Three days before the first stable isotope experiment, subjects were asked to write down their food intake and to consume the same food items before every other stable isotope experiment.

Subjects were asked not to consume any products with a high abundance of 13 C carbohydrates derived from C4 plants such as maize and sugar cane 1 week before and during the entire experimental period.

Subjects were asked to refrain from physical activity 2 days before the sampling of the muscle biopsy and before the stable isotope experiments. Subjects trained three times per week for 12 weeks.

Training duration for subjects per session was Heart rate was monitored continuously during the training sessions Polar Electro, Oy, Finland. After 4 and 8 weeks of exercise training, a maximal aerobic exercise test was performed, and the training workload and duration were adjusted if necessary.

All training sessions took place at the university under the supervision of a professional trainer. One week before and after the training program, body density was determined by underwater weighing in the fasted state.

Body weight was measured with a digital balance, accurate to 0. Lung volume was measured simultaneously with the helium dilution technique using a spirometer Volugraph ; Mijnhardt. Body fat percentage was calculated using the equations of Siri Fat-free mass, in kilograms, was calculated by subtracting fat mass from total body mass.

One week before and after the training program, each subject performed an incremental exercise test on an electronically braked cycle ergometer Lode Excalibur to determine maximal oxygen consumption V o 2max and maximal power output W max.

Subjects started cycling at 75 W for 5 min. Thereafter, workload was increased by 50 W every 2. When subjects were approaching exhaustion, as indicated by heart rate and subjective scoring, the increment was reduced to 25 W.

Heart rate was registered continuously using a Polar Sport tester Kempele, Finland. Oxygen consumption and carbon dioxide production were measured using open circuit spirometry Oxycon-β; Mijnhardt.

At a. after an overnight fast, subjects underwent an isotope infusion test. Teflon catheters were inserted in an antecubital vein for isotope infusion and retrogradely into a contralateral dorsal hand vein for sampling of arterialized venous blood.

After placement of the catheters, subjects rested on a bed, and the cannulated hand was placed in a hotbox, in which air was circulated at 60°C to obtain arterialized venous blood.

After 30 min, baseline oxygen consumption and carbon dioxide production was measured, and breath and blood samples were collected. Immediately thereafter, subjects were given an intravenous dose of 0.

Then, at time zero, a constant intravenous infusion of either [U- 13 C]palmitate 0. With these infusion rates, the amount of 13 C infused during palmitate and acetate infusion are similar. Blood samples and breath samples were taken at 0, , , and min at rest and , , and min during exercise.

At rest, V o 2 and V CO 2 were measured continuously during the first 90 min using open circuit spirometry Oxycon-β. During exercise, V o 2 and V CO 2 were measured immediately before the measurement of breath 13 CO 2 enrichment.

To determine the exact infusion rate, the concentration of palmitate in the infusate was measured for each experiment using analytical gas chromatography GC using heptadecanoic acid as internal standard see sample analysis.

The acetate concentration was measured in each infusate with an enzymatic method Boehringer Mannheim, Mannheim, Germany. Muscle biopsies were taken from the mid-thigh region from M.

vastus lateralis according to the technique of Bergstrom et al. The subjects were required to abstain from training or vigorous exercise 48 h before the biopsy.

The biopsy was used for isolation of total RNA using the acid phenol method of Chomozynski and Sacchi 28 , with an additional DNAse digestion step with concomitant acid phenol extraction and ethanol precipitation. The mRNA levels of LPL, hexokinase II, GLUT4, ACC2, and UCP3 were quantified by RT-competitive PCR For the assays, the RT reaction was performed from 0.

The competitive PCR assays were performed as previously described 30 — To improve the quantification of the amplified products, fluorescent dye-labeled sense oligonucleotides were used. The PCR products were separated and analyzed on an ALFexpress DNA sequencer Pharmacia with the Fragment Manager Software.

Total RNA preparations and RT-competitive PCR assays of the two skeletal muscle samples from the same individual before and after weight loss were performed simultaneously. Oxygen saturation Hemoximeter OSM2; Radiometer, Copenhagen, Denmark was determined immediately after sampling in heparinized blood and used to check arterialization.

