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Interactions Between Delivery, Transport, and Phosphorylation of Glucose in Governing Uptake Into Human Skeletal Muscle

¹ Department of Information Engineering, University of Padova, Padova, Italy
² Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
³ Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania

Address correspondence and reprint requests to David E. Kelley, 807N Montefiore-University Hospital, 3459 Fifth Ave., Pittsburgh, PA 15213. E-mail: kelley{at}dom.pitt.edu

Key Words: 3-OMG, 3-O-methyl glucose • FDG, fluoro-deoxy glucose • MRI, magnetic resonance imaging • PET, positron emission tomography • ROI, region of interest

	ABSTRACT

TOP ABSTRACT RESEARCH DESIGN AND METHODS RESULTS DISCUSSION REFERENCES

 
Skeletal muscle accounts for a large proportion of insulin-stimulated glucose utilization. It is generally regarded that much of the control over rates of uptake is posited within the proximal steps of delivery, transport, and phosphorylation of glucose, with glucose transport as the main locus of control. Whether insulin modulates the distribution of control across these steps and in what manner remains uncertain. The current study addressed this in vivo using dynamic positron emission tomography (PET) imaging of human muscle with sequential injections of three tracers ([¹⁵O]H₂O, [¹¹C]3-O-methyl glucose [3-OMG], and [¹⁸F]fluoro-deoxy glucose [FDG]) that enabled quantitative determinations of glucose delivery, transport, and its phosphorylation, respectively. Lean, healthy, research volunteers were studied during fasting conditions (n = 8) or during a euglycemic insulin infusion at 30 mU/min per m² (n = 8). PET images were coregistered with magnetic resonance imaging to contrast glucose kinetics in soleus, a highly oxidative muscle, with tibialis anterior, a less oxidative muscle. During fasting conditions, uptake of [¹¹C]3-OMG was similar in soleus and tibialis anterior muscles, despite higher delivery to soleus (by 35%; P < 0.01). Uptake of [¹⁸F]FDG was also similar between muscle during fasting, and glucose transport was found to be the dominant locus of control (90%) for glucose uptake under this condition. Insulin increased uptake of [¹¹C]3-OMG substantially and strongly stimulated the kinetics of bidirectional glucose transport. Uptake of [¹¹C]3-OMG was higher in soleus than tibialis anterior muscle (by 22%; P < 0.01), a difference partially due to higher delivery, which was again found to be 35% higher to soleus (P < 0.01). The uptake of [¹⁸F]FDG was 65% greater in soleus compared with tibialis anterior muscle, a larger difference than for [¹¹C]3-OMG (P < 0.01), indicating an added importance of glucose phosphorylation in defining insulin sensitivity. Analysis of the distribution of control during insulin-stimulated conditions revealed that most of the control was posited at delivery and transport and was equally divided between these steps. Thus, insulin evokes a broader distribution of control than during fasting conditions in governing glucose uptake into skeletal muscle. This redistribution of control is triggered by the robust stimulation of glucose transport, which in turn unmasks a greater dependence upon delivery and glucose phosphorylation.

Insulin accelerates the clearance of glucose from plasma into tissues. Uptake of glucose into skeletal muscle is a powerful determinant of this systemic effect (1,2). It is generally considered that much of the control of rates of glucose uptake into skeletal muscle is posited at the proximal steps of glucose delivery, transport, and phosphorylation (3–6) and that among these, stimulation of GLUT4 translocation by insulin is pivotal. Because only slight accumulation of free glucose occurs within muscle during insulin-stimulated conditions, it is cited as clear support for transport as the dominant locus of control rather than more distal steps (5,7–9). However, an absence of glucose accumulation could also be consistent with constraint (and hence rate control) proximal to glucose transport, at glucose delivery (10). There is a general conceptual paradigm regarding what primarily determines control manifest by substrate delivery, and this concerns tissue permeability for a substrate (11). When permeability is low, and with regard to muscle, glucose transport capacity can be considered to represent a permeability factor; rates of delivery should have only minor influence, and, conversely, increases of permeability should proportionately increase control manifest by delivery (11). However, the distribution of control between glucose delivery and transport during insulin-stimulated conditions in human skeletal muscle remains uncertain.

