Abstract
Background:The purpose of this study was to investigate the effect of short-term supplementation of amino acids before and during a 100 km ultra-marathon on variables of skeletal muscle damage and muscle soreness. We hypothesized that the supplementation of amino acids before and during an ultra-marathon would lead to a reduction in the variables of skeletal muscle damage, a decrease in muscle soreness and an improved performance. Methods:Twenty-eight experienced male ultra-runners were divided into two groups, one with amino acid supplementation and the other as a control group. The amino acid group was supplemented a total of 52.5 g of an amino acid concentrate before and during the 100 km ultra-marathon. Pre- and post-race, creatine kinase, urea and myoglobin were determined. At the same time, the athletes were asked for subjective feelings of muscle soreness. Results:Race time was not different between the groups when controlled for personal best time in a 100 km ultra-marathon. The increases in creatine kinase, urea and myoglobin were not different in both groups. Subjective feelings of skeletal muscle soreness were not different between the groups. Conclusions:We concluded that short-term supplementation of amino acids before and during a 100 km ultra- marathon had no effect on variables of skeletal muscle damage and muscle soreness. Background Apart from the classical marathon distance of 42.195 km, an increasing number of studies of athletes partici- pating in ultra-marathons over 100 km [1-3] or further [4-6] has been published in recent years. Based on the high eccentric demands of these activities, marathon and ultra-marathon running as eccentric exercise lead to skeletal muscle damage resulting in an increase in myo- cellular enzymes such as plasma creatine kinase [1,4,6], urea [3,7,8], and myoglobin [1,7,9]. It has been shown that the breakdown of body protein during endurance exercise occurs
has been published in recent years. Based on the high eccentric demands of these activities, marathon and ultra-marathon running as eccentric exercise lead to skeletal muscle damage resulting in an increase in myo- cellular enzymes such as plasma creatine kinase [1,4,6], urea [3,7,8], and myoglobin [1,7,9]. It has been shown that the breakdown of body protein during endurance exercise occurs and the mobilized amino acids are available for increased rates of oxidation and gluconeogenesis during endurance performances [10]. The increase in variables of skeletal muscle damage during ultra-endurance running might be associated with the decrease in skeletal muscle mass as has been shown in ultra-marathoners [2,11,12]. In recent years, several laboratory studies in cyclists reported reductions of myocellular enzymes indicative of skeletal muscle damage during endurance performances, and enhanced performance after combined ingestion of carbohydrates and protein. It has been demonstrated that consumption of a carbohydrate-protein beverage during an intense cycling performance led to a reduced increase in plasma creatinekinase [13,14] and myoglo- bin [15]. Subjects were given 200 ml of a carbohydrate * Correspondence: beat.knechtle@hispeed.ch 1 Gesundheitszentrum St. Gallen, St. Gallen, Switzerland Full list of author information is available at the end of the article Knechtleet al.Journal of the International Society of Sports Nutrition2011,8:6 http://www.jissn.com/content/8/1/6 © 2011 Knechtle et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
(6%) or carbohydrate plus casein hydrolysate (6% carbo- hydrate + 1.8% protein hydrolysate) 500 ml immediately pre-exercise and every 5 km in the study of Saunders et al.[15]. In the study of Valentineet al.[15], partici- pants consumed 250 ml placebo, carbohydrates (7.75%), carbohydrate plus carbohydrates (9.69%) or carbohy- drates plus protein (7.76% + 1.94%) every 15 min until fatigue. The combined intake of carbohydrate and pro- tein enhanced cycling performance [16,17] and reduced ratings of muscle soreness [14]. The ingestion of amino acids before a performance reduced both delayed onset of muscle soreness and muscle fatigue for several days after exercise [18]. In addition, it was discovered that amino acid supplementation during training prevented exercise induced muscle proteolysis [19]. To date, no study has investigated whether the supple- mentation of amino acids would have an effect on vari- ables of skeletal muscle damage and performance in ultra-endurance runners competing in events further than the classic marathon distance. We therefore asked whether the short-term supplementation of amino acids before and during a 100 km ultra-marathon might have an effect on variables of skeletal muscle damage in ultra-endurance athletes. Regarding the present litera- ture, we hypothesized that the supplementation of amino acids before and during an ultra-marathon