In this study we exposed lean, physically fit men to two ∼3 day dietary treatments, namely low‐CHO/high‐fat and starvation, which had in common significant restriction of CHO intake. We hypothesized that these diets would induce equivalent levels of IMTG accumulation and reductions of insulin sensitivity despite large differences in fat intake and energy content. All results were compared with those observed after the same period of a normal mixed diet.

We contend that in lean, healthy individuals, dietary CHO restriction independently mediates IMTG accumulation and insulin resistance. It seems teleologically sensible that insulin resistance and IMTG accumulation should occur as a co‐ordinated (non‐pathological) physiological response to CHO restriction. This is because the central nervous system (CNS), being obligate for CHO and not requiring insulin for glucose uptake, has priority over muscle for residual circulating glucose. Yet, at the same time, preservation of a non‐CHO intramuscular substrate is necessary for physical ability, and elevation of IMTG content fulfils this role ( Stannard & Johnson, 2004 ).

However, whilst insulin resistance may be caused by fat accumulation at a cellular level, it is not exclusively a function of dietary fat intake in the intact human. For example, in lean, healthy individuals, short‐term starvation reduces whole‐body and muscle insulin sensitivity ( Mansell & Macdonald, 1990 ; Webber et al. 1994 ). Starvation also elevates IMTG ( Stannard et al. 2002 ), which is largely a function of the increased circulating free fatty acid (FFA) concentration associated with energy restriction ( Cahill et al. 1966 ; Klein et al. 1993 ). Thus, a high‐fat diet and starvation are similar in that they both result in IMTG accumulation and concurrent whole‐body insulin resistance, despite the fact that they differ vastly in dietary fat and energy intake. Investigation is therefore required to ascertain the overarching role of diet in IMTG kinetics and insulin sensitivity in human physiology.

Differences in nutritional intake were compared by Student's paired t test. All basal measures (plasma glucose, insulin, FFA, blood β‐OH and IMCL:water) and differences in indices of glucose tolerance, insulin sensitivity and S g between conditions were compared by one‐way repeated measures ANOVA. Plasma glucose, insulin and FFA concentrations during IVGTT were compared by two‐way repeated measures ANOVA for investigation of treatment and time (diet–time) interactions. Pearson correlation coefficients (two‐tailed) were used to express the relationship between IMCL:water and S i and in IMCL:water content between dietary conditions. Statistical significance was accepted at P < 0.05. Calculations were performed using SPSS for Windows version 11. All values are expressed as means ±s.d.

Indices of estimated whole‐body insulin sensitivity were also obtained via: (a) the ratio of the AUC for plasma glucose to insulin (SI); (b) the method proposed by Galvin and coworkers which correlates highly (= 0.85) with insulin sensitivity measured via hyperinsulinaemic–euglycaemic clamp ():and (c) an index of insulin sensitivity (ISI) validated for the OGTT against the hyperinsulinaemic–euglycaemic clamp as described by, assuming its application to the IVGTT:where [glucose]is the resting glucose concentration, [insulin]is the resting insulin concentration, [glucose]is the mean concentration of glucose during IVGTT and [insulin]is the mean concentration of insulin during the IVGTT.

Glucose tolerance was determined by the rate of decline in plasma glucose concentration between 10 and 40 min of IVGTT () as outlined bywhere:A measure of glucose tolerance was also made by calculation of the area under the curve (AUC) for plasma glucose above the basal glucose concentration for glucosetime (). Insulin sensitivity index () and glucose effectiveness () were determined via the Minimal Model analysis of the plasma glucose and insulin response to IVGTT () using MINMOD Millenium (version 6.02, MinMod, University of Southern California, Los Angeles, CA, USA). Plasma insulin concentrations were converted from units of picomoles per litre to microunits per litre for these calculations (1 μU l= 6 pmol l). Plasma glucose was converted from units of millimols per litre to milligrams per decilitre (1 mmol l= 18 mg dl).

