Insulin regulation of glucose transport and phosphorylation in
skeletal muscle assessed by PET
David E.
Kelley1,3,
Katherine
V.
Williams1,3, and
Julie C.
Price2
Departments of 1 Medicine and
2 Radiology, University of
Pittsburgh, and 3 Medical
Research Service, Pittsburgh Veterans Affairs Medical Center,
Pittsburgh, Pennsylvania 15261
 |
ABSTRACT |
The current study examined in vivo insulin
regulation of glucose transport and phosphorylation in skeletal muscle
of healthy, lean volunteers. Positron emission tomography (PET) imaging
and compartmental modeling of the time course of skeletal muscle uptake and utilization after a bolus injection of
2-deoxy-2-[18F]fluoro-D-glucose
([18F]FDG) was
performed during metabolic steady-state conditions at four rates of
euglycemic insulin infusion. Leg glucose uptake (LGU) was determined by
arteriovenous limb balance assessments. The metabolism of
[18F]FDG strongly
correlated with skeletal muscle LGU (r = 0.72, P < 0.01). On the basis of
compartmental modeling, the fraction of glucose undergoing
phosphorylation (PF) increased in a dose-responsive manner from 11%
during basal conditions to 74% at the highest insulin infusion rate
(P < 0.001). The PF and LGU were
highly correlated (r = 0.73, P < 0.001). Insulin also increased
the volume of distribution of nonphosphorylated
[18F]FDG
(P < 0.05). In step-wise regression
analysis, the volume of distribution of nonphosphorylated
[18F]FDG and the rate
constant for glucose phosphorylation accounted for most of the variance
in LGU (r = 0.91, P < 0.001). These findings indicate
an important interaction between transport and phosphorylation in the
control of insulin-stimulated glucose metabolism in skeletal muscle.
insulin sensitivity; positron emission tomography; deoxy-D-glucose
 |
INTRODUCTION |
INSULIN STIMULATES glucose transport into skeletal
muscle. This is achieved both by promoting translocation of glucose
transporters to the sarcolemma and transverse tubules (18) and by
increasing glucose delivery through effects on muscle hemodynamics (3). Yet, muscle biopsy data would suggest that even with increased glucose
transport, intracellular concentration of free glucose does not
increase within skeletal muscle (19). This suggests that glucose
transport is the principal site of control for insulin-stimulated glucose metabolism in skeletal muscle. However, there are additional data suggesting that steps distal to glucose transport may also contribute to the control of insulin-stimulated glucose metabolism. With the use of a hindlimb perfusion model in animals, Kubo and Foley
(23) found that changes in glucose clearance during maximal insulin
stimulation indicated that a process beyond glucose transport helped to
regulate rates of glucose metabolism. A similar conclusion was reached
in subsequent human forearm balance studies, which measured glucose
utilization across a range of insulin and glucose concentrations (39).
Ferrannini et al. (11) calculated that the volume of distribution of
free glucose increased in response to insulin, on the basis of the
kinetics of labeled glucose
([3-3H]glucose)
disappearance, suggesting a step beyond glucose transport is involved
in the control of insulin-stimulated glucose metabolism. More recently,
a tracer method developed to examine the kinetics of glucose transport
and phosphorylation across the human forearm indicates insulin
regulation at both steps in healthy volunteers (31) and defects of both
glucose transport and phosphorylation in patients with type 2 diabetes
mellitus (DM) (4). Moreover, studies with magnetic resonance
spectroscopy of human skeletal muscle have found reduced glucose
6-phosphate in type 2 DM during insulin-stimulated conditions (30),
suggesting an important impairment at either transport or
phosphorylation or, potentially, a combined impairment.
One of the classic approaches to in vitro studies of glucose transport
and phosphorylation in skeletal muscle has been to use a
deoxy-D-glucose analog, the
metabolism of which is largely blocked distal to phosphorylation (14).