Animal studies using the glucose transport–specific tracer 3-O-methyl glucose (3-OMG) support the concept that when functional capacity of glucose transport is high, physiological conditions exist under which supply constrains uptake (10,12,13). Factors such as glycogen content in muscle also modulate glucose uptake, but much of this effect may be mediated through regulation of glucose transport kinetics (14). Transgenic animals in which expression of hexokinase in muscle has been manipulated suggest that the capacity for glucose phosphorylation can influence rates of glucose uptake but that this effect is most clearly manifested when both delivery and transport are at high capacity, as during exercise (12,15); effects of glucose phosphorylation capacity are less evident under insulin-stimulated conditions (6,12).

The current studies were performed to address the hypothesis that a crucial aspect of normal insulin action is to modulate a redistribution of control across the steps of delivery, transport, and phosphorylation in skeletal muscle of healthy lean individuals. Methods that have examined this in animals have been largely based on using 3-OMG and/or deoxyglucose, metabolism of which are limited to bidirectional transport and to glucose phosphorylation, respectively. Recently, we have introduced methods for quantitative dynamic positron emission tomography (PET) imaging of [¹¹C]3-OMG in human skeletal muscle (16,17). The current study is the first clinical investigation to use both [¹¹C]3-OMG and [¹⁸F]fluoro-deoxy glucose (FDG) in order to compare uptake of a tracer constrained to transport with one that can undergo phosphorylation. In the current study, [¹¹C]3-OMG and [¹⁸F]FDG were used in conjunction with dynamic PET imaging of the lower leg in healthy lean volunteers under fasting or insulin-stimulated conditions to delineate the time course of accumulation of each tracer following its injection. Compartmental modeling of tissue activity for both [¹¹C]3-OMG and [¹⁸F]FDG reveal a kinetic parameter that is ascribed to delivery from plasma to the tissue bed (16,18). To test the validity of this attribution, a third tracer, [¹⁵O]H₂O, was used to quantify tissue perfusion and hence provide an independent criterion method. Another technical aspect of the study design was to examine and compare two specific muscle groups, soleus, a predominately oxidative muscle, with tibialis anterior, a less oxidative muscle. To our knowledge, this is a novel noninvasive ascertainment of insulin sensitivity in individual muscles in humans and is feasible through coregistration of PET and magnetic resonance images (17). It was undertaken to more fully understand how interactions across delivery, transport, and phosphorylation serve to determine gradations of insulin sensitivity between different muscles under identical systemic conditions.

	RESEARCH DESIGN AND METHODS

TOP ABSTRACT RESEARCH DESIGN AND METHODS RESULTS DISCUSSION REFERENCES

 
Lean healthy young adults with normal glucose tolerance were recruited by advertisement in the general community. Each volunteer had a medical examination to verify good health. The clinical characteristics of the volunteers participating in insulin-stimulated (insulin) and fasting (basal) studies are shown in Table 1. The two groups were well matched for age, BMI, and sex distribution. Informed written consent was obtained from all participants, and the protocol was approved by the University of Pittsburgh Institutional Review Board.

PET imaging.
PET imaging was performed at the University of Pittsburgh PET Center. A Siemens/CTI ECAT HR+ PET scanner in 3-D imaging mode (63 parallel planes, axial field-of-view 15.2 cm, slice width 2.4 mm) was used. The final reconstructed PET image resolution was about 6 mm. Participants were positioned in the PET scanner with the mid-calf area in the center of the field, and to minimize movement during PET imaging, the legs were supported with pliable block molding.

[¹⁵O]H₂O imaging.
Insulin was infused for at least 1 h before PET imaging of [¹⁵O]H₂O uptake in skeletal muscle. [¹⁵O]H₂O was given as a 30-mCi bolus, and arterial blood sampling was obtained with a Siemens liquid activity monitor through a short (<15 cm) length of polytetrafluoroethylene tubing controlled by a peristalsis pump positioned distal to the activity monitor. PET scanning began with the injection and lasted 3 min (18 x 10 s frames). PET data were corrected for radioactive decay and scatter (19).