Plasma glucose concentration was measured by autoanalyser (EML, Copenhagen, Denmark). The plasma concentration of FFAs was determined using a Wako NEFA C Test kit (WAKO Chemical, Richmond, VA, USA) scaled for use in a microplate (Bio‐Rad, Hercules, CA, USA). The method of Ruell & Gass (1991) was used for the spectrophotometric determination of blood β‐OH concentration. All measurements were made in duplicate and the mean reported. Plasma insulin concentration was determined by microplate enzyme immunoassay (MEIA) using a fully automated procedure (AxSYM®, Abbot Laboratories, Sydney, Australia).

Prior to the IVGTT, 3 ml of venous blood was sampled by syringe, 0.75 ml of which was added to 1.5 ml of 0.6 m perchloric acid for later determination of blood β‐hydroxybutyrate (β‐OH) concentration. The remainder was transferred into EDTA, placed on ice and then centrifuged at 2000 g within 30 min of collection. The plasma was stored at −85°C and later analysed for FFA concentration. An additional 2 ml of venous blood was withdrawn into a lithium heparin‐pelleted syringe. This sample was mixed and rested on ice for ∼5 min, after which 1.3 ml was transferred into blood tubes, centrifuged at 2000 g , and the plasma frozen (−85°C) for later determination of plasma insulin concentration. Residual blood remained on ice in the lithium heparin‐pelleted syringe for later determination of plasma glucose concentration. Blood for glucose, insulin and FFA measurement was sampled according to these methods during the ensuing IVGTT (1 ml for EDTA) according to the sampling schedule outlined above.

Following determination of IMTG content, subjects reported to the laboratory where glucose tolerance was assessed by frequently sampled intravenous glucose tolerance test (IVGTT). Intravenous rather than oral glucose tolerance test (OGTT) was chosen in order to avoid potential confounding effects of diet (including starvation; Corvilain et al. 1995 ) on gastric emptying ( Horowitz et al. 1993 ) and subsequent glucose tolerance. Intravenous glucose tolerance test was undertaken after a 12 h overnight fast (C and LC; 67 h of dietary intervention). Venous cannulae were inserted into the antecubital veins of each arm. One cannula was used for glucose infusion and the other for venous blood collection. Basal blood samples were collected after 15 min at rest, following which the IVGTT was initiated. Participants rested in a supine position throughout the IVGTT. The subject was infused with 0.3 g kg −1 of glucose (50% anhydrous glucose with sodium bicarbonate or hydrochloric acid for pH adjustment; AstraZeneca, Sydney, Australia) via syringe evenly over 2 min. Glucose infusion was immediately followed by infusion of 10 ml of saline. Venous blood was sampled for determination of plasma glucose and insulin concentrations from the indwelling cannula in the contralateral arm at 3, 4, 5, 6, 7, 8, 10, 14, 19, 22, 25, 30, 40, 60, 70, 80, 100, 140 and 180 min after the initiation of glucose infusion ( Pacini & Bergman, 1986 ). All samples were collected within 15 s. Additional blood samples were collected at 15, 30, 60 and 120 min for determination of plasma FFA concentrations. Throughout the experiment, cannulae were kept patent by periodic flushing with saline.

After 65 h of each diet, vastus lateralis IMTG content was measured via proton magnetic resonance spectroscopy ( 1 H‐MRS). As is customary for 1 H‐MRS, IMTG content was determined by the methylene (—(CH 2 ) n ) resonance from intramyocellular lipid (IMCL) at 1.3 p.p.m. referenced to intracellular water ( Szczepaniak et al. 1999 ). High‐resolution T 1 ‐weighted imaging and image‐guided, localized 1 H‐MRS were performed on a 1.5 Tesla Gyroscan NT whole‐body system (Philips Medical Systems; Best, The Netherlands) using a combination of whole‐body and circular polarized standard extremity coils for radio frequency signal transmission and reception. Volumes of interest were centred within the vastus lateralis muscle at the level of mid‐femur. Legs were fixed with the thigh orientated so that the muscle fibres of the vastus lateralis were aligned with the magnetic field of the body coil. A vitamin E capsule was taped to the skin to identify the area of interest on the MR images. Image‐guided spectra were acquired using the PRESS technique (repition time [TR]= 5000 ms, spin echo time [TE]= 32 ms, 32 measurements, 1024 sample points; acquisition time, 3 min). Fully automated shimming was performed on a 5 cm × 1.5 cm × 1.5 cm voxel to ensure maximum field homogeneity. Excitation water suppression was used to suppress the water signal during data acquisition. Unsuppressed water spectra were acquired for use as an internal standard. Spectral data were processed with magnetic resonance user interface software (jMRUI version 1.1, EU Project ‘Advanced Signal Processing for Medical Magnetic Resonance Imaging and Spectroscopy’, TMR, FMRX‐CT97‐0160; Naressi et al. 2001 ) according to the constraints previously described ( Johnson et al. 2003 ). Absolute IMTG content was also calculated in mmol (kg wet weight [w.w.]) −1 using the internal reference of muscle water concentration by assuming a water concentration of 55 mmol (kg w.w.) −1 , a tissue water fraction of 0.81 and density of 1.05 ( Szczepaniak et al. 1999 ) and assuming an IMCL structure similar to trioleate (61.0 mmol of 1 H (ml triglyceride) −1 ).