Tracer amounts of radiolabeled deoxy-D-glucose have also been
used for in vivo animal studies, but this approach does not facilitate
measuring the kinetics of transport and phosphorylation due to a need
for measuring the time course of tissue activity (14). The technology
of emission imaging of the positron-emitting glucose analog
2-deoxy-2-[18F]fluoro-D-glucose
([18F]FDG) does enable
acquisition of dynamic patterns (i.e., time course of tissue activity)
in a relatively noninvasive manner. Positron emission tomography (PET)
has been used for animal (27) and human investigations (17, 20, 29) of
skeletal muscle glucose metabolism. Dynamic PET imaging denotes
uninterrupted imaging of the target organ or tissue after a bolus
radiotracer injection, so that a tissue-time activity curve can be
determined. From these data, physiological modeling, with a
three-compartmental model of
[18F]FDG metabolism
(15, 16, 34), can be employed to derive rate constants for glucose
transport and phosphorylation. In our initial application of this
methodology, the rate constants for glucose transport and
phosphorylation were ascertained for skeletal muscle in response to a
single dose of insulin infusion in lean, obese, and type 2 diabetic
volunteers (20). In lean subjects, insulin stimulated an increase in
the rate constants for both glucose transport and phosphorylation.
Compared with the lean subjects, obese nondiabetic subjects had a
reduction in the insulin response of the transport rate constant,
whereas obese subjects with type 2 DM had reduced insulin activation of
the rate constants for both transport and phosphorylation.
The dose-response effects of insulin on the regulation of glucose
transport and phosphorylation in humans to our knowledge have not been
studied. The current study was undertaken with a relatively novel
application of PET imaging to more fully examine the effects of insulin
on the regulation of glucose transport and phosphorylation in skeletal
muscle of healthy lean volunteers. During steady-state metabolic
conditions at four rates of euglycemic insulin infusion, dynamic PET
imaging of skeletal muscle was performed and compartmental modeling of
[18F]FDG metabolism
was used to derive values for rate constants for glucose transport and
phosphorylation. The three-compartmental model entails a plasma
compartment, a tissue compartment for free [18F]FDG, and a tissue
compartment for phosphorylated
[18F]FDG and
first-order rate constants for forward and reverse transport and
phosphorylation. The individual rate constants can be used to estimate
steady-state parameters for the volume of distribution between
nonphosphorylated
[18F]FDG in tissue and
plasma and also to calculate the phosphorylation fraction, which is a
parameter reflecting the disposition of
[18F]FDG for
phosphorylation or efflux from tissue to plasma (12). From the
individual rate constants, an overall parameter for tissue utilization
of [18F]FDG can also
be calculated. To place the
[18F]FDG data and the
rate constants within context, we simultaneously measured steady-state
rates of glucose metabolism by leg tissues with the arteriovenous limb
balance method (40).
 |
MATERIALS AND METHODS |
Subjects. Eighteen nonobese,
glucose-tolerant subjects were recruited by advertisement and randomly
assigned to euglycemic insulin infusion studies at rates of 0 (n = 4), 20 (n = 4), 40 (n = 6), and 120 (n = 4)
mU · m
2 · min
1.
Subjects were 35 ± 2 (means ± SE) yr old, had a mean body mass index of 24.6 ± 0.6 kg/m2, and
had mean fasting plasma insulin of 5 ± 1 µU/ml. There were no
significant differences across groups for these characteristics. Fourteen of the volunteers were male. Before participating in this
study, each volunteer had a medical examination, and those found to be
in good general health with stable weight and normal hematologic,
renal, thyroid, and hepatic function and not taking chronic medication
were invited to participate after giving informed consent. The
University of Pittsburgh Institutional Review Board approved this investigation.
Insulin infusion and leg balance
studies. Subjects were admitted to the University of
Pittsburgh General Clinical Research Center on the evening before
studies, having been previously instructed to ingest a diet containing
at least 200 g carbohydrate for at least 3 days before studies and to
refrain from exercise on the preceding day. Subjects received a dinner
of a standard composition (10 kcal/kg; 50% carbohydrate, 30% fat, and
20% protein) on the evening of admission and then fasted overnight.
PET-imaging studies of
[18F]FDG uptake into
mid-thigh skeletal muscle were performed at the University of
Pittsburgh Positron Emission Tomography Center. On the morning of a
study, at ~7 AM, an intravenous catheter was placed in an antecubital
vein for infusion of insulin and glucose and for injection of
[18F]FDG. To obtain
the arterial samples for determination of
[18F]FDG in plasma (to
be used as an input function for the compartmental modeling of tissue
uptake), a catheter was placed in a radial artery. For limb balance
determinations across the leg, a catheter was placed in a femoral vein.