[¹¹C]3-OMG imaging.
Radiosynthesis of [¹¹C]3-OMG was performed as previously described (16). [¹¹C]3-OMG was administered as a slow bolus (5 mCi) over 20 s, 30 min after completing PET imaging of [¹⁵O]H₂O. A 90-min, dynamic PET scan was started (36 frames: 8 x 15 s, 8 x 15 s, 4 x 1 min, and 16 x 5 min) at the injection. Arterial [¹¹C]3-OMG was measured in 0.5-ml samples obtained manually (10 samples every 6 s, 8 samples every 15 s, 7 samples every min, 10 samples every 5 min, and 3 samples every 10 min) over a total time of 90 min. Blood samples were immediately centrifuged, and 200 µl plasma removed for immediate [¹¹C] counting using a COBRA Auto-Gamma model 5003 counter (Packard Instruments, Meriden, CT).

[¹⁸F]FDG imaging.
Two hours after injection of [¹¹C]3-OMG, 6 mCi [¹⁸F]FDG was given as a slow (20 s) intravenous bolus. [¹⁸F]FDG was synthesized using a modification of the Hamacher method (20). Beginning with this injection, 90-min dynamic PET scanning was started (28 frames: 8 x 30 s, 8 x 60 s, 8 x 4 min, and 4 x 8 min). Blood draws for arterial [¹⁸F]FDG activity were hand drawn as 0.5-ml arterial samples at 10 x 6 s, 8 x 15 s, 7 x 1 min, 10 x 5 min, and 3 x 10 min. Blood was immediately centrifuged, and 100 µl plasma was used for [¹⁸F] counting (>350 keV).

Magnetic resonance imaging of skeletal muscle.
On the same day as PET imaging and using the same foam blocking to maintain the same alignment of the lower legs, a T1-weighted magnetic resonance imaging (MRI) of the mid-calf was obtained. This consisted of a series of T1-weighted images (acquisition parameters: axial plane, relaxation time = 31 ms; echo time = 15 ms; flip angle = 10°; field of view = 40 x 20 cm; matrix size = 256 x 192 x 120; partition thickness = 1.5 mm; and contiguous partitions, one average, total acquisition time = 12.75 min) acquired for high-resolution anatomy. The magnetic resonance images were aligned to PET images using a previously described method (21,22). Briefly, summation PET images were created from the frames of the initial 15 min of the scanning period and coregistered with MRI, so that precise anatomical alignment was achieved.

Measuring tissue activity in PET images.
A region of interest (ROI) was placed over anterior tibialis and soleus muscles. This was applied to each of the frames (18 for [¹⁵O]H₂O and 28 for [¹¹C]3-OMG and [¹⁸F]FDG) across 58 of the 68 planes, of each leg, omitting the proximal and distal 5 planes to reduce influence of scatter. Thus, for [¹¹C]3-OMG, for example, radioactivity within 3,248 ROIs were used to develop the dataset for tissue activity within each muscle. Tracer activity within an ROI was converted to radioactivity concentration (microcuries per milliliter) using an empiric phantom-based calibration factor (microcuries per milliliter per PET counts per pixel).

Compartmental modeling.
The model of Ketty (23) was used to estimate tissue perfusion of skeletal muscle. The measured arterial concentration of [¹⁵O]H₂O was corrected for tubing and peripheral dispersion by deconvolution, assuming that each dispersion source can be described with a first-order exponential function. Compartmental modeling of [¹¹C]3-OMG kinetics was performed, as previously described in detail (16,17). Briefly, the model has three compartments (plasma and two tissue pools) with four rate constants as shown in Fig. 1 (upper panel). This model can is described by:

1

2

3

where C_p is [¹¹C]3-OMG plasma arterial concentration; C_i concentration of [¹¹C]3-OMG in the first tissue compartment, normalized to tissue volume; C_e [¹¹C]3-OMG concentration in the second tissue compartment; C measured [¹¹C]3-OMG tissue time activity; C_b whole-blood tracer concentration; V_b the fraction of total volume occupied by blood pool. The rate constants k₁ (ml/ml per min) and k₂ (min^–1) describe reversible exchange between plasma and first tissue compartment; k₃ (min^–1) and k₄ (min^–1) describe reversible exchange between the first and second tissue compartments. From these rate constants, an overall partition coefficient (V_d) for uptake of [¹¹C]3-OMG from plasma to tissue can be calculated:

4

This partition coefficient is also commonly termed the volume of distribution and can be further subdivided into a partition coefficient for the first tissue compartment, V_ic:

5

and a partition coefficient for the second tissue compartment, V_ec:

6

View larger version (5K): [in this window] [in a new window]   FIG. 1. The structure of the compartmental model used to estimate the kinetics of [11C]3-OMG radioactivity in muscle and for the kinetics of glucose uptake. The rate constants k1 and k2 refer to reversible exhange between plasma and the first tissue compartment (attributed to interstitial space), and the rate constants k3 and k4 refer to reversible exhange between the first and second tissue compartments (attributed to bidirectional glucose transport). The rate constant k5 describes the kinetics of glucose phosphorylation.