Upon completion of exercise, subjects ingested a snack high or low in CHO content, according to their allocation to the C or LC condition, respectively. This liquid meal provided 1 g CHO (kg body weight) −1 (100% energy as CHO) in C or an isocaloric meal comprising 1% energy as CHO, 98% as fat and 1% as protein in the LC treatment. Subjects ingested an evening meal 2 h later prior to sleep. This meal comprised 1.5 g CHO (kg body weight) −1 as 50% CHO, 35% fat and 15% of energy as protein in C and an isocaloric meal with 2% CHO, 83% fat and 15% of energy as protein in the LC treatment. Beginning the following morning and continuing for the remainder of the dietary treatment (48 h), subjects received diets in both C and LC which provided energy to match a daily expenditure of 1.5 × RMR. This equated with the recommendations of the National Health and Medical Research Council (NHMRC) for resting energy requirement and light daily activity in young males ( NHMRC, 2003 ). Isocaloric provision of energy was intended to deliver 50% of energy as CHO, 35% as fat and 15% as protein in C and negligible CHO; ∼85% fat and 15% of energy as protein in LC. Thus, both the control (C) condition and LC dietary treatment were designed to provide enough energy to sustain metabolic requirement for rest and light activity, to be equal in protein and to differ only in CHO and fat content. After exercise in the S treatment, participants continued a water‐only diet until completion of the experimental treatment. Diet composition was quantified via Foodworks (Xyris Software®, Melbourne, Australia). In all dietary interventions, subjects were instructed to maintain activities of daily living and avoid all forms of recreational exercise.

As a standardized preconditioning measure prior to the initiation of the treatments, participants ingested a mixed meal that provided 1.5 g CHO (kg body weight) −1 with a macronutrient contribution of 50, 35 and 15% as CHO, fat and protein, respectively. Four hours after this meal, participants performed a 60 min bout of laboratory‐based cycling exercise at a workload calculated to elicit 65% of . This exercise (performed at the same power output for each individual prior to all experimental treatments), in combination with the control meal, was designed to standardize endogenous substrate availability prior to the dietary manipulation in addition to controlling for effects of exercise on subsequent insulin sensitivity and glucose tolerance. For further standardization, subjects were also required to record their exercise training and diet during the 24 h preceding the control exercise bout, and the same exercise and diet regime was followed prior to all dietary interventions.

All subjects underwent three dietary interventions, separated by at least 7 days. Each diet period was of 67 h duration and comprised: (a) water‐only starvation (S); (b) very low‐CHO/high‐fat intake (LC); or (c) mixed CHO control diet (C). These extreme diets were selected because they allowed the physiological responses to a normal versus low CHO intake to be examined (C versus LC and S), whilst controlling for protein (C and LC), fat (S and LC) and energy intakes (LC and C). The order in which dietary interventions were administered was randomized. Participants were supervised during all dietary interventions.

