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Dynamic PET Imaging Reveals Heterogeneity of Skeletal Muscle Insulin Resistance Jason M. Ng, Alessandra Bertoldo, Davneet S. Minhas, Nicole L. Helbling, Paul M. Coen, Julie C. Price, Claudio Cobelli, David E. Kelley, and Bret H. Goodpaster
Purpose: Skeletal muscle insulin resistance (IR) often precedes hyperglycemia and type 2 diabetes. However, variability exists within different skeletal muscle types and can be influenced by 3 primary steps of control: glucose delivery, transport, and phosphorylation. We performed dynamic positron emission tomography imaging studies to determine the extent to which heterogeneity in muscle type and control of insulin action contribute to IR. Methods: Thirteen volunteers from normal weight to obese underwent dynamic positron emission tomography imaging of [15O]H2O, [11C]3-O-methylglucose, and [18F]fluorodeoxyglucose, measuring delivery, transport, and phosphorylation rates, respectively, in soleus and tibialis anterior muscle during a hyperinsulinemic-euglycemic clamp. Subjects were classified as insulin-sensitive (IS) or insulin-resistant (IR) based on the median systemic glucose infusion rate needed to maintain euglycemia. Results: In soleus, transport kinetic rates were significantly higher (P ⬍ .05) in IS (0.126 ⫾ 0.028 min⫺1) vs IR (0.051 ⫾ 0.008 min⫺1) subjects. These differences were not as evident in tibialis anterior. These differences were paralleled in overall insulin-stimulated tissue activity, higher in IS (0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1) vs IR (0.011 ⫾ 0.002 mL 䡠 cm3 䡠 min⫺1) in soleus (P ⬍ .05), without significant differences in tibialis anterior. No significant differences were observed for either muscle in delivery or phosphorylation. Both muscle types displayed a control shift from an even distribution among the steps in IS to transport exerting greater control of systemic insulin sensitivity in IR. Conclusion: Lower glucose transport rates are the major feature underlying IR preceding type 2 diabetes, although substantial heterogeneity in insulin action across muscle types highlight the complexity of skeletal muscle IR. (J Clin Endocrinol Metab 99: E102–E106, 2014)
S
keletal muscle is the major site for insulin-stimulated glucose disposal in humans after a meal and is controlled by 3 steps: delivery, transport, and phosphorylation (1, 2). Previous studies have reported glucose transport and impairment of phosphorylation in insulin resistance (IR) and type 2 diabetes mellitus (T2DM) (3– 6). It is known that muscle IR can develop in obesity before
T2DM, and IR is not uncommon among normal-weight persons, termed the lean but metabolically obese phenotype (4, 5, 7). Understanding skeletal muscle IR is complicated by skeletal muscle group fiber heterogeneity (oxidative type 1 and glycolytic type 2) and potentially multiple sites for metabolic control, and this has been challenging to deci-
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2014 by The Endocrine Society Received May 1, 2013. Accepted October 15, 2013. First Published Online October 29, 2013
Abbreviations: BMI, body mass index; FDG, fluorodeoxyglucose; IR, insulin resistance; IS, insulin sensitivity; MR, magnetic resonance; OMG, O-methylglucose; PET, positron emission tomography; ROI, region of interest; T2DM, type 2 diabetes mellitus.
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J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
doi: 10.1210/jc.2013-2095
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Division of Endocrinology and Metabolism Department of Medicine (J.M.N., N.L.H., B.H.G.) and Departments of Radiology (D.S.M., J.C.P.) and Health and Physical Activity (P.M.C.), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15231; Department of Information Engineering (A.B., C.C.), University of Padova, Padova, Italy; and Merck, Sharp, and Dohme Corporation (D.E.K.), Rahway, New Jersey 07065
doi: 10.1210/jc.2013-2095
Materials and Methods Study design The study included 13 volunteers ranging from normal weight (n ⫽ 6; 4 females, 2 males) to overweight and obese (n ⫽ 7; 5 females, 2 males). The study protocol was previously described (3). Informed, written consent was obtained after the study was described in detail and all questions answered for all participants. Briefly, after an overnight fast, catheters were placed in an antecubital vein for insulin infusion, glucose infusion, and PET tracer injection and in a radial artery for blood sampling. After insulin initiation (40 mU 䡠 m⫺2 䡠 min⫺1), arterial glucose was measured every 5 minutes with a YSI glucose analyzer. An adjustable 20% dextrose infusion preserved euglycemia. PET images were acquired using an ECAT HR⫹ PET scanner (Siemens/CTI) in 3-dimensional imaging mode. Pliable block molding was used to support the legs, minimize motion, and maintain leg alignment during imaging. The final reconstructed PET image was 6 mm. The insulin infusion began 1 hour before any radiotracer injections. Radioactive tracers were injected in the following sequence: [15O]H2O, [11C]3-O-methylglucose (OMG), and [18F]fluorodeoxyglucose (FDG). The study design is presented in Supplemental Figure 1 (published on The Endocrine Society’s Journals Online website at http://jcem.endojournals.org). During the same week, a midcalf T1-weighted magnetic resonance (MR) imaging of skeletal muscle was conducted. The imaging methodology for this study is summarized in previous publications (3).