7

8

9

10

where C_p*, C_i*, and C_e* are [¹⁸F]FDG concentrations in arterial plasma, the first (normalized to tissue volume) and second tissue compartments, respectively; C_m* is [¹⁸F]FDG-6-P in the second tissue compartment; C* is measured tracer activity; k₁* (ml/ml/min) describes delivery of [¹⁸F]FDG from plasma to the first tissue compartment; k₂* (min^–1) efflux of tracer from the first tissue compartment to plasma; k₃* (min^–1) describes inward transport of [¹⁸F]FDG from the first to the second tissue compartment; k₄* (min^–1) efflux from the second to the first tissue compartment; and k₅* (min^–1) describes the phosphorylation of [¹⁸F]FDG. V_b* and C_b* have the same meaning as previously stated.

From the five rate constants, one can calculate by the fractional uptake of [¹⁸F]FDG, K:

11

Glucose.
A specific glucose tracer was not used in this study; instead, a glucose model was developed from the kinetics determined using [¹¹C]3-OMG and [¹⁸F]FDG. An impressive number of in vitro experiments have shown that 3-OMG is an almost ideal glucose tracer to probe transmembrane transport specifically (26). This has also been verified experimentally in vivo by Bonadonna et al. (27), who injected 3-OMG and glucose into the brachial artery in the postabsorptive state and showed that the two washout curves were virtually superimposed, suggesting that the kinetics of transport of 3-OMG and glucose are indistinguishable. This means that k₁, k₂, k₃, and k₄ of 3-OMG are also the k₁, k₂, k₃, and k₄ of glucose. Thus, glucose kinetics can be described by using the model in Fig. 1 (lower panel), where, in addition to k₁–k₄, glucose phosphorylation (k₅) is considered. k₅ can be derived from the knowledge of [¹¹C]3-OMG kinetics and of the "lumped constant" (LC), which embodies differences between deoxyglucose and glucose for transport and affinity to hexokinase. The LC is defined as:

12

from which:

13

Thus, k₅ can be derived from OMG rate constants k₁–k₄, the fractional uptake of [¹⁸F]FDG, K, and the LC. In human skeletal muscle, the LC has been shown by two groups who utilized different approaches (28,29) to exhibit very small variations over a wide range of insulin concentrations with an average of 1.2.

From glucose k₁–k₅ parameters, additional information can be derived, in particular two partition coefficients of tracer in tissue relative to plasma; one for the extracellular compartment, V_ec, and the second for the intracellular compartment, V_ic:

14

15

The values for rate constants of glucose were further used to estimate intracellular glucose concentration, using the equation:

16

The derivation of Eq. 16 is presented in the online appendix (available at http://diabetes.diabetesjournals.org). It is also possible to quantitatively infer the rate-limiting step of glucose kinetics in human skeletal muscle among delivery (from plasma to extracellular space), transport, and phosphorylation. In particular, following the theory of the Metabolic Control Analysis (30,31), the control coefficients (CC) of delivery, transmembrane transport, and phosphorylation can be calculated as:

17

The higher the value of a control coefficient, the more this process is rate limiting and according a locus of control. For instance, considering for simplicity only, the interaction between transport and phosphorylation, after entry into the cell glucose, can either be trapped by phosphorylation (k₅) or exit (k₄) as free glucose. If all entering glucose is phosphorylated, then transport is rate limiting, i.e., CC_transport >> CC_phosphor. In contrast, if the majority of glucose that enters a cell exits without being phosphorylated, then phosphorylation would be the rate-limiting step or locus of control, i.e., C_transport << C_phosphor.