Fifteen milliliters of arterialized venous blood was sampled in tubes containing EDTA to prevent clotting and immediately centrifuged at 3, rpm 1, g for 10 min at 4°C.

Plasma substrates were determined using the hexokinase method Roche, Basel for glucose, the Wako NEFA nonesterified fatty acid C test kit Wako Chemicals, Neuss, Germany for FFAs, and the glycerolkinase-lipase method Boehringer Mannheim for glycerol and triglycerides. For determination of plasma palmitate, FFAs were extracted from plasma, isolated by thin-layer chromatography, and derivated to their methyl esters.

From palmitate oxidation, plasma-derived fatty acid oxidation was then calculated by dividing palmitate oxidation rate by the fractional contribution of palmitate to the total FFA concentration.

Differences in measured variables before and after training were tested using paired t tests. Repeated measures one-way ANOVA were used to detect differences in variables in time.

For testing differences in blood parameters between treatments, areas under the concentration versus time curve where calculated for 0— min at rest and — during exercise. On average, subjects completed a total of 31 ± 1.

Therefore, the average exercise duration per week was 2. The week training program had no influence on percentage body fat or V o 2max Table 1. At rest, total fat oxidation was not significantly influenced by the week training program ± 18 vs.

Similarly, plasma-derived fatty acid oxidation was not significantly influenced by the week training program ± 24 vs. Plasma-derived fatty acid oxidation during exercise was not significantly influenced by the training program ± 88 vs. Rate of appearance of FFA was not influenced by the training program, neither at rest ± 41 vs.

The percentage of R a that was oxidized was also not influenced by the training program, neither at rest 40 ± 4 vs. At rest, carbohydrate oxidation was not significantly affected by the training program ± 9 vs. Carbohydrate oxidation during exercise tended to be lower after training 1, ± vs.

Energy expenditure, both at rest 4. Acetate recovery, both at rest Plasma triglyceride concentrations Fig. Both at rest and during exercise, the average concentrations for plasma glucose at rest: 4. The week training program had no effect on two genes involved in the transport and oxidation of blood glucose: hexokinase II 2.

However, the expression of two genes encoding for key enzymes in fatty acid metabolism were affected by the training program: skeletal muscle ACC2 was significantly lower after training ± 24 vs. The expression of UCP3 The effect of endurance training on the contribution of different fat sources to total fat oxidation after endurance training is under debate.

Part of this controversy could be explained by the methodological difficulties in using [ 13 C]- and [ 14 C]-fatty acid tracers to estimate the oxidation of plasma fatty acids, especially in the resting state However, Sidossis et al.

We showed that this acetate recovery is reproducible 25 but has a high interindividual variation and is influenced by infusion period, metabolic rate, respiratory quotient, and body composition 21 and therefore needs to be determined in every individual under similar conditions and at similar time points as the measurement of plasma-derived fatty acid oxidation.

In the present study, we therefore measured the acetate recovery factor at all time points in each individual both before and after the training program at least 7 days separated from the last training session to exclude the influence of the last exercise bout on the measurements and were therefore able to correct plasma-derived fatty acid oxidation rate for loss of label in the TCA cycle.

With the available stable isotope tracer methodology, we cannot distinguish between IMTG- or VLDL-derived fatty acid oxidation. Using electron microscopy, it has previously been shown that endurance-trained athletes have increased IMTG concentrations 36 , and because endurance athletes have an increased fat oxidation capacity, it seems logical that this increased IMTG storage after endurance training is an adaptation mechanism to allow IMTG oxidation during exercise.

The localization of the IMTG near the mitochondria would make these triglyceride pools an efficient source of substrate, especially during exercise. However, biochemical analysis of IMTGs is problematic, and therefore the use of IMTG remains controversial.

On the other hand, the contribution of VLDL-derived fatty acids to fat oxidation during exercise is also still under debate 18 , The increased expression of LPL mRNA after training, as observed in our study, which is in accordance with previous studies showing increased LPL activity after endurance training in rodents 38 , 39 , and the reduced plasma triglyceride levels after the training program suggest that VLDL-derived fatty acids contribute significantly to total fat oxidation.

