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PLoS One. 2010; 5(12): e14197.
Published online 2010 December 1. doi:  10.1371/journal.pone.0014197
PMCID: PMC2995737

Fat Oxidation, Fitness and Skeletal Muscle Expression of Oxidative/Lipid Metabolism Genes in South Asians: Implications for Insulin Resistance?

Jose A. L. Calbet, Editor

Abstract

Background

South Asians are more insulin resistant than Europeans, which cannot be fully explained by differences in adiposity. We investigated whether differences in oxidative capacity and capacity for fatty acid utilisation in South Asians might contribute, using a range of whole-body and skeletal muscle measures.

Methodology/Principal Findings

Twenty men of South Asian ethnic origin and 20 age and BMI-matched men of white European descent underwent exercise and metabolic testing and provided a muscle biopsy to determine expression of oxidative and lipid metabolism genes and of insulin signalling proteins. In analyses adjusted for age, BMI, fat mass and physical activity, South Asians, compared to Europeans, exhibited; reduced insulin sensitivity by 26% (p = 0.010); lower VO2max (40.6±6.6 vs 52.4±5.7 ml.kg−1.min−1, p = 0.001); and reduced fat oxidation during submaximal exercise at the same relative (3.77±2.02 vs 6.55±2.60 mg.kg−1.min−1 at 55% VO2max, p = 0.013), and absolute (3.46±2.20 vs 6.00±1.93 mg.kg−1.min−1 at 25 ml O2.kg−1.min−1, p = 0.021), exercise intensities. South Asians exhibited significantly higher skeletal muscle gene expression of CPT1A and FASN and significantly lower skeletal muscle protein expression of PI3K and PKB Ser473 phosphorylation. Fat oxidation during submaximal exercise and VO2max both correlated significantly with insulin sensitivity index and PKB Ser473 phosphorylation, with VO2max or fat oxidation during exercise explaining 10–13% of the variance in insulin sensitivity index, independent of age, body composition and physical activity.

Conclusions/Significance

These data indicate that reduced oxidative capacity and capacity for fatty acid utilisation at the whole body level are key features of the insulin resistant phenotype observed in South Asians, but that this is not the consequence of reduced skeletal muscle expression of oxidative and lipid metabolism genes.

Introduction

South Asians have a high risk of diabetes, particularly when they migrate away from the Indian Subcontinent [1][4], with increased insulin resistance likely to play a key role [5][9]. For a given BMI, South Asians generally have higher percentages of body fat, increased waist-to-hip ratios and increased truncal skinfold thickness than European comparators [3], [10] – although interestingly increased visceral fat is not a consistent finding [7], [11] – and it has been suggested that this tendency to increased adiposity and central fat distribution contributes to the increased insulin resistance observed in this group. However, additional studies have shown that even after adjustment for BMI, waist-hip-ratio, and skin-fold thickness, insulin levels (both fasting and post glucose-load) remain significantly higher in South Asians [11], [12]. Furthermore, even when South Asian men are closely matched for BMI, waist-to-hip ratios and visceral fat areas with European men, they exhibit substantially increased insulin resistance [11]. In addition, South Asians develop diabetes and metabolic disturbances associated with insulin resistance at lower BMI values than Europeans [13]. Thus, it appears that the increased insulin resistance in South Asians cannot be fully explained by differences in adiposity and/or abdominal fat accumulation.

Accumulation of lipid within skeletal muscle – particularly of active lipid intermediates such as long chain fatty acyl-CoA, diacylglycerol and ceramide – is likely to play a causal role in insulin resistance [14]. It has been reported that South Asians have 30% higher intramuscular triglyceride (IMTG) concentrations than BMI-matched Europeans [11]. Although it is now generally accepted that IMTG per se (as opposed to lipid intermediates) is unlikely to play a direct role in insulin resistance, IMTG does provide a useful marker of cytosolic lipid accumulation [14], thus the observation of elevated IMTG in South Asians is suggestive of a deficiency in skeletal muscle lipid metabolism. Accumulating evidence indicates that defects in skeletal muscle oxidative capacity and low rates of skeletal muscle lipid oxidation are likely to contribute to skeletal muscle lipid accumulation and consequent insulin resistance [15][17]. However, Nair and colleagues reported that middle-aged non-diabetic Asian Indians had increased skeletal muscle expression of genes involved with oxidative phosphorylation and the citrate cycle and increased capacity for mitochondrial ATP production than matched Americans of European descent, despite being more insulin resistant, concluding that mitochondrial dysfunction could not account for the Asian Indians' greater insulin resistance [9]. However, these data may not tell the whole story. In contrast to the skeletal muscle data indicating increased mitochondrial capacity, the available evidence at the whole-body level indicates that South Asians have lower maximal oxygen uptake (VO2max) values – an index of oxidative capacity at the whole-body level – than matched European comparators [12], [18] and VO2max is a strong independent predictor of whole body insulin sensitivity [19], [20]. However, while it is known that cardiorespiratory fitness is closely associated with skeletal muscle lipid oxidative capacity [21][23], it is not known whether capacity for lipid oxidation is reduced in South Asians compared to Europeans, or whether these factors contribute to South Asians' increased insulin resistance.

Thus, in order to gain further insight into the potential role of altered capacity for lipid oxidation in mediating the South Asian insulin resistant phenotype, we undertook a detailed investigation of oxidative capacity and capacity for fatty acid utilisation in matched South Asian and European men using a range of whole-body and skeletal muscle measures. In addition, we characterised the expression of insulin signalling molecules in skeletal muscle biopsies, to determine whether alterations in key signalling proteins were associated with alterations in oxidative capacity and/or insulin sensitivity.

Methods

Subjects and recruitment

Twenty men of South Asian ethnic origin and 20 men of white European decent, individually matched for age (±5 years) and BMI (±2 kg.m−2) were recruited via a study website and local advertising. Data from one European man was excluded as he was subsequently discovered to have diabetes: the final study group therefore contained 20 South Asian and 19 European men. Anthropometric, physiological and biochemical characteristics of the volunteers included in the analyses are shown in Tables 1, ,22 and and3.3. All volunteers currently resided in Glasgow; 18 of the European and 4 of the South Asian men had lived in the UK all of their lives. Of the 16 South Asians born outside the UK, mean (± SD) duration of UK residence was 2.5±5.0 years. All participants reported low to moderate levels of physical activity (<2 hours of planned exercise per week and physically inactive job), and were non-smokers, aged 18–40 years, in generally good health, with blood pressure <160/90 mmHg, and no known history of diabetes or cardiovascular disease. Other than one European using steroid and β2 agonist inhalers for asthma and topical steroids for eczema and another European using topical steroids for eczema, no volunteer was taking any medications. The study was approved by the North Glasgow NHS Trust Research Ethics Committee and was conducted according to the principles expressed in the Declaration of Helsinki. All participants gave written informed consent.

Table 1
Anthropometric data for European and South Asian men.
Table 2
Fitness and physical activity data for European and South Asian men.
Table 3
Metabolic data for European and South Asian men.

Body composition assessment

Dual X-Ray Absorptiometry (DEXA) scans (LUNAR Prodigy DEXA scanner, GE Healthcare Diagnostic Imaging, Slough, UK) were used to determine body composition and fat distribution. Height, body mass, waist and hip circumferences were also determined using standard protocols [24].