Parameter estimation.
All three [¹⁵O]H₂O, [¹¹C]3-OMG, and [¹⁸F]FDG kinetic models were numerically identified by nonlinear least squares as previously described (9,10,20,21,31). To quantify the glucose kinetic model, i.e., k₅, instead of calculating k₅ directly from Eq.13, with a fixed LC, potential interindividual differences in LC values were considered to account for interindividual differences in values for K and for k₁, k₂, k₃, and k₄. Thus, the [¹¹C]3-OMG model was utilized while assuming LC to have a Gaussian distribution with a mean of 1.2 and an SD of 0.08, as presented in previous studies (28,29), and utilizing maximum a posteriori Bayesian estimation (32).

Statistics.
Means ± SE are reported. ANOVA was used to examine for significance of differences in comparing basal and insulin, as well as for differences between soleus and tibialis anterior muscles. A P value <0.05 was considered significant.

	RESULTS

TOP ABSTRACT RESEARCH DESIGN AND METHODS RESULTS DISCUSSION REFERENCES

 
Metabolic conditions during PET imaging.
Mean values for plasma glucose were similar during basal and insulin studies (Table 2). Plasma insulin concentrations during insulin studies were at a midphysiological elevation and approximately fourfold higher than during basal studies. Plasma free fatty acid concentrations were substantially suppressed during insulin studies. Exogenous glucose was not infused during basal studies. Rates of exogenous glucose infusion during insulin studies were stable throughout the three sequential intervals of PET imaging (6.4 ± 1.0, 6.5 ± 0.7, and 6.9 ± 0.8 mg · kg^–1 · min^–1 during [¹⁵O]H₂O, [¹¹C]3-OMG, and [¹⁸F]FDG imaging, respectively; P = 0.31), with an overall mean value of 6.6 ± 0.4 mg · kg^–1 · min^–1.

View larger version (4K): [in this window] [in a new window]   FIG. 2. Mean tissue activity curves for [15O]H2O radioactivity in the tissue beds of soleus (solid line) and tibialis anterior (dashed line) muscle are shown during basal and insulin conditions.

View larger version (5K): [in this window] [in a new window]   FIG. 3. Mean tissue activity curves for [11C]3-OMG radioactivity in the tissue beds of soleus (solid line) and tibialis anterior (dashed line) muscle are shown during basal and insulin conditions.

View larger version (5K): [in this window] [in a new window]   FIG. 4. Mean tissue activity curves for [18F]FDG radioactivity in the tissue beds of soleus (solid line) and tibialis anterior (dashed line) muscle are shown during basal and insulin conditions.

Tissue uptake of glucose.
The estimates for the parameters describing glucose kinetics are shown in Table 5. The values for k₁–k₄ are those obtained from [¹¹C]3-OMG quantification, while k₅, V_ec, V_ic, and the mass ratio are estimated by Eqs. 14 and 15. A higher value for k₁ in soleus compared with tibialis anterior muscle was observed during both basal (P < 0.01) and insulin (P < 0.01) conditions. Physiologically, the rate constant k₁ is ascribed to tracer delivery from plasma to the tissue compartment. As shown in Table 5, k₁ was estimated with excellent precision (estimation of error <5%), and there was a strong concordance between values for k₁ and the respective values for tissue perfusion determined using [¹⁵O]H₂O. The ratio between soleus and tibialis anterior muscles for k₁ was 1.35 ± 0.09, which was essentially identical to the ratio found for tissue perfusion, 1.37 ± 0.15, that was obtained using [¹⁵O]H₂O. During insulin, compared with basal, there was no change for k₁ in either soleus or tibialis anterior muscle. There were significant changes in each of the other four rate constants. There was approximately a twofold decrease in k₂ during insulin conditions, a response that was similar in soleus and tibialis anterior muscles. k₂ is the rate constant describing fractional efflux from the first tissue compartment to plasma. There was a highly significant increase in values for k₃ during insulin (P < 0.01); this was similar in soleus and tibialis anterior muscles, increasing by sixfold in soleus and by fivefold in tibialis anterior muscle. k₃ describes the fractional exchange of glucose from the first into the second tissue compartments and is attributed physiologically to the kinetics of inward transmembrane transport for glucose. There was also an increase in k₄ during insulin, the rate constant that describes the fractional exchange of glucose from the second back into the first tissue compartment and attributed physiologically to outward transmembrane transport for glucose. The increase in k₄ during insulin compared with basal was similar in soleus and tibialis anterior muscles. k₅, the rate of glucose phosphorylation, significantly increased in values during insulin (P < 0.01); this was similar in soleus and tibialis anterior muscles, increasing by fourfold in soleus and by twofold in tibialis anterior. The changes in k₃ and k₅ were the most prominent effect of insulin.