Alternatively, an increase in LPL after training might serve to provide fatty acids for the replenishment of IMTGs that have been oxidized during exercise Certainly, further studies are needed to clarify the contribution of IMTG- and VLDL-derived fatty acid oxidation to total fat oxidation.

Another important aspect of the present study is that we have examined the effect of a low-intensity training program for only 2 h per week. Because endurance training has been shown to increase the capacity to oxidize fatty acids, it has been proposed to be beneficial in overcoming the disturbances in fat oxidation often observed in obesity and diabetes 9.

To investigate the mechanisms behind the changes in substrate oxidation after the endurance-training program, we measured mRNA levels of several genes involved in glucose and fatty acid metabolism. A muscle biopsy was taken 6—7 days before the training program and 6—7 days after the last training session to exclude the influence of acute exercise on mRNA expression.

The expression of two genes involved in regulatory steps of glucose metabolism, i. As mentioned above, mRNA expression of LPL, which hydrolyzes plasma triglycerides and directs the released FFAs into the tissue 22 , tended to increase after training, suggesting that the capacity of skeletal muscle to hydrolyze VLDL triglycerides may be improved by the training program.

Inside the muscle cell, ACC2 activity has recently been suggested to control the rate of fatty acid oxidation and triglyceride storage ACC2 catalyzes the carboxylation of acetyl-CoA to form malonyl-CoA, an intermediate that inhibits the activity of CPT1.

CPT1 catalyzes the rate-limiting step in the transfer of fatty acyl-CoA into mitochondria, where they undergo oxidation. Although we were not able to measure ACC2 enzyme activity, it is tempting to speculate that a decrease in ACC2 activity after training was responsible for the observed training-induced increase in fat oxidation.

Because high levels of malonyl-CoA have been associated with insulin resistance 42 , the reduction of ACC2 with endurance training could possibly be beneficial in the treatment of type 2 diabetes. Finally, we determined the expression of the human UCP3, which has recently also been implicated in the transport of fatty acids across the inner mitochondrial membrane In a cross-sectional study, we have previously found that UCP3 mRNA was lower in trained than in untrained subjects In the present study, we did not find a significant effect of the training program on UCP3 mRNA expression, suggesting that the training program was not severe enough to result in changes in UCP3 mRNA.

Remarkably, we recently found that, in the same study, UCP3 protein content was significantly decreased after training in all subjects The reason for the discrepancy between the effect of training on UCP3 mRNA expression and protein cannot be deduced from the present study but might involve posttranslational regulation, although the number of subjects is too limited to make such a conclusion.

The mechanism behind this adaptation seems to involve a chronic upregulation of LPL mRNA expression and a chronic downregulation of ACC2, potentially leading to lower malonyl-CoA concentration and less inhibition of CPT1.

In contrast to moderate- to high-intensity endurance training, the mild training protocol did not increase hexokinase II and GLUT4 expression, indicating that specifically fat oxidation was improved. This study was supported by a grant from the Netherlands Organization for Scientific Research NWO to P.

and a grant from the Netherlands Heart Foundation to D. The laboratories are members of the Concerted Action FATLINK FAIR-CT , supported by the European Commission.

The authors thank Paulette Vallier for help in mRNA analysis and Dr. Diraison for making and validating the ACC2 competitor. Address correspondence and reprint requests to Dr. Schrauwen, Department of Human Biology, Maastricht University, P. Box , MD Maastricht, the Netherlands. E-mail: p.

schrauwen hb. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes. Advanced Search.

User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 51, Issue 7. Previous Article Next Article. RESEARCH DESIGN AND METHODS.

Article Information. Article Navigation. Pathophysiology July 01 The Effect of a 3-Month Low-Intensity Endurance Training Program on Fat Oxidation and Acetyl-CoA Carboxylase-2 Expression Patrick Schrauwen ; Patrick Schrauwen.

This Site. Google Scholar. Dorien P. van Aggel-Leijssen ; Dorien P. van Aggel-Leijssen. Gabby Hul ; Gabby Hul. Anton J. Wagenmakers ; Anton J. Hubert Vidal ; Hubert Vidal. Wim H. Saris ; Wim H. Marleen A. van Baak Marleen A. These findings suggest that caffeine ingestion in the morning could be used by athletes as an ergogenic aid to help them avoid morning-induced reduction in muscle performance.