Exercise tests

Exercise tests, undertaken following a 12-hour overnight fast, were performed to determine VO2max and rates of fat oxidation during sub-maximal exercise. Following an exercise tolerance test to ensure no cardiovascular contraindications to maximal exercise [25], VO2max was assessed using the modified Taylor incremental treadmill test protocol [26], with 1-minute expired air samples taken continuously using Douglas Bags and heart rate monitored by short-range telemetry. Achievement of VO2max was verified by volitional exhaustion together with a rate of perceived exertion (RPE) of 19–20 [27], a respiratory exchange ratio >1.15, and heart rate within 10 beats of age-predicted maximum.

On a separate day subjects underwent a submaximal incremental treadmill test at 5.5 km.h−1, with an initial gradient calculated to elicit an oxygen uptake of ~40% VO2max. Gradient increased by 1% every 4 minutes, until an RPE of 15–16 was achieved. Expired air, heart rate and RPE were taken during the final minute of each stage. Fat and carbohydrate oxidation rates at each exercise stage was determined from VO2 and VCO2 measurements in expired air by indirect calorimetry [28]. As skeletal muscle capacity for mitochondrial fat oxidation correlates strongly with fat oxidation during sub-maximal exercise [21], this test was used to provide an index of skeletal muscle fat oxidative capacity.

Determination of habitual physical activity and diet

Habitual physical activity was assessed using the long form of the International Physical Activity Questionnaire [29] and habitual diet was assessed using a 120-item food-frequency questionnaire [30].

Metabolic assessment and muscle biopsy

For these measurements volunteers attended the laboratory after 12-hour overnight fast, and at least a 60-hour abstention from planned exercise. Following a 10-minute rest lying on a couch, a 20-minute expired air sample was collected using a ventilated hood system (Oxycon Pro, Jaeger, Germany). Metabolic rate and rates of fat and carbohydrate oxidation were calculated by indirect calorimetry [28], assuming urinary nitrogen excretion to be 0.11 mg.kg−1.min−1 [31], [32]. A fasting blood sample was then taken, followed by a muscle biopsy from the vastus lateralis of the right leg, 20 cm above the patella, under local anaesthesia using a ‘semi-open’ technique [33]. Visible fat and connective tissue was removed with sterile forceps and samples were divided in six pieces. Four pieces were immediately snap-frozen in liquid N2, the remaining two pieces were incubated for 15 minutes in Krebs Ringer Hepes buffer (118 mM NaCl, 25 mM Hepes-NaOH, pH 7.4, 5 mM NaHCO3, 4.7 mM KCl, 1.2 mM MgSO4, 1.2 mM NaH2PO4, 2.5 mM CaCl2, 5mM glucose, 0.1% (w/v) bovine serum albumin) at 37°C, gassed with O2 prior to incubation for 10 min in the presence or absence of 10 nM human soluble insulin (Actrapid, Novo Nordisk), before snap-freezing in liquid N2 prior to homogenisation for immunoblotting analysis. The 10 nM insulin dose was chosen to maximally stimulate insulin signalling [34]. Subjects then consumed 75 g glucose orally in a 300 ml volume, with further blood samples taken at 30-minute intervals for 120 minutes.

Plasma analyses

Blood was collected into potassium EDTA tubes, placed on ice, separated within 15 minutes and stored at -80°C until analysis. Glucose, TG, non-esterified fatty acid (NEFA), total cholesterol, and HDL cholesterol concentrations were determined by enzymatic colorimetric methods using commercially available kits (Roche Diagnostics Gmbh, Mannheim, Germany; Wako Chemicals GmbH, Neuss, Germany and Randox Laboratories Ltd., Co. Antrim, Ireland). Insulin was determined using a commercially available ELISA with <0.01% cross-reactivity with pro-insulin (Mercodia AB, Uppsala, Sweden). Adiponectin, leptin, IL-6 and TNFα concentrations were also determined by ELISA (R&D Systems Europe, Abingdon, United Kingdom).

Determination of skeletal muscle expression of oxidative and lipid metabolism genes

RNA was extracted from muscle using an E.Z.N.A. Tissue RNA kit (Omega Bio-Tek, Inc., Norcross, GA) according to the manufacturer's protocol using Precellys Ceramic Homogenisation beads (CK14, PEQLAB Ltd, Farnborough, UK) and a Hybaid Ribolyser (Thermo Scientific, Loughborough, United Kingdom). cDNA was synthesised using an Applied BioSystems High Capacity cDNA Reverse Transcription kit (Life Technologies Corporation, Carlsbad, CA) with random hexamers according to the manufacturers protocol, but doubling the volumes to increase yield. Quantitative polymerase chain reaction (qPCR) assays were designed for each transcript (Table S1) using the Roche Universal ProbeLibrary Assay Design Center (http://www.roches-applied-science.com/) and mRNA expression levels of transcripts were determined as described previously [35].

Determination of skeletal muscle mitochondrial DNA (mtDNA) to nuclear DNA (nDNA) ratio

DNA was extracted from muscle using a QIAamp DNA Mini Kit (Qiagen Ltd., Crawley, United Kingdom) according to the manufacturer's protocol (including the RNase treatment) using Precellys Ceramic Homogenisation beads (CK14, PEQLAB Ltd, Farnborough, UK) and a Hybaid Ribolyser (Thermo Scientific, Loughborough, United Kingdom). qPCR assays were designed, using the Roche Universal ProbeLibrary Assay Design Center, for the mitochondrial genome overlapping two neighbouring genes (tRNA leucine 1 and NADH dehydrogenase 1) and the nuclear genome using the β2-adrenergic receptor gene promoter (Table S1). Relative DNA levels were determined in a similar fashion to the mRNA expression levels.

Determination of skeletal muscle insulin signalling protein expression

Muscle biopsies were homogenised in 8 volumes of homogenisation buffer (50 mM Tris-HCl, pH 7.4 at 4°C, 250 mM sucrose, 1 mM EDTA, 1 mM EGTA, 5 mM NaF, 5 mM Na4P2O7, 1 mM dithiothreitol, 1 mM Na3VO4, 0.1 mM benzamidine, 0.1 mM phenylmethylsuplhonyl fluoride, 5 µg.ml−1 soybean trypsin inhibitor) by 20 passes in a Dounce homogeniser at 4°C. Homogenates were centrifuged (350,000 g, 30 min, 4°C) to obtain cytosolic supernatant fractions. Pellets were re-suspended in 150 µl homogenisation buffer supplemented with 1% (v/v) NP-40 and incubated on ice for 30 min prior to centrifugation (100,000 g, 30 min, 4°C) to obtain microsomal supernatant fractions. Cytosolic and microsomal protein concentrations were assessed according to the method of Bradford [36].

Equal amounts of cytosolic/microsomal fraction protein were resolved by SDS-PAGE and subjected to immunoblotting using rabbit anti-IRS-1 (New England Biolabs, Hitchin, Hertfordshire, UK), mouse anti-phosphatidylinositol 3′-kinase (PI3K) p85 subunit (BD Biosciences, Oxford, Oxfordshire, UK), rabbit anti-PI3K p110β subunit and anti-PKCβ1 (Santa Cruz Biotechnology, Santa Cruz, CA, USA), mouse anti-glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (Applied Biosystems, Warrington, Cheshire, UK), rabbit anti-PKB and anti-phospho-PKB Ser473 (New England Biolabs) antibodies. Blots were scanned and band intensity analysed using Image J software, normalised by comparison with an internal control human muscle lysate.

Data analysis

Insulin sensitivity was calculated from fasting and post-glucose plasma glucose and insulin concentrations using the Insulin Sensitivity Index (ISI) derived by Matsuda and DeFronzo – i.e. 10000/√[(fasting glucose x fasting insulin) x (mean glucose during OGTT x mean insulin during OGTT)], which correlates highly with whole-body glucose disposal rate during a euglyaemic hyperinsulinaemic clamp [37].