PET imaging data analysis MR images were used to generate regions of interest (ROI) on soleus and tibialis anterior muscle avoiding major vessels and bones of the lower leg. PET images were summed over the initial 15 minutes after the injection scanning period to emphasize and, consequently, avoid the blood component. PET and MR images were coregistered using previously described methods (8 –10). The ROI was applied to each frame across each leg omitting the proximal and distal 5 planes to reduce scatter influence and was applied to the soleus and tibialis anterior muscle groups in the thigh of each leg. Tracer activity within the ROI is tissue activity representing the tracer within the muscle. Tissue activity was converted to radioactivity concentrations (kilobecquerels per milliliter) using an empiric phantom-based calibration factor (kilobecquerels per milliliter per PET count per pixel). A representative illustration is shown in Supplemental Figure 2. Compartmental modeling was performed to
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quantify the physiological parameters describing skeletal muscle glucose delivery, transport, and phosphorylation using previously described methods (3) with the following significance: k1 is strongly related to capillary perfusion, k2 is proportional to outward perfusion; k3 is inward transmembrane transport for [11C]3-OMG, k4 is outward transmembrane transport for [11C]3-OMG, k5 is the phosphorylation rate constant, and K is overall fractional uptake.
Statistical analysis Data are expressed as a mean ⫾ SE unless otherwise indicated. ANOVA was used to examine differences between groups. A P value ⬍ .05 was considered significant. Spearman’s correlations were used to calculate correlations between variables.
Results The mean glucose infusion rate was 5.7 ⫾ 0.4 mg 䡠 min⫺1 䡠 kg⫺1 for all subjects, with a median of 6.4 mg 䡠 min⫺1 䡠 kg⫺1 and a significant difference (P ⬍ .05) between IR (4.3 ⫾ 0.4) and IS (7.0 ⫾ 0.3). The gender distribution was 4 female and 3 male IS subjects and 5 female and 1 male IR subject. The IS and IR groups were similar in age, fasting glucose, hemoglobin A1c, total cholesterol, and plasma triglycerides. Body mass index (BMI) was not significantly different. Clinical characteristics and kinetic estimates representing the steps of skeletal muscle glucose metabolism with insulin stimulation are shown as mean ⫾ SE with P values in Table 1. Glucose delivery, either inward (k1) or outward (k2), was not significantly different between IR and IS in either muscle group as determined by [15O]H2O (n ⫽ 11). Inward (k3) and outward (k4) transport was significantly higher in IS (0.126 ⫾ 0.028 minutes⫺1) vs IR (0.051 ⫾ 0.008 minutes⫺1) in soleus (P ⬍ .05), but significant differences in glucose transport kinetics were not observed in tibialis anterior as determined by [11C]3-OMG (IS, 0.071 ⫾ 0.018; IR, 0.057 ⫾ 0.010; P ⫽ .55). The fractional phosphorylation rate (k5) was not significantly different between IR and IS. The overall fractional uptake (K) was significantly higher in IS (0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1) in soleus muscle compared with IR (0.011 ⫾ 0.002) (P ⬍ .05). Tibialis anterior trended toward higher tissue activity (IR, 0.013 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1; IS, 0.017 ⫾ 0.001, P ⫽ .13) as determined by [18F]FDG. Kinetic values are shown in Figure 1. Control coefficients were determined to assess the influence each step had on skeletal muscle glucose metabolism under insulin stimulation (Figure 2), with a higher percentage indicating a higher level of control at that specific step. In both soleus and tibialis anterior, the control in IS was significantly different from IR, with more evenly distributed control (less control at transport and increased control at deliv-
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pher in humans (6). Positron emission tomography (PET) imaging allows for specific muscle group measurements of insulin sensitivity (IS) and has previously provided valuable information regarding glucose metabolism proximal control sites and skeletal muscle type heterogeneity in lean healthy adults (3). However, this methodology has not specifically been performed to evaluate the effects of IR. Using PET imaging to distinguish specific muscle groups, this study provides novel data regarding the IR effect on specific muscle fiber type heterogeneity in human skeletal muscle and the control distribution of insulin-stimulated glucose uptake before hyperglycemia or diabetes.
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J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
Table 1. Clinical Characteristics and PET-Derived Kinetic Measurementsa
a
Data are represented as mean ⫾ SE.
b
P ⬍ .05 represents a significant difference between IS and IR.
IR Group
P Value
43.7 ⫾ 2.9 86 ⫾ 2 5.3 ⫾ 0.1 189 ⫾ 13 109 ⫾ 29 24.0 ⫾ 1.8 7.0 ⫾ 0.3b
37.3 ⫾ 1.8 87 ⫾ 2 5.4 ⫾ 0.2 186 ⫾ 19 116 ⫾ 18 29.2 ⫾ 1.9 4.3. ⫾ 0.4
.1314 .9818 .5380 .8849 .8736 .1005 .0002
0.029 ⫾ 0.004 0.128 ⫾ 0.024
0.025 ⫾ 0.004 0.084 ⫾ 0.021
.5925 .2457
0.025 ⫾ 0.002 0.146 ⫾ 0.028 0.126 ⫾ 0.028b 0.041 ⫾ 0.005b
0.026 ⫾ 0.003 0.151 ⫾ 0.024 0.051 ⫾ 0.008 0.021 ⫾ 0.005
.8314 .9038 .0469 .0200
0.031 ⫾ 0.003 0.299 ⫾ 0.079 0.444 ⫾ 0.087b 0.008 ⫾ 0.001 0.025 ⫾ 0.003 0.017 ⫾ 0.001b
0.028 ⫾ 0.004 0.169 ⫾ 0.037 0.153 ⫾ 0.031 0.010 ⫾ 0.003 0.030 ⫾ 0.004 0.011 ⫾ 0.002
.5290 .2239 .0196 .6693 .3714 .0329
0.202 ⫾ 0.037 0.010 ⫾ 0.001b
0.219 ⫾ 0.037 0.006 ⫾ 0.001
.7657 .0236
0.022 ⫾ 0.002 0.108 ⫾ 0.021
0.022 ⫾ 0.003 0.094 ⫾ 0.037
.9945 .7913
0.018 ⫾ 0.001 0.051 ⫾ 0.005 0.071 ⫾ 0.018 0.055 ⫾ 0.012
0.020 ⫾ 0.002 0.097 ⫾ 0.024 0.057 ⫾ 0.010 0.029 ⫾ 0.005
.6378 .0924 .5490 .1166
0.027 ⫾ 0.003 0.134 ⫾ 0.049 0.291 ⫾ 0.058 0.013 ⫾ 0.002 0.025 ⫾ 0.003 0.017 ⫾ 0.001
0.027 ⫾ 0.004 0.211 ⫾ 0.037 0.324 ⫾ 0.064 0.012 ⫾ 0.003 0.028 ⫾ 0.003 0.013 ⫾ 0.001
.9025 .2804 .7334 .8803 .4740 .1291
0.253 ⫾ 0.035 0.009 ⫾ 0.001
0.203 ⫾ 0.029 0.007 ⫾ 0.001
.3512 .1506
ery; both P ⬍ .05) vs IR, which saw the inverse with much greater control at transport.
