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Intramyocellular Lipids: Anthropometric Determinants and Relationships with Maximal Aerobic Capacity and Insulin Sensitivity

Department of Endocrinology and Metabolism (C.T., O.B., M.H., D.D., O.T., A.F., S.J., H.-U.H., M.S.) and Section on Experimental Radiology (J.M., B.W., K.B., C.C., F.S.), Department of Diagnostic Radiology, Eberhard-Karls-University, D-72076 Tübingen, Germany; and Medical Clinic (A.N.), Department of Sports Medicine, University of Freiburg, D-79106 Freiburg, Germany

Address all correspondence and requests for reprints to: Dr. Michael Stumvoll, Medizinische Universitätsklinik, Otfried-Müller-Strasse 10, D-72076 Tübingen, Germany. E-mail: michael.stumvoll{at}med.uni-tuebingen.de.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The existence of metabolically relevant intramyocellular lipids (IMCL) as assessed by the noninvasive ¹H-magnetic resonance spectroscopy (MRS) has been established. In the present studies, we analyzed the relationships between IMCL in two muscle types [the predominantly nonoxidative tibialis muscle (tib) and the predominantly oxidative soleus muscle (sol)] and anthropometric data, aerobic capacity (VO₂max, bicycle ergometry, n = 77) and insulin sensitivity (hyperinsulinemic euglycemic clamp, n = 105) using regression analysis.

In univariate regression, IMCL (tib) was weakly but significantly correlated with percentage of body fat (r = 0.28, P = 0.01), whereas IMCL (sol) was better correlated with waist-to-hip ratio (r = 0.41, P < 0.0001). No significant univariate correlation with age or maximal aerobic power was observed. After adjusting for adiposity, IMCL (tib) was positively correlated with measures of aerobic fitness. A significant interaction term between VO₂max and percentage of body fat on IMCL (tib) (P = 0.04) existed (whole model r² = 0.26, P = 0.001). In contrast, aerobic fitness did not influence IMCL (sol). No correlation between insulin sensitivity as such and IMCL (tib) (r = -0.13, P = 0.2) or IMCL (sol) (r = 0.03, P = 0.72) was observed. Nethertheless, a significant interaction term between VO₂max and IMCL on insulin sensitivity existed [P = 0.04 (tib) and P = 0.02 (sol)]; [whole model (sol) r² = 0.61, P < 0.0001, (tib) r² = 0.60, P < 0.0001].

In conclusion, obesity and aerobic fitness are important determinants of IMCL. IMCL and insulin sensitivity are negatively correlated in untrained subjects. The correlation between the two parameters is modified by the extent of aerobic fitness and cannot be found in endurance trained subjects. Thus, measurements of aerobic fitness and body fat are indispensable for the interpretation of IMCL and its relationship with insulin sensitivity.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
THE EXISTENCE OF metabolically relevant lipid stores in skeletal muscle has long been established (1). In addition to glycogen, lipids represent a storage form of energy in muscle. Consequently, their regulation by physical exercise and their relationship with insulin-stimulated glucose metabolism has been of interest. Endurance training, for example, was shown to increase the im lipid content. In insulin-resistant Pima Indians, im lipids were also increased and proposed to have some causal role in the pathogenesis of type 2 diabetes (2).

More recently, a quantification method based on magnetic resonance spectroscopy has greatly facilitated the study of im lipids and their relationship with insulin sensitivity. Moreover, this noninvasive technique permitted distinction between lipids within muscle cells (intramyocellular lipids, IMCL) from lipid interlaced between muscle fibers (extramyocellular, EMCL) and has been demonstrated to be as accurate as biochemical or histological methods (3). Using this technique, several groups reported a negative association between the IMCL content and insulin sensitivity (4, 5, 6, 7). In addition, IMCL appears to be acutely regulated. Experimental elevation of free fatty acids resulted in an increase in IMCL (8, 9), whereas prolonged endurance exercise decreased IMCL (10).