Control coefficient for glucose skeletal muscle uptake.
The rate constants describing glucose kinetics were used to calculate the control coefficient for delivery (CC_delivery), transport (CC_transport), and phosphorylation (CC_{phosphorylation}) during basal and insulin conditions for soleus and tibialis anterior muscles. These results are shown in Fig. 5. The results indicate that both soleus and tibialis anterior glucose transport and phosphorylation (hexokinase) largely account for control of glucose kinetics in human skeletal muscle during basal conditions. Of these, transport exerted stronger control than phosphorylation (0.60 vs. 0.35 in soleus and 0.70 vs. 0.24 in tibialis anterior). Thus, glucose delivery was not found to substantially control glucose uptake into skeletal muscle during basal conditions. This pattern of distribution of control shifted during insulin conditions for both soleus and tibialis anterior and was quite similar in both muscle groups. Under insulin-stimulated conditions, glucose delivery and transport contributed nearly equally to the control of glucose uptake and together accounted for 90% of control, whereas phosphorylation was calculated to manifest only the remaining 10% of rate control for the kinetics of glucose uptake.

View larger version (7K): [in this window] [in a new window]   FIG. 5. The coefficients of control governing rates of glucose uptake during basal () and insulin () are shown for soleus and tibialis anterior muscle.

	DISCUSSION

TOP ABSTRACT RESEARCH DESIGN AND METHODS RESULTS DISCUSSION REFERENCES

The fulcrum by which insulin increases the control exerted by glucose delivery is through a robust stimulation of glucose transport. Dynamic PET imaging with the tracers [¹⁵O]H₂O and [¹¹C]3-OMG, the former profiling tissue perfusion and hence glucose delivery, enabled the kinetics of glucose transport to be separately and quantitatively ascertained. In response to insulin, we observed that the efficiency of glucose transport is increased approximately sixfold compared with fasting conditions. This changes the step of glucose transport from the bottleneck it poses during fasting, wherein it is the main control point, to one that more closely approximates an equilibration process. With this change in transport capacity, uptake became more overtly controlled by rates of delivery and more influenced by the efficiency with which glucose is trapped within muscle through phosphorylation. Dynamic PET imaging performed using [¹⁸F]FDG indicated that glucose phosphorylation does not exert strong rate control on glucose uptake during insulin-stimulated conditions but does help determine normal physiological gradations of insulin sensitivity that exist between different skeletal muscles, as has been earlier reported in animal studies (6). In contrasting insulin sensitivity of soleus and tibialis anterior muscles, 65% higher uptake of [¹⁸F]FDG was observed during insulin-stimulated conditions in soleus, a muscle with high oxidative capacity. This gradient for [¹⁸F]FDG uptake between soleus and tibialis anterior muscles was significantly larger than the differences observed for perfusion (35% higher in soleus) or transport (22% higher partition coefficient for [¹¹C]3-OMG in soleus). Through a main effect to activate glucose transport, insulin enables fuller utilization of and is also constrained by the capacities of glucose delivery and phosphorylation. Thus, a consequence of insulin action is to broaden the distribution of control from a singular predominance of transport that prevails during fasting conditions to that in which delivery, transport, and phosphorylation contribute substantively in governance of glucose uptake.

Previous studies using biopsy samples and spectroscopy imaging indicate that under insulin-stimulated conditions, regardless of vigorously increased glucose uptake into skeletal muscle, there is just a slight increase in free (unphosphorylated) glucose (5,8,9). This lack of accumulation of glucose has been logically interpreted as signifying that glucose transport, rather than a distal step, limits glucose uptake under insulin-stimulated conditions. However, this finding could also be compatible with a limitation proximal to transport. In recent years, a series of in vivo animal studies from Wasserman and colleagues (10,12,13) have yielded findings consistent with the notion that glucose delivery constrains uptake during insulin-stimulated conditions. In these studies, it was found that the trans-sarcolemmal gradient for 3-OMG fell compared with fasting conditions and approximated zero during insulin-stimulated conditions (10,12,13). This denotes that the functional capacity of transport under insulin-stimulated conditions is quite sufficient and, therefore, rates of delivery constrain uptake. Our studies in healthy lean men and women using [¹¹C]3-OMG are in complete accord with an effect of insulin to shift the distribution of control from predominately transport during fasting conditions toward a larger role for glucose delivery. During fasting conditions, soleus and tibialis anterior muscles differed significantly in tissue perfusion but had nearly identical rates of uptake for both [¹¹C]3-OMG and [¹⁸F]FDG. Indeed, the only discernible difference between these muscles was a brief initial higher tissue activity in the tissue bed of soleus that of itself denotes higher delivery.