Discussion This PET imaging study revealed that across a range of normal-weight to obese subjects without diabetes, 1) glucose transport kinetic defects are principally affected with increasing IR, with less or no impairment in either glucose delivery
or phosphorylation; 2) transport defects are significantly more pronounced in soleus compared with tibialis anterior; 3) and in IS subjects, the control of glucose uptake is more evenly distributed among delivery and transport. In contrast, control of glucose transport has a stronger influence on glucose uptake in IR individuals. Previous studies are not entirely consistent with respect to which step is rate-limiting in skeletal muscle IR (11–14). Our novel data indicate that metabolically healthy IS persons disperse control more evenly among the key steps, with roughly
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Clinical characteristics Age, y Fasting glucose, mg/dL HbA1c. % Total cholesterol, mg/dL Triglycerides, mg/dL BMI Glucose infusion rate, mg/min 䡠 kg Kinetic parameters Soleus [15O]H2O (n ⫽ 11) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 [11C]3-OMG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 18 [ F]FDG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Glucose (n ⫽ 13) k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Tibialis anterior [15O]H2O (n ⫽ 11) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 [11C]3-OMG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 [18F]FDG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Glucose (n ⫽ 13) k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1
IS Group
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Figure 1. Glucose delivery (top), transport (middle), and phosphorylation (bottom) kinetics in soleus (left) and tibialis anterior (right) muscles. The graphs represent kinetic parameters for skeletal muscle glucose metabolism with insulin stimulation of 40 mU 䡠 m⫺2 䡠 min⫺1. Black bars represent IR, and white bars represent IS. *, P ⬍ .05.
equal control at delivery and transport in both muscle groups. However, with increasing IR, a dynamic shift occurs in which delivery control is lessened and transport control increased. This may explain findings from previous studies in which maximizing delivery did not improve skeletal muscle glucose uptake with increasing obesity (15). Our data support this concept, because systemic IS positively correlated with increasing delivery control (soleus, r ⫽ 0.61, P ⬍ .05; tibialis anterior, r ⫽ 0.86, P ⬍ .01) and negatively correlated with transport control (soleus, r ⫽ ⫺0.76, P ⬍ .01; tibialis anterior, r ⫽ ⫺0.82, P ⬍ .01). Our data also indicate that glucose transport is particularly impaired in specific skeletal muscle groups; transport in
soleus was strongly associated with IS (r ⫽ 0.83, P ⬍ .01), but this was not significant in tibialis anterior (r ⫽ 0.16, P ⫽ .60). This novel finding demonstrates specific muscle group heterogeneity in relation to IS and glucose transport. This could potentially be due to muscle fiber type differences. Previous studies have shown that fiber type is associated with IS (6, 16). Soleus and tibialis anterior muscles are composed of different proportions of type I and II muscle fibers, with soleus having more type I fibers than tibialis anterior. Therefore, a possible mechanism is that oxidative muscle with higher mitochondrial content (higher proportion of type I fibers) is more insulin-sensitive, with higher rates of glucose transport, than muscle groups with a more even distribution of type I and II muscle fibers (17, 18). Soleus is vital for plantarflexion (walking, running, and maintaining a standing posture), whereas tibialis anterior is involved in dorsiflexion (ankle stabilization). We postulate that differences in contractile activity patterns are related to the heterogeneity in IS and that this difference between IS and IR is magnified in more highly oxidative muscle. Additional studies are needed to determine the quantitative contributions of specific muscle types on systemic IS. Previous studies have shown links between increasing BMI and increasing IR (4, 7). Generally, our data agree with these observations with a negative correlation between increasing BMI and IS (r ⫽ ⫺0.57, P ⬍ .05). A novel observation, however, is that the IS group had significantly higher glucose transport and overall fractional uptake rates despite having a BMI that was only modestly (and not significantly) different. This observation confirms that IR is multifactorial in nature beyond just obesity. For example, potential differences in skeletal muscle IS in individuals of the same weight may partially explain the lean but metabolically obese phenotype that has been previously reported (5). Limitations of this study include ROI being estimates of whole organ/tissue metabolism through extrapolation rely-
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Figure 2. Control coefficient distribution under insulin stimulation. Black bars represent delivery, white bars represent transport, and gray bars represent phosphorylation. *, Significant difference between IS and IR (P ⬍ .05).
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Acknowledgments We gratefully acknowledge the efforts and cooperation of the research volunteers and support from the staffs at the University of Pittsburgh General Clinical Research Center, PET Center, and Endocrinology and Metabolism Research Center. Address all correspondence and requests for reprints to: Bret H. Goodpaster, PhD, Senior Investigator, Translational Research Institute for Metabolism and Diabetes, Florida Hospital and Sanford/Burnham Medical Research Institute, 301 East Princeton Street, Orlando, FL 32804. E-mail: [email protected]. This work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (DK-6055502), the University of Pittsburgh General Clinical Research Center (5MO1RR00056), and the Obesity and Nutrition Research Center (NIDDK P30-DK-46204).