Data were analysed using Statistica (version 6.0, StatSoft Inc., Oklahoma) and Minitab (version 14, Minitab Inc., Pennsylvania). Data were tested for normality using the Ryan-Joiner normality test and transformed as appropriate (determined using Box-Cox plots). General linear models were used to compare data between European and South Asian groups. As age and BMI were not identical between the two groups (although not significantly different), statistical analysis was undertaken both unadjusted and adjusted for age and BMI. Further adjustment was undertaken as appropriate to determine independence from potential confounders. Regression analysis was used to determine relationships between variables. A homogeneity-of-slopes regression model was used to identify whether the slope of relationships between variables differed between the South Asian and European groups. Where the slopes differed significantly between the two groups, univariate regressions were performed for the South Asian and European groups separately, otherwise univariate regressions were performed on the combined group to maximize statistical power. Partial correlations were undertaken where appropriate to adjust for the effect of potential confounders (such as age, BMI, fat mass and physical activity level) on relationships between variables. Statistical significance was accepted at the p<0.05 level.

Results

Anthropometric characteristics

Anthropometric data are presented in Table 1. There were no significant differences in age, BMI or body mass between South Asians and Europeans, but the South Asians were shorter; had greater total, trunk, arm and leg fat mass; and lower fat-free mass, and total, trunk and leg lean mass than the Europeans. These differences persisted after adjustment for age and BMI. Further adjustment for fat mass abolished differences in trunk, arm and leg fat between groups, indicating no significant differences in regional distribution between Europeans and South Asians.

Physical activity and dietary data

Neither habitual physical activity levels (Table 2), nor energy (South Asians: 8.8±2.0 MJ.day−1, Europeans: 9.4±2.0 MJ.day−1, p = 0.41), fat (71±18 g.day−1 vs 80±26 g.day−1, p = 0.19), carbohydrate (290±90 g.day−1 vs 260±50 g.day−1, p = 0.20) or protein (87±17 g.day−1 vs 98±25 g.day−1, p = 0.12) intake differed significantly between the South Asian and European groups. However, self-reported alcohol intake was significantly higher in the Europeans (South Asians: 3±7 g.day−1, Europeans: 20±17 g.day−1, p = 0.0002).

Exercise test data

Fitness and physical activity data are presented in Table 2 and Figures 1 and and2.2. South Asians had significantly lower VO2max values than Europeans, irrespective of the units of expression. These differences remained significant after adjustment for age, BMI and fat mass. South Asians had lower rates of fat oxidation than Europeans during sub-maximal exercise, whether intensity was expressed in absolute terms (i.e. ml.kg−1.min−1) (Figure 1A) or relative to VO2max (Figure 2A). This difference persisted after adjustment for age, BMI and fat mass. Carbohydrate oxidation rates in South Asians during sub-maximal exercise were similar to Europeans at the same relative exercise intensity (Figure 2B), and higher at the same absolute exercise intensity (Figure 1B).

Figure 1
Fat oxidation (A) and carbohydrate oxidation (B) during incremental submaximal exercise.
Figure 2
Fat oxidation (A) and carbohydrate oxidation (B) during incremental submaximal exercise.

Metabolic data

Metabolic data are presented in Table 3 and Figures 3 and and4.4. ISI and HDL-cholesterol were lower in South Asians than Europeans in unadjusted analysis; this persisted after adjustment for age, BMI and fat mass. Insulin AUC and 2-hour insulin were higher in South Asians than Europeans in unadjusted analysis and after adjustment for age and BMI. 2-hour insulin remained higher after further adjustment for fat mass. Although not different between groups in the unadjusted analysis, fasting insulin was higher in South Asians than Europeans after adjustment for age, BMI and fat mass. Adjustment for trunk fat mass, instead of total fat mass, did not alter the findings (data not shown). The significant difference in ISI (p = 0.044) and HDL-cholesterol concentrations (p = 0.004) between South Asian and Europeans was retained when data were adjusted for percentage body fat, rather than total fat mass, but with this adjustment the difference in fasting (p = 0.12) and 2-hour (p = 0.13) insulin concentrations between groups was lost. When ISI values were further adjusted for VO2max, or for the rate of fat oxidation fat oxidation during sub-maximal exercise at 55% VO2max, the significant difference between South Asian and European groups was abolished (p = 0.16 and 0.12, respectively). Resting metabolic rate and rate of fat oxidation (expressed per kg fat-free mass) did not differ between groups.

Figure 3
Plasma insulin (A), glucose (B) and NEFA (C) responses to a 75 g oral glucose load.
Figure 4
Individual insulin sensitivity index values for the European and South Asian men.

Skeletal muscle mtDNA to nDNA ratio

The mtDNA to nDNA ratio in skeletal muscle did not differ between South Asians and Europeans (mean (95% CI) South Asians: 0.94 (0.71 to 1.21), Europeans: 1.13 (0.82 to 1.49), p = 0.39).

Skeletal muscle expression of oxidative and lipid metabolism genes

Expression of oxidative and lipid metabolism genes in skeletal muscle is shown in Table 4. Expression of carnitine palmitoyltransferase 1A (CPT1A) was 1.79-fold greater (p = 0.023) and expression of fatty acid synthase (FASN) was 1.96-fold greater (p = 0.036) in South Asians than Europeans.

Table 4
Oxidative and lipid metabolism gene expression in skeletal muscle in European and South Asian men.

Skeletal muscle insulin signalling protein expression

Insulin signalling protein expression data (and n for each variable) are shown in Table 5. Representative blots are shown in Figure 5. Technical difficulties limited these data to a sub-set of participants, and one outlier (>9 SDs from mean) for p110β PI3K subunit expression was excluded as its inclusion prevented data normalization. Expression of IRS-1, PI3K (p110β), PKB and PKCβ1 was principally observed in the soluble cytosolic fraction, whereas expression of PI3K (p85) was principally observed in the microsomal fraction (Figure 5). Cytosolic IRS-1 protein expression was significantly lower in South Asians than Europeans in unadjusted analysis, but this difference was abolished on adjustment (Table 5). Microsomal expression of the PI3K p85 subunit was ~50% lower in South Asians than Europeans; this remained significant after adjustment for age, BMI and fat mass (Table 5). Cytosolic PKB protein expression was also ~50% lower in South Asians than Europeans. This difference remained after adjustment for age and BMI, and became borderline significant after further adjustment for fat mass (Table 5, p = 0.054). Neither protein expression of the PI3K p110β subunit, nor protein expression of cytosolic or microsomal PKCβ1 differed significantly between groups. Ex vivo stimulation of muscle with insulin had no effect on the expression of IRS-1, PI3K (p85 or p110β), PKB or PKCβ1 in microsomal or soluble cytosolic fractions (Figure 5). Basal PKB phosphorylation at Ser473 was over 60% lower in South Asians than Europeans; this remained significant after adjustment (Table 5). Insulin-stimulated PKB phosphorylation did not differ significantly between groups (Table 5). The ratio of PKB phosphorylation at Ser473 to PKB expression did not differ significantly between South Asians and Europeans under either basal or insulin-stimulated conditions.

Figure 5
Insulin signalling molecule expression in subjects.
Table 5
Skeletal muscle insulin signalling protein expression in South Asian and European men.

Anthropometric and physiological correlates with insulin sensitivity index and insulin signalling protein expression

The regression slopes for these relationships did not differ significantly between South Asians and Europeans so data are presented for the combined group. As expected, square-root ISI correlated significantly with BMI (r = −0.373, p = 0.019), waist circumference (r = −0.387, p = 0.015) and trunk fat mass (r = −0.359, p = 0.025). Square-root ISI correlated significantly with height (r = 0.329, p = 0.041). None of the other measured body composition variables significantly correlated with square-root ISI.

