The oral minimal model method

Abstract

The simultaneous assessment of insulin action, secretion, and hepatic extraction is key to understanding postprandial glucose metabolism in nondiabetic and diabetic humans. We review the oral minimal method (i.e., models that allow the estimation of insulin sensitivity, β-cell responsivity, and hepatic insulin extraction from a mixed-meal or an oral glucose tolerance test). Both of these oral tests are more physiologic and simpler to administer than those based on an intravenous test (e.g., a glucose clamp or an intravenous glucose tolerance test). The focus of this review is on indices provided by physiological-based models and their validation against the glucose clamp technique. We discuss first the oral minimal model method rationale, data, and protocols. Then we present the three minimal models and the indices they provide. The disposition index paradigm, a widely used β-cell function metric, is revisited in the context of individual versus population modeling. Adding a glucose tracer to the oral dose significantly enhances the assessment of insulin action by segregating insulin sensitivity into its glucose disposal and hepatic components. The oral minimal model method, by quantitatively portraying the complex relationships between the major players of glucose metabolism, is able to provide novel insights regarding the regulation of postprandial metabolism.

Figure 1

Net S_I (i.e., insulin action on glucose disposal and production) versus S_I^D (i.e., insulin action on glucose disposal only from IVGTT data).

Figure 2

Top: MTT (left) and OGTT (right) plasma glucose (top), insulin (middle), and C-peptide (bottom) in the same subject. Bottom: Partition analysis of the system allows us to separately estimate S_I, β-cell responsivity, and hepatic extraction without the confounding effect of the two other parameters. Relevant input and output signals of the three models are shown.

Figure 3

The oral glucose minimal models that allow us to estimate S_I (top), β-cell responsivity (middle), and hepatic insulin extraction (bottom).

Figure 4

Schematic diagram to illustrate the importance of expressing β-cell responsivity in relation to S_I by using the DI metric (i.e., the product of β-cell responsivity times S_I is assumed to be a constant). Left: A normal subject (state I) reacts to impaired S_I by increasing β-cell responsivity (state II), while a subject with impaired tolerance does not (state 2). In state II, β-cell responsivity is increased but the DI is unchanged, and normal glucose tolerance is retained normal; while in state 2, β-cell responsivity is normal but not adequate to compensate the decreased S_I (state 2), and glucose intolerance is developed. Right: Impaired glucose tolerance can arise due to defects of β-cell responsivity and/or defects of S_I. In this hypothetical example, subject x is intolerant due to his poor β-cell function, while subject y has poor S_I. The ability to dissect the underlying physiological defects (S_I or β-cell responsivity) allows us to optimize medical treatments.

Figure 5

The oral-labeled minimal models. Left: The exogenous glucose model. Right: The endogenous glucose model.

Figure 6

Left: S_I^D, MTT versus clamp. Right: S_I^L, MTT versus clamp.

Figure 7

Net S_I (i.e., insulin action on glucose disposal and production) versus S_I^D (i.e., insulin action on glucose disposal only) from MTT data.