It is still unclear, however, how an augmented aerobic capacity increases insulin sensitivity while paradoxically being associated with increased IMCL. It is also not known whether in obesity increased IMCL predicts insulin resistance independent of excess body fat as such and whether genetic factors play a role in presetting the individual IMCL content. We therefore analyzed statistical associations between anthropometric data [age, sex, percentage of body fat, waist to hip ratio (WHR), maximal aerobic power] and IMCL in a cohort of 105 healthy nondiabetic individuals covering a broad range of those variables. IMCL was determined by magnetic resonance spectroscopy both in tibialis anterior muscle (tib), a fast-twitching, white muscle, and in soleus muscle (sol), a slow-twitching, red muscle. Furthermore, we studied the relationship between IMCL and insulin sensitivity (hyperinsulinemic-euglycemic), taking into account the influence of anthropometric measures, especially the role of maximal aerobic capacity (VO₂max). The relatively large size of our cohort permitted use of multivariate linear regression analysis to identify relevant and independent relationships.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Subjects

A total of 105 healthy nondiabetic subjects were recruited from the Tübingen Family Study for Type 2 Diabetes (see Table 1 for details) and underwent determination of IMCL as described below. In a subgroup of 77 of these subjects, an exercise test to volitional exhaustion on a cycle ergometer to determine maximal oxygen uptake (VO₂max).

Determination of IMCL by MRS

Neutral lipids within the muscle cell (IMCL) and those interlaced between the muscle fibers (EMCL) can be differentiated due to their geometrical arrangement using proton magnetic resonance spectroscopy (¹H-MRS; Refs. 11, 12). Localized image guided proton spectra of the tib anterior muscle representing a muscle of mixed type I and II fibers and of the sol representing a muscle of predominantly type I fibers with high oxidative capacity were acquired on a 1.5-Tesla whole body imager (Magnetom Vision, Siemens, Erlangen, Germany). For volume selection, a single voxel STEAM technique was applied. Measurement parameters: echo time = 10 msec, repetition time = 2 sec, volume of interest 11 x 11 x 20 mm³, 40 acquisitions. IMCL and EMCL were quantified as previously described (11, 12).

Euglycemic hyperinsulinemic clamp

After a 12-h overnight fast around 0700 h, an antecubital vein was cannulated for infusion of insulin and glucose. A dorsal hand vein of the contra lateral arm was cannulated and placed under a heating device to permit sampling of arterialized blood. After basal blood was drawn, subjects received a primed insulin infusion at a rate of 1.0 mU·kg^-1·min^-1 for 2 h. Blood was drawn every 5 min for determination of blood glucose, and a glucose infusion was adjusted appropriately to maintain the fasting glucose level. An insulin sensitivity index (ISI; in µmol·kg^-1·min^-1·pM^-1) for systemic glucose uptake was calculated as the mean infusion rate of glucose (in µmol·kg^-1·min ^–1) necessary to maintain euglycemia during the last 60 min of the euglycemic hyperinsulinemic clamp divided by the steady state serum insulin concentration.

Measurement of VO₂max

Subjects underwent continuous, incremental exercise test to volitional exhaustion on a cycle ergometer. The cycle ergometer test was performed on an electromagnetically braked cycle ergometer (ergometrics 800 S, Ergoline, Bitz, Germany). Oxygen consumption was measured using a spiroergometer (MedGraphics System Breese Ex 3.02 A, St. Paul, MN). Subjects were asked to choose a pedaling rate of 60 rpm and to maintain that rate throughout the test. After a 2-min warm-up period at 0 W, the test was initiated at an initial power output of 20 W. Stepwise increments of 40 W were made every minute until exhaustion. VO₂max is expressed as percentage of predicted peak VO₂ (ml/min) based on sex, age, and body mass index as described previously (13). For the purpose of the present analyses, we used this parameter as measure of physical fitness.

Statistical analyses

All data are given as mean ± SEM unless otherwise stated. The statistical software package JMP (SAS Institute Inc., Cary, NC) was used for statistical analyses. Age, percentage body fat, VO₂max, and ISI were not normally distributed and log transformed before analyses.