Disclosure Summary: J.M.N., A.B., D.S.M., N.L.H., P.M.C., J.C.P., C.C., and B.H.G. have nothing to disclose. D.E.K. is currently employed by the Merck, Sharp, and Dohme Corporation.
References 1. Kelley DE, Reilly JP, Veneman T, Mandarino LJ. Effects of insulin on skeletal muscle glucose storage, oxidation, and glycolysis in humans. Am J Physiol. 1990;258:E923–E929. 2. Bonadonna RC, Saccomani MP, Seely L, et al. Glucose transport in human skeletal muscle. The in vivo response to insulin. Diabetes. 1993;42:191–198. 3. Bertoldo A, Pencek RR, Azuma K, et al. Interactions between delivery, transport, and phosphorylation of glucose in governing uptake into human skeletal muscle. Diabetes. 2006;55:3028 –3037. 4. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840–846. 5. Romero-Corral A, Somers VK, Sierra-Johnson J, et al. Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur Heart J. 2010;31:737–746. 6. James DE, Jenkins AB, Kraegen EW. Heterogeneity of insulin action in individual muscles in vivo: euglycemic clamp studies in rats. Am J Physiol. 1985;248:E567–E574. 7. Bogardus C, Lillioja S, Mott D, Reaven GR, Kashiwagi A, Foley JE. Relationship between obesity and maximal insulin-stimulated glucose uptake in vivo and in vitro in Pima Indians. J Clin Invest. 1984; 73:800 – 805. 8. Minoshima S, Berger KL, Lee KS, Mintun MA. An automated method for rotational correction and centering of three-dimensional functional brain images. J Nucl Med. 1992;33:1579 –1585. 9. Woods RP, Mazziotta JC, Cherry SR. MRI-PET registration with automated algorithm. J comput Assist Tomogr. 1993;17:536 –546. 10. Bertoldo A, Price J, Mathis C, et al. Quantitative assessment of glucose transport in human skeletal muscle: dynamic positron emission tomography imaging of [O-methyl-11C]3-O-methyl-D-glucose. J Clin Endocrinol Metab. 2005;90:1752–1759. 11. Bonadonna RC, Del Prato S, Bonora E, et al. Roles of glucose transport and glucose phosphorylation in muscle insulin resistance of NIDDM. Diabetes. 1996;45:915–925. 12. Cline GW, Petersen KF, Krssak M, et al. Impaired glucose transport as a cause of decreased insulin-stimulated muscle glycogen synthesis in type 2 diabetes. N Engl J Med. 1999;341:240 –246. 13. Bonadonna RC, Del Prato S, Saccomani MP, et al. Transmembrane glucose transport in skeletal muscle of patients with non-insulindependent diabetes. J Clin Invest. 1993;92:486 – 494. 14. Kelley DE, Mintun MA, Watkins SC, et al. The effect of non-insulin-dependent diabetes mellitus and obesity on glucose transport and phosphorylation in skeletal muscle. J Clin Invest. 1996;97:2705–2713. 15. Laine H, Yki-Jarvinen H, Kirvela O, et al. Insulin resistance of glucose uptake in skeletal muscle cannot be ameliorated by enhancing endothelium-dependent blood flow in obesity. J Clin Invest. 1998; 101:1156 –1162. 16. Coen PM, Dubé JJ, Amati F, et al. Insulin resistance is associated with higher intramyocellular triglycerides in type I but not type II myocytes concomitant with higher ceramide content. Diabetes. 2010;59:80 – 88. 17. Gollnick PD, Sjödin B, Karlsson J, Jansson E, Saltin B. Human soleus muscle: a comparison of fiber composition and enzyme activities with other leg muscles. Pflugers Arch. 1974;348:247–255. 18. Henriksson-Larsén KB, Lexell J, Sjöström M. Distribution of different fibre types in human skeletal muscles. I. Method for the preparation and analysis of cross-sections of whole tibialis anterior. Histochem J. 1983;15:167–178. 19. Kelley DE, Williams KV, Price JC, Goodpaster B. Determination of the lumped constant for [18F] fluorodeoxyglucose in human skeletal muscle. J Nucl Med. 1999;40:1798 –1804.
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ing on the lumped constant. However, previous PET studies have independently verified the validity of using the lumped constant in modeling of skeletal muscle (19). It is noted that reliance on any one radioactive tracer relies on mathematical modeling of that tracer to assess for differences. However, using multiple tracers allowed us to independently determine which steps were impaired as, for example, the transport impairment seen in both [11C]3-OMG and [18F]FDG of soleus muscle. We did not examine T2DM in this study. It is possible that more severe IR in T2DM could manifest in different or additional impairments in glucose metabolism and reveal different results in specific skeletal muscle group impairments. Another limitation to our study is the relatively small sample size, which precluded more sophisticated statistical analyses of gender or age, and a more robust linear regression of PETderived kinetic parameters across a broader range of subject characteristics. Although larger studies should be performed, these data highlight the heterogeneity in muscle glucose metabolism that contributed to IR. In summary, in a range of normal-weight to obese volunteers without diabetes, profound glucose transport defects were observed with increasing IR more clearly in specific skeletal muscle groups, eg, soleus muscle, that were not as evident in tibialis anterior. These transport defects are not explained by obesity alone. Dynamic shifts occur within the steps of skeletal muscle glucose metabolism from a fairly even distribution between delivery and transport to a transportpredominant model with increasing IR. These data suggest that the heterogeneity in skeletal muscle contributes to the variability in IR or that different muscle types are more or less susceptible to factors that cause IR. These dynamic PET imaging studies indicate the complexity of human skeletal muscle IR preceding T2DM.