In addition, Boyett et al. These findings are partially in line with those of the present study, suggesting that acute caffeine intake before exercise serves as an effective ergogenic aid for reversing morning-induced reductions in resistance exercise performance and endurance-like performance.

Moreover, we did not control the sleep quality and quantity of the participants. Further, the present study was performed in active men; the results cannot, therefore, be directly extrapolated to women or sedentary populations, etc. Finally, the sample size was relatively small. Caffeine intake increases MFO and Fat max as well as VO 2 max independent of the time of day.

Caffeine increases MFO in the morning to a value similar to that seen without caffeine in the afternoon. A combination of acute caffeine intake and exercise at moderate intensity in the afternoon provides the best scenario for individuals seeking to increase MFO.

Further, the existence of a diurnal variation in MFO, Fat max and VO 2max was confirmed, with values for all being higher in the afternoon than in the morning. The present findings also support the notion that caffeine ingestion in the morning helps to increase MFO and Fat max levels during exercise in the afternoon.

These results support the use of caffeine as an ergogenic aid during training or competition during the morning. The combination of acute caffeine intake and exercise at moderate intensity in the afternoon seems to be the best scenario for individuals seeking to increase the amount of fat utilized during continuous aerobic exercise.

Whether higher doses of caffeine induce greater effects on whole-body fat oxidation during graded exercise tests and further improves endurance performance remains to be investigated.

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Ganio MS, Klau JF, Casa DJ, Armstrong LE, Maresh CM. Effect of caffeine on sport-specific endurance performance: a systematic review. J Strength Cond Res. Download references. We are grateful to Adrian Burton for language and editing assistance and to Harrison Sport Nutrition HSN store for its technical support.

Department of Physiology. Faculty of Medicine, University of Granada, Av. Mauricio Ramírez-Maldonado, Lucas Jurado-Fasoli, Jonatan R. Centre for Sport Studies, Rey Juan Carlos University, Madrid, Spain. You can also search for this author in PubMed Google Scholar.

MRM carried out the study procedures, and drafted the manuscript; LJF conceived of the study, discussed the results, revised the manuscript and approved the final version; JcC discussed the results, revised the manuscript and approved the final version; JRR conceived of the study, discussed the results, revised the manuscript and approved the final version; FAG conceived of the study, and participated in its design and coordination, drafted the manuscript and revised and approved the final version.

Correspondence to Francisco J. All subjects provided oral and written informed consent before their enrolment.

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All participants provided their written informed consent before the laboratory measurements. Statistical analysis was carried out with IBM SPSS Statistics A one-way random model was used to calculate the intraclass correlation coefficients ICCs between the MZ co-twins. An ICC compares within-pair variation with between-pair variation and thus explains how similar the co-twins are when compared with the other pairs.

Pairwise correlations and differences were analysed with Pearson correlation coefficient and paired-sample t test, respectively. Twin individual-based correlations were analysed with simple linear regression, and the within-pair dependency was taken into account Williams with the clustering option of Stata.

In all regression analyses, RFO or PFO was treated as the dependent variable. All the variables or the regression analysis residuals were determined normally distributed with the Shapiro—Wilk test or with the visual inspection of the histograms and the normality plots. The p value 0.

For clarity, RFO or PFO without a unit symbol is used in the text when the statistical significance persists both when using absolute or LBM relative values in the analysis.

Table 1 presents the participant characteristics. Overall, the study population consisted of healthy men aged 32—37 years with varying physical activity, body composition and cardiorespiratory fitness levels.

The calculated ICCs of the resting metabolism variables and PFO showed significant resemblance between co-twins Table 2. We also categorised the co-twins as more active or less active based on their month LTMET index to calculate pairwise correlations Figs.

This division did not lead to significant mean differences between the groups in RFO 0. Pairwise correlations of a absolute and b lean body mass LBM relative resting fat oxidation RFO in 21 MZ twin pairs.