would lead to a reduced increase in the variables of skeletal muscle damage, a decrease in muscle soreness and an improved performance. Methods An interventional field study at the‘100 km Lauf Biel’ in Biel, Switzerland was used for this research. The organizer contacted all participants of the race in 2009 via a separate newsletter at the time of inscription to the race, in which they were asked to participate in the study. About 1,000 male Caucasian runners started in the race; a total of 30 male ultra-runners volun- teered to participate in this investigation. This study was approved by the Institutional Review Board for use of Human Subjects of the University of Berne, Switzerland. Subjects A total of 28 athletes participated in this investigation. Table 1 represents the anthropometric data for the par- ticipants, Table 2 their pre-race training variables. The athletes were informed of
male ultra-runners volun- teered to participate in this investigation. This study was approved by the Institutional Review Board for use of Human Subjects of the University of Berne, Switzerland. Subjects A total of 28 athletes participated in this investigation. Table 1 represents the anthropometric data for the par- ticipants, Table 2 their pre-race training variables. The athletes were informed of the experimental risks and gave their informed written consent. Measurements and Calculations Ultra-runners volunteering for this investigation kept a comprehensive training dairy, including recording their weekly training units in running, showing duration (minutes) and distance (kilometres), from inscription to the study until the start of the race. In addition, they reported their number of finished 100 km runs including their personal best time in a 100 km. ultra-marathon. The personal best time was defined as the best time the athletes ever had achieved in their active career as an ultra-runner. The athletes who agreed to participate were randomly assigned to the amino acid supplementation group or the control group upon inscription to the study. In case an athlete withdrew, the next athlete filled the gap. Twenty-eight of the expected 30 athletes reported to the investigators at the race site, between 04:00 p.m. and 09:00 p.m. on June 12 2009. The athletes in the group using amino acid supple- mentation received, on the occasion of the pre-race measurements, a pre-packed package of amino acids in the form of a commercial brand of tablets (amino- loges ® , Dr. Loges + Co. GmbH, 21423 Winsen (Luhe), Germany). The composition of the product is repre- sented in Table 3. These athletes ingested 12 tablets one hour before the start of the race, and then four tablets at each of the 17 aid stations. The runners took a total of 80 tablets in the pockets of their race clothing. In total, they ingested 52.5 g of amino acids; 20 g were branched-chain amino acids. During the run, they con- sumed food and fluids at the aid stationsad libitum.At each aid station, they recorded their intake of nutrition Table 1 Comparison of pre-race age and
The runners took a total of 80 tablets in the pockets of their race clothing. In total, they ingested 52.5 g of amino acids; 20 g were branched-chain amino acids. During the run, they con- sumed food and fluids at the aid stationsad libitum.At each aid station, they recorded their intake of nutrition Table 1 Comparison of pre-race age and anthropometry of the participants Amino acids (n = 14) Control (n = 14) Age (years) 42.4 (9.1) 45.1 (6.1) Body mass (kg) 72.1 (6.4) 75.1 (5.6) Body height (m) 1.74 (0.06) 1.80 (0.06) Body mass index (kg/m 2 ) 23.5 (1.5) 22.9 (2.2) Percent body fat (%) 14.1 (3.0) 16.0 (4.5) Results are presented as mean (SD). No significant differences were found between the two groups. Table 2 Comparison of pre-race training and experience of the participants Amino acids (n = 14) Control (n = 14) Years as active runner 13.1 (9.4) 10.3 (8.3) Average weekly running volume (km) 81.6 (21.8) 60.0 (16.2) Average weekly running volume (h) 7.4 (2.3) 5.7 (2.0) Average speed in running during training (km/h) 10.9 (1.8) 11.2 (1.1) Number of finished 100 km runs 5.7 (5.1) (n = 10) 2.8 (2.3) (n = 8) Personal best time in a 100 km run (min) 601 (107) 672 (98) Results are presented as mean (SD). No significant differences were found between the two groups. Knechtleet al.Journal of the International Society of Sports Nutrition2011,8:6 http://www.jissn.com/content/8/1/6 Page 2 of 8