J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
O N L I N E
B r i e f
R e p o r t — E n d o c r i n e
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Dynamic PET Imaging Reveals Heterogeneity of Skeletal Muscle Insulin Resistance Jason M. Ng, Alessandra Bertoldo, Davneet S. Minhas, Nicole L. Helbling, Paul M. Coen, Julie C. Price, Claudio Cobelli, David E. Kelley, and Bret H. Goodpaster
Purpose: Skeletal muscle insulin resistance (IR) often precedes hyperglycemia and type 2 diabetes. However, variability exists within different skeletal muscle types and can be influenced by 3 primary steps of control: glucose delivery, transport, and phosphorylation. We performed dynamic positron emission tomography imaging studies to determine the extent to which heterogeneity in muscle type and control of insulin action contribute to IR. Methods: Thirteen volunteers from normal weight to obese underwent dynamic positron emission tomography imaging of [15O]H2O, [11C]3-O-methylglucose, and [18F]fluorodeoxyglucose, measuring delivery, transport, and phosphorylation rates, respectively, in soleus and tibialis anterior muscle during a hyperinsulinemic-euglycemic clamp. Subjects were classified as insulin-sensitive (IS) or insulin-resistant (IR) based on the median systemic glucose infusion rate needed to maintain euglycemia. Results: In soleus, transport kinetic rates were significantly higher (P ⬍ .05) in IS (0.126 ⫾ 0.028 min⫺1) vs IR (0.051 ⫾ 0.008 min⫺1) subjects. These differences were not as evident in tibialis anterior. These differences were paralleled in overall insulin-stimulated tissue activity, higher in IS (0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1) vs IR (0.011 ⫾ 0.002 mL 䡠 cm3 䡠 min⫺1) in soleus (P ⬍ .05), without significant differences in tibialis anterior. No significant differences were observed for either muscle in delivery or phosphorylation. Both muscle types displayed a control shift from an even distribution among the steps in IS to transport exerting greater control of systemic insulin sensitivity in IR. Conclusion: Lower glucose transport rates are the major feature underlying IR preceding type 2 diabetes, although substantial heterogeneity in insulin action across muscle types highlight the complexity of skeletal muscle IR. (J Clin Endocrinol Metab 99: E102–E106, 2014)
S
keletal muscle is the major site for insulin-stimulated glucose disposal in humans after a meal and is controlled by 3 steps: delivery, transport, and phosphorylation (1, 2). Previous studies have reported glucose transport and impairment of phosphorylation in insulin resistance (IR) and type 2 diabetes mellitus (T2DM) (3– 6). It is known that muscle IR can develop in obesity before
T2DM, and IR is not uncommon among normal-weight persons, termed the lean but metabolically obese phenotype (4, 5, 7). Understanding skeletal muscle IR is complicated by skeletal muscle group fiber heterogeneity (oxidative type 1 and glycolytic type 2) and potentially multiple sites for metabolic control, and this has been challenging to deci-
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2014 by The Endocrine Society Received May 1, 2013. Accepted October 15, 2013. First Published Online October 29, 2013
Abbreviations: BMI, body mass index; FDG, fluorodeoxyglucose; IR, insulin resistance; IS, insulin sensitivity; MR, magnetic resonance; OMG, O-methylglucose; PET, positron emission tomography; ROI, region of interest; T2DM, type 2 diabetes mellitus.
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J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
doi: 10.1210/jc.2013-2095
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Division of Endocrinology and Metabolism Department of Medicine (J.M.N., N.L.H., B.H.G.) and Departments of Radiology (D.S.M., J.C.P.) and Health and Physical Activity (P.M.C.), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15231; Department of Information Engineering (A.B., C.C.), University of Padova, Padova, Italy; and Merck, Sharp, and Dohme Corporation (D.E.K.), Rahway, New Jersey 07065
doi: 10.1210/jc.2013-2095
Materials and Methods Study design The study included 13 volunteers ranging from normal weight (n ⫽ 6; 4 females, 2 males) to overweight and obese (n ⫽ 7; 5 females, 2 males). The study protocol was previously described (3). Informed, written consent was obtained after the study was described in detail and all questions answered for all participants. Briefly, after an overnight fast, catheters were placed in an antecubital vein for insulin infusion, glucose infusion, and PET tracer injection and in a radial artery for blood sampling. After insulin initiation (40 mU 䡠 m⫺2 䡠 min⫺1), arterial glucose was measured every 5 minutes with a YSI glucose analyzer. An adjustable 20% dextrose infusion preserved euglycemia. PET images were acquired using an ECAT HR⫹ PET scanner (Siemens/CTI) in 3-dimensional imaging mode. Pliable block molding was used to support the legs, minimize motion, and maintain leg alignment during imaging. The final reconstructed PET image was 6 mm. The insulin infusion began 1 hour before any radiotracer injections. Radioactive tracers were injected in the following sequence: [15O]H2O, [11C]3-O-methylglucose (OMG), and [18F]fluorodeoxyglucose (FDG). The study design is presented in Supplemental Figure 1 (published on The Endocrine Society’s Journals Online website at http://jcem.endojournals.org). During the same week, a midcalf T1-weighted magnetic resonance (MR) imaging of skeletal muscle was conducted. The imaging methodology for this study is summarized in previous publications (3).
PET imaging data analysis MR images were used to generate regions of interest (ROI) on soleus and tibialis anterior muscle avoiding major vessels and bones of the lower leg. PET images were summed over the initial 15 minutes after the injection scanning period to emphasize and, consequently, avoid the blood component. PET and MR images were coregistered using previously described methods (8 –10). The ROI was applied to each frame across each leg omitting the proximal and distal 5 planes to reduce scatter influence and was applied to the soleus and tibialis anterior muscle groups in the thigh of each leg. Tracer activity within the ROI is tissue activity representing the tracer within the muscle. Tissue activity was converted to radioactivity concentrations (kilobecquerels per milliliter) using an empiric phantom-based calibration factor (kilobecquerels per milliliter per PET count per pixel). A representative illustration is shown in Supplemental Figure 2. Compartmental modeling was performed to
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quantify the physiological parameters describing skeletal muscle glucose delivery, transport, and phosphorylation using previously described methods (3) with the following significance: k1 is strongly related to capillary perfusion, k2 is proportional to outward perfusion; k3 is inward transmembrane transport for [11C]3-OMG, k4 is outward transmembrane transport for [11C]3-OMG, k5 is the phosphorylation rate constant, and K is overall fractional uptake.