In unadjusted univariate correlations, VO2max, expressed in ml.kg−1.min−1 (r = 0.399, p = 0.012) or ml.kg−1 fat-free mass.min−1 (r = 0.352, p = 0.028) correlated significantly with square-root ISI. In addition, fat oxidation during sub-maximal exercise at 55% VO2max, expressed in mg.kg−1.min−1 (r = 0.423, p = 0.011) (Figure 6) or in mg.kg−1 fat-free mass.min−1 (r = 0.409, p = 0.015), and fat oxidation at an absolute VO2 of 25 mg.kg−1.min−1 (r = 0.370, p = 0.029) correlated significantly with square-root ISI. Adjustment for age, BMI, fat mass and physical activity slightly attenuated the relationships. However, even after adjustment significant relationships were observed between square root ISI, and VO2max expressed in ml.kg−1 fat-free mass.min−1 (r = 0.318, p = 0.049) and fat oxidation during submaximal exercise at 55% VO2max, expressed in mg.kg−1.min−1 (r = 0.337, p = 0.048) or in mg.kg−1 fat-free mass.min−1 (r = 0.358, p = 0.035). Thus, independent of age, body composition and physical activity level, VO2max or fat oxidation during submaximal exercise explained 10-13% of the variance (i.e. r2) in square-root ISI.

Figure 6
Relationship between exercise fat oxidation and insulin sensitivity index (A) and basal PKB Ser473 phosphoryation (B).

Neither fat oxidation rate at rest nor resting metabolic rate (however expressed) correlated significantly with square-root ISI. In addition, fat oxidation rate at rest did not correlate significantly with fat oxidation rates during exercise (however expressed).

Basal PKB phosphorylation at Ser473 correlated significantly with square-root ISI (r = 0.407, p = 0.044) (Figure 7), and indices of body composition (significant negative correlations with total, arm, leg and trunk fat mass, and waist (r = −0.401 to −0.440, all p<0.05); and significant positive correlations with fat-free mass and total, leg and trunk lean mass (r = 0.538 to 0.546, all p<0.05)). In addition, basal PKB Ser473 phosphorylation was strongly correlated with VO2max, expressed in ml.kg−1.min−1 (r = 0.634, p = 0.001) or ml.kg−1 fat-free mass.min−1 (r = 0.539, p = 0.005); fat oxidation during exercise at 55% VO2max, expressed in mg.kg−1.min−1 (r = 0.475, p = 0.025) (Figure 4); and fat oxidation at an absolute VO2 of 25 mg.kg−1.min−1 (r = 0.588, p = 0.004). There was a borderline significant correlation between basal Ser473 PKB phosphorylation and fat oxidation during exercise at 55% VO2max, expressed in mg.kg−1 fat-free mass.min−1 (r = 0.406, p = 0.061). Although there was no relationship between basal and insulin-stimulated Ser473 PKB phosphorylation (r = 0.080, p = 0.705), and insulin-stimulated Ser473 PKB phosphorylation did not differ significantly between the South Asian and European groups, insulin-stimulated PKB phosphorylation at Ser473 also correlated significantly with square-root ISI (r = 0.427, p = 0.033) and indices of body composition (negative correlations with total and trunk fat mass, BMI and waist (r = −0.456 to – 0.533, all p<0.05)). However, insulin-stimulated Ser473 PKB phosphorylation did not correlate significantly with VO2max or fat oxidation during exercise, however expressed. None of the other measured insulin signalling proteins correlated significantly with square-root ISI, or any indices of body composition, but protein expression of IRS-1 correlated significantly with VO2max, expressed in ml.kg−1.min−1 (r = 0.677, p = 0.006) or ml.kg−1 fat-free mass.min−1 (r = 0.649, p = 0.009).

Figure 7
Relationship between basal PKB Ser473 phosphoryation and insulin sensitivity index.

Relationships between skeletal muscle and whole-body metabolism

Homogeneity-of-slopes regression analysis revealed significant interactions between South Asians and Europeans in the slope of the relationships between expression of a number of skeletal muscle genes and whole-body indices. South Asian and European groups were therefore considered separately in these analyses. There was a significant negative correlation between square-root ISI and log CPT1A gene expression in South Asians (r = − 0.533, p = 0.016), but not in Europeans (r = 0.035, p = 0.886). Expression of none of the other measured oxidative and lipid metabolism genes correlated significantly with square-root ISI in either group.

Figure 8 shows the relationships between fat oxidation during exercise at 55% VO2max, expressed in mg.kg−1.min−1 and skeletal muscle expression of oxidative and lipid metabolism genes in the South Asian and European groups. In general, positive associations were seen between skeletal muscle gene expression and fat oxidation during exercise in the Europeans, with significant positive correlations observed with fat oxidation during exercise and skeletal muscle CS, FASD3, HADHA, CD36, ACACA, ACACB, CPT1A and COX1 gene expression (r = 0.487 to 0.697, all p<0.05). In contrast negative association were seen in South Asians between fat oxidation during exercise and skeletal muscle CS, FADS3, HADHA, ACACA, ACACB and CPT1A (r = −0.519 to −0.779, all p<0.05). For 10 of the 12 genes investigated, a significant interaction was observed between the European and South Asian groups in the relationship between skeletal muscle gene expression and fat oxidation during exercise (Figure 8). Expressing fat oxidation during exercise in mg.kg−1 fat-free mass.min−1 yielded essentially the same results.

Figure 8
Relationships between exercise fat oxidation and skeletal muscle expression of oxidative and lipid metabolism genes.

There were no significant correlations between skeletal muscle expression of any oxidative and lipid metabolism gene and VO2max in either the South Asian or the European group.

Discussion

We report four main novel findings from this study: 1) that South Asians oxidised less fat during submaximal exercise than Europeans, a difference which persisted after adjustment for age, BMI and fat mass; 2) that South Asians had reduced skeletal muscle expression of key insulin signalling proteins than Europeans; 3) that VO2max and fat oxidation during submaximal exercise correlated significantly with whole-body insulin sensitivity (and PKB Ser473 phosphorylation), independently of age and body composition; and 4) that the relationship between fat oxidation during submaximal exercise and skeletal muscle expression of oxidative and lipid metabolism genes differed between South Asians and Europeans. Collectively, these data indicate that reduced oxidative capacity and capacity for fatty acid utilisation at the whole-body level are key features of the insulin resistant phenotype observed in South Asians, but that this is not the consequence of reduced skeletal muscle expression of oxidative and lipid metabolism genes.