After basal measurements of arterial insulin and arterial and femoral
venous glucose, insulin infusions were begun. During insulin infusions,
arterial glucose was measured at 5-min intervals and an infusion of
20% dextrose was adjusted to maintain euglycemia. Femoral venous
glucose was measured every 30 min, increasing to every 10 min during
PET imaging. Plasma glucose was measured with a YSI glucose analyzer,
(Yellow Springs, OH). Arterial samples for later determination of
plasma insulin concentration with a RIA were obtained every 30 min.
Euglycemic insulin infusion was maintained for 3 h before the start of
dynamic PET imaging, so that steady-state metabolic conditions would
prevail and be maintained during PET imaging. Blood flow to the leg was measured with venous occlusion strain-gauge plethysmography, as previously described (9), and was obtained before PET imaging was initiated.
PET image acquisition. Subjects were
positioned in the PET scanner so that the mid-thigh corresponded to the
midpoint axial field-of-view. Before each emission scan, a 20-min
transmission scan was performed with rotating rods of
68Ge/68Ga
to correct the emission data for photon attenuation. An intravenous injection of 4 mCi of
[18F]FDG, synthesized
with a modification of the Hamacher method (13), was injected and a
90-min dynamic PET scan was simultaneously initiated (19 frames: 4 × 30 s, 4 × 2 min, 6 × 5 min, 5 × 10 min). The
PET scans were acquired in two-dimensional and three-dimensional imaging modes with a Siemens CTI 951 R/31
(n = 10) scanner and an ECAT ART
scanner (n = 8), respectively. The
imaging characteristics of the two scanners were comparable. The
Siemens 951R/31 scanner acquired 31 imaging planes simultaneously
[two-dimensional, in-plane resolution 6.0 mm FWHM (ramp filter),
axial slice width: 3.4 mm], whereas 47 imaging planes were
acquired with the ECAT ART scanner [three-dimensional, in-plane
resolution 6.0 mm FWHM (ramp filter), axial slice width: 3.4 mm].
The scatter fraction was low for the two-dimensional Siemens CTI 951 (13%; Ref. 2), and no scatter correction was performed after
conventional methods. The three-dimensional ART had a scatter fraction
that was ~37% (1), and these emission data were corrected for
scattered photons with a model-based correction method (37). After
correction of the PET data for radioactive decay, the tissue
time-activity data were converted to units of radioactivity
concentration (µCi/ml) with an empiric phantom-based calibration
factor (µCi/ml of PET counts/pixel).
Plasma input function. Sampling of
arterial blood for plasma
[18F]FDG radioactivity
began simultaneously with PET scanning. Arterial samples were obtained
at 6-s intervals for 2 min, 20-s intervals for 1 min, 30-s intervals
for 1 min, at 5, 7, 10, 15, 20 and 30 min, and then every 15 min until
90 min postinjection of
[18F]FDG. Exact timing
of each sample was recorded. Blood was centrifuged, and 200 µl of
plasma were removed for assay of plasma radioactivity concentration
with a Packard Canbarra well counter. The counts per minute value for
each sample was corrected for radioactive decay and converted to units
of µCi/ml based on the well-counter sensitivity.
Defining regions of interest in skeletal
muscle. To more clearly define skeletal muscle on PET
images, three cross-sectional computed tomography (CT) scans of 1-cm
thickness were obtained at upper, mid, and lower boundaries of the
region of mid-thigh to be scanned during PET imaging. These CT images
were coregistered with the matching PET transmission images as
previously described (20). Regions of interest (ROIs) were drawn in
medial and lateral thigh muscle with Sunview (CTI PET Systems) software
and saved as template files for application to PET images of
[18F]FDG. The ROIs
were applied to the dynamic PET scans and integrated and expressed as
mean counts per pixel.
Modeling of PET data. Data of the
time-activity curves of skeletal muscle
[18F]FDG imaging were
analyzed with a three-compartmental model (15, 16, 34). The
three-compartmental model is an analytic method applied to the entire
dynamic pattern of tissue activity, beginning from the point of
[18F]FDG injection.
Specific model equations are implemented and nonlinear least squares
curve-fitting methods are used to determine individual kinetic
parameters that correspond to the transport and metabolism of
[18F]FDG.
