Negative Energy Balance does not alter Fat Free Mass during the Yukon Arctic Ultra – the Longest and the Coldest Ultramarathon

Negative Energy Balance does not alter Fat Free Mass during the Yukon Arctic Ultra – the Longest and the Coldest Ultramarathon

 

Michelle M Johannsen1*, Adriane Schalt2*, Jimin Kim1, Richard Chen1, Carl J Murphy1, Melynda S Coker1, Hanns-Christian Gunga2, Robert H Coker1, Mathias Steinach2,

 

University of Alaska Fairbanks1, Institute of Arctic Biology, Fairbanks, AK;

Charité-Universitätsmedizin Berlin, Institute of Physiology, Center for Space Medicine and Extreme Environments Berlin2, Berlin, Germany

 

*contributed equally to the manuscript

 

Keywords: cold exposure, body composition,  cytokines, environment, ultramarathon

 

Running Title: Yukon Arctic Ultra 2017

 

Manuscript Word Count: 2926

Abstract Count: 249

 

Corresponding Author Information:

 

Address for Correspondence:

Robert H. Coker, Ph.D.

Institute of Arctic Biology

University of Alaska-Fairbanks

902 North Koyukuk Drive

email: rcoker@alaska.edu

Fairbanks, AK 99775-7000

Telephone #    907-474-6701

FAX #             907-474-5700

 

 

Abstract:

Purpose: The objective of this study was to determine alterations in caloric balance, body composition, metabolites, and cytokines in athletes participating in the Yukon Arctic Ultra. Methods: Ten participants traveling on foot in the 2017 692-km event were recruited for the study. Measurements and samples were obtained at pre-event, 278-km (C1), 384-km (C2), and post-event. Body composition measurements were obtained using bioelectrical impedance analysis. Accelerometer devices were utilized to provide an estimation of caloric expenditure and dietary recalls provided assessments of caloric intake. Blood serum samples were collected, processed, and analyzed using enzyme-linked immunosorbent assays or nuclear magnetic resonance. Results were analyzed using one-way ANOVA, presented as means±SEM and considered significant at P<0.05. Results: Participants (37±10 yr; body mass index: 24.4±2.5 kg/m2; 8 males, 2 females) were recruited. Four males and one female completed the entire event in 260±19 hours. Caloric intake/expenditure was 4,126±1115 kcal/day and 6,387±781 kcal/day, respectively, indicating a caloric deficit of 2,261±1543 kcal/day. Total mass, body mass index, and fat mass were reduced at each time point of the event. Fat free mass was unchanged throughout the event. Follistatin was increased at C1 (1,715±876 pg/mL) in comparison to baseline. Acetoacetate increased significantly at post-event (6.1±1.5 mg/ml). Conclusions: Despite a pronounced caloric deficit and sustained activity under extreme cold conditions, fat free mass was preserved with an increase in serum follistatin and acetoacetate. Future studies should be directed at the role of nutrient strategies and/or training methods on the retention of fat free mass under these conditions.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Introduction:

The Yukon Arctic Ultra (YAU) has been advertised as the “World’s Toughest and Coldest Ultra” (Montane 2017). Participants must travel 692 kilometers (430 miles) from Whitehorse to Dawson City, Yukon Territory. The event takes place in the winter months when temperatures can easily reach as low as -48ºC. Historical data shows individuals average a speed of 3-5 km/hour, only sleep 2-6 hours per night and it typically takes participants 7-12 days to complete the event. Due to the strenuous nature of the YAU, it is not uncommon for 50% or more of the individuals to drop out. Rigorous safety standards may also disqualify individuals from continuing if officials deem that it is unsafe (e.g., signs of frostbite).

 

Over twenty years ago, the physiological resilience of two men who walked 2300 km across Antarctica completely unsupported was described (Stroud et al., 2008). Utilizing a high fat diet, these individuals maintained stable to high levels of protein synthesis that fostered the preservation of lean tissue (Stroud et al., 2008). This type of dietary approach has been suggested to promote metabolic flexibility and improve the utilization of fuel substrates (Coker et al., 2017). We have previously evaluated changes in body composition, serum cytokines, and metabolites during the 2015 Yukon Arctic Ultra. We demonstrated that fat mass (FM) was reduced but fat free mass (FFM) was remarkably preserved (Coker et al., 2017). Additional studies performed with athletes participating in the Alaska Mountain Wilderness Ski Classic under similar Arctic winter conditions also demonstrated the preservation of lean tissue mass despite high levels of energy expenditure, as measured by dual energy x-ray absorptiometry (Johannsen et al., 2018). While these data were interesting, the studies from 1996 and 2015 (Coker et al., 2017; Johannsen et al., 2018) were limited by small numbers of participants that actually completed the events. Also, alterations in FM relative to FFM in conjunction with the assessment of caloric intake and energy expenditure have not been thoroughly investigated.