Simple linear regression was applied to examine the relationships between age, percentage body fat, WHR, VO₂max, and IMCL, and Pearson’s regression coefficient was calculated. Multiple linear regression models with sex, age, percentage body fat, WHR and VO₂max as independent variables were used to calculate the predictive effect on the dependent variable IMCL. The effect of the interaction term between IMCL and VO₂max on insulin sensitivity was calculated using multiple linear regression models after adjusting for sex, age, percentage body fat, and WHR. Stepwise linear regression was used to determine the variation in ISI explained by the interaction term between IMCL and VO₂max.

Three-dimensional mesh graphs were used to illustrate interaction effects in a qualitative fashion. The x and y variable were divided into a 4 x 4 grid, resulting in 16 categories. The mean z variable of the points contained in each category was used to construct the mesh. z values for empty categories were interpolated. The inverse distance method as provided by the software package SigmaPlot (SPSS, Inc., Richmond, CA) was used with values for weight of three and for intervals of four. Several iterations were performed until a smooth surface was obtained.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Determinants of IMCL

IMCL was found to be higher in sol compared with tib [12.0 ± 0.5 arbitrary units (AU); range 3.3–34.0 AU] vs. 4.0 ± 0.2 AU (range 0.7 – 10.1 AU; P < 0.0001). In the whole cohort, IMCL (tib) was highly correlated with IMCL (sol, r = 0.43; P < 0.0001; Fig. 1). IMCL (tib) was slightly higher in females than males (4.3 ± 0.3 vs. 3.8 ± 0.2 AU), but this did not reach statistical significance (P = 0.1). IMCL (sol) was significantly higher in males than in females (12.8 ± 0.7 vs. 9.8 ± 0.6 AU, P = 0.01). IMCL (tib) was significantly correlated with percentage body fat (r = 0.28, P = 0.01) but not with age (P = 0.77), WHR (P = 0.15) or waist circumference (P = 0.11). IMCL (sol) was correlated with WHR (r = 0.41, P < 0.0001), waist circumference (r = 0.31, P = 0.001) and age (r = 0.17, P = 0.06) but not with percentage body fat (P = 0.64). VO₂max was not correlated with IMCL neither in the tib (P = 0.46) nor in the sol (P = 0.54).

View larger version (16K): [in this window] [in a new window]   Figure 1. Correlation between IMCL (tib) and IMCL (sol).

View larger version (39K): [in this window] [in a new window]   Figure 2. Three dimensional relationship between VO2max, percentage of body fat and IMCL in tib anterior muscle. The 4 x 4 grid was generated by dividing both VO2max and percentage of body fat into four equal intervals. The mean IMCL value of the subjects contained in one square was used to construct the mesh graph. In lean subjects, VO2max was positively correlated with IMCL. In untrained individuals, increased percentage of body fat was strongly associated with increased IMCL (please note that the category with highest VO2max and highest percentage of body fat contained no data points).

In the entire group (n = 105), insulin sensitivity was not correlated with IMCL (sol) (r = -0.03, P = 0.72) or IMCL (tib) (r = -0.13, P = 0.2). This was similar in the subgroup with aerobic power measurements available (n = 77, r = 0.1, P = 0.35, sol; and r = -0.07 P = 0.53, tib). In a multivariate regression analysis with ISI as dependent variable neither IMCL (tib; P = 0.76) nor IMCL (sol; P = 0.35) were independent determinants of ISI after adjusting for age, percentage of body fat and VO₂max (Table 4, model 1). Interestingly, for both muscle types an interaction term between IMCL and VO₂max was an independent predictor of insulin sensitivity. This relationship remained significant after adjusting for sex, age, percentage of body fat, and VO₂max (see Table 4). The interaction effect between IMCL (tib) and VO₂max on ISI is illustrated in Fig. 3. While in subjects with low aerobic power, ISI was negatively correlated with IMCL (tib), it was positively correlated in subjects with high aerobic fitness.

