Feedback Received, and a Scientific Basis for Fat Fueling During High-Intensity Exercise in Well-Tr


We appreciate the comments and feedback received in response to our recent study. There were two main themes of feedback expressed that we’ll address in this post. Response Theme 1:

“I’m surprised by the findings. Are they valid? Why the use of potentially invalid substrate oxidation equations?” We addressed this point in the discussion section of our paper, but it would be good to review. We state (p7-8): "We have estimated fat and carbohydrate oxidation based on indirect calorimetry using equations proposed for “high-intensity exercise” [10]. However, the intensity of exercise used in the present study exceeded the author’s guidelines for these equations. Substrate utilization calculations based on oxygen consumption and carbon dioxide release assume a steady state exercise intensity where lactic acid production and elimination are in equilibrium such that bicarbonate buffering of H+ by HCO3- does not ultimately contribute to non-oxidative CO2 removal via hypernea. Indirect calorimetry has been previously shown to be a valid method for quantifying rates of substrate oxidation up to about 85% of VO2max [15]. The peak exercise intensities used in the present study exceeded 85% of VO2max and net lactate production exceeded total elimination throughout the interval bout in WT, albeit only slightly after the first exercise bout. Stable CO2 production rates were seen in both WT and RT after the first work/recovery cycle, suggesting that the chosen paces during work and recovery elicited a quasi-equilibrium of lactate production and elimination. Furthermore, although we did not measure the HCO3- pool, the relatively stable lactate concentrations seen after the first work period suggest it to be stable [16,17]; a requirement for reliable estimations of fat oxidation from indirect calorimetry [15]. While contamination of non-oxidative sources to the VCO2 values is possible, this potential source of error contributes to underestimation, not overestimation, of fat oxidation."

New Info I met a new colleague at the recent Sport and Exercise Science New Zealand conference in Queenstown, Associate Professor David Rowlands, also a handy cyclist. I’m only discovering this now, but David did some important work in this area during his PhD. In our next post, I’ll talk about his key study, but briefly and related to the current issue, you can see in this figure how David made some corrections to the bicarb issue mentioned (red circle), so that a more realistic estimate of substrate oxidation at high exercise intensity is made (based on tracer studies).

The left panel of this figure shows the substrate oxidation over a six-stage progressive exercise test (like the runners in our study did), and also their response to a 100-km time trial (right panel). Note how the estimated fat contribution to incremental maximal exercise in these highly-trained cyclists is supplying at least a third of the energy at maximal exercise after fat oxidation is corrected. The dotted line shows the uncorrected value with the bicarbonate issue we outlined. More on this excellent study in our next post.

What Matters... As a close colleague kindly stated to us in Email correspondence: “What matters, and what is clear here, is that the fitter and faster guys show greater fat use than the less trained and slower ones, irrespective of the equation validity. We are assuming here that the validity, or lack thereof, would be the same for both groups. What needs to be discussed further is the actual magnitude of fat use, and also whether our results may be biased by the (potentially) unreliable equations.” “What we can be more confident in saying is that highly trained athletes manage to use more fat at high exercise intensities, since there is no evidence to suggest that the equation is more accurate in one population than the other.” That leads us to the important question: What is the scientific basis for a fat fuelling contribution to high-intensity exercise in well-trained athletes?

Response Theme 2:

“Duh guys… Aren't your findings kind of obvious?" Right. So a number of readers responded that they simply weren't that surprised by the findings. They would have expected as much to explain the differences in training status. Isn't that just what happens with training? Maybe it's not rocket science, but what we found is not what's stated in mainstream understanding and practice. What is often believed is that carbohydrate oxidation only fuels high-intensity exercise. Our new findings question the tenant: Should we be solely focused on maximising carbohydrate oxidation during high-intensity exercise or do we promote training strategies that elicit adaptations to maximise the use of both fuels? Regardless, there’s a fair bit of logic to support our main findings. That is, the 3-fold higher fat oxidation rates that explained the higher energy expenditure and running speed in the well- trained versus recreationally-trained runners.

To be clear, our study was cross-sectional in design, comparing two groups of runners with clearly different training backgrounds and aerobic capacities (above). However, you can fathom that the capacity to run fast and gather the energy needed to do so is due partly to the same progressive adaptations occurring in skeletal muscle that happen with training. The polarised approach to training used by various elite endurance athlete groups, which involves generally an 80:20 blend of high-volume and high-intensity training, may elicit similar downstream signalling at the cellular level (via AMPK, CaMK, which target the so-called 'master switch', PGC-1a). These signals with training, likely occurring also in progressively larger motor unit pools, ultimately lead to the enhancement of mitochondrial size and number and fat oxidative capacity (termed beta-oxidation).

From Laursen (2010). Simplified model of the adenosine monophosphate kinase (AMPK) and calcium–calmodulin kinase (CaMK) signaling pathways, as well as their similar downstream target, the peroxisome proliferator-activated receptor-g coactivator-1a (PGC- 1a). This ‘‘master switch’’ is thought to be involved in promoting the development of the aerobic muscle phenotype. High- intensity training appears more likely to signal via the AMPK pathway, while high-volume training appears more likely to operate through the CaMK pathway. ATP, adenosine triphosphate; AMP, adenosine monophosphate; GLUT4, glucose transporter 4; [Ca2+], intramuscular calcium concentration.

Here’s a schematic of a general cell (such as a muscle cell) from Marieb (2009) to remind us specifically

what we’re talking about. The signals from endurance training cause muscle cells to make more of those bean-shaped ATP-producing mitochondria (red circle), as well as the enzymes that feed more fat (their breakdown product - acetyl CoA) to those powerhouses. This beneficial adaptation enhances the capacity of the muscle cell to do work because more energy is available.

Figure 1. General schematic of a cell from Marieb (2009). Red circle showing the mitochondria, which change in size and number in response to the signals described above.

In summary, we appreciate the feedback received to date on our study as it pushes us to establish further clarity on the subject. While we acknowledge the study's limitations, we herein outline a plausible basis for substantial fat fuelling contribution during high-intensity exercise in well-trained athletes. In our next post, we’ll outline some practical considerations and methods to enhance fat oxidation rates and performance.


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