Low VO2max values are often [19], [20], [38], but not always [38], associated with insulin resistance in white European and American populations, and low cardiorespiratory fitness is an independent predictor of type 2 diabetes risk [39]. Cardiorespiratory fitness is closely associated with skeletal muscle lipid oxidative capacity [21][23] and it is likely that fitness influences insulin sensitivity, at least in part, via effects on muscle lipid metabolism [40], [41]. In the present report, adjusting ISI values for either VO2max or rate of fat oxidation during exercise abolished the difference in insulin sensitivity between the South Asian and European groups, and strong correlations were evident between VO2max and fat oxidation during exercise (r = 0.58 to 0.67, depending on units of measurement, all p<0.0005). This supports the suggestion that low oxidative capacity/capacity for fatty acid utilisation is a central feature of the South Asian insulin resistance phenotype, and highlights the fact that the lower cardiorespiratory fitness and reduced capacity to oxidize fat in this group are likely to largely reflect the same underlying mechanism. Interestingly, while South Asians oxidised ~40% less fat than Europeans during submaximal exercise, fat oxidation rates did not differ between the groups at rest, and fat oxidation during exercise, but not at rest, correlated with body insulin sensitivity. There are two potential reasons for this. Firstly, whole-body fat oxidation during exercise largely reflects fat oxidation in skeletal muscle. In the present study, fat oxidation increased ~3−6 fold during exercise compared to rest and this increase would almost exclusively be attributable to changes in skeletal muscle. In contrast, skeletal muscle only contributes about 20−30% of resting energy expenditure [42], thus whole-body fat oxidation at rest is to a large degree determined by tissues other than skeletal muscle. Thus, if skeletal muscle, rather than whole-body, fat oxidation is the key regulator of insulin sensitivity, the relationship would be more clearly revealed in whole-body measurements made during exercise rather than at rest. Secondly, it is possible that a deficiency in the capacity of muscle to oxidise fat becomes more evident when energy demand is high, and is thus revealed during exercise. These findings highlight the value of exercise testing in providing insights into muscle metabolism in a relatively non-invasive manner.

However, in contrast to the observations made at the whole-body level, South Asians did not exhibit lower expression of oxidative and lipid metabolism genes in skeletal muscle biospies than Europeans, and indeed expression of CPT1A and FASN were higher in South Asians. In addition, other than a negative correlation between expression of CPT1A and ISI in the South Asians – the opposite direction of the expected association – expression of none of these genes was related to whole-body insulin sensitivity. Furthermore, the mtDNA to nDNA ratio, which provides an index of mitochondrial biogenesis [43], did not differ between the two groups. Our data therefore indicate that reduced skeletal muscle expression of oxidative and lipid metabolism genes does not explain the increased insulin resistance observed in South Asians. These findings are broadly consistent with those of Nair and colleagues reported that Asian Indians living in the USA had increased skeletal muscle capacity for oxidative phosphorylation and a higher mitochondrial DNA copy number than age- and BMI-matched men of Northern European descent, concluding that mitochondrial dysfunction could not account for the Asian Indians' greater insulin resistance [9]. Thus, it seems likely that the reduced capacity of South Asians to oxidise fat during exercise represents a defect in substrate delivery to muscle, rather than in mitochondrial capacity to oxidise lipids. In Europeans, capacity for mitochondrial fat oxidation in ex vivo muscle biopsy samples has been shown to correlate strongly with whole-body fat oxidation during sub-maximal exercise (but not at rest) [21]; this is consistent with observations in the present study where positive correlations were observed between skeletal muscle expression of oxidative and lipid metabolism genes and fat oxidation during submaximal exercise in the European group. However, strikingly, this pattern was reversed in the South Asian group where negative correlations were observed between skeletal muscle gene expression and fat oxidation during exercise, and significant interactions in the relationships between skeletal muscle gene expression and fat oxidation during exercise were evident between the European and South Asian groups. Thus, the South Asians with the highest expression of oxidative and lipid metabolism genes oxidised the least fat during exercise. Conceivably, this might reflect a compensatory adaptation within muscle in response to impaired microvascular perfusion leading to reduced fuel delivery. While we have no data from the present study to support this suggestion, South Asian men have been shown to have impaired endothelial function in forearm resistance vessels [44] and reduced nitric oxide bioavailability both at rest and during exercise [45], which would be consistent with this hypothesis. Furthermore, there is clear evidence that skeletal muscle oxidative capacity [46][48], capacity for fat utilisation [47], [49] and insulin sensitivity [50][52], are governed not only by mitochondrial function, but also capillary density and recruitment. Clearly, further study is now needed to determine whether the increased insulin resistance and reduced ability to oxidise fat in South Asians, is a consequence of impairments in vascular function.

It is important to recognise that it is the mismatch between fatty acid mobilisation and oxidation, rather than a low ability of muscle to oxidise fat per se, which can lead to insulin resistance. Recent studies have shown improvements in insulin sensitivity with weight loss (which reduces fatty acid mobilisation [53]), in the absence of changes in oxidative capacity or fatty acid oxidation rates [53][55], and have shown that increasing fatty acid mobilisation by lipid infusion can abolish improvements in insulin sensitivity elicited by exercise training, despite fatty acid oxidation rates remaining elevated [53]. Thus, capacity for fatty acid oxidation clearly only provides one part of the story, and further study is needed to determine whether differences in fatty acid mobilisation exist between South Asians and Europeans that may contribute to the greater insulin resistance in the former group.

To the best of our knowledge, there have been no previously published data comparing insulin signalling molecule expression between any ethnic groups. Our novel data reveal that, in unadjusted analysis, South Asians had significantly lower protein expression of IRS-1, the p85 subunit of PI3K, PKB and basal PKB Ser473 phosphorylation. IRS-1 is the principal IRS involved in muscle insulin-stimulated glucose transport [56]. However, it is unclear from the literature the extent to which altered IRS-1 expression is a characteristic of insulin resistant conditions in humans. While reduced IRS-1 expression has been reported in muscle of individuals with type 2 diabetes or obese subjects [57], [58], other studies have reported no difference in muscle IRS-1 expression in subjects with polycystic ovary syndrome (PCOS) [59] insulin resistance [60], or type 2 diabetes [61], implying that changes in the insulin signalling pathway downstream of IRS-1 may play a more important role in human insulin resistance. The present data imply reduced IRS-1 signalling in South Asians, which may manifest as impaired insulin-stimulated glucose transport and a degree of insulin resistance in the muscle, although this did not correlate significantly with our whole-body measurement of insulin sensitivity. However, it is probable that this reduced IRS-1 expression is simply a consequence of the greater adiposity in the South Asian group, rather than a fundamental difference in the properties of South Asians' skeletal muscle, as the difference was abolished after adjustment for adiposity.

Our data also revealed lower expression of p85, yet unaltered expression of p110β subunit of PI3K in the muscles of South Asians compared to Europeans. Furthermore, the difference persisted after adjustment for age, BMI and fat mass, implying a fundamental difference in these aspects of insulin signalling between South Asian and European skeletal muscle. The implications, however, of altered PI3K p85 subunit expression on insulin resistance are somewhat unclear in the literature, in which the majority of studies have reported increased p85 expression to be associated with insulin resistance in human muscle and animals [62][65] and downregulation of p85 has been reported to reverse the inhibition of insulin-stimulated glucose transport in 3T3-L1 adipocytes caused by constitutively active PKB [66]. In contrast, reduced p85 expression has also been reported to be associated with obesity in a single study in placenta [67]. The reduction observed in South Asians in the current study is, therefore, in disagreement with many studies of insulin-resistant cohorts, yet this may reflect the requirement for an optimal level of p85 expression, whereby increased or decreased expression both have detrimental consequences in terms of insulin sensitivity.

PKB exists as three isoforms, α (Akt1), β (Akt2) and γ (Akt3), and studies in knockout mice have indicated that PKBβ is the principal isoform regulating glucose homeostasis [68], [69]. Impaired insulin-stimulated PKB phosphorylation/activity has been observed in skeletal muscle from subjects with type 2 diabetes or PCOS [70][72], yet other studies have reported no significant difference in insulin-stimulated PKB activity or phosphorylation in skeletal muscle of subjects with type 2 diabetes [63], [73], [74]. In the present study, PKB expression and phosphorylation at Ser473 was assessed with antibodies that do not distinguish between the different isoforms. Intriguingly, PKB protein expression was ~50% lower in South Asians than Europeans, although adjustment for age, BMI and fat mass, reduced this to borderline statistical significance (p = 0.054). Furthermore, basal Ser473 phosphorylation of PKB was over 60% lower in South Asians, a difference that persisted after adjustment for age, BMI and fat mass. In addition, expression correlated significantly with whole-body insulin sensitivity. The increased basal Ser473 phosphorylation observed in Europeans is unlikely to be a consequence of endogenous insulin associated with the muscle biopsies after washing, as South Asians exhibited higher fasting insulin concentrations. In addition, basal PKB serine 473 phosphorylation correlated strongly and significantly with whole-body fat oxidation rates during exercise, suggesting that differences in capacity for fat oxidation between Europeans and South Asians may influence insulin sensitivity via effects at this point in the insulin signalling pathway. In contrast to our findings on PKB, there were no differences between South Asian and European muscle in protein expression of cytosolic or microsomal PKC β1, which negatively regulates insulin signalling [75], suggesting that PKC β1 does not underlie the increased skeletal muscle insulin resistance observed in South Asians.