View larger version (40K): [in this window] [in a new window]   Figure 3. Three-dimensional relationship between VO2max, IMCL in tib anterior muscle and insulin sensitivity. The 4 x 4 grid was generated by dividing both VO2max and IMCL (tib) into four equal intervals. The mean IMCL value of the subjects contained in one square was used to construct the mesh graph. In untrained individuals high IMCL predicts low insulin sensitivity. In highly trained individuals, this relationship is reversed and high IMCL predicts high insulin sensitivity.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Aim of the present study was to identify anthropometric determinants of the IMCL content as measured by ¹H-MRS and to analyze the correlation with insulin action in a large cohort. IMCL was measured in the predominantly nonoxidative tib anterior muscle and in the predominantly oxidative sol. Although the IMCL content in the two muscles was significantly correlated, a high individual variability remained (Fig. 1). Moreover, the anthropometric parameters as statistical determinants of IMCL were clearly different between the two muscle types. This probably reflects differences in fiber type composition. For example, VO₂max was identified as an important determinant of IMCL (tib) but not of IMCL (sol; Table 3). Soleus muscle is rich in oxidative, slow-twitch type I fibers, whereas tibialis anterior muscle is rich in fast-twitch type 2 fibers (14). Therefore, the lack of an association with the predominantly oxidative muscle may reflect the higher and possibly compensating oxidative capacity of sol in response to endurance training that could prevent accumulation of lipids. In addition, the MR spectroscopic measurement of IMCL in sol is generally more difficult and characterized by a greater experimental variation (15).

Determinants of the IMCL content differed between the two muscle types. In this study, a relatively weak correlation between muscle lipids and measures of obesity was observed. IMCL (tib) was correlated with percentage of body fat, whereas the best single predictor of IMCL (sol) was WHR. This suggests that adiposity as such reflecting caloric oversupply has a weak but significant effect on the IMCL content. This appears to be at variance with a previous report finding no significant association between percentage of body fat and skeletal muscle triglyceride contents in 37 Pima Indians (2). In this study, however, only total muscle triglycerides were measured by a lipid extraction method and no distinction between intramyocellular vs. extramyocellular localizations could be made. Moreover, the relatively weak association with adiposity may become detectable only with greater samples sizes.

The weak association of IMCL (tib) with sex disappeared in multivariate analyses. The association of IMCL (sol) with sex became weaker and depended on the parameters included in the model. In some instances, sex effects were explained by WHR, a crude measure of body fat distribution. In multivariate regression analyses WHR was the best predictor of both IMCL (tib) and IMCL (sol) (model 2, Table 3). It is possible that, just like for other fat depots, hormonal factors may be involved in the regulation of IMCL.

The performance of the models predicting IMCL (tib) improved markedly upon inclusion of VO₂max as independent variable. After adjusting for percentage of body fat VO₂max was positively correlated with IMCL. Moreover, the model performed even better after including an interaction term between VO₂max and percentage of body fat as indicated by the increase in r² from 0.19–0.26 (Table 3). In plain words, the correlation between IMCL (tib) and adiposity depends on VO₂max (Fig. 2).

In our entire study, population insulin sensitivity and IMCL in either muscle were not correlated. This contrasts with previous reports including one from our laboratory on small well-matched groups in which IMCL were shown to be increased in insulin-resistant individuals (4, 6, 7). The underlying mechanisms were proposed to include elevation of intramyocellular fatty acid metabolites such as diacyl-glycerol, fatty acyl coenzyme A and ceramides and, consequently, reduced insulin-induced tyrosine phosphorylation of the insulin receptor and phosphatidylinositol 3-kinase activity (7, 16).

More recent studies indicated that the relationship between IMCL and insulin resistance is more complex and influenced by the oxidative capacity of skeletal muscle (17). The oxidative capacity of skeletal muscle, which increases with training, is in part assessed by our measurement of VO₂max. We identified a striking and statistically significant interaction effect between the VO₂max and the IMCL content on insulin sensitivity in both muscle types (Fig. 3). The interaction effect indicates that the relationship between IMCL and ISI is modified by aerobic fitness. Only in untrained individuals, high IMCL predicted low insulin sensitivity. In trained athletes, this relationship was reversed and high IMCL predicted high insulin sensitivity. Our findings are generally compatible with results of Goodpaster and colleagues (17, 18), demonstrating increased intramyocellular lipid using histochemical lipid staining in endurance trained athletes compared with lean controls, whereas insulin sensitivity was comparable. The authors subsequently hypothesized that the association between IMCL content and insulin sensitivity may be influenced by the oxidative capacity of skeletal muscle.

