of OC equal to 0.2 mg/kg.…”

“…dynamic relationship between glucose, insulin and nonesterified fatty acids [35,36]. Subjects received a dose of OC equal to 0.2 mg/kg.…”

Insulin Activation of Plasma Nonesterified Fatty Acid Uptake in Metabolic Syndrome

“…We found different response times to be both necessary and reasonable in terms of the underlying molecular cell biology. An innovative approach by one group 5, 46 extends the minimal model concept even further by treating plasma glucose, rather than plasma insulin, as the driver of the surrogate control signal, obviating the need for insulin measurements altogether. Thus, the spectrum of models ranges from those with a focus on parameter estimation, to those endeavoring to represent explicitly the relevant physiological and molecular processes as they are currently understood.…”