Pairwise correlations of a absolute and b lean body mass LBM relative peak fat oxidation PFO during exercise in 19 MZ twin pairs. Figure 3 illustrates individual RFO and PFO results and within-pair relationships.

As reported earlier Rottensteiner et al. However, there were no differences in REE, RER at rest or RFO between active and inactive co-twins. On average, the active co-twins tended to have higher PFO rates and lower FAT MAX when compared with the inactive co-twins, but the differences were not statistically significant.

Figures include group means and standard deviations. Colours represent the same twin pairs in both charts. Note the different scale in the y -axis. RFO or PFO were not correlated with fasting glucose, fasting insulin or the Matsuda index in the twin individual-based analysis Table 4.

For the first time, our study data showed that fat oxidation rates at rest and during exercise were similar between MZ co-twins, even though the study group was enriched with pairs who had discordant LTPA habits.

The co-twins also exhibited similar FAT MAX values and thus tended to reach PFO at the same absolute exercise intensities. The finding supports those of Toubro et al.

In a study involving male MZ twin pairs Bouchard et al. As the researchers also investigated the substrate use of dizygotic twins, they were able to control their analysis for the common environmental effect. Their calculated heritability estimates ranged from 0.

However, as RER only describes the relative use of energy substrates, this study broadens the concept by showing that absolute fat oxidation rates behave accordingly and supports the earlier suggestion that genes play a role in determining fat oxidation capacity during exercise Jeukendrup and Wallis ; Randell et al.

This assumption seems evident, as the large cross-sectional studies investigating fat oxidation during exercise have been able to describe only partly the observed inter-individual variability in PFO Venables et al. We identified a subpopulation of MZ twin pairs, where the co-twins differed in their past 3-year LTPA.

In this study, we found no differences between the co-twins in their systemic energy metabolism at rest or during exercise. In previous observational studies, PFO was associated with self-reported physical activity Venables et al.

However, it is highly likely that physical activity participation and fat oxidation capacity have shared genetic factors, and the relationship noted in observational studies is partly genetically mediated.

In experimental studies, endurance-training interventions commonly increased PFO, at least in untrained populations reviewed by Maunder et al. Earlier mechanistic evidence from our laboratory also supports the role of physical activity as a modulator of PFO.

In same-sex twin pairs, an over year long physical activity discordance led to significant differences in myocellular gene expression related to oxidative phosphorylation and lipid metabolism Leskinen et al.

The effects of physical activity on RFO have been investigated less, with mixed results. A modest increase in fat oxidation rates at rest has been reported in some Barwell et al. When the current scientific evidence is taken together with our results, physical activity seems to be able to influence PFO, while its effect on RFO is questionable.

However, we found no association between PFO and the Matsuda index, our main surrogate of insulin sensitivity. As explained in the methods section, the Matsuda index is influenced by fasting values, which were not associated with PFO in our study. Previously, Robinson et al.

As Robinson et al. However, it should be mentioned that PFO does not always seem to be associated with a healthier metabolic phenotype because an obesity-related increase in fatty acid availability has also been linked to higher PFO Ara et al.

In contrary to PFO, RFO was not associated with a healthy metabolic response to the OGTT. Previous studies have noted mixed findings. Rosenkilde et al.

However, there were no differences in fasting glucose or insulin levels between the groups. Some case—control studies Perseghin et al. An elevated RFO could potentially function as a protective mechanism against insulin resistance Perseghing et al. Overall, further research is needed to clarify the interaction between systemic fat oxidation and metabolic health.

Our study has both strengths and limitations. A key strength was our ability to measure RFO and PFO in 21 and 19 MZ twin pairs, respectively. This enabled us to investigate the influence of hereditary factors on RFO and PFO in a reasonably sized study group.

The calculated ICCs represent the upper bound of heritability, as differences between MZ twins are due to non-genetic factors. However, as MZ twin pairs share also many aspects of their development and environment, the actual heritability of the trait may be lower.

A more precise estimation of heritability would require several kinds of relatives for quantitative trait modeling or very large study population for measurement of all genetic variation by whole genome sequencing. Additionally, since our study included only males, the results cannot be generalised to females.