A possible explanation for this apparently paradoxical finding may have to do with the increased glucose transport capacity in endurance trained muscle (19, 20). Increased glucose transport would facilitate im triglyceride synthesis and at the same time improve insulin sensitivity. This mechanism is not operative or not visible in untrained subjects because here IMCL accumulation driven by chronic caloric (particularly fat) oversupply dominates the effect of training. Consistent with this hypothesis, in healthy individuals an increase in IMCL could be rapidly induced by intralipid plus heparin infusion and high fat diet (8, 21). In addition, IMCL may exist in more than one compartment—spatial or functional—that are indistinguishable by the MRS technique. And IMCL of a trained athlete may be localized in a different compartment than IMCL of an obese, insulin-resistant individual.

In conclusion, in this large heterogeneous cohort of healthy, nondiabetic subjects, percentage of body fat, and VO₂max were independent determinants of IMCL (tib) but not of IMCL (sol). It is possible that the ratio of IMCL (sol) over IMCL (tib) harbors additional information yet to be uncovered. A significant interaction effect between VO₂max and percentage of body fat on IMCL (tib) was detected suggesting that the association between VO₂max and IMCL (tib) is influenced by presence or absence of obesity. Insulin sensitivity is a negative function of IMCL only in untrained subjects, whereas in endurance-trained subjects high IMCL actually predicted high insulin sensitivity. Thus, measurements of aerobic fitness and body fat are indispensable for the interpretation of IMCL measurements and its relationship with insulin sensitivity.

	Acknowledgments

 
We thank our volunteers for their participation.

	Footnotes

 
This work was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG No. JA-1005/1-1, DFG Stu-192/9-1), the Federal Ministry of Education and Research (Fö. 01KS9602), a grant from the European Community (QLRT-1999-00674) and the Interdisciplinary Center of Clinical Research Tübingen (IZKF).

Abbreviations: EMCL, Extramyocellular lipids; IMCL, intramyocellular lipids; ISI, insulin sensitivity index; MRS, magnetic resonance spectroscopy; sol, soleus muscle; tib, tibialis muscle; WHR, waist to hip ratio; VO₂max, maximal aerobic capacity.

Received October 28, 2002.