This study is not without limitations. We assessed insulin sensitivity from glucose and insulin responses to an oral glucose tolerance test, rather than using the gold-standard euglycaemic hyperinsulinaemic clamp. However, the insulin sensitivity index we used correlates well with clamp-derived measures of insulin sensitivity [37], has been widely accepted in the literature (>1000 citations in last decade), and was in our data set associated with skeletal muscle insulin signalling. In addition, we only assessed expression of insulin signalling proteins in the basal state – i.e. signalling protein expression in response to fasting insulin concentrations – and in response to maximal insulin stimulation. While the direction of the differences in expression in the basal data between South Asians and Europeans precludes potential confounding by differences in fasting insulin concentrations (South Asians had reduced signalling despite a tendency for higher insulin concentrations), this study does not provide data on insulin signalling across the range of physiological insulin doses and further study is needed to ascertain whether insulin signalling differs between South Asians and Europeans at insulin doses between basal and maximal. We also only measured gene expression of oxidative and lipid metabolism genes in skeletal muscle. None of these was lower in the South Asians than the Europeans, indicating that transcription of these genes is not defective in South Asian muscle, but further study is needed to determine whether differences in protein levels or activity of these enzymes exist between South Asian and European skeletal muscle. Finally, although the men were extensively phenotyped, we did not directly determine IMTG or skeletal muscle concentrations of lipid intermediates in this study and further investigation is needed to ascertain the extent to which these differ between South Asians and Europeans, and how they relate to capacity for fat oxidation during exercise and insulin sensitivity.

In summary, the present novel observations indicate that South Asians have reduced cardiorespiratory fitness and capacity for fat oxidation during exercise compared to matched Europeans, and these factors are associated with their lower insulin sensitivity, independent of adiposity, both at a whole body level and at the level of skeletal muscle PKB Ser473 phosphorylation. In particular, reduced basal PKB Ser473 phosphorylation appears to be an innate feature of South Asian, compared to European, muscle which is related to insulin resistance at the whole body level. However the reduced capacity for fat oxidation during exercise was not reflected in reduced skeletal muscle expression of oxidative and lipid metabolism genes, and the relationship between expression of these genes and whole-fat oxidation during exercise in South Asians was negative. This indicate that reduced skeletal muscle expression of oxidative and lipid metabolism genes does not explain the increased insulin resistance observed in South Asians, and further investigation is needed to elucidate the mechanisms underpinning the reduced capacity for fat oxidation in South Asians and how this relates to their reduced insulin sensitivity.

Supporting Information

Table S1

Primer sequences and Universal ProbeLibrary Set probe numbers used for qPCR. Where more than one transcript is shown for an individual gene, the primers are common to all transcripts.

(0.10 MB DOC)

Footnotes

Competing Interests: N. Hariharan was a paid employee of Wyeth (Pfizer) Pharmaceuticals. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.

Funding: This work was supported by a project grant from Diabetes UK (www.diabetes.org.uk) (Grant number: 06/0003224) and an award (Grant number: CVMD-GU-004) from the Translational Medicine Research Collaboration (www.tmrc.co.uk), a consortium made up of the Universities of Aberdeen, Dundee, Edinburgh and Glasgow, the four associated NHS Health Boards (Grampian, Tayside, Lothian and Greater Glasgow and Clyde), Scottish Enterprise and Pfizer (formerly Wyeth) Pharmaceuticals. The funders had no role in study design, data collection or decision to publish.