and fluid. Due to the manufacturer’s concerns regarding the high calcium content of the placebo tablets which, in combination with an expected dehydration, could be harmful for the renal function of the athletes, we had to resign from a placebo control. Thus the athletes ran- domly assigned to the control group also consumed food and fluidsat libitumand recorded their nutrient and fluid intake, but did not receive any placebo tablets. Twenty-eight of the expected 30 athletes reported, between 04:00 p.m. and 09:00 p.m. on June 12 2009 to the investigators for their pre-race anthropometric mea- surements and the collection of blood samples. Upon arrival at the finish, the same measurements were per- formed within one hour after finishing, there being 27 finishers. Questionnaires of subjective feelings In combination with the pre- and post-race measure- ments, the athletes were asked about their subjective feelings of muscle soreness, using a subjective 0-20 scale from 0 (absolutely no muscle soreness) to 20 (highest subjective discomfort with muscle soreness). After the race, the athletes were asked whether they had per- formed the run as expected, weaker than expected or better than expected. Anthropometric measurements Body mass was measured using a commercial scale (Beurer BF 15, Beurer GmbH, Ulm, Germany) to the nearest 0.1 kg. Body height was determined using a sta- diometer to the nearest 1 cm. Body mass index (kg/m 2 ) was calculated using body mass and body height. The percentage of body fat was estimated using the following anthropometric formula according to Ball et al.: Percent body fat = 0.465 + 0.180 * (Σ7SF) - 0.0002406 * (Σ7SF) 2 + 0.0661 * (age), whereΣ7SF = sum of skin-fold thickness of pectoralis,axilla,triceps,sub scapular, abdomen, suprailiac and thigh [20]. Skin-fold data were obtained using a skin-fold caliper (GPM- Hautfaltenmessgerät, Siber & Hegner, Zurich, Switzer- land) and recorded to the nearest 0.2 mm. One trained investigator took all the anthropometric measurements in order to eliminate inter-tester variability. The skin- fold measurements were taken once for the entire eight skin-folds and were then repeated twice more by the same investigator; the mean of the three
using a skin-fold caliper (GPM- Hautfaltenmessgerät, Siber & Hegner, Zurich, Switzer- land) and recorded to the nearest 0.2 mm. One trained investigator took all the anthropometric measurements in order to eliminate inter-tester variability. The skin- fold measurements were taken once for the entire eight skin-folds and were then repeated twice more by the same investigator; the mean of the three times was then used for the analyses. The timing of the taking of the skin-fold measurements was standardized to ensure reliability, and the readings were performed after 4 s fol- lowing Becqueet al.[21]. Analysis of blood samples After venipuncture of an antecubital vein in the right arm while the participants were seated, two Sarstedt S-Monovettes (serum gel, 7.5 ml) for chemical analysis were drawn. Monovettes for serum were centrifuged at 3,000 g for 10 min at 4°Celsius. The serum was col- lected, stored on ice and transported immediately after collection to the laboratory for analysis within 6 hours. In the serum, urea, creatine kinase, and myoglobin were measured using COBAS INTEGRA ® 800 (Roche, Mannheim, Germany). Estimation of energy intake and energy expenditure During the run, the athletesconsumed food and drinks ad libitumand reported their intake of fluids and solid nutrition at each aid station. At these aid stations, liquids and food such as hypotonic sports drinks, tea, soup caffeinated drinks, water, bananas, oranges, energy bars and bread were prepared in a standardized manner, i.e. beverages and food were provided in standardized size portions. The drinking cups were filled to 0.2 L; the energy bars and the fruits were halved. Ingestion of fluids and solid food were determined according to the reports of the athletes using a food table [22]. Energy expenditure during the event was estimated using body mass, mean velocity and time spent running [23]. Statistical Analyses The Shapiro-Wilk test was used to check for normality distribution. Data is presented as mean and standard deviation (mean ± SD). Parametric- and non-parametric, both within a group (pre-compared to post-race) and between groups (differences during the race between the supplementation and control group), comparisons were performed as appropriate. Correlation analyses
mean velocity and time spent running [23]. Statistical Analyses The Shapiro-Wilk test was used to check for normality distribution. Data is presented as mean and standard deviation (mean ± SD). Parametric- and non-parametric, both within a group (pre-compared to post-race) and between groups (differences during the race between the supplementation and control group), comparisons were performed as appropriate. Correlation analyses were applied in order to investigate the effect of the amino acid supplementation on the variables of skeletal muscle damage and changes in anthropometry. In addition we calculated Cohen’sƒ 2 as an appropriate effect size that can be applied in the context of multiple regressions to estimate the relative importance of the differences between the two groups. By convention,ƒ 2 effect sizes of 0.02, 0.15, and 0.35 are termed small, medium, and Table 3 Composition of the amino acid supplementation Amino acid Per Tablet (mg) During the whole race (g) L-Leucine 125 10 L-Ornithine 62.5 5 L-Isoleucine 62.5 5 L-Valine 62.5 5 L-Arginine 62.5 5 L-Choline 31.25 2.5 L-Cysteine 50 4 L-Tyrosine 50 4 L-Lysine 31.25 2.5 L-Phenylalanine 31.25 2.5 L-Threonine 31.25 2.5 L-Histidine 31.25 2.5 L-Methionine 12.5 1 L-Tryptophan 12.5 1 Knechtleet al.Journal of the International Society of Sports Nutrition2011,8:6 http://www.jissn.com/content/8/1/6 Page 3 of 8