This enabled us to conduct a more in-depth examination of the possible associations between fat oxidation and metabolic health. However, our study protocol was not optimal for PFO determination, which should be considered when interpreting the results.

Nutrition intake the day before Støa et al. In this study, we did not control for the nutrition intake before the exercise test. For example, this could partially explain why we did not find any association between RFO and PFO, as previously shown by Robinson et al. Moreover, we used 2-min exercise stages during PFO testing.

The 2-min stages might be too short to reach a steady-state, especially for the subjects with lower cardiorespiratory fitness Dandanell et al. To assess whether the stage duration excessively affected the results, we compared VO 2 and VCO 2 between intervals 90— s and — s of the PFO-stage.

There were no systematic differences in VO 2 or VCO 2 between the intervals. Removing these participants from the analyses did not materially change the results.

Therefore, the influence of the stage duration was considered acceptable. Thus, the measurements seemed to reflect the PFO of our study participants. In conclusion, we show that fat oxidation rates at rest and during exercise are similar between MZ co-twins.

Our results support the suggestion that hereditary factors influence fat oxidation capacity. The internal factors likely set the baseline for fat oxidation capacity that the external factors can modulate. In our study, the role of physical activity seemed smaller, especially concerning RFO.

Furthermore, we observed that only higher capacity to utilize fatty acids during exercise associated with better metabolic health.

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Am J Physiol Endocrinol Metab 5 :E—E Flatt JP, Ravussin E, Acheson KJ, Jéquier E Effects of dietary fat on postprandial substrate oxidation and on carbohydrate and fat balances. J Clin Invest 76 3 — Fletcher G, Eves FF, Glover EI, Robinson SL, Vernooij CA, Thompson JL, Wallis GA Dietary intake is independently associated with the maximal capacity for fat oxidation during exercise.

Am J Clin Nutr 4 — Frayn KN Calculation of substrate oxidation rates in vivo from gaseous exchange. J Appl Physiol Respir Environ Exerc Physiol 55 2 — CAS PubMed Google Scholar. Goedecke JH, St Clair Gibson A, Grobler L, Collins M, Noakes TD, Lambert EV Determinants of the variability in respiratory exchange ratio at rest and during exercise in trained athletes.

Am J Physiol Endocrinol Metab 6 :E—E The HR was recorded continuously using an HR monitor Si, Polar Electro OY, Kempele, Finland.

During Test 1 and Test 2, HR and gas exchange data , collected during the final 5-min of the pre-exercise resting phase and during the last 2-min of each stage of the submaximal incremental exercise test were averaged and used for calculations.

RER was calculated as the ratio between and , while F ox and CHO ox were calculated using stoichiometric equations [7] , with the assumption that the urinary nitrogen excretion rate was negligible: 1 2.

F ox as a function of exercise intensity is reflected by two different linear relationships: a progressive decrease of 1—RER and a linear increase of as power output is increased.

The SIN model [12] was used to model and characterize whole-body F ox kinetics: 6. Dilatation d , symmetry s and translation t are the three independent variables representing the main modulations of the curve.

To fit the experimental data i. F ox rates and to model the F ox kinetics, the three variables were independently changed using an iterative procedure by minimizing the sum of the mean squares of the differences between the estimated energy derived from fat based on the SIN model and the energy derived from fat calculated from the raw F ox data, as described in a previous study [12].

For each subject, Fat max was calculated by differentiation of the SIN model equation. Graphical depiction of F ox values as a function of exercise intensity was performed by constructing a third polynomial curve with intersection at 0;0 [11].

Fat max was calculated by differentiation of the P3 equation, and corresponded to the intensity at which the value of the differentiated equation was equal to zero.

From the graphical representation of F ox values as a function of exercise intensity, the stage at which the value of measured F ox rates was maximal was determined, and the corresponding intensity was identified [3] , [8] — [10] , [23].

In order to investigate how the CV of and are linked to the CVs of parameters informing of substrate utilization RER, F ox , CHO fat , 1-RER, ENE fat three theoretical scenarios were created.

Data are expressed as the means ± standard deviation SD for all variables. Intra-individual CVs were calculated for the physiological variables studied in the three theoretical scenarios.