References

1. Lee J, Heng D, Chia KS, Chew SK, Tan BY, et al. Risk factors and incident coronary heart disease in Chinese, Malay and Asian Indian males: the Singapore Cardiovascular Cohort Study. Int J Epidemiol. 2001;30:983–988. [PubMed]
2. McKeigue PM, Ferrie JE, Pierpoint T, Marmot MG. Association of early-onset coronary heart disease in South Asian men with glucose intolerance and hyperinsulinemia. Circulation. 1993;87:152–161. [PubMed]
3. McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet. 1991;337:382–386. [PubMed]
4. McKeigue PM, Miller GJ, Marmot MG. Coronary heart disease in south Asians overseas: a review. J Clin Epidemiol. 1989;42:597–609. [PubMed]
5. Abate N, Chandalia M, Snell PG, Grundy SM. Adipose tissue metabolites and insulin resistance in nondiabetic Asian Indian men. J Clin Endocrinol Metab. 2004;89:2750–2755. [PubMed]
6. Chandalia M, Abate N, Garg A, Stray-Gundersen J, Grundy SM. Relationship between generalized and upper body obesity to insulin resistance in Asian Indian men. J Clin Endocrinol Metab. 1999;84:2329–2335. [PubMed]
7. Chandalia M, Lin P, Seenivasan T, Livingston EH, Snell PG, et al. Insulin resistance and body fat distribution in South Asian men compared to Caucasian men. PLoS ONE. 2007;2:e812. [PMC free article] [PubMed]
8. Forouhi NG, Rumley A, Lowe GD, McKeigue P, Sattar N. Specific elevation in plasma tissue plasminogen activator antigen concentrations in South Asians relative to Europeans. Blood Coagul Fibrinolysis. 2003;14:755–760. [PubMed]
9. Nair KS, Bigelow ML, Asmann YW, Chow LS, Coenen-Schimke JM, et al. Asian Indians have enhanced skeletal muscle mitochondrial capacity to produce ATP in association with severe insulin resistance. Diabetes. 2008;57:1166–1175. [PubMed]
10. Misra A, Vikram NK. Insulin resistance syndrome (metabolic syndrome) and obesity in Asian Indians: evidence and implications. Nutrition. 2004;20:482–491. [PubMed]
11. Forouhi NG, Jenkinson G, Thomas EL, Mullick S, Mierisova S, et al. Relation of triglyceride stores in skeletal muscle cells to central obesity and insulin sensitivity in European and South Asian men. Diabetologia. 1999;42:932–935. [PubMed]
12. Davey GJG, Roberts JD, Patel S, Pierpoint T, Godsland IF, Davies B, McKeigue PM. Effects of exercise on insulin resistance in South Asians and Europeans. J Exerc Physiol. 2000;3:6–11.
13. Razak F, Anand SS, Shannon H, Vuksan V, Davis B, et al. Defining obesity cut points in a multiethnic population. Circulation. 2007;115:2111–2118. [PubMed]
14. Kraegen EW, Cooney GJ. Free fatty acids and skeletal muscle insulin resistance. Curr Opin Lipidol. 2008;19:235–241. 10.1097/01.mol.0000319118.44995.9a [doi];00041433-200806000-00004 [pii]. [PubMed]
15. Kelley DE, Goodpaster BH. Skeletal muscle triglyceride. An aspect of regional adiposity and insulin resistance. Diabetes Care. 2001;24:933–941. [PubMed]
16. Bruce CR, Hawley JA. Improvements in insulin resistance with aerobic exercise training: a lipocentric approach. Med Sci Sports Exerc. 2004;36:1196–1201. [PubMed]
17. Kelley DE, Goodpaster B, Wing RR, Simoneau JA. Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol. 1999;277:E1130–E1141. [PubMed]
18. Hardy CP, Eston RG. Aerobic fitness of Anglo-Saxon and Indian students. Br J Sports Med. 1985;19:217–218. [PMC free article] [PubMed]
19. Bruce CR, Anderson MJ, Carey AL, Newman DG, Bonen A, et al. Muscle oxidative capacity is a better predictor of insulin sensitivity than lipid status. J Clin Endocrinol Metab. 2003;88:5444–5451. [PubMed]
20. Nyholm B, Nielsen MF, Kristensen K, Nielsen S, Ostergard T, et al. Evidence of increased visceral obesity and reduced physical fitness in healthy insulin-resistant first-degree relatives of type 2 diabetic patients. Eur J Endocrinol. 2004;150:207–214. [PubMed]
21. Sahlin K, Mogensen M, Bagger M, Fernstrom M, Pedersen PK. The potential for mitochondrial fat oxidation in human skeletal muscle influences whole body fat oxidation during low-intensity exercise. Am J Physiol Endocrinol Metab. 2007;292:E223–E230. [PubMed]
22. Venables MC, Achten J, Jeukendrup AE. Determinants of fat oxidation during exercise in healthy men and women: a cross-sectional study. J Appl Physiol. 2005;98:160–167. [PubMed]
23. Helge JW, Biba TO, Galbo H, Gaster M, Donsmark M. Muscle triacylglycerol and hormone-sensitive lipase activity in untrained and trained human muscles. Eur J Appl Physiol. 2006;97:566–572. [PubMed]
24. Marfell-Jones M, Olds T, Stewart A, Carter L. Potchefstroom, South Africa: ISAK; 2006. International standards for anthropometric assessment.
25. Bruce RA, Kusumi F, Hosmer D. Maximal oxygen intake and nomographic assessment of functional aerobic impairment in cardiovascular disease. American Heart Journal. 1973;85:546–562. [PubMed]
26. Taylor HL, Burskirk E, Henschel A. Maximal oxygen uptake as an objective measure of cardio-respiratory fitness. Journal of Applied Physiology. 1955;8:73–80. [PubMed]
27. Borg GA. Perceived exertion: a note on history and methods. Medicine and Science in Sports. 1973;5:90–93. [PubMed]
28. Frayn KN, Macdonald IA. Assessment of substrate and energy metabolism in vivo. In: Draznin B, Rizza R, editors. Clinical Research in Diabetes and Obesity Part I: Methods, Assessment, and Metabolic Regulation. Totowa NJ: Humana Press; 1997. pp. 101–124.
29. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395. [PubMed]
30. Fehily AM, Yarnell JW, Butland BK. Diet and ischaemic heart disease in the Caerphilly Study. Hum Nutr Appl Nutr. 1987;41:319–326. [PubMed]
31. Flatt JP, Ravussin E, Acheson KJ, Jequier E. Effects of dietary fat on postprandial substrate oxidation and on carbohydrate and fat balances. J Clin Invest. 1985;76:1019–1024. [PMC free article] [PubMed]
32. Melanson EL, Donahoo WT, Dong F, Ida T, Zemel MB. Effect of low- and high-calcium dairy-based diets on macronutrient oxidation in humans. Obes Res. 2005;13:2102–2112. [PubMed]
33. Henriksson KG. “Semi-open” muscle biopsy technique. A simple outpatient procedure. Acta Neurol Scand. 1979;59:317–323. [PubMed]
34. Andreasson K, Galuska D, Thorne A, Sonnenfeld T, Wallberg-Henriksson H. Decreased insulin-stimulated 3-0-methylglucose transport in in vitro incubated muscle strips from type II diabetic subjects. Acta Physiol Scand. 1991;142:255–260. [PubMed]
35. Moran CN, Barwell ND, Malkova D, Cleland SJ, McPhee I, et al. Effects of diabetes family history and exercise training on the expression of adiponectin and leptin and their receptors. Metabolism. 2010. S0026-0495(09)00545-9 [pii];10.1016/j.metabol.2009.12.026 [doi]. [PMC free article] [PubMed]
36. Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem. 1976;72:248–254. [PubMed]
37. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22:1462–1470. [PubMed]
38. Ostergard T, Andersen JL, Nyholm B, Lund S, Nair KS, et al. Impact of exercise training on insulin sensitivity, physical fitness, and muscle oxidative capacity in first-degree relatives of type 2 diabetic patients. Am J Physiol Endocrinol Metab. 2006;290:E998–1005. [PubMed]
39. Wei M, Gibbons LW, Mitchell TL, Kampert JB, Lee CD, et al. The association between cardiorespiratory fitness and impaired fasting glucose and type 2 diabetes mellitus in men. Ann Intern Med. 1999;130:89–96. [PubMed]
40. Goodpaster BH, Katsiaras A, Kelley DE. Enhanced fat oxidation through physical activity is associated with improvements in insulin sensitivity in obesity. Diabetes. 2003;52:2191–2197. [PubMed]
41. Goodpaster BH, Brown NF. Skeletal muscle lipid and its association with insulin resistance: what is the role for exercise? Exerc Sport Sci Rev. 2005;33:150–154. [PubMed]
42. Zurlo F, Larson K, Bogardus C, Ravussin E. Skeletal muscle metabolism is a major determinant of resting energy expenditure. J Clin Invest. 1990;86:1423–1427. [PMC free article] [PubMed]
43. Williams RS, Salmons S, Newsholme EA, Kaufman RE, Mellor J. Regulation of nuclear and mitochondrial gene expression by contractile activity in skeletal muscle. J Biol Chem. 1986;261:376–380. [PubMed]