large, respectively [24]. Fisher’sexacttestwasapplied for categorical data to assess the effect of amino-acid supplementation on the subjective estimation of race outcome. Statistical significance was set at a two-sided p-level < 0.05 for all comparisons. Results Baseline characteristics with regard to anthropometry (Table 1) training and pre-race experience (Table 2) showed no differences between the athletes receiving amino acid supplementation and the control group. Performance One athlete in the control group dropped out after 71 km due to medical problems. Mean (±SD) finishing time of the 14 athletes in the amino acid group was 624.3 (79.5) min., whereas the remaining 13 athletes out of the control group finished in 697.8 (89.7) min. The mean difference of 73.6 min. in race time between the two groups was statistically significant (p= 0.033). The corresponding 95% confidence limits of the race time difference were between 6.5 min. and 140.6 min. Race time was significantly associated with personal best time in a 100 km ultra-marathon for both the supple- mentation and the control group, with Pearson correla- tion coefficients of 0.77 and 0.81 (p< 0.05 for both), respectively. The corresponding mean (95% CI) differ- ence in personal best time between the groups was 71.0 (-33.2 to 175.1) min (p= 0.17). Due to the similar mean differences in race time and personal best time in a 100 km ultra-marathon between the two groups, and the significant association between the race time and thepersonalbesttimeina100kmultra-marathon,we performed a linear regression controlling for personal best time in a 100 km ultra-marathon as a potential confounder for the difference between 100 km race times. The resulting mean (SE) race time difference of 5.5 (±28.6) min. remained no longer statistically signifi- cant when adjusted for the personal best time in a 100 km ultra-marathon. Energy balance and fluid intake The athletes in the amino acid group consumed 8.5 (±3.2) L of fluids during the run, the runners in the con- trol group 7.9 (±3.5) L (p > 0.05). Energy intake, energy expenditure and energy balance were not different between the two groups (Table 4). The athletes in the amino acid group ingested
km ultra-marathon. Energy balance and fluid intake The athletes in the amino acid group consumed 8.5 (±3.2) L of fluids during the run, the runners in the con- trol group 7.9 (±3.5) L (p > 0.05). Energy intake, energy expenditure and energy balance were not different between the two groups (Table 4). The athletes in the amino acid group ingested significantly more protein compared to the control group. The energy deficit was significantly related to the decrease in body mass of the runners in the amino acid group (Pearsonr=0.7,p= 0.003). The additional effect (Cohen’sƒ 2 )oftheamino acid supplementation on the association between the loss of body mass and the energy deficit was 0.018. In the amino acid group, body mass decreased by 1.8 (±1.6) kg, in the control group by 1.9 (±2.0) kg (p> 0.05). No associations between the 100 km race time and the change in body mass have been observed in the two groups. Changes in serum variables Plasma concentrations of creatine kinase, urea and myo- globin decreased significantly in the two groups (Table 5). The changes from post- to pre-race (Δ) were no different between the two groups. The post-race values for creatine kinase, serum urea and myoglobin were 2,637 (±1,278) %, 175 (±32) %, and 14,548 (±8,522) % higher than the pre- race values in the amino acid group; and 2,749 (±1,962) %, 168 (±38) %, and 13,435 (±10,724) % in the control group (p< 0.01). The increases were not different between the two groups. In the amino acid group, race time was positively cor- related to the increase in plasma urea concentration (Pearsonr=0.56,p= 0.038), which was not the case in the control group (Pearsonr= -0.30,p=0.3).Thecor- responding effect size (Cohen’sƒ 2 ) for the observed dif- ference between the race time and the change in urea concentration between the two groups was 0.23. Subjective feelings of muscle soreness and performance In the amino acid group, the subjective feeling of muscle soreness increased from 0.9 (±2.2) pre-race to 11.3 (±4.3) post-race (p< 0.05); in the control group from 0.4 (±1.0) pre-race to 9.4 (±4.6) post-race (p< 0.05).