 

Myostatin and follistatin have been posited to exert a direct role in skeletal muscle growth and proliferation (Bragg et al., 2014; Lee et al., 2010). Studies have also described the short-term influence of modest exercise and/or limited cold exposure on these glycoproteins (Haman 2006; Wolfe et al., 1984). Given that myostatin plays an inhibitory role in muscle growth (Bragg et al., 2014) and follistatin has been shown to stimulate muscle hypertrophy (Lee et al., 2010), these proteins may play a particularly important role in the preservation of FFM and physiological resilience during the YAU or similar events/scenarios.

 

The objective of the present study was to determine the impact of the participation in the YAU on: a) caloric balance and metabolites, b) body composition, and c) follistatin and myostatin that have not been comprehensively evaluated under these conditions. We hypothesized that participants would sustain a chronic net negative caloric balance, develop a ketogenic profile, and maintain FFM. We further hypothesized that myostatin would decrease, and follistatin would increase in conjunction with the retention of FFM. The mechanisms responsible for survival in the cold environment are heavily dependent upon the preservation of lean tissue mass (Haman 2006; Haman and Blondin 2017). Therefore, it is important to completely understand these mechanisms that might be extrapolated to circumstances involving military or space personnel, bush pilots, and other minimally supported individuals who may face similar occupational conditions.

 

Materials and Methods:

Participants of the 2017 YAU 692-km (430-mile) event were recruited for this study (n=10, 8 males, 2 females, 37 ± 10 years of age). Nine of the participants were of Caucasian descent; only four of these individuals completed. One was of Asian descent and did not finish the entire event. These individuals were at chronic risk for the development of frostbite and/or hypothermia. First-time athletes were required to complete a training course that detailed first aid, shelter, equipment, nutrition, trails, and other necessary information necessary to sufficiently prepare the individuals for the arduous conditions. All competitors were required to pull their own sleds to carry equipment. Vital equipment included food, water, clothing, cooking utensils, sleeping preparations, and emergency preparedness items. In spite of these precautions, 50% of the study participants in 2017 were unable to complete the race for a variety of reasons ranging from severe muscle cramps to frostbite. We added an additional checkpoint in comparison to our work on the 2015 event so that data and sample collection were collected at pre-event (Whitehorse), checkpoint-1 (C1) at 278 km (Carmacks), checkpoint-2 (C2) at 384 km (Pelly Crossing), and post-event (Dawson City).

 

Body composition was measured using bioelectrical impedance analysis (BIA) via the tetrapolar electrode method (Sun et al., 2003). These measurements were taken with an Akern BIA 101 (Florence, Italy) at the four checkpoints of the event: pre-event, C1, C2, and post-event. The BIA measurements provided values for FM, FFM, and percent body fat for the individuals. At each of the checkpoints, measurements were conducted indoors, just after awakening from an overnight rest, with a voided bladder, prior to breakfast, and dressed with light underwear.

 

Dietary recall information was obtained from the participants via a “Food & Energy Intake Form” and confirmed by a nutritional specialist. Participants were required to fill out the form in advance, naming the food items and including information such as kcals, weight, quantity packed, and quantity consumed. The caloric content of meals prepared by race organizers at the checkpoints were estimated using the type of dish on the menu as reference. Estimation of caloric content from the completed forms were based on information provided in “Food and Nutrition Tables” (Souci et al., 2016). All values were then verified by a professional from the Charité Health Academy.

 

Energy expenditure was estimated using the SenseWear armband Pro3 (Bodymedia, Pittsburgh, PA). The SenseWear Professional software was used to analyze and intepret the raw data. (Almeida et al., 2011; King et al., 2004; Welk et al., 2007). Data for dietary recall and energy expenditure were used to calculate net caloric balance for the participants.