44. Murphy C, Kanaganayagam GS, Jiang B, Chowienczyk PJ, Zbinden R, et al. Vascular dysfunction and reduced circulating endothelial progenitor cells in young healthy UK South Asian men. Arterioscler Thromb Vasc Biol. 2007;27:936–942. [PubMed]
45. Cubbon RM, Murgatroyd SR, Ferguson C, Bowen TS, Rakobowchuk M, et al. Human exercise-induced circulating progenitor cell mobilization is nitric oxide-dependent and is blunted in South Asian men. Arterioscler Thromb Vasc Biol. 2010;30:878–884. ATVBAHA.109.201012 [pii];10.1161/ATVBAHA.109.201012 [doi]. [PubMed]
46. Riou ME, Pigeon E, St Onge J, Tremblay A, Marette A, et al. Predictors of cardiovascular fitness in sedentary men. Appl Physiol Nutr Metab. 2009;34:99–106. [PubMed]
47. Saltin B, Kiens B, Savard G, Pedersen PK. Role of hemoglobin and capillarization for oxygen delivery and extraction in muscular exercise. Acta Physiol Scand. 1986;556(Suppl):21–32. [PubMed]
48. Hepple RT, Mackinnon SL, Goodman JM, Thomas SG, Plyley MJ. Resistance and aerobic training in older men: effects on VO2peak and the capillary supply to skeletal muscle. J Appl Physiol. 1997;82:1305–1310. [PubMed]
49. Kiens B, Essen-Gustavsson B, Christensen NJ, Saltin B. Skeletal muscle substrate utilization during submaximal exercise in man: effect of endurance training. J Physiol. 1993;469:459–478. [PubMed]
50. Hedman A, Berglund L, Essen-Gustavsson B, Reneland R, Lithell H. Relationships between muscle morphology and insulin sensitivity are improved after adjustment for intra-individual variability in 70-year-old men. Acta Physiol Scand. 2000;169:125–132. [PubMed]
51. Lillioja S, Young AA, Culter CL, Ivy JL, Abbott WG, et al. Skeletal muscle capillary density and fiber type are possible determinants of in vivo insulin resistance in man. J Clin Invest. 1987;80:415–424. [PMC free article] [PubMed]
52. Lithell H, Lindgarde F, Hellsing K, Lundqvist G, Nygaard E, et al. Body weight, skeletal muscle morphology, and enzyme activites in relation to fasting serum insulin concentration and glucose tolerance in 48-year-old men. Diabetes. 1981;30:19–25. [PubMed]
53. Schenk S, Harber MP, Shrivastava CR, Burant CF, Horowitz JF. Improved insulin sensitivity after weight loss and exercise training is mediated by a reduction in plasma fatty acid mobilization, not enhanced oxidative capacity. J Physiol. 2009;587:4949–4961. jphysiol.2009.175489 [pii];10.1113/jphysiol.2009.175489 [doi]. [PubMed]
54. Berggren JR, Boyle KE, Chapman WH, Houmard JA. Skeletal muscle lipid oxidation and obesity: influence of weight loss and exercise. Am J Physiol Endocrinol Metab. 2008;294:E726–E732. 00354.2007 [pii];10.1152/ajpendo.00354.2007 [doi]. [PubMed]
55. Toledo FG, Menshikova EV, Azuma K, Radikova Z, Kelley CA, et al. Mitochondrial capacity in skeletal muscle is not stimulated by weight loss despite increases in insulin action and decreases in intramyocellular lipid content. Diabetes. 2008;57:987–994. db07-1429 [pii];10.2337/db07-1429 [doi]. [PubMed]
56. Sesti G, Federici M, Hribal ML, Lauro D, Sbraccia P, et al. Defects of the insulin receptor substrate (IRS) system in human metabolic disorders. FASEB J. 2001;15:2099–2111. [PubMed]
57. Stentz FB, Kitabchi AE. Transcriptome and proteome expressions involved in insulin resistance in muscle and activated T-lymphocytes of patients with type 2 diabetes. Genomics Proteomics Bioinformatics. 2007;5:216–235. [PubMed]
58. Brozinick JT, Jr, Roberts BR, Dohm GL. Defective signaling through Akt-2 and -3 but not Akt-1 in insulin-resistant human skeletal muscle: potential role in insulin resistance. Diabetes. 2003;52:935–941. [PubMed]
59. Rajkhowa M, Brett S, Cuthbertson DJ, Lipina C, Ruiz-Alcaraz AJ, et al. Insulin resistance in polycystic ovary syndrome is associated with defective regulation of ERK1/2 by insulin in skeletal muscle in vivo. Biochem J. 2009;418:665–671. [PubMed]
60. Hammarstedt A, Jansson PA, Wesslau C, Yang X, Smith U. Reduced expression of PGC-1 and insulin-signaling molecules in adipose tissue is associated with insulin resistance. Biochem Biophys Res Commun. 2003;301:578–582. [PubMed]
61. Krook A, Bjornholm M, Galuska D, Jiang XJ, Fahlman R, et al. Characterization of signal transduction and glucose transport in skeletal muscle from type 2 diabetic patients. Diabetes. 2000;49:284–292. [PubMed]
62. Friedman JE, Ishizuka T, Shao J, Huston L, Highman T, et al. Impaired glucose transport and insulin receptor tyrosine phosphorylation in skeletal muscle from obese women with gestational diabetes. Diabetes. 1999;48:1807–1814. [PubMed]
63. Bandyopadhyay GK, Yu JG, Ofrecio J, Olefsky JM. Increased p85/55/50 expression and decreased phosphotidylinositol 3-kinase activity in insulin-resistant human skeletal muscle. Diabetes. 2005;54:2351–2359. [PubMed]
64. Barbour LA, Mizanoor RS, Gurevich I, Leitner JW, Fischer SJ, et al. Increased P85alpha is a potent negative regulator of skeletal muscle insulin signaling and induces in vivo insulin resistance associated with growth hormone excess. J Biol Chem. 2005;280:37489–37494. [PubMed]
65. Hammarstedt A, Sopasakis VR, Gogg S, Jansson PA, Smith U. Improved insulin sensitivity and adipose tissue dysregulation after short-term treatment with pioglitazone in non-diabetic, insulin-resistant subjects. Diabetologia. 2005;48:96–104. [PubMed]
66. Adochio R, Leitner JW, Hedlund R, Draznin B. Rescuing 3T3-L1 adipocytes from insulin resistance induced by stimulation of Akt-mammalian target of rapamycin/p70 S6 kinase (S6K1) pathway and serine phosphorylation of insulin receptor substrate-1: effect of reduced expression of p85alpha subunit of phosphatidylinositol 3-kinase and S6K1 kinase. Endocrinology. 2009;150:1165–1173. en.2008-0437 [pii];10.1210/en.2008-0437 [doi]. [PubMed]
67. Colomiere M, Permezel M, Riley C, Desoye G, Lappas M. Defective insulin signaling in placenta from pregnancies complicated by gestational diabetes mellitus. Eur J Endocrinol. 2009;160:567–578. [PubMed]
68. Cho H, Mu J, Kim JK, Thorvaldsen JL, Chu Q, et al. Insulin resistance and a diabetes mellitus-like syndrome in mice lacking the protein kinase Akt2 (PKB beta). Science. 2001;292:1728–1731. [PubMed]
69. Cleasby ME, Reinten TA, Cooney GJ, James DE, Kraegen EW. Functional studies of Akt isoform specificity in skeletal muscle in vivo; maintained insulin sensitivity despite reduced insulin receptor substrate-1 expression. Mol Endocrinol. 2007;21:215–228. [PubMed]
70. Krook A, Roth RA, Jiang XJ, Zierath JR, Wallberg-Henriksson H. Insulin-stimulated Akt kinase activity is reduced in skeletal muscle from NIDDM subjects. Diabetes. 1998;47:1281–1286. [PubMed]
71. Karlsson HK, Zierath JR, Kane S, Krook A, Lienhard GE, et al. Insulin-stimulated phosphorylation of the Akt substrate AS160 is impaired in skeletal muscle of type 2 diabetic subjects. Diabetes. 2005;54:1692–1697. [PubMed]
72. Hojlund K, Glintborg D, Andersen NR, Birk JB, Treebak JT, et al. Impaired insulin-stimulated phosphorylation of Akt and AS160 in skeletal muscle of women with polycystic ovary syndrome is reversed by pioglitazone treatment. Diabetes. 2008;57:357–366. [PubMed]
73. Kim YB, Nikoulina SE, Ciaraldi TP, Henry RR, Kahn BB. Normal insulin-dependent activation of Akt/protein kinase B, with diminished activation of phosphoinositide 3-kinase, in muscle in type 2 diabetes. J Clin Invest. 1999;104:733–741. [PMC free article] [PubMed]
74. Meyer MM, Levin K, Grimmsmann T, Beck-Nielsen H, Klein HH. Insulin signalling in skeletal muscle of subjects with or without Type II-diabetes and first degree relatives of patients with the disease. Diabetologia. 2002;45:813–822. [PubMed]
75. Standaert ML, Bandyopadhyay G, Galloway L, Soto J, Ono Y, et al. Effects of knockout of the protein kinase C beta gene on glucose transport and glucose homeostasis. Endocrinology. 1999;140:4470–4477. [PubMed]

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