Two-factorial analysis of variance for repeated measures RMANOVA was carried out to test for systematic changes in: a Fat max , and physiological measures at Fat max factor 1: tests, factor 2: data analysis approaches , and b gas exchange data, HR and substrate oxidation rates factor 1: tests; factor 2: exercise intensity.

For the same outcome measures, one-way RMANOVA was carried out to test for systematic changes in the intra-individual CV at Fat max. Bland-Altman scatterplots are presented for Fat max and MFO determined with SIN, P3 and MV. They show the difference between two corresponding measurements plotted against the mean of the measurements.

Reference lines for the mean difference±1. Statistical analysis was performed with the software SPSS Fat max and physiological measures at Fat max determined with three data analysis approaches SIN, P3 and MV are presented in Table 2.

Average values for Fat max and related measures obtained with the three different approaches were also not significantly different i.

On the other hand, the within-individual CVs for Fat max determined with SIN was The Bland—Altman scatterplots for Fat max and MFO Figure 1 reveal considerable intra-individual variability.

A large between-individual difference in the variability between Test 1 and Test 2 was also seen. However, the size of the difference between Test 1 and Test 2 appeared to be independent of the average value between the two measurements. In both tests, the range of HR frequencies corresponding to the Fat max zone was broad it was 38±8 bpm, and ranged from 95±16 to ±20 bpm.

The course of average , , RER, HR, F ox and CHO ox in response to two identical submaximal graded test performed on separate days Test 1 and Test 2 is presented in Figure 2.

There was no significant difference between Test 1 and Test 2 in any of the parameters assessed. For instance, CVs for , and RER were 7. In contrast, CVs for CHO ox and F ox were markedly higher.

The CV for F ox was LoA between Test 1 and Test 2 are presented in Table 4. In case scenario 1 and 2, the CVs of F ox from were markedly different 3. From the analysis of the three theoretical scenarios as well as from the analysis of the whole dataset of 15 participants we also observed that the CV of F ox can be calculated from sum or subtraction of the CV of 1-RER and the CV of Appendix S1 , eq.

For example, in case 2, the CV of F ox was In case 3, the CV of F ox was In this study we assessed the reproducibility of Fat max measurements determined with three different data analysis approaches and of CHO ox and F ox at rest while sitting and in response to each stage of an individualized graded test.

The reproducibility of F ox values at each stage of a graded test, despite being a key aspect in the determination of Fat max , was previously unexplored.

In the current study, the CVs found for the parameters from which Fat ox is calculated , and RER were in line with previous observations. At rest, the CV for RER was 3.

In the present study the resting assessment was performed with the individuals in a seated position and this needs to be taken into consideration when making comparisons with studies in which resting metabolism was assessed with participants lying supine.

During exercise, the average CVs for , and RER were 3. This shows that even though CHO ox and F ox are calculated from and by means of the stoichiometric equations [7] , a low variability in those parameters is not necessarily indicative of low variability in CHO ox and F ox.

To further study how the CVs of and are related to the CVs of RER and the CV of F ox , three theoretical scenarios were created.

At present, scientific reports as well as companies validating calorimeters tend to draw information on the variability of substrate oxidation from the CVs of , and RER. The results of the theoretical scenarios Table 5 and the mathematical explanations presented in the appendix S1 illustrate that those CVs do not provide sufficient information on the variability of substrate oxidation rates.

As can be seen in case 2, when the and vary in different directions between two tests increase in and decrease in or viceversa , the variability of F ox is high. This is because in such conditions, the standard deviation of F ox results from the sum of the standard deviations of and , multiplied by a factor 1.

Therefore, in addition to the size of the change in and between tests, it is crucial to know whether they change in the same or opposite sense between measurements. The RER is the ratio between and and, therefore, provides information on the relationship between those measurements.

This is because the RER is value bounded in an interval separate from zero 0. On the other hand, the CV of 1-RER appears to be an informative marker on the variability in F ox rates: it provides the same results as the CV of ENE fat , it accounts for a large proportion of the CV of F ox , and it is simple to calculate.