 

Blood serum samples were collected by a physician under consistent room temperature conditions at each checkpoint and centrifuged to separate whole blood from serum. Serum samples were then pipetted into cryovials and stored in a liquid nitrogen dewar for transport at -80°C and later analysis.

 

Myostatin and follistatin were measured by enzyme-linked immunosorbent assay according to manufacturers’ instructions. All samples were analyzed in triplicate. Serum samples for NMR analysis were thawed and vortexed to ensure homogeny and transferred into 5-mm NMR tubes (Wilmad Lab Glass, Buena, NJ). 1H–NMR spectra were acquired at 17°C (based on Methanol calibration) with a 600-MHz Bruker Avance-III system running TopSpin 3.2 software (Bruker Biospin, Fremont, CA), and using a dual resonance high resolution SmartProbe with single axis Z-gradient (Nicholson et al., 1995). The water signal was suppressed using NOESY presaturation followed by CPMG relaxation, editing for suppression of macromolecules (“PROF_CPMG” parameter set in TopSpin 3.2). A standard, trimethylsilyl propionic-2,2,3,3-tetradeuteropropionic acid (TMSP, 3.87 mM in D2O) contained in a sealed insert and placed in the NMR tube was used for metabolite quantification of fully relaxed 1H–NMR spectra and as a 1H chemical shift reference (0.0 ppm). After Fourier transformation, phasing, and baseline correction in TopSpin, each 1H peak was integrated (Bogren et al., 2014). The 1H–NMR peaks for single metabolites were identified and referred to published chemical shift or a metabolite chemical shift library. The absolute concentration of each metabolite was then referred to the TMSP integral and calculated according to the equation: Cx = (Ix/Nx•C)/I/9; where Cx is metabolite concentration (µmol/mL), Ix is integral of metabolite 1H peak, Nx is number of protons in metabolite 1H peak, C is TMSP concentration, and I is integral of TMSP 1H peak at 0 ppm (this is nine as TMSP contains nine protons) (Serkova et al., 2005). An additional correction factor of 11.304 was applied to adjust for the differences in diameters between the NMR tube and the insert (determined using reference samples). The final metabolite concentrations were expressed as mg/ml.

 

Statistical analysis was performed using R Studio software. Since 50% of the participants were unable to complete the event, missing data points existed and data were analyzed using a linear mixed model approach. The mixed-effect approach works in essence the same as a traditional ANOVA, but accounts for missing data as well as the repeated measures study design when determining if differences exist between the four time points of the event (Gelman and Hill, 2007; Mallinckrod et al., 2008). A post hoc analysis using the Tukey Honest Significant Difference test was then used to determine if differences were statistically significant (Gelman and Hill, 2007; Mallinckrod et al., 2008). Values are reported as means±SD and were considered significant with a P<0.05.

 

Results:

 

Characteristics:

Eight males and two females were initially recruited for the study (n=10; age=37±10 years). Due to the harsh environmental conditions, only 5 of the 10 participants were able to complete the 2017 event. One male and one female dropped out before C1. By C2, two males had dropped out. Between C2 and the finish, another male dropped out of the event. Of the 5 participants that were able to complete the event, the average completion time was 260±19 hours. Therefore, four males and one female completed the entire event.

 

Body Composition:

Total body mass, body mass index, and FM were reduced at each time point (Table 1). There were no significant changes in FFM or fat free mass index (FFMI) (Table 1). 

 

 

 

Caloric Balance:

Complete dietary recall data were provided by all five participants who finished the event. The average caloric intake for these participants was 4,126±1,115 kcals/day. Their corresponding average energy expenditure was 6,387±781 kcals/day, indicating a negative caloric balance of 2,261±1,543 kcals/day.

 

Metabolites:

            Fatty acids and derivatives, and alanine and ß-glucose were decreased initially at C1 and remained reduced throughout the event (Table 2). There was a transient decrease in serum lactate at C1 and C2 and a reduction in serum histidine at (C2) (Table 2). Serum acetoacetate was increased substantially at Post-Event (Table 2).