When used in cell culture experiments, in which delivery is not an issue, it is clear that 3-OMG profiles bidirectional glucose transport. When given in vivo, the kinetics of its uptake into a tissue bed necessarily include a component of delivery. Mathematical analysis of the tissue activity curves measured for [¹¹C]3-OMG reveal the interaction of two reversible processes (16), which in the earlier initial studies we posited to be [¹¹C]3-OMG delivery from plasma to the tissue bed and bidirectional trans-membrane transport. Based on the findings of the present study obtained with sequential imaging with [¹⁵O]H₂O and [¹¹C]3-OMG, these attributions can be verified. PET imaging of [¹⁵O]H₂O is widely used to assess tissue perfusion (33), including in skeletal muscle (34,35). Its high permeability into tissue makes uptake dependent upon flow. Values obtained for skeletal muscle tissue perfusion in the current study are similar to those earlier reported and provide a criterion for comparison with k₁, the first rate constant estimated from tissue activities for [¹¹C]3-OMG and for [¹⁸F]FDG. There was solid concordance between values for k₁ ascertained for [¹¹C]3-OMG and [¹⁸F]FDG with the values for tissue perfusion. This demonstrates that k₁ portrays the kinetics of tracer delivery (36) and, from a methodological perspective, indicates that in future studies, imaging with [¹⁵O]H₂O can be omitted since this information is obtainable with compartmental modeling analysis of [¹¹C]3-OMG and [¹⁸F]FDG.

In the current study, values for tissue perfusion, measured using [¹⁵O]H₂O and respective values for k₁ values determined in modeling of tissue activities of [¹¹C]3-OMG and [¹⁸F]FDG, did not change during insulin infusion as compared with fasting in either soleus or tibialis anterior. During the past decade, there has been an emerging body of data stating that a component of insulin action on skeletal muscle includes hemodynamic effects. Recent clinical investigations using contrast-enhanced ultrasound, and other methods in animal studies, indicate that insulin stimulates capillary recruitment (37,38). This occurs fairly quickly and at physiological levels of insulin. Capillary recruitment increases distribution to nutritive vessels, even without increased arterial flow, indeed, perhaps, slowing flow at the capillary level and facilitating substrate exchange. Measurement of capillary recruitment is beyond the spatial resolution of PET since each pixel can be estimated to contain hundreds or thousands of capillaries in muscle. Yet, what is quite interesting is that even without overt (or detectable) changes in values for tissue perfusion, the current multitracer studies reveal the importance of perfusion in governing glucose uptake because of the sufficient increase in transport capacity. Higher resolution methodologies may yield further insight as to how interaction between delivery and transport regulates glucose uptake.

The concordance between values for tissue perfusion and values for k₁ is also important because this clarifies the physiological attribution of the second kinetic component mathematically evident in tissue activity for [¹¹C]3-OMG (16,17). During fasting conditions, it is well accepted that glucose uptake by skeletal muscle is minimal (39), with a fractional extraction of 1% estimated using arteriovenous balance across the leg or forearm (1,40). In the current study, fasting values for k₃ (minute^–1), which is the rate constant ascribed to inward glucose transport for [¹¹C]3-OMG, indicated that 1% per minute of tracer entered the second from the first tissue compartment. Similar kinetics (i.e., similar values for k₃) were found in modeling tissue activity of [¹⁸F]FDG during fasting conditions. Calculation of the control coefficients indicated that 85% of control was attributable to glucose transport during fasting conditions. During insulin-stimulated conditions, GLUT4 content at the cell surface of myocytes and along T-tubules increases by two- to threefold (41). Our mathematical modeling of tissue activity for [¹¹C]3-OMG indicates robust insulin stimulation of the kinetics of glucose transport, increasing sixfold in soleus and fivefold in tibialis anterior muscle. These findings are highly similar to values we reported earlier in separate volunteers imaged under similar metabolic conditions (17). In these recent studies using dynamic PET imaging of [¹¹C]3-OMG during each of a two-step insulin infusion, k₃ increased approximately 6-fold at the lower rate (which was similar to the rate of infusion used in the current study) and by nearly 20-fold above fasting at the higher rate of insulin infusion (17). Thus, in interpreting the findings of the present study, it is not appropriate to categorize glucose transport as being maximally stimulated. At this midphysiological level of insulin, we estimate that 40% of rate control over glucose uptake is due to glucose transport so this is still a major locus of control, albeit substantially reduced from its singular importance during fasting.