Resting metabolic rate (RMR) was determined within 1 week of initiation of the first diet manipulation. Subjects presented for assessment following a 12 h overnight fast. After resting supine for 30 min, respiratory gases were collected through a face‐mask connected to a two‐way rebreathable valve and Douglas bag. Expired respiratory gas was collected for 15 min, and mean calculated. Oxygen and CO 2 fractions of expired air were measured using zirconium cell‐based O 2 and CO 2 sensors (Pm111E; Ir1507, Servomex, Crowborough, UK). Both analysers were calibrated immediately before each test using gases of known composition. Pulmonary ventilation volume was measured by automated volume meter (Harvard, Edenbridge, UK). Body density was assessed via hydrodensitometry, and percentage body fat then calculated using a two‐compartment model, as described by Brozek et al. (1963) . The best of three measurements is reported. Underwater body weight measurements were corrected for estimated residual lung volume ( Goldman & Becklake, 1959 ).

One week prior to participation in the dietary intervention phases of the study, maximal oxygen uptake during cycling exercise was determined for each participant via electronically braked cycle ergometer (Schoberer Radmesstechnik, Konigskamp, Germany). The test required the subject to cycle at four submaximal steady‐state power outputs, followed by an incremental increase in power (45 W min −1 ) until volitional fatigue. Oxygen consumption was measured by the Douglas bag method and expired gas was collected for no less than 40 s immediately prior to fatigue for determination of . External power output and attained during the final 2 min of each submaximal workload and the maximal ramp were used to formulate regression equations from which workloads for the control exercise bout were derived.

Seven healthy, physically fit males volunteered for this study (age, 30.0 ± 6.0 years; weight, 72.8 ± 5.9 kg). All subjects reported regularly undertaking exercise for more than 1.5 h daily, at least 5 days per week. Participants were informed of the study protocol and risks before providing their written consent. The study was approved by the Human Research Ethics Committee of The University of Sydney and conformed with the Declaration of Helsinki.

Compared with C, ‘insulin sensitivity’ assessed by SI AUC was higher in LC and S ( P < 0.01 for both), indicating reduced insulin sensitivity in these treatments. SI Galvin and the ISI values indicated reduced insulin sensitivity in S ( P < 0.01 for both) but did not reach statistical significance between LC and C ( P = 0.08–0.09). No difference in insulin sensitivity was evident between S and LC as determined by SI Galvin ( P = 0.32), but SI AUC and ISI indices demonstrated lower insulin sensitivity in S versus LC ( P < 0.05 for both; Table 4 ).

Glucose tolerance as measured by K g was impaired in LC ( P < 0.05) and S ( P < 0.01). No difference in K g was evident between LC and S ( P = 0.29; Table 4 ). When compared with C, mean AUC for glucose was 83 and 122% higher in LC and S, respectively ( P < 0.01 for both; Table 4 ). The AUC for plasma glucose was also significantly higher in S compared with LC ( P < 0.01).

Insulin sensitivity index ( S i ) measured via the Minimal Model was significantly impaired in S when compared with C ( P < 0.05). There was a tendency for insulin sensitivity to be impaired in LC versus C although this did not reach statistical significance ( P = 0.08). There was no difference in insulin sensitivity index ( S i ) between LC and S ( P = 0.27; Table 4 ). There was no effect for diet on S g ( P = 0.55; Table 4 ).

In all dietary interventions, the plasma glucose concentration increased rapidly following intravenous glucose infusion, reaching a peak 5–10 min thereafter. Glucose concentration declined after this time and was not different between conditions by 140 min ( Fig. 2 A ). There was a significant diet–time interaction for the plasma glucose response to IVGTT ( P = 0.01). While no difference in glucose concentration was evident between dietary interventions 3–8 min after glucose infusion, plasma glucose concentration was significantly higher after this time in LC and S compared with C ( Fig. 2 A ). There was no difference in plasma glucose response to glucose infusion between LC and S ( Fig. 2 A ). For three data points, the plasma insulin concentration was lower than the limit detectable by the assay (< 6 pmol l −1 ). A value of 5 pmol l −1 was assumed for these instances. In addition, one sample was haemolysed, so the value was subsequently fitted to the curve from a polynomial (concentration versus time) fitted to the rest of the individuals insulin data. In all dietary interventions, the plasma insulin concentration increased rapidly following intravenous glucose infusion, reaching a peak between 4 and 8 min. Thereafter, insulin concentration declined and was similar to basal levels after ∼140 min in all dietary treatments ( Fig. 2 B ). There was no significant effect of diet on the plasma insulin response to glucose infusion ( Fig. 2 B ). Plasma FFAs are expressed for five subjects during IVGTT because multiple samples were haemolysed in one individual and insufficient blood was available from another. There was a significant difference in the plasma FFA concentration between dietary interventions during the IVGTT ( P < 0.01). Free fatty acids declined following glucose infusion, reaching a nadir at ∼60 min. There was a significant difference in the FFA response to glucose infusion between diets ( P < 0.05), with the decline in plasma FFAs following glucose infusion being more pronounced in S versus C between 0 and 30 min of the IVGTT ( Fig. 2 C ).