 

Cytokines:

Blood serum was analyzed for myostatin and follistatin concentrations at each of the aforementioned time points (Figure 1). There were no significant changes in myostatin (Pre: 14,187±10,556 pg/mL, C1: 27,325±9,944 pg/mL, C2: 15,917±4,040 pg/mL, Post: 15,172±5,070 pg/mL), but the values at C1 and C2 were below detectable limits for one participant (P=0.35) (Figure 1). Follistatin was significantly higher at C1 than any other time point of the event (Pre: 883±394 pg/mL, C1: 1,715±819 pg/mL, C2: 1,406±497 pg/mL, Post: 1,374±486 pg/mL) (Figure 1).

 

Discussion:

The focus of the current study was centered on the assessment of caloric intake and caloric expenditure, body composition, alterations in serum metabolites, and potential changes in follistatin and myostatin in athletes traversing the entire 692 km distance of the Yukon Arctic Ultra. Four of the five athletes who completed the event were in negative energy balance and lost FM but retained FFM. Exceptionally challenging cold conditions, considerably worse during the first half of the event, made food preparation difficult. In spite of this situation, energy intake was quite high at over 4,000 kcal/day. The significant increase in follistatin returned to baseline and paralleled alterations in heart rate variability and psychological biometrics in this same cohort (Rundfeldt et al., 2018). These findings seem to suggest that successful athletes may utilize dietary feeding and pacing strategies that enable adaptive metabolic responses to the physical, psychological, and environmental stresses of the event.

 

Typically, energy balance plays a signficant role in the modulation of protein turnover and maintenance of FFM (Pasiakos 2010). Previous work performed in conjunction with US Army Ranger training over an 8-week period demonstrated a negative energy balance of ~1,000 kcal/day. The caloric deficit was derived from a combination of dietary restriction and physical training and resulted in muscle atrophy and decreased physical function (Nindl et al., 2007). This work highlights one of the more dramatic scenarios describing negative caloric balance over a significant period of time. Moreover, the interactive influence of variable nutritional intake, caloric deprivation, and physical exertion across the duration of this type of physiological stress plays a major role in the risk of muscle atrophy (Tassone et al,. 2017).

 

Recent research has shown that participants of ultra endurance events tend to maintain FFM even with the added stress of cold exposure (Coker et al., 2017; Johannsen et al., 2018; Saugy et al., 2013; Stroud et al., 1996). In our previous work with athletes participating in the Yukon Arctic Ultra, caloric expenditure and intake were not examined in conjunction with body composition analysis (Coker et al., 2017). We have now demonstrated that athletes were able to maintain FFM even with an estimated net caloric deficit of approximately 2,200 kcals/day. While this may seem counterintuitive, pre-clincial studies have already highlighted the interorgan transfer of amino acids that may contribute to the conservation of muscle and other tissues, even during short term exercise (Williams et al., 1996). These physiological responses are difficult to examine in humans, but the increased release of essential amino acids from the splanchnic region may be vitally important during conditions of continued physical activity under limited caloric intake or negative caloric balance (Wolfe et al., 1984). This assertion has been further supported by the results of clinical studies that utilized stable isotope methodology to demonstrate that protein degradation is not increased by acute exercise and that amino acids are actually diverted towards the exercised muscle (Devlin et al., 1990). Moreover, these acute physiological responses may be enhanced by the combination of exercise and cold exposure (Williams et al., 1996). The interpretation of these studies has been limited by the acute nature of these well-controlled environments in laboratory settings.

 

In addition to the influence of exercise on the sequestration of amino acids by the working muscle (Devlin et al., 1990), nutrient intake and/or progressive, exertion-linked changes in fuel selection may play a significant role in the sparing of amino acids that facilitate the maintenance of FFM (Burke 2015). Macronutrient intake data were not available in this particular study, but similar expeditions have reported variable dietary intake of approximately ~35-66% carbohydrate, 29-55% fat, and 17-20% protein in ultra athletes (Gannon et al., 2001; Praz et al., 2015; Stroud et al., 1993; Wolfe 1984). We know from our own anecdotal observations during the 2015 and 2017 YAU that many of these athletes may consume more fat than described in earlier studies. This seems plausible, as these particular athletes were required to carry the majority of their dietary provisions in their pulks during the event and dietary fat represents a more efficient method of caloric delivery relative to the amount of weight pulled. In our study, plasma acetoacetate increased progressively, 8-fold relative to baseline by the end of the event. This indicates an increasing reliance on ketones as a fuel during prolonged exercise (Galvin et al., 1968) and that these YAU participants may optimize the utilization of fat as fuel (Pitsiladis et al., 1999). Reductions in lactate and alanine suggest a gluconeogenic shift in the provision of circulating glucose, but are not conclusive due to the inability to assess glucose kinetics in this environmental setting (Coker and Kjœr, 2005). Future studies in this cohort will focus on whether athletes “train” their ability to convert to ketosis and/or whether these adaptations play a role in their resilience.