Compartmental modeling, with the dynamically acquired PET data with the
arterial plasma time course of
[18F]FDG activity
(CP) as a model input function,
employed a nonlinear least squares method to iteratively derive values
for the individual rate constants:
k1
(ml · min
1 · ml
1),
k2
(min
1), and
k3
(min
1). The rate
constants represent inward transport
(k1), outward transport (k2),
and phosphorylation
(k3) of
[18F]FDG as shown in
the equation
Dephosphorylation of
2-deoxy-2-[18F]fluoro-D-glucose-6-phosphate
([18F]FDG-6-P),
represented by the parameter
k4
(min
1), is often assumed
to be negligible during the relatively brief duration of emission
studies (10), although in the current study a fixed or zero value for
k4 was not employed.
After administration of
[18F]FDG, the total
[18F]FDG tissue
concentration (Ci) is the sum of
the free [18F]FDG
(CE) and
[18F]FDG-6-P
(CM) skeletal muscle
concentrations, and is expressed for each PET scan at time
(t) as:
This model assumes that the arterial blood volume is
negligible. In the present work, a vascular volume term
(VV) was incorporated into this
model as Ci
(t) = CE
(t) + CM
(t) + (VV)(CP),
and the values obtained were likewise exceedingly small and did not
differ by insulin dose. According to the compartmental model shown
above, the time derivatives of the skeletal muscle concentrations can be expressed in terms of the compartmental transport parameters, k1 through
k4, and
[18F]FDG in plasma,
CP (16, 33)
|
(1)
|
and
|
(2)
|
The solutions to the model equations are based on the Laplace
transform method (6) and are given below (16)
|
(3)
|
|
(4)
|
where
X denotes the operation of convolution and
The kinetic parameters (ki)
were determined with iterative curve fitting and the minimization
method of Marquardt (26). The validity of discrimination of the
individual kinetic parameters was supported by the standard error
values that were determined with the estimated covariance matrix of the
fitted parameters. Occasionally the errors for the individual kinetic parameters exceeded 50%, but the level of error was reduced when the
individual rate constants were combined to calculate the additional combined parameters described in the next paragraph. In
the present work, computer-simulation experiments were performed to
examine the impact of insulin on the kinetics of free
(CE), phosphorylated (CM), and total
(Ci)
[18F]FDG
concentrations in skeletal muscle with
Eq. 3
and 4, with a group mean of the
kinetic parameters and the arterial input function data for each
insulin dose.
With the use of the individual kinetic parameters, three additional
combined parameters were calculated that correspond to the distribution
volume (DV) of free (nonphosphorylated)
[18F]FDG
(DVCE = k1/k2,
ml/ml), the phosphorylation fraction (PF) of
[18F]FDG [PF = k3/(k2 + k3)],
and the overall uptake rate of
[18F]FDG
[K = (k1 × k3)/(k2 + k3),
ml · min
1 · ml
1].
The DVCE parameter reflects the distribution of
free [18F]FDG in
skeletal muscle relative to plasma and indicates to what extent free
[18F]FDG is available
in the tissue precursor pool (15). An increase in
DVCE would indicate an increase in
the availability of free [18F]FDG within
skeletal muscle. The PF is a fraction with a potential range of
0-1, reflecting the disposition for nonphosphorylated [18F]FDG within the
tissue compartment to be phosphorylated (as
k3 > k2) or to
egress from the tissue compartment back to the plasma compartment. It
has been further interpreted as an index of the extent to which glucose
phosphorylation vis a vis glucose transport serves as the rate-limiting
step of glucose metabolism (12). For example, if
k3
k2, then the
value for PF approaches 1, indicating that phosphorylation occurs much
more readily than efflux of nonphosphorylated glucose, and thus rates
of glucose metabolism would be limited by glucose availability within
tissue (i.e., transport) rather than by glucose phosphorylation.
Conversely, if k3
k2, then PF
would approach 0, indicative that the hexokinase (HK) reaction poses a
limitation on rates of glucose metabolism.
Application of this three-compartmental model is based on several
assumptions, which are 1) that
[18F]FDG is
administered in trace amounts, 2)
that glucose metabolism is in steady state,
3) that transport of
[18F]FDG and
[18F]FDG-6-P
between compartments have first-order kinetics, and 4) that arterial plasma glucose
concentration is constant (16). In addition, the model assumes that
compartments are of homogenous composition and that arterial
concentrations approximate mean capillary concentrations (16).
