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Effect of protein overfeeding on energy expenditure measured in a metabolic chamber

Background: Energy expenditure increases with overfeeding, but it is unclear how rapidly this is related to changes in body composition, increased body weight, or diet.

Objective: The objective was to quantify the effects of excess energy from fat or protein on energy expenditure of men and women living in a metabolic chamber.

Design: We conducted a randomized controlled trial in 25 participants who ate 40% excess energy for 56 d from 5%, 15%, or 25% protein diets. Twenty-four-hour EE (24EE) and sleeping EE (SleepEE) were measured on days 1, 14, and 56 of overfeeding and on day 57 while consuming the baseline diet (usually day 57). Metabolic and molecular markers of muscle metabolism were measured in skeletal muscle biopsy specimens.

Results: In the low-protein diet group whose excess energy was fat, the 24EE and SleepEE did not increase during the first day of overfeeding. When extra energy contained protein, both 24EE and SleepEE increased in relation to protein intake (r= 0.50, P = 0.02). The 24EE over 8 wk in all 3 groups was correlated with protein intake (r = 0.60, P = 0.004) but not energy intake (r = 0.16; P = 0.70). SleepEE was unchanged by overfeeding in the low-protein diet group, and baseline surface area predicted increased 24EE in this group. Protein and fat oxidation were reciprocally related during overfeeding. Observed 24EE was higher than predicted on days 1 (P ≤ 0.05), 14 (P = 0.0001), and 56 (P = 0.0007). There was no relation between change in fat mass and change in EE.

Conclusions: Excess energy, as fat, does not acutely increase 24EE, which rises slowly as body weight increases. Excess energy as protein acutely stimulates 24EE and SleepEE. The strongest relation with change in 24EE was the change in energy expenditure in tissue other than muscle or fat-free mass.

Full-text

Alex’s Notes: The idea of metabolic adaptation still exists in the grey zone. We know it occurs in response to underfeeding for reasons related to hormonal changes such as with leptin, and changes in bodyweight and activity levels, but adaptation in response to overfeeding is far less understood. Some but not all investigators believe that metabolic adaptation is one reason some individuals seem so resistant to weight gain. From a dietary perspective, much attention has been given to protein. Indeed, protein may play a central role in energy balance because of its greater energetic cost to utilize.

Additionally, some studies suggest that individuals adapt to overfeeding through dissipating some of the excess energy as heat. The study at hand was thus conducted to answer several questions:

  1. Does overfeeding produce changes in EE that exceed what is predicted from the change in metabolic body size measured as fat-free body mass and fat mass?
  2. If so, does this occur in both sleeping and total EE?
  3. Does the quantity of dietary protein intake affect the pattern of response?

To answer these, the current study is an analysis of data from a previous randomized, parallel arm, inpatient study that was designed to determine whether the level of dietary protein differentially affected body composition, weight gain, or energy expenditure under tightly controlled conditions.

Twenty-five healthy but sedentary men and women aged 18-35 years were randomly assigned to one of three different protein diets that were consumed while living within the research center for 12 weeks. None were obese, but the BMI range was 19.7 – 29.6 kg/m2 with an average of 25.2 kg/m2, suggesting that at least half the participants were overweight (and I doubt it was muscle given the sedentary lifestyle). These persons were overfed by about 40% of their weight maintenance energy requirements while following a diet supplying 5% (low-protein diet; LPD), 15% (normal-protein diet; NPD), or 25% (high-protein diet; HPD) of energy as protein.

  Baseline LPD - 5% NPD - 15% HPD - 25%
Calories (kcal/day) 2400 3130 3500 3440
Carbohydrate (g) 360 (60%) 340 (42%) 370 (41%) 375 (41%)
Fat (g) 70 (25%) 170 (52%) 160 (44%) 110 (33%)
Protein (g) 90 (15%) 47 140 228
Protein (g/kg BW) 1.83 0.68 1.80 3.01

All food was prepared by the research kitchen and consumed by the participants under researcher supervision to ensure both compliance and accuracy of the dietary protocols. Importantly, because carbohydrates are the middle-man between protein and fat in terms of thermogenic effects, carbohydrate intake was maintained throughout the overfeeding period in all diets.