Accepted January 15, 2003.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 

1. Dagenais GR, Tancredi RG, Zierler KL 1976 Free fatty acid oxidation by forearm muscle at rest, and evidence for an intramuscular lipid pool in the human forearm. J Clin Invest 58:421–431
2. Pan DA, Lillioja S, Kriketos AD, Milner MR, Baur LA, Bogardus C, Jenkins AB, Storlien LH 1997 Skeletal muscle triglyceride levels are inversely related to insulin action. Diabetes 46:983–988[Abstract]
3. Szczepaniak LS, Babcock EE, Schick F, Dobbins RL, Garg A, Burns DK, McGarry JD, Stein DT 1999 Measurement of intracellular triglyceride stores by H spectroscopy: validation in vivo. Am J Physiol 276(5 Part 1):E977–E989
4. Jacob S, Machann J, Rett K, Brechtel K, Volk A, Renn W, Maerker E, Matthaei S, Schick F, Claussen CD, Haring HU 1999 Association of increased intramyocellular lipid content with insulin resistance in lean nondiabetic offspring of type 2 diabetic subjects. Diabetes 48:1113–1119[Abstract]
5. Krssak M, Falk Petersen K, Dresner A, DiPietro L, Vogel SM, Rothman DL, Roden M, Shulman GI 1999 Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study. Diabetologia 42:113–116[CrossRef][Medline]
6. Perseghin G, Scifo P, De Cobelli F, Pagliato E, Battezzati A, Arcelloni C, Vanzulli A, Testolin G, Pozza G, Del Maschio A, Luzi L 1999 Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans: a 1H–13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic parents. Diabetes 48:1600–1606[Abstract]
7. Virkamaki A, Korsheninnikova E, Seppala-Lindroos A, Vehkavaara S, Goto T, Halavaara J, Hakkinen AM, Yki-Jarvinen H 2001 Intramyocellular lipid is associated with resistance to in vivo insulin actions on glucose uptake, antilipolysis, and early insulin signaling pathways in human skeletal muscle. Diabetes 50:2337–2343[Abstract/Free Full Text]
8. Bachmann OP, Dahl DB, Brechtel K, Machann J, Haap M, Maier T, Loviscach M, Stumvoll M, Claussen CD, Schick F, Haring HU, Jacob S 2001 Effects of intravenous and dietary lipid challenge on intramyocellular lipid content and the relation with insulin sensitivity in humans. Diabetes 50:2579–2584[Abstract/Free Full Text]
9. Boden G 1997 Role of fatty acids in the pathogenesis of insulin resistance and NIDDM. Diabetes 46:3–10[Abstract]
10. Brechtel K, Niess AM, Machann J, Rett K, Schick F, Claussen CD, Dickhuth HH, Haering HU, Jacob S 2001 Utilisation of intramyocellular lipids (IMCLs) during exercise as assessed by proton magnetic resonance spectroscopy (1H-MRS). Horm Metab Res 33:63–66[CrossRef][Medline]
11. Schick F, Eismann B, Jung WI, Bongers H, Bunse M, Lutz O 1993 Comparison of localized proton NMR signals of skeletal muscle and fat tissue in vivo: two lipid compartments in muscle tissue. Magn Reson Med 29:158–167[Medline]
12. Boesch C, Slotboom J, Hoppeler H, Kreis R 1997 In vivo determination of intra-myocellular lipids in human muscle by means of localized 1H-MR-spectroscopy. Magn Reson Med 37:484–493[Medline]
13. Hansen JE, Sue DY, Wasserman K 1984 Predicted values for clinical exercise testing. Am Rev Respir Dis 129(2 Part 2):S49–S55
14. Polgar J, Johnson MA, Weightman D, Appleton D 1973 Data on fibre size in thirty-six human muscles. An autopsy study. J Neurol Sci 19:307–318[CrossRef][Medline]
15. Brechtel K, Machann J, Jacob S, Strempfer A, Schick F, Haring HU, Claussen CD 1999 In-vivo 1H-MR spectroscopy: the determination of the intra- and extramyocellular lipid content depending on the insulin effect in the direct offspring of type-2 diabetics. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr 171:113–120[Medline]
16. Shulman GI 2000 Cellular mechanisms of insulin resistance. J Clin Invest 106:171–176[Medline]
17. Goodpaster BH, He J, Watkins S, Kelley DE 2001 Skeletal muscle lipid content and insulin resistance: evidence for a paradox in endurance-trained athletes. J Clin Endocrinol Metab 86:5755–5761[Abstract/Free Full Text]
18. Kelley DE, Goodpaster B, Wing RR, Simoneau JA 1999 Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol 277(6 Part 1):E1130–E1141
19. Etgen Jr GJ, Jensen J, Wilson CM, Hunt DG, Cushman SW, Ivy JL 1997 Exercise training reverses insulin resistance in muscle by enhanced recruitment of GLUT-4 to the cell surface. Am J Physiol 272(5 Part 1):E864–E869
20. Ploug T, Stallknecht BM, Pedersen O, Kahn BB, Ohkuwa T, Vinten J, Galbo H 1990 Effect of endurance training on glucose transport capacity and glucose transporter expression in rat skeletal muscle. Am J Physiol 259(6 Part 1):E778–E786
21. Boden G, Lebed B, Schatz M, Homko C, Lemieux S 2001 Effects of acute changes of plasma free fatty acids on intramyocellular fat content and insulin resistance in healthy subjects. Diabetes 50:1612–1617[Abstract/Free Full Text]

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