Statistics. Data are expressed as
means ± SE. ANOVA, and when appropriate Kruskal-Wallis tests were
used to examine for the effects of insulin on the various metabolic
parameters [e.g., leg glucose uptake (LGU) and
K] with
P < 0.05 considered significant. Linear regression and step-wise regression were used to examine potential correlation among variables.
 |
RESULTS |
Glucose uptake across the leg and systemic insulin
sensitivity. Basal and insulin-stimulated values for
the arteriovenous fractional extraction of glucose across the leg,
rates of glucose uptake across the leg (LGU), and rates of exogenous
glucose infusion needed to maintain euglycemia are shown in Table
1. Insulin stimulated a significant
increase in the fractional extraction of glucose, increasing this value
by ~20-fold across the dose range of insulin rates. Similar changes
were observed for rates of LGU, and there was a significant correlation
between LGU and respective rates of exogenous glucose infusion
(r = 0.68, P < 0.01).
Rate constants from modeling tissue activity of
[18F]FDG in skeletal
muscle. The rate constant
K, reflecting net utilization of
[18F]FDG from the
arterial compartment into skeletal muscle of the mid-thigh, was
determined by the three-compartmental modeling method. Compared with
values for K in the absence of insulin
infusion, values for K during insulin
infusions increased ~10-fold (P < 0.001) and were significantly correlated with rates of LGU
(r = 0.72, P < 0.01).
Rate constants for glucose transport and
phosphorylation. Representative examples of
time-activity curves and model fits are shown in Fig.
1. The mean values for individual rate
constants and for the parameters of the distribution volume of
nonphosphorylated [18F]FDG and the
phosphorylation fraction are shown in Table
2. Values for
k1 and
k2 did not change
significantly in response to insulin, although the
DVCE did increase significantly
compared with basal. The relatively large SE for the
DVCE shown in Table 2 reflects the
wide interindividual variation in this parameter. However, the ability
of the model to predict DVCE was
robust, with a mean within-subject error of 28% (excluding 2 outliers). Likewise, insulin significantly increased values for
k3 (the rate constant for phosphorylation) and for PF compared with basal. The
effect of insulin on the PF revealed a clear dose-response pattern of
increase. The fraction of
[18F]FDG within the
tissue compartment that was phosphorylated increased from 0.11 ± 0.02 during basal conditions to 0.74 ± 0.12 during the infusion of
insulin at 120 mU/m2. Values
obtained for k4
were negligible (0.004-0.013
min
1) across insulin
doses.

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Fig. 1.
Representative examples of time-activity curves and model fits at basal
(0 insulin) and under insulin-stimulated (120 U) conditions. Observed
( ) and estimated (solid line) values are shown. Units for skeletal
muscle 18F are in µCi/ml.
Fluoro-D-glucose,
FDG.
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Table 2.
Rate constants from three-compartmental modeling of dynamic positron
emission tomography of [18F]FDG metabolism in
skeletal muscle
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On the basis of the mean values of the rate constants at each insulin
infusion rate and the time course of tissue activity within skeletal
muscle, the concentrations of nonphosphorylated [18F]FDG
(CE) and phosphorylated
[18F]FDG
(CM) were calculated from
Eqs.
3 and 4 and are depicted graphically in Fig.
2. On the basis of the observed increase in the phosphorylation fraction in response to insulin, a progressive increase in phosphorylated
[18F]FDG was observed
across insulin doses. In contrast, the relative proportion of
nonphosphorylated
[18F]FDG appeared to
rise and then fall across insulin doses, reflecting the pattern
observed for k1
and the DVCE.

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Fig. 2.
Computer-generated simulations of tissue concentrations of
nonphosphorylated
[18F]FDG
(CE; ), phosphorylated
[18F]FDG
(CM; ), and total tissue
[18F]FDG
(CE + CM; ) at each insulin dose,
calculated with mean values of rate constants (Table 2) and plasma
data.
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Relation of rate constants to LGU. To
examine the extent to which the rate constants derived from
compartmental modeling corresponded to the patterns of
insulin-stimulated glucose metabolism in skeletal muscle, as determined
by the collateral leg balance studies of true glucose metabolism,
regression analysis was performed with these two sets of independently
measured parameters. The correlations between rate constants for
[18F]FDG and the
independent measures of fractional extraction of glucose across the
leg, blood flow, or rates of LGU are shown in Table
3. The fractional extraction of glucose
across the leg bore a significant correlation with
k2 and
k3, as well as
with the DVCE, but the strongest correlation was
with PF, as shown in Fig. 3. For leg blood
flow, only the inward transport rate constant,
k1, had a
significant correlation as opposed to no relationship between leg blood
flow and rate constants reflecting later time points. For LGU, both the
k1-to-k2
ratio and PF had strong positive correlations of similar magnitude,
whereas the k2
rate constant had a modest negative correlation.