Statistical analysis Data are expressed as a mean ⫾ SE unless otherwise indicated. ANOVA was used to examine differences between groups. A P value ⬍ .05 was considered significant. Spearman’s correlations were used to calculate correlations between variables.
Results The mean glucose infusion rate was 5.7 ⫾ 0.4 mg 䡠 min⫺1 䡠 kg⫺1 for all subjects, with a median of 6.4 mg 䡠 min⫺1 䡠 kg⫺1 and a significant difference (P ⬍ .05) between IR (4.3 ⫾ 0.4) and IS (7.0 ⫾ 0.3). The gender distribution was 4 female and 3 male IS subjects and 5 female and 1 male IR subject. The IS and IR groups were similar in age, fasting glucose, hemoglobin A1c, total cholesterol, and plasma triglycerides. Body mass index (BMI) was not significantly different. Clinical characteristics and kinetic estimates representing the steps of skeletal muscle glucose metabolism with insulin stimulation are shown as mean ⫾ SE with P values in Table 1. Glucose delivery, either inward (k1) or outward (k2), was not significantly different between IR and IS in either muscle group as determined by [15O]H2O (n ⫽ 11). Inward (k3) and outward (k4) transport was significantly higher in IS (0.126 ⫾ 0.028 minutes⫺1) vs IR (0.051 ⫾ 0.008 minutes⫺1) in soleus (P ⬍ .05), but significant differences in glucose transport kinetics were not observed in tibialis anterior as determined by [11C]3-OMG (IS, 0.071 ⫾ 0.018; IR, 0.057 ⫾ 0.010; P ⫽ .55). The fractional phosphorylation rate (k5) was not significantly different between IR and IS. The overall fractional uptake (K) was significantly higher in IS (0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1) in soleus muscle compared with IR (0.011 ⫾ 0.002) (P ⬍ .05). Tibialis anterior trended toward higher tissue activity (IR, 0.013 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1; IS, 0.017 ⫾ 0.001, P ⫽ .13) as determined by [18F]FDG. Kinetic values are shown in Figure 1. Control coefficients were determined to assess the influence each step had on skeletal muscle glucose metabolism under insulin stimulation (Figure 2), with a higher percentage indicating a higher level of control at that specific step. In both soleus and tibialis anterior, the control in IS was significantly different from IR, with more evenly distributed control (less control at transport and increased control at deliv-
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pher in humans (6). Positron emission tomography (PET) imaging allows for specific muscle group measurements of insulin sensitivity (IS) and has previously provided valuable information regarding glucose metabolism proximal control sites and skeletal muscle type heterogeneity in lean healthy adults (3). However, this methodology has not specifically been performed to evaluate the effects of IR. Using PET imaging to distinguish specific muscle groups, this study provides novel data regarding the IR effect on specific muscle fiber type heterogeneity in human skeletal muscle and the control distribution of insulin-stimulated glucose uptake before hyperglycemia or diabetes.
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Table 1. Clinical Characteristics and PET-Derived Kinetic Measurementsa
a
Data are represented as mean ⫾ SE.
b
P ⬍ .05 represents a significant difference between IS and IR.
IR Group
P Value
43.7 ⫾ 2.9 86 ⫾ 2 5.3 ⫾ 0.1 189 ⫾ 13 109 ⫾ 29 24.0 ⫾ 1.8 7.0 ⫾ 0.3b
37.3 ⫾ 1.8 87 ⫾ 2 5.4 ⫾ 0.2 186 ⫾ 19 116 ⫾ 18 29.2 ⫾ 1.9 4.3. ⫾ 0.4
.1314 .9818 .5380 .8849 .8736 .1005 .0002
0.029 ⫾ 0.004 0.128 ⫾ 0.024
0.025 ⫾ 0.004 0.084 ⫾ 0.021
.5925 .2457
0.025 ⫾ 0.002 0.146 ⫾ 0.028 0.126 ⫾ 0.028b 0.041 ⫾ 0.005b
0.026 ⫾ 0.003 0.151 ⫾ 0.024 0.051 ⫾ 0.008 0.021 ⫾ 0.005
.8314 .9038 .0469 .0200
0.031 ⫾ 0.003 0.299 ⫾ 0.079 0.444 ⫾ 0.087b 0.008 ⫾ 0.001 0.025 ⫾ 0.003 0.017 ⫾ 0.001b
0.028 ⫾ 0.004 0.169 ⫾ 0.037 0.153 ⫾ 0.031 0.010 ⫾ 0.003 0.030 ⫾ 0.004 0.011 ⫾ 0.002
.5290 .2239 .0196 .6693 .3714 .0329
0.202 ⫾ 0.037 0.010 ⫾ 0.001b
0.219 ⫾ 0.037 0.006 ⫾ 0.001
.7657 .0236
0.022 ⫾ 0.002 0.108 ⫾ 0.021
0.022 ⫾ 0.003 0.094 ⫾ 0.037
.9945 .7913
0.018 ⫾ 0.001 0.051 ⫾ 0.005 0.071 ⫾ 0.018 0.055 ⫾ 0.012
0.020 ⫾ 0.002 0.097 ⫾ 0.024 0.057 ⫾ 0.010 0.029 ⫾ 0.005
.6378 .0924 .5490 .1166
0.027 ⫾ 0.003 0.134 ⫾ 0.049 0.291 ⫾ 0.058 0.013 ⫾ 0.002 0.025 ⫾ 0.003 0.017 ⫾ 0.001
0.027 ⫾ 0.004 0.211 ⫾ 0.037 0.324 ⫾ 0.064 0.012 ⫾ 0.003 0.028 ⫾ 0.003 0.013 ⫾ 0.001
.9025 .2804 .7334 .8803 .4740 .1291
0.253 ⫾ 0.035 0.009 ⫾ 0.001
0.203 ⫾ 0.029 0.007 ⫾ 0.001
.3512 .1506
ery; both P ⬍ .05) vs IR, which saw the inverse with much greater control at transport.
