A modelling approach to hepatic glucose production estimation.

Area of Science:

• Metabolic Research
• Isotope Tracing
• Physiological Modeling

Background:

• Stable isotopes are crucial for measuring glucose fluxes and assessing insulin sensitivity.
• Current methods, like Steele's model, face challenges in accurately estimating glucose appearance and disappearance rates, especially during dynamic physiological states.
• Existing models can produce artefactual results, such as paradoxical increases or negative rates in endogenous glucose production (EGP).

Purpose of the Study:

• To develop and validate a new modeling approach for robust estimation of glucose disappearance (RD) and endogenous glucose production (EGP).
• To overcome the limitations and artefacts associated with the conventional Steele's single-pool model.
• To demonstrate accurate EGP estimation using a single tracer with improved physiological modeling.

Main Methods:

• A novel approach involving simultaneous fitting of cold and labeled ([6, 6-2H2]) glucose observations.
• Representation of both RD and EGP using simple, physiologically plausible functions.
• Application of the method to an intravenous glucose infusion experiment with variable cold glucose administration.

Main Results:

• The proposed method allows for robust estimation of EGP without the artefacts commonly seen with Steele's method.
• Simultaneous fitting of tracer and tracee data improves the accuracy of glucose flux calculations.
• The model successfully estimates EGP even with single-tracer administration under perturbed conditions.

Conclusions:

• A new, robust modeling strategy enables accurate estimation of glucose metabolism parameters, including EGP.
• This approach offers a significant improvement over existing methods for glucose flux analysis.
• The findings support the use of advanced modeling for reliable assessment of glucose kinetics and insulin sensitivity.