During insulin-stimulated conditions, uptake of [¹⁸F]FDG was 65% higher in soleus than in tibialis anterior muscle. This gradient between the two muscles was significantly greater than for uptake of [¹¹C]3-OMG (22% higher in soleus) and for tissue perfusion (35% higher in soleus). Gradations of insulin sensitivity between muscles are commonly observed in animal studies. Muscles comprised of mostly slow-twitch fibers manifest higher insulin sensitivity than those with predominately fast-twitch fibers, a difference generally attributed to higher insulin sensitivity of oxidative versus glycolytic muscles (6,42,43). Human skeletal muscles are, however, generally of mixed fiber type, though ex vivo determinations of oxidative capacity contributes to gradations of insulin sensitivity or resistance (44). Soleus is a muscle of relatively high oxidative capacity, and in keeping with this, it is known to differ in lipid content from tibialis anterior muscle (45). The fact that the difference for uptake of [¹⁸F]FDG between soleus and tibialis anterior was more than twice the difference between muscles for perfusion ([¹⁵O]H₂O) and for transport ([¹¹C]3-OMG) indicates that the step of glucose phosphorylation contributes substantially to higher insulin sensitivity in soleus muscle. By definition, muscles that are of higher oxidative capacity possess higher mitochondrial content, and hexokinase is largely bound to mitochondria near porin, the site of ADP and ATP exchange (46,47). In oxidative muscle, expression of GLUT4 and hexokinase are coordinately regulated (48) and capillary density is greater. Consistent with these principles, in the current study, compared with tibialis anterior muscle, soleus muscle had higher perfusion and higher capacity for glucose phosphorylation, denoting close coordination across the steps of delivery, transport, and phosphorylation. However, it is also interesting that in neither tibialis anterior nor soleus was there much rate control attributable to glucose phosphorylation during insulin-stimulated conditions, even though we estimated a relatively small but significant increase in the concentration of intracellular glucose during insulin-stimulated compared with basal conditions in both muscles. This would indicate that the capacity for glucose phosphorylation in each muscle was competent to accommodate insulin-stimulated glucose flux. Recent transgenic animal studies also indicate that hexokinase emerges as a rate control on glucose uptake only when transport and delivery are strongly activated during physical activity but that delivery is a more important locus of control than phosphorylation during insulin-stimulated conditions at rest (12,15).

In summary, by robust stimulation of the kinetics of glucose transport, insulin modulates the distribution of control among delivery, transport, and phosphorylation. Insulin sensitivity in skeletal muscle of healthy lean men and women is influenced discernibly by each of these three steps, operating in close and interdependent coordination. This triple-tracer PET imaging method should prove useful in investigating insulin resistance of skeletal muscle and assessing whether this is due to a single predominant impairment or as a consequence of distributed impediments across these proximal steps.

	ACKNOWLEDGMENTS

 
These studies were supported by grants from the National Institutes of Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (DK60555-02), by the University of Pittsburgh General Clinical Research Center (no. 5MO1RR00056), and by the Obesity and Nutrition Research Center (NIH/NIDDK; P30-DK-46204). This work was also supported by NIH grant EB-01975.

We gratefully acknowledge the efforts and cooperation of the research volunteers and the support from the staffs of the University of Pittsburgh General Clinical Research Center and the PET Center.

	FOOTNOTES

 
Additional information for this article can be found in an online appendix at http://diabetes.diabetesjournals.org.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received for publication June 5, 2006 and accepted in revised form August 11, 2006

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