Discussion This PET imaging study revealed that across a range of normal-weight to obese subjects without diabetes, 1) glucose transport kinetic defects are principally affected with increasing IR, with less or no impairment in either glucose delivery
or phosphorylation; 2) transport defects are significantly more pronounced in soleus compared with tibialis anterior; 3) and in IS subjects, the control of glucose uptake is more evenly distributed among delivery and transport. In contrast, control of glucose transport has a stronger influence on glucose uptake in IR individuals. Previous studies are not entirely consistent with respect to which step is rate-limiting in skeletal muscle IR (11–14). Our novel data indicate that metabolically healthy IS persons disperse control more evenly among the key steps, with roughly
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Clinical characteristics Age, y Fasting glucose, mg/dL HbA1c. % Total cholesterol, mg/dL Triglycerides, mg/dL BMI Glucose infusion rate, mg/min 䡠 kg Kinetic parameters Soleus [15O]H2O (n ⫽ 11) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 [11C]3-OMG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 18 [ F]FDG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Glucose (n ⫽ 13) k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Tibialis anterior [15O]H2O (n ⫽ 11) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 [11C]3-OMG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 [18F]FDG (n ⫽ 13) K1, mL 䡠 cm⫺3 䡠 min⫺1 k2, min⫺1 k3, min⫺1 k4, min⫺1 k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1 Glucose (n ⫽ 13) k5, min⫺1 K, mL 䡠 cm⫺3 䡠 min⫺1
IS Group
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Figure 1. Glucose delivery (top), transport (middle), and phosphorylation (bottom) kinetics in soleus (left) and tibialis anterior (right) muscles. The graphs represent kinetic parameters for skeletal muscle glucose metabolism with insulin stimulation of 40 mU 䡠 m⫺2 䡠 min⫺1. Black bars represent IR, and white bars represent IS. *, P ⬍ .05.
equal control at delivery and transport in both muscle groups. However, with increasing IR, a dynamic shift occurs in which delivery control is lessened and transport control increased. This may explain findings from previous studies in which maximizing delivery did not improve skeletal muscle glucose uptake with increasing obesity (15). Our data support this concept, because systemic IS positively correlated with increasing delivery control (soleus, r ⫽ 0.61, P ⬍ .05; tibialis anterior, r ⫽ 0.86, P ⬍ .01) and negatively correlated with transport control (soleus, r ⫽ ⫺0.76, P ⬍ .01; tibialis anterior, r ⫽ ⫺0.82, P ⬍ .01). Our data also indicate that glucose transport is particularly impaired in specific skeletal muscle groups; transport in
soleus was strongly associated with IS (r ⫽ 0.83, P ⬍ .01), but this was not significant in tibialis anterior (r ⫽ 0.16, P ⫽ .60). This novel finding demonstrates specific muscle group heterogeneity in relation to IS and glucose transport. This could potentially be due to muscle fiber type differences. Previous studies have shown that fiber type is associated with IS (6, 16). Soleus and tibialis anterior muscles are composed of different proportions of type I and II muscle fibers, with soleus having more type I fibers than tibialis anterior. Therefore, a possible mechanism is that oxidative muscle with higher mitochondrial content (higher proportion of type I fibers) is more insulin-sensitive, with higher rates of glucose transport, than muscle groups with a more even distribution of type I and II muscle fibers (17, 18). Soleus is vital for plantarflexion (walking, running, and maintaining a standing posture), whereas tibialis anterior is involved in dorsiflexion (ankle stabilization). We postulate that differences in contractile activity patterns are related to the heterogeneity in IS and that this difference between IS and IR is magnified in more highly oxidative muscle. Additional studies are needed to determine the quantitative contributions of specific muscle types on systemic IS. Previous studies have shown links between increasing BMI and increasing IR (4, 7). Generally, our data agree with these observations with a negative correlation between increasing BMI and IS (r ⫽ ⫺0.57, P ⬍ .05). A novel observation, however, is that the IS group had significantly higher glucose transport and overall fractional uptake rates despite having a BMI that was only modestly (and not significantly) different. This observation confirms that IR is multifactorial in nature beyond just obesity. For example, potential differences in skeletal muscle IS in individuals of the same weight may partially explain the lean but metabolically obese phenotype that has been previously reported (5). Limitations of this study include ROI being estimates of whole organ/tissue metabolism through extrapolation rely-
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Figure 2. Control coefficient distribution under insulin stimulation. Black bars represent delivery, white bars represent transport, and gray bars represent phosphorylation. *, Significant difference between IS and IR (P ⬍ .05).
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Acknowledgments We gratefully acknowledge the efforts and cooperation of the research volunteers and support from the staffs at the University of Pittsburgh General Clinical Research Center, PET Center, and Endocrinology and Metabolism Research Center. Address all correspondence and requests for reprints to: Bret H. Goodpaster, PhD, Senior Investigator, Translational Research Institute for Metabolism and Diabetes, Florida Hospital and Sanford/Burnham Medical Research Institute, 301 East Princeton Street, Orlando, FL 32804. E-mail: [email protected]. This work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (DK-6055502), the University of Pittsburgh General Clinical Research Center (5MO1RR00056), and the Obesity and Nutrition Research Center (NIDDK P30-DK-46204).