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Table 3.
Correlations between rate constants for [18F]FDG
transport and phosphorylation determined by dynamic positron emission
tomography and leg balance across all insulin levels
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Fig. 3.
Scatterplot of relationship between fractional extraction of glucose
across leg and phosphorylation fraction of
[18F]FDG.
k2, Outward
transport; k3,
phosphorylation.
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With the use of step-wise multivariate regression analysis with
fractional extraction of glucose as the dependent variable, after
inclusion of PF (r = 0.86, P < 0.001), the
k1-to-k2
ratio added a slight amount of additional significance
(r = 0.89, P < 0.001). With the use of LGU as
the dependent variable, the
k1-to-k2 ratio was the strongest simple correlate
(r = 0.74, P < 0.001), and after adjusting for
this, the rate constant
k3 added
substantial additional significance (F = 20.7, P < 0.001), and this model (k1-to-k2
ratio and k3,
together) accounted for 84% of the variance in LGU. This model
suggests that partitioning of free nonphosphorylated [18F]FDG from plasma
to muscle, and the efficiency with which it phosphorylated, account for
most of the variance in insulin-stimulated glucose metabolism in
skeletal muscle.
 |
DISCUSSION |
There is considerable evidence that glucose transport is a key point of
control for glucose metabolism within skeletal muscle (3, 18, 19), yet
there are also data suggesting that control of insulin-stimulated
glucose metabolism is distributed to additional steps (4, 11, 20, 23,
30, 39). The current study was undertaken to test the hypothesis that
insulin modulates the relative importance of glucose transport and
phosphorylation as points of control over glucose metabolism in
skeletal muscle. To examine insulin regulation of the interaction
between glucose transport and phosphorylation within skeletal muscle in
healthy volunteers, dynamic PET was used to image muscle metabolism of the deoxyglucose analog
[18F]FDG. The tissue
time-activity patterns were analyzed with a compartmental physiological
model to derive rate constants for transport and phosphorylation. The
principal findings are that insulin increases both the distribution
volume for glucose within muscle and the efficiency with which glucose
is phosphorylated, that each effect is strongly related to
insulin-stimulated glucose metabolism, and that interaction between
these steps, although evident across the dose range of insulin
stimulation, is modulated in a dynamic manner by insulin.
Recent studies (4, 30), including one from our laboratory with dynamic
PET and [18F]FDG (20),
implicate defects at both glucose transport and glucose phosphorylation
within insulin-resistant skeletal muscle in individuals with type 2 DM.
If impediments at each step do contribute to insulin resistance, then
this raises anew the question of how insulin might affect the
interaction between these two interdependent proximal steps of glucose
metabolism. The step of glucose phosphorylation, catalyzed by HK,
serves to trap glucose within muscle, and this serves to sustain a
favorable gradient for the movement of glucose across the sarcolemma
(38). Prior animal studies, with single muscle fiber analysis, indicate
strong coregulation in expression and activity of GLUT-4 and HK II
(22). Transgenic studies of overexpression of HK II in skeletal muscle indicate that increased HK II enhances insulin-stimulated glucose metabolism, although the effects are relatively modest and not discernible during fasting conditions (7). Overexpression of GLUT-4
within skeletal muscle in transgenic animals leads to enhanced rates of
glucose utilization (24), whereas a combined overexpression of GLUT-4
and HK II improves insulin sensitivity but not absolute rates of
glucose metabolism (25). Thus it would seem that the effects of
enhanced glucose transport capacity are more clearly discernible than
is an impact of increased HK II.