Following dietary intervention, the basal plasma glucose concentration was lower in S versus C ( P < 0.01) but was not different between LC and C ( P = 0.13). The basal plasma glucose concentration tended to be lower after S versus LC ( P = 0.06; Table 3 ). The basal plasma insulin concentration was significantly lower in S versus C ( P < 0.01) and in LC versus C ( P < 0.05). The basal plasma insulin concentration tended towards being lower after S versus LC ( P = 0.08; Table 3 ). The basal plasma FFA and blood β‐OH concentrations were higher in S versus C ( P = 0.01) and in LC versus C ( P < 0.01). Free fatty acids and β‐OH concentrations were higher in S versus LC ( P = 0.01; Table 3 ).

Owing to limited availability of the 1 H‐MRS, the period of dietary intervention was extended from 67 to 69 h for one subject. All other interventions for this individual were adjusted to 69 h, accordingly. The ratio of vastus lateralis IMCL:water was significantly higher in LC (13.6 ± 3.5 × 10 −3 ) and S (13.0 ± 2.4 × 10 −3 ) when compared with C (7.3 ± 3.2 × 10 −3 ; P < 0.01 for both). The ration of IMCL:water was not different between LC and S ( P = 0.46; Fig. 1 ). Calculated absolute IMTG content was 12.9 ± 5.3, 23.8 ± 6.0 and 22.6 ± 4.1 mmol (kg w.w.) −1 in C, LC and S, respectively. Intramyocellular triglyceride content in the treatment conditions demonstrated a high within‐subject correlation with that measured in C ( r = 0.94, LC versus C; r = 0.92, S versus C, P < 0.01 for both).

Carbohydrate intake in LC was significantly lower than in C ( P < 0.01), the diets providing 13.9 ± 0.9 and 392.0 ± 31.5 g kg −1 day −1 , respectively. Dietary fat intake was significantly higher in LC versus C ( P < 0.01; Table 2 ). Daily energy and protein intakes were not different between LC and C ( P > 0.05). Despite our efforts to abolish its intake, CHO consumption in LC was higher than that during S ( P < 0.01; Table 2 ).

Discussion

This study is the first to demonstrate that, when compared directly within the same individuals, IMTG accumulation consequent to a short‐term low‐CHO/high‐fat diet was comparable in magnitude to that evident after an equal period of total restriction of energy intake (starvation; P= 0.46, Fig. 1). Three days of low‐CHO/high‐fat intake and starvation had previously been independently shown to induce IMTG accumulation (Stannard et al. 2002) and insulin resistance (Bachmann et al. 2001) in lean, healthy individuals. Novel to this research was also the observation that these dietary interventions induced similar levels of impairment of Minimal Model‐derived insulin sensitivity (P= 0.27) and glucose tolerance (P= 0.29) in the same physically fit population (Table 4). Intramyocellular triglyceride accumulation and insulin resistance were similar in magnitude between low‐CHO/high‐fat (LC) and starvation (S) treatments, despite marked differences in fat (276 ± 22 versus 0 g day−1) and energy intake (12.5 ± 1.0 versus 0 MJ day−1), respectively.