ference between the race time and the change in urea concentration between the two groups was 0.23. Subjective feelings of muscle soreness and performance In the amino acid group, the subjective feeling of muscle soreness increased from 0.9 (±2.2) pre-race to 11.3 (±4.3) post-race (p< 0.05); in the control group from 0.4 (±1.0) pre-race to 9.4 (±4.6) post-race (p< 0.05). The changes between the two groups were not different. When the athletes were asked, post-race, whether they had completed the race as expected, better than expected or worse than planned, no differences were found. Discussion In the present study, we have investigated the potential effects of a short term amino-acid supplementation on variables of skeletal muscle damage in ultra-runners during a 100 km ultra-marathon. We hypothesized that Table 4 Comparison of energy balance and nutrient intake of the participants during the race Amino acids (n = 14) Control (n = 13) Energy expenditure (kcal) 7,160 (844) 7,485 (621) Energy intake (kcal) 3,311 (1,450) 2,590 (1,334) Energy balance (kcal) - 3,848 (1,369) - 4,894 (1,641) Intake of carbohydrates (g) 755.7 (354.8) 608.8 (326.4) Intake of protein (g) 79.9 (12.7) ** 26.7 (22.0) Intake of fat (g) 5.1 (4.8) 7.0 (7.1) Results are presented as mean (SD). Athletes in the amino acid group ingested highly significantly more protein compared to the control group. ** =p< 0.01. Knechtleet al.Journal of the International Society of Sports Nutrition2011,8:6 http://www.jissn.com/content/8/1/6 Page 4 of 8
the supplementation of amino acids before and during an ultra-marathon would reduce the increase in the variables of skeletal muscle damage, decrease the subjec- tive feeling of muscle soreness and improve race perfor- mance. In contrast to our hypothesis, the amino acid supplementation showed no effect on variables of skele- tal muscle damage, i.e. creatine kinase and myoglobin, on subjective feelings of muscle soreness and on perfor- mance. Potential explanations for these negative findings could be the time and duration of amino acid supple- mentation and the type of exercise. Change in variables of skeletal muscle damage We hypothesized that an amino acid supplementation would lower post-race values of variables of skeletal muscle damage compared to control participants. In contrast, we found no differences in the increase in serum concentrations of creatine kinase, urea and myo- globin between the two groups. Cockburnet al.demon- strated that creatine kinase and myoglobin increased to a lower extent after supplementation with a milk-based protein [25]. However, they measured creatine kinase and myoglobin 24 h and 48 h after exercise, which might explain the disparate findings. In marathon runners, post-race creatine kinase was significantly elevated among faster compared to slower runners and the elevations of creatine kinase drawn 24 hours after a marathon were inversely related to the finishing times [26]. Skenderiet al.described 39 runners in the Spartathlon, a 246 km ultra-marathon, which the athletes completed within 33.3 (±0.5) h [6]. The finish- ing time was not correlated to the post race creatine kinase concentration, as has been found in the present study. Duration of amino acid supplementation Our athletes ingested the amino acids as a pre-race load of 12 g and then 4 g at each aid station during the 100 km ultra-marathon. The total amount was 52.5 g amino acids and the time of supplementation was between 12 and 13 hours. This time period might be too short to show an effect of the amino acid supplementation on performance. An amino acid supplementation period of two weeks [27], four weeks [28] or even eight weeks [29] showed beneficial effects on performance. The sup-
Description
Amino acid supplementation showed no effect on muscle damage or performance in ultra-runners.