Disclosure Summary: J.M.N., A.B., D.S.M., N.L.H., P.M.C., J.C.P., C.C., and B.H.G. have nothing to disclose. D.E.K. is currently employed by the Merck, Sharp, and Dohme Corporation.
References 1. Kelley DE, Reilly JP, Veneman T, Mandarino LJ. Effects of insulin on skeletal muscle glucose storage, oxidation, and glycolysis in humans. Am J Physiol. 1990;258:E923–E929. 2. Bonadonna RC, Saccomani MP, Seely L, et al. Glucose transport in human skeletal muscle. The in vivo response to insulin. Diabetes. 1993;42:191–198. 3. Bertoldo A, Pencek RR, Azuma K, et al. Interactions between delivery, transport, and phosphorylation of glucose in governing uptake into human skeletal muscle. Diabetes. 2006;55:3028 –3037. 4. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840–846. 5. Romero-Corral A, Somers VK, Sierra-Johnson J, et al. Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur Heart J. 2010;31:737–746. 6. James DE, Jenkins AB, Kraegen EW. Heterogeneity of insulin action in individual muscles in vivo: euglycemic clamp studies in rats. Am J Physiol. 1985;248:E567–E574. 7. Bogardus C, Lillioja S, Mott D, Reaven GR, Kashiwagi A, Foley JE. Relationship between obesity and maximal insulin-stimulated glucose uptake in vivo and in vitro in Pima Indians. J Clin Invest. 1984; 73:800 – 805. 8. Minoshima S, Berger KL, Lee KS, Mintun MA. An automated method for rotational correction and centering of three-dimensional functional brain images. J Nucl Med. 1992;33:1579 –1585. 9. Woods RP, Mazziotta JC, Cherry SR. MRI-PET registration with automated algorithm. J comput Assist Tomogr. 1993;17:536 –546. 10. Bertoldo A, Price J, Mathis C, et al. Quantitative assessment of glucose transport in human skeletal muscle: dynamic positron emission tomography imaging of [O-methyl-11C]3-O-methyl-D-glucose. J Clin Endocrinol Metab. 2005;90:1752–1759. 11. Bonadonna RC, Del Prato S, Bonora E, et al. Roles of glucose transport and glucose phosphorylation in muscle insulin resistance of NIDDM. Diabetes. 1996;45:915–925. 12. Cline GW, Petersen KF, Krssak M, et al. Impaired glucose transport as a cause of decreased insulin-stimulated muscle glycogen synthesis in type 2 diabetes. N Engl J Med. 1999;341:240 –246. 13. Bonadonna RC, Del Prato S, Saccomani MP, et al. Transmembrane glucose transport in skeletal muscle of patients with non-insulindependent diabetes. J Clin Invest. 1993;92:486 – 494. 14. Kelley DE, Mintun MA, Watkins SC, et al. The effect of non-insulin-dependent diabetes mellitus and obesity on glucose transport and phosphorylation in skeletal muscle. J Clin Invest. 1996;97:2705–2713. 15. Laine H, Yki-Jarvinen H, Kirvela O, et al. Insulin resistance of glucose uptake in skeletal muscle cannot be ameliorated by enhancing endothelium-dependent blood flow in obesity. J Clin Invest. 1998; 101:1156 –1162. 16. Coen PM, Dubé JJ, Amati F, et al. Insulin resistance is associated with higher intramyocellular triglycerides in type I but not type II myocytes concomitant with higher ceramide content. Diabetes. 2010;59:80 – 88. 17. Gollnick PD, Sjödin B, Karlsson J, Jansson E, Saltin B. Human soleus muscle: a comparison of fiber composition and enzyme activities with other leg muscles. Pflugers Arch. 1974;348:247–255. 18. Henriksson-Larsén KB, Lexell J, Sjöström M. Distribution of different fibre types in human skeletal muscles. I. Method for the preparation and analysis of cross-sections of whole tibialis anterior. Histochem J. 1983;15:167–178. 19. Kelley DE, Williams KV, Price JC, Goodpaster B. Determination of the lumped constant for [18F] fluorodeoxyglucose in human skeletal muscle. J Nucl Med. 1999;40:1798 –1804.
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ing on the lumped constant. However, previous PET studies have independently verified the validity of using the lumped constant in modeling of skeletal muscle (19). It is noted that reliance on any one radioactive tracer relies on mathematical modeling of that tracer to assess for differences. However, using multiple tracers allowed us to independently determine which steps were impaired as, for example, the transport impairment seen in both [11C]3-OMG and [18F]FDG of soleus muscle. We did not examine T2DM in this study. It is possible that more severe IR in T2DM could manifest in different or additional impairments in glucose metabolism and reveal different results in specific skeletal muscle group impairments. Another limitation to our study is the relatively small sample size, which precluded more sophisticated statistical analyses of gender or age, and a more robust linear regression of PETderived kinetic parameters across a broader range of subject characteristics. Although larger studies should be performed, these data highlight the heterogeneity in muscle glucose metabolism that contributed to IR. In summary, in a range of normal-weight to obese volunteers without diabetes, profound glucose transport defects were observed with increasing IR more clearly in specific skeletal muscle groups, eg, soleus muscle, that were not as evident in tibialis anterior. These transport defects are not explained by obesity alone. Dynamic shifts occur within the steps of skeletal muscle glucose metabolism from a fairly even distribution between delivery and transport to a transportpredominant model with increasing IR. These data suggest that the heterogeneity in skeletal muscle contributes to the variability in IR or that different muscle types are more or less susceptible to factors that cause IR. These dynamic PET imaging studies indicate the complexity of human skeletal muscle IR preceding T2DM.
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