Therefore, while our present findings concur with a notion of ‘lipid‐induced insulin resistance’ (Roden et al. 1996), IMTG accumulation and the development of insulin resistance following starvation are normal physiological responses mediated by an increase in adipose‐derived plasma FFAs. Whilst it is possible that the equivalent level of IMTG accumulation and insulin resistance observed after LC in the present study may have occurred by chance consequent to fat ingestion, we interpret this outcome as indicating that these diabetogenic perturbations are mediated by a common factor following starvation and low‐CHO/high‐fat diets, namely dietary CHO restriction. In contrast to CHO, fat intake has previously been shown to exert no effect on adipose lipolysis, whole‐body substrate selection or plasma FFA and insulin concentrations (Klein & Wolfe, 1992; Schwarz et al. 1995). Thus, we suggest that dietary‐induced IMTG accumulation and insulin resistance in healthy humans may be largely influenced by circulating FFAs, whose availability (in turn) is regulated by dietary CHO intake.

However, from the present data we cannot conclude that IMTG accumulation, glucose intolerance and insulin resistance were mediated exclusively by dietary CHO restriction and its effects on FFA availability. In other words, we cannot exclude a possible contribution of ‘non‐FFA’ lipid sources, such as plasma triglycerides (TAGs) and food‐derived chylomicrons to IMTG accumulation and insulin resistance (in LC). For example, whilst cessation of food‐derived chylomicron appearance and unchanged plasma triglyceride concentrations during starvation (Stannard et al. 2002) suggest that these metabolic alterations are solely a consequence of circulating FFA uptake and esterification, identification of any contribution from dietary lipids to IMTG formation and insulin resistance in LC would require isotope labelling of ingested lipid. Furthermore, an assumption of this study was that the low‐CHO/high‐fat diet (LC) employed would exert a physiological effect consistent with that observed following nil CHO ingestion. However, removing all the dietary CHO in the LC treatment was not possible if the diet was to contain the same energy and protein content as the control (C) treatment. Whilst both CHO‐restricted treatments significantly lowered basal plasma insulin and elevated FFA concentrations (Table 3), these outcomes were slightly but significantly augmented in S versus LC, possibly owing to the residual quantity of dietary CHO (and/or protein) ingested in the low‐CHO/high‐fat (LC) treatment. Despite this, insulin sensitivity and IMTG content were similar between S and LC conditions. Lastly, owing to the duration, macronutrient mix and energy content employed in the treatments, our results do not describe the time course of these metabolic responses and do not infer that CHO influences these diabetogenic alterations across a wide range of energy/fat intakes. We measured IMTG content and insulin sensitivity after 67 h of diet manipulation to equate with other literature reports of IMTG accumulation (Bachmann et al. 2001; Stannard et al. 2002) and insulin resistance (Webber et al. 1994; Bachmann et al. 2001) following starvation or high‐fat diets. It is likely that short‐term consumption of excess energy/fat intake may precipitate further IMTG formation (Fox et al. 2004) and possibly augment insulin resistance, although Fox et al. (2004) failed to demonstrate the latter after 24 h of excess fat consumption in healthy individuals.

Taken together, these findings provide support for our hypothesis that short‐term restriction of CHO intake independently influences IMTG accumulation and insulin resistance, at least under ‘normal’ dietary conditions, excluding those which promote weight gain and obesity. However, due to the design of the present study, we cannot exclude some role for dietary fat in these metabolic responses.

Owing to the difficulty in assessing insulin sensitivity from the variable plasma glucose and insulin concentrations observed during glucose tolerance tests, we employed several methods purported to evaluate the effect of insulin on circulating glucose disposal. In both healthy individuals and those with type 2 diabetes, Minimal Model‐derived insulin sensitivity (S i ) correlates highly (r= 0.8–0.9) with that determined by the hyperinsulinaemic–euglycaemic clamp (Bergman et al. 1987; Saad et al. 1994; Anderson et al. 1995). Our S i values are similar to those reported in two recent investigations using IVGTT and Minimal Model analysis in physically fit individuals (Goedecke et al. 2001; Schenk et al. 2005). The finding of similar Minimal Model‐derived insulin resistance between LC and S is intuitive given the marked glucose intolerance observed in these conditions yet similarity of the dynamic plasma insulin and glucose responses to glucose infusion between these treatments (Fig. 2). That a similar reduction of ‘insulin sensitivity’ between LC and S treatments was not confirmed by the ISI index (Matsuda & DeFronzo, 1999) or by the ratio of the area under the curve (AUC) for glucose:insulin (Table 4) is likely to be a reflection of differences in basal glucose and insulin concentrations between LC and S rather than differences in the dynamic glucose–insulin interaction.