In the current study, the rate constant for glucose phosphorylation
increased progressively in response to increasing insulin concentrations. This is consistent with, and extends further, our
previous PET studies in which the effect of a single rate of insulin
infusion was compared with basal conditions (20). Our present findings
of insulin activation of the efficiency of glucose phosphorylation are
also consistent with findings from a forearm tracer method developed to
investigate insulin regulation of transport and phosphorylation (4,
31). In the current study, the phosphorylation fraction during basal
conditions was ~10%, indicating a relatively inefficient net
retention of free glucose. At the highest rate of insulin infusion
examined in our study (120 mU · m
2 · min
1),
which achieved circulating insulin levels substantially higher than are
attained during usual conditions of daily living, the phosphorylation
fraction increased to ~75%. This high efficiency of glucose
phosphorylation suggests that during maximal insulin stimulation
virtually all glucose entering muscle would undergo phosphorylation.
Thus further increases in rates of intracellular glucose metabolism
would require greater transport of additional free glucose. Yet, it is
also important to emphasize that between the two extremes of fasting
and maximal (or near-maximal) insulin stimulation, the phosphorylation
fraction at physiological levels of insulin stimulation (as attained
with insulin infusions of 20 and 40 mU · m
2 · min
1)
had values of 40 and 60%, respectively. Our interpretation is that
HK-mediated glucose phosphorylation does contribute to the control of
insulin-stimulated glucose metabolism in skeletal muscle and that this
contribution may be of particular importance within physiological
levels of insulin stimulation.
In addition to these data on the effects of insulin on glucose
phosphorylation, the current study reaffirms the crucial importance of
insulin-stimulated glucose transport. Insulin had a robust effect to
increase the volume of distribution of nonphosphorylated [18F]FDG within
skeletal muscle. This finding is indicative of a strong effect of
insulin to enhance glucose transport. Within the current study, in
relating PET-imaging data to rates of muscle glucose metabolism
measured by arteriovenous leg balance methods, the strongest predictor
(r = 0.74, P < 0.001) of LGU was the volume of
distribution of nonphosphorylated
[18F]FDG. Thus, the
availability of glucose as achieved by the process of glucose transport
is clearly an important control point across the range of insulin
doses. It is of interest, however, that a clear dose-response effect of
insulin was not observed to increase the rate constant for glucose
transport or the volume of distribution of free glucose in muscle
tissue. One explanation might be that different individuals were
studied at the various insulin doses, rather than the same subjects
across the entire dose range. Our approach, although introducing
potentially confounding effects of interindividual variation in insulin
sensitivity, was largely dictated by the rigors of the experimental
design that entailed not only PET imaging but also leg balance studies.
Another explanation is that insulin stimulates transport but achieves a
plateau effect at relatively modest insulin concentrations and that
subsequent steps of metabolism, such as phosphorylation, modulate
whether the increase in glucose transport is carried through to
increased rates of glucose metabolism. This is essentially the
hypothesis being tested in the current study, and the patterns of
muscle free glucose concentrations estimated by the modeling of dynamic PET imaging are consistent with this concept. As the insulin doses increase from infusion rates of 20 to 40 and then to 120 mU · m
2 · min
1,
the estimated muscle free glucose concentration declines, and the rate
of increase in phosphorylated glucose increases. This suggests that the
higher rates of metabolized glucose (as reflected by phosphorylated
glucose) derive not only from availability of free glucose but also
from the efficiency with which glucose is phosphorylated and that
insulin modulates the interplay of these steps in a dynamic manner.
Thus, at progressively higher levels of insulin stimulation, the share
of each step in the control of metabolism is shifted and realigned.
Additional evidence, albeit inferential, is that in multivariate
regression analysis, with LGU as the dependent variable, the PET
parameters of transport and phosphorylation contributed independently
to account for ~80% of the variance in rates of glucose metabolism
by skeletal muscle. This is a robust relationship, and it indicates
both the crucial level of regulation over insulin-stimulated skeletal
muscle glucose metabolism that is posited at these two proximal steps
and the strong interaction between these two steps of glucose metabolism.