 

We measured myostatin and follistatin because of their widely known roles in regulating muscle growth and metabolism (Bragg et al., 2014; Druet et al., 2014; Lee et al., 2010). It has been demonstrated that these particular cytokines are influenced by factors other than exercise including cold exposure, diet, and sleep deprivation (Allen et al., 2011; Coker and Kjœr, 2005, Hansen et al., 2011, Vamvini et al., 2011).  It is highly likely that participants in this event experienced all of these physiological stressors. As such, it is difficult to elucidate the primary mediator responsible for alterations in these cytokines. While numerous factors play a role in protein metabolism under conditions of physiological stress, interleukin-6 has been demonstrated to initially increase during strenuous exercise, promote alterations in substrate utilization that  could be beneficial to skeletal muscle (Pedersen et al., 2001), and then decline in a fashion similar to the alterations in follistatin.

 

We found that the modest shifts in myostatin and follistatin occured in parallel with previously published changes in heart rate variability and mood status in this same cohort (Rundfeldt et al., 2018). Heart rate variability and mood status are frequently assessed among athletes for signs of overtraining and as predictors of performance (Taralov et al., 2015). When examining the results of participants in the present study, individuals who completed the entire event displayed improved recovery of cardiac autonomic balance and positive mood balance. Therefore, the potential interaction between these factors may offer some insight into the mechanisms responsible for overall resilience of athletes who successfully completed the event.

 

In this study we were able to extend our previous findings suggesting the complete preservation of FFM during the Yukon Arctic Ultra. We have now delineated that FFM preservation occurs despite a sustained level of pronounced negative caloric balance. Serum concentrations of metabolites and progressively increasing levels of acetoacetate suggest alterations in metabolic regulation that favor an eventual reliance on ketones as fuel. We have also demonstrated that follistatin increases initially and then returns to baseline, which is consistent with greater vagal withdrawal and sympathetic activation previously reported in fininshers compared to non-finishers. Future studies should be directed at the assessment of macronutrient intake and additional cytokines that may be related to successful completion of this event.

 

 

Acknowledgements: Research reported in this publication was primarily supported by the DLR grant 50WB1330. Additional support was also provided by the National Institute of General Medical Sciences of the National Institutes of Health under Award Numbers UL1GM118991, TL4GM118992, or RL5GM118990. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We express our sincere gratitude to the participants, volunteers, and organizers of the 2017 Yukon Arctic Ultra, including Michael Kronitz and Jo Davis. We also express our appreciation to the late Jessica Simon, a Whitehorse resident, author, and stalwart volunteer asssistant for the event.  

 

Author contributions: MJ assisted in sample transport, conducted analysis on cytokines and metabolites, and contributed to manuscript; AS conducted research, recruited participants, collected all samples, calculated energy expenditure and energy intake, and contributed to the manuscript; JK and RC conducted analysis on cytokines and contributed to manuscript; CM conducted analysis on metabolites and was responsible for the oversight of molecular analysis; MC assisted in sample transport and contributed to the manuscript, HG contributed to research plan and manuscript, RC contributed to research plan and cytokine analysis, was responsible for sample transport, and the final draft of the manuscript, MS contributed to research plan recruited participants, collected all samples, served as study physician, calculated energy expenditure and energy intake, and contributed to the manuscript.

 

Conflict of Interest: Dr. Coker is a Managing Partner and Co-Owner of Essential Blends, LLC that has received funding from the National Institutes of Health to develop clinical nutrition products. The data presented in this manuscript are unrelated. We declare that the results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.

 

 

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FIGURE LEGENDS

Figure 1. Serum follistatin and myostatin during Pre-Event, C1, C2 and Post-Event. Data points colored in black represent finishers and data points represented in gray represent drop-outs. For samples below the limit of detection of the assay (270 pg/mL for myostatin) the samples were assigned a value of half the LOD to avoid biasing the results up or down and are designated with a triangle data point. Values are expressed as mean ± SD. *Represents significant difference from baseline.