In this investigation we observed a significant negative correlation (r=−0.63, P < 0.01) between IMTG concentration and Minimal Model insulin sensitivity (S i ) after 65–67 h of dietary manipulation (Fig. 3). This supports an increasing volume of evidence which links the excessive availability of circulating lipids (Roden et al. 1996; Bachmann et al. 2001), IMTG (Krssak et al. 1999; Goodpaster et al. 2001) and related intramyocellular fatty acid moieties (Schmitz‐Peiffer et al. 1999; Ellis et al. 2000; Boden et al. 2001; Itani et al. 2002) to impairment of insulin‐mediated blood glucose disposal. While confirming other reports of lipid‐induced IMTG accumulation in response to high‐fat diets (Bachmann et al. 2001) and artificial lipid infusion (Bachmann et al. 2001; Boden et al. 2001), our study provides support for the hypothesis that the physiological trigger for this coupling in the healthy individual may be a short‐term challenge to dietary CHO availability. That we have observed these diabetogenic alterations in a physically fit population, which is purported to be insulin sensitive yet exhibits high IMTG concentrations (the ‘athlete paradox’) (Goodpaster et al. 2001), supports our contention that they represent an adaptive rather than pathological response. This substantiates our previous assertion that alterations in glucose tolerance and insulin sensitivity associated with dynamic changes to the plasma and/or lean tissue lipid profile are part of a normal co‐ordinated adaptation to short‐term changes in food availability (Stannard & Johnson, 2004) and perhaps, more specifically, to fluctuations of dietary CHO availability.

Figure 3 Open in figure viewer PowerPoint Pearson correlation between individual IMCL:water and Minimal Model insulin sensitivity (S i ) following 65 h low LC, S and C n= 7 subjects.

The human organism has a limited capacity to store glucose yet an obligatory glucose requirement for CNS function. As a consequence, humans have an inherent need regularly to ingest food containing CHO or to reduce the metabolism of CHO at the expense of more readily available substrates when faced with restricted CHO availability or high rates of CHO metabolism. It has been well established that dietary CHO restriction results in the rapid mobilization of stored FFAs into the circulation, increased ketogenesis and fat oxidation and a reduced rate of glucose oxidation by skeletal muscle (Webber et al. 1994; Schwarz et al. 1995; Peters et al. 2001). This short‐term alteration is teleologically sound because it limits competition between skeletal muscle and glucose obligate tissues for circulating glucose substrate when its availability becomes limited. Irrespective of a causal relationship, the coupling between IMTG accumulation and reduced insulin sensitivity may also represent a co‐ordinated adaptive (non‐pathological) response to CHO stress (Stannard & Johnson, 2004). Upon CHO restriction, the partitioning of endogenous fatty acids from the adipose tissue to skeletal muscle would, in IMTG, provide an alternative energy source for muscle contraction when muscle glycogen formation is low. Intramyocellular triglyceride has been shown to become a more important substrate for exercise metabolism following short‐term CHO stress (Johnson et al. 2003). A concomitant resistance in muscle to the effects of insulin on glucose uptake during CHO stress maintains normoglycaemia and thus the preservation of plasma glucose for use by the CNS and glucose‐obligate tissues (Reaven, 1998). Dissociation of insulin action by way of muscle insulin resistance rather than attenuation of insulin secretion means that residual circulating insulin levels can be maintained (Klein et al. 1993), thereby preventing rampant proteolysis (Fryburg et al. 1990), lipolysis (Kather et al. 1985) and perhaps hepatic glucose release, whilst unnecessary uptake of blood glucose by muscle is prevented.

In conclusion, this investigation demonstrated that in the same lean, physically fit men, dietary‐induced elevation of intramyocellular triglyceride and impairment of glucose tolerance/insulin sensitivity were similar after 67 h of low‐CHO/high‐fat diet and the same period of starvation. These findings may indicate that short‐term dietary‐induced IMTG accumulation and the concurrent development of insulin resistance in physically fit men are mediated largely by dietary CHO restriction rather than fat intake.