The three-compartmental model used in the current study was originally
developed by Sokoloff et al. (34) to investigate cerebral glucose
metabolism, and does not employ any tissue-specific constants or
coefficients. A three-compartmental model has been widely used to study
glucose metabolism in myocardium (8, 28, 29, 36), and data suggest that
in myocardium, the control point for glucose metabolism may shift from
transport toward phosphorylation under the influence of insulin (5). As
this model has not been widely used to investigate skeletal muscle (20,
32), we also sought in the current study to carry out collateral
methods to place the findings within a broader context. As reported
previously (20, 21), and described above, there was substantial
correlation between rates of
[18F]FDG metabolism by
skeletal muscle and rates of actual glucose metabolism. With respect to
the individual rate constants, there was also strong relation to other
parameters of glucose metabolism ascertained by leg balance methods and
in a pattern that would be logical to expect. The phosphorylation
fraction, a modeling parameter representing the efficiency with which
skeletal muscle traps glucose, was strongly correlated with
arteriovenous glucose differences, a parameter that also represents the
net trapping of glucose within tissue. In addition, there was a
significant correlation between rates of blood flow (measured by venous
occlusion plethysmography) and values for the inward transport rate
constant (k1),
the latter a parameter signifying movement from the plasma compartment
to tissue. This is a parameter that is conceptually dependent on rates
of flow and is a finding similar to compartmental modeling studies in
cerebral tissue and myocardium (15). A recent PET study of skeletal
muscle flow and glucose metabolism has found that skeletal muscle
uptake of [18F]FDG
spatially colocalizes with insulin-stimulated blood flow (35). In a
separate report, we recently presented data on the effect of insulin on
the skeletal muscle "lumped constant," the parameter that
represented the quantitative relation between metabolism of
[18F]FDG and that of
actual glucose (21). Briefly, these measurements indicate a mean value
for the lumped constant of ~1.2, and an effect of insulin to modulate
the lumped constant was not observed (21). It is of course axiomatic
that all physiological models, regardless of their complexity or
simplicity, and the three-compartmental model that is a relatively
simple model, are imperfect. Furthermore, it is difficult to fully
validate parameters that are otherwise difficult to attain, notably the
parameters of in vivo glucose transport and phosphorylation in human
skeletal muscle. The relation of the rate constants determined within
the current study to values obtained by the classic and independently
measured limb balance method represents progress in this direction and
reflect positively on the potential of emission tomography to provide
unique data on the spatial mapping of metabolism in humans. Future
studies will examine the robustness of kinetic parameters under basal vs. insulin-stimulated conditions to characterize under which conditions the rate constants are optimally described.
In summary, the findings of the current study indicate that insulin
stimulates both glucose transport and its phosphorylation within
skeletal muscle. The effect of insulin to increase the availability of
glucose is a key determinant of rates of insulin-stimulated glucose
metabolism, yet our findings suggest that transport is not the sole
locus of control over rates of insulin-stimulated glucose metabolism.
The present findings indicate that insulin also modulates the
efficiency of glucose phosphorylation. During basal conditions, the
efficiency of glucose phosphorylation is quite low, as represented by a
phosphorylation fraction of ~10%, and this appears to increase in a
step-wise manner across the range of insulin stimulation. At moderate
levels of insulin stimulation, the efficiency of the phosphorylation
fraction is ~50%, whereas at near-maximal insulin stimulation, there
is a higher degree of efficiency for glucose phosphorylation. This
dynamic response of the efficiency of glucose phosphorylation across
the dose range of insulin stimulation is consistent with an important
role in modulating insulin-stimulated glucose metabolism within
skeletal muscle. In conclusion, physiological modeling of dynamic
emission tomography of insulin-stimulated
[18F]FDG metabolism in
skeletal muscle indicates distributed control between the steps of
glucose transport and phosphorylation in the regulation of glucose
metabolism. Further application of these methods could be important in
better understanding dysregulated patterns of glucose metabolism within
insulin- resistant skeletal muscle.
 |
ACKNOWLEDGEMENTS |
We are grateful to our research volunteers and for the nursing,
dietary, and technical staff support at the General Clinical Research
Center and the Positron Emission Tomography Center of the University of
Pittsburgh. We would also like to acknowledge the technical expertise
of Sue Andreko and Janice Beattie.
 |
FOOTNOTES |
These studies were supported by a Veterans Affairs Merit Award (D. E. Kelley), the University of Pittsburgh General Clinical Research Center
(2MO1 RR00056-36), and a National Institutes of Health Research
Training in Diabetes and Endocrinology Grant (2T32 DK-07052-22, K. V. Williams).
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: D. E. Kelley,
Associate Professor of Medicine, Univ. of Pittsburgh School of
Medicine, Division of Endocrinology and Metabolism, E-1140 Biomedical
Science Tower, Pittsburgh, PA 15261 (E-mail:
kelley{at}med1.dept-med.pitt.edu).
Received 6 January 1999; accepted in final form 15 April 1999.
 |
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