Prior to beginning the intervention, the participants spent 2-3 weeks in a “baseline” period to establish maintenance energy requirements and perform baseline tests while consuming an isocaloric diet (see table above). The subjects returned to this diet on day 57, one day after the overfeeding intervention ended. Energy expenditure and substrate oxidation were measured over a 24 hour period at baseline, on days 1, 14, and 56 of the overfeeding, and on day 57, the first day immediately after the overfeeding when subjects consumed the baseline diet. Body composition was measured with DXA at baseline and every two weeks thereafter. Muscle biopsies were collected after 2 and 8 weeks of overfeeding.

Quick word on the original study

All the participants gained in the study gained weight with no significant differences between sex or ethnicity. The LPD gained significantly less weight than the NPD or HPD (about half as much), but this was only due to a failure for the LPD to increase lean-body mass. Indeed, fat mass gain was equivalent in all groups, but only the NPD and HPD gained lean body mass. In fact, looking at the graphs it appears that the LPD actually lost lean-body mass and gained slightly more fat mass than the other groups.

Overeating led to a significant increase in resting energy expenditure in both the NPD and HPD groups, which occurred mainly in the first 2 to 4 weeks and was not significantly different from one another. However, the resting energy expenditure in the LPD did not change significantly with overfeeding. It was found that the increase in resting energy expenditure was strongly related to protein intake. Similarly, it was found that extra energy intake predicted both the increase in lean body mass and body fat, while protein intake predicted the increase in lean body mass, but not the change in fat storage.

The differences in the metabolic efficiency of the diets are clear. The LPD stored more than 90% of the extra energy was as fat. In the NPD and HPD groups, only about 50% of the excess energy was stored as fat with most of the rest burned off as heat (thermogenesis). The high total energy expenditure probably reflects the higher cost of protein turnover and storage.

Returning to the study at hand

To continue to build on this picture of energy expenditure that we have started to build, the current analysis found that all groups experienced an evident increase in EE after each meal, as well as a decline during sleep. However, this decline was significantly attenuated in the NPD and HPD groups.

Nitrogen balance was found to increase in the NPD and HPD groups, but the LPD actually entered negative nitrogen balance, suggesting that a 40% overfeeding of fat does not have a protein sparring effect. This is supported by the fact that on the 57th day when the participants again ate the baseline diet (15% energy as protein); there was a quick turn towards positive nitrogen balance in the LPD group only.

Protein oxidation was inversely related to fat oxidation at days 1, 14, and 56 of overfeeding but not at baseline. Additionally, changes in EE reflected diet composition and not energy intake. For instance, there was no increase in total EE or sleep EE in the LPD, but both significantly increased in the other two groups. On day 57, when the diet was returned to baseline energy and protein levels, the total EE and sleep EE remained significantly above baseline in the HPD group only. The total EE was also higher on day 57 in the NPD group, but the sleep EE was not.

The researchers used the DXA body composition data and some equations to estimate the mass of the brain, skeletal muscle, bone, adipose tissue, and residual mass (liver, skin, viscera, etc.) in order to examine where the EE contributions were coming from. They found that all except adipose tissue had a significant correlation with EE throughout the day and during sleep. In fact, the increase in EE in the residual tissues during overfeeding accounts for nearly two-thirds of the increase in total EE in the NPD and HPD groups. Physical activity level was the same at baseline in each group and did not change during overfeeding, and there were some differences related to overfeeding in gene expression within skeletal muscle but no significant differences between dietary treatments.

Collectively, this suggests that it is not the skeletal muscle that sucks of the excess protein. Rather, it is organs such as the liver, kidneys, and intestines that had increased their energy utilization to catabolize the excess protein. This is supported by the absence of changes in the genes involved with protein synthesis (mTOR) and other genes associated with thermogenesis (UCP3 and ANT1) and muscle metabolism (AMPKA1, PPARgC1A, and COX5a).

Much of what is referred to as “adaptive” thermogenesis may thus be a reflection of changes in protein-induced thermogenesis occurring in tissues other than muscle. Nonetheless, some of the protein does venture towards muscle, as evidenced by the increased lean body mass of the NPD and HPD groups.

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