In this study, as well as in other studies investigating the reproducibility of indirect calorimetry measures [8] , [13] , [14] , [16] — [19] , the total variation observed between Test 1 and Test 2 is the sum of both biological and equipment variation.

It was beyond the scope of this study to assess the relative contribution of each. However, the average variation of the equipment gas analysis system used in this study is known.

It was assessed using a portable metabolic simulator which excludes any biological variability and the average CV for and was 1. In addition to investigating the variability in F ox and related parameters at each stage of a graded test, a novel feature of this study was the assessment of the intra-individual variability in Fat max determined with the SIN model and its comparison with the variability of Fat max measures obtained using different data analysis approaches.

These results support the use of SIN over other approaches in future studies given that it is more reliable and provides more detailed information. The intra-individual variability of Fat max and related parameters found in this study was in line with those of Meyer et al.

Further, also consistent with the results published by Meyer et al. On the other hand, the CV for Fat max observed in this study, on average, was slightly higher than those reported in other studies [8] , [13] , [24]. The lower CV found by Achten et al.

This highlights the need for a better understanding of the determinants of intra-individual variability in Fat max. Previous studies in the field considered an intra-individual variability of ±10 bpm in the HR at Fat max acceptable, since this value reflects a realistic margin in individuals who use HR for the monitoring of training intensity [8] , [14].

In the present study this target was met by the majority, but not all, participants. Therefore, despite its variability, training prescription at Fat max ensures that high rates of F ox are elicited on different days.

The determination of F ox and Fat max and therefore the determination of their variability is influenced by a number of methodological factors including the exercise test design, the data analysis approach and the pre-test conditions.

In this study, a robust methodological approach was employed. The submaximal graded exercise was individualized based upon the results of a maximal test. Further, the statistical analysis was carried out in accordance with the recommendations for reliability assessment in sport medicine [15].

Pre-test conditions included a hour overnight fast and 24 hours of standardization in diet and physical activity prior to each submaximal graded exercise test.

This level of standardization was adopted because it appears to be the most commonly employed approach in our research field [3] , [8] , [28] — [32] and because more rigorous standardization is difficult to achieve both in out-clinic and research settings.

However, while more strict pre-test standardization leads to greater internal validity, it also leads to poorer external validity i. e harder translation of the results into practice. A number of questions on the reproducibility of substrate metabolism during exercise are still to be answered.

Further research is required to: a describe how standardization in physical activity and diet prior to testing impact on reliability of measurements, b study the determinants of the variability in CHO ox and F ox and c explore the reproducibility in F ox in other cohorts including overweight and untrained individuals.

The CV of 1-RER appears to be a more representative measure of the variability in substrate oxidation than CV of RER. In a research setting, differences in Fat max and F ox within and between groups can be detected as long as a sufficiently large number of participants is recruited.

Further research in this area is required. The authors would like to thank Aleš Neubert for mathematical inputs, and Graeme Macdonald and John Prins for helpful suggestions and criticisms. Conceived and designed the experiments: IC FB NB RW IH XC DM. Performed the experiments: IC FB XC DM.

Analyzed the data: IC FB XC DM. Wrote the paper: IC. Revised the manuscript for important intellectual content and approved the final version: IC FB NB RW IH XC DM.

The mechanism behind this adaptation seems to involve a chronic upregulation of LPL mRNA expression and a chronic downregulation of ACC2, potentially leading to lower malonyl-CoA concentration and less inhibition of CPT1.

In contrast to moderate- to high-intensity endurance training, the mild training protocol did not increase hexokinase II and GLUT4 expression, indicating that specifically fat oxidation was improved.

This study was supported by a grant from the Netherlands Organization for Scientific Research NWO to P. and a grant from the Netherlands Heart Foundation to D.

The laboratories are members of the Concerted Action FATLINK FAIR-CT , supported by the European Commission. The authors thank Paulette Vallier for help in mRNA analysis and Dr. Diraison for making and validating the ACC2 competitor.

Address correspondence and reprint requests to Dr. Schrauwen, Department of Human Biology, Maastricht University, P. Box , MD Maastricht, the Netherlands. E-mail: p. schrauwen hb. Sign In or Create an Account. Search Dropdown Menu.

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