Mid Sweden University

BACKGROUND: This study used metabolic phenotyping to explore the responses of highly-trained cross-country skiers to a standardized exercise test, which was part of the athletes' routine testing, and determine whether metabolic phenotyping could discriminate specific physiological, performance, and illness characteristics.

METHODS: Twenty-three highly-trained cross-country skiers (10 women and 13 men) participated in this study. Capillary whole-blood samples were collected before (at rest) and 2.5 min after (post-exercise) a roller-ski treadmill test consisting of 5-6 × 4-min submaximal stages followed by a self-paced time trial (~ 3 min) and analyzed using mass spectrometry. Performance level was defined by International Ski Federation distance and sprint rankings. Illness data were collected prospectively for 33 weeks using the Oslo Sports Trauma Research Center Questionnaire on Health Problems. Orthogonal partial least squares-discriminant analyses (OPLS-DA) followed by enrichment analyses were used to identify metabolic phenotypes of athlete groups with specific physiological, performance, and illness characteristics.

RESULTS: Blood metabolite phenotypes were significantly different after the standardized exercise test compared to rest for metabolites involved in energy, purine, and nucleotide metabolism (all OPLS-DA p < 0.001). Acute changes in the metabolic phenotype from rest to post-exercise could discriminate athletes with: (1) higher vs. lower peak blood lactate concentrations; (2) superior vs. inferior performance levels in sprint skiing, and (3) ≥ 2 vs. ≤ 1 self-reported illness episodes in the 33-week study period (all p < 0.05). The most important metabolites contributing to the distinction of groups according to (1) post-exercise blood lactate concentrations, (2) sprint performance, and (3) illness frequency were: (1) inosine, hypoxanthine, and deoxycholic acid, (2) sorbitol, adenosine monophosphate, and 2-hydroxyleuroylcarnitine, and (3) glucose-6-phosphate, squalene, and deoxycholic acid, respectively.

CONCLUSION: Metabolic phenotyping discriminated between athlete groups with higher vs. lower post-exercise blood lactate concentrations, superior vs. inferior sprint skiing performance, and more vs. less self-reported illnesses. While the biological relevance of the identified biomarkers requires validation in future research, metabolic phenotyping shows promise as a tool for routine monitoring of highly-trained endurance athletes.

Purpose: To provide a descriptive analysis of the warm-up (WU) strategies employed by cross-country skiers prior to distance and sprint competitions at a national championship and to compare the skiers' planned and executed WUs prior to the respective competitions.

Methods: Twenty-one national- and international-level skiers (11 women and 10 men) submitted WU plans prior to the distance and sprint competitions, and after the competitions, reported any deviations from the plans. Skiers used personal monitors to record heart rate (HR) during WU, races, and cooldown. Quantitative statistical analyses were conducted on WU durations, durations in HR-derived intensity zones, and WU loads. Qualitative analyses were conducted on skiers' WU plans and their reasons for deviating from the plans.

Results: Skiers' planned WUs were similar in content and planned time in HR-derived intensity zones for both the distance and sprint competitions. However, 45% of the women and 20% of the men reported that their WU was not carried out as planned, with reasons detailed as being due to incorrect intensities and running out of time. WU activities including skiing across variable terrain, muscle-potentiating exercises, and heat-maintenance strategies were missing from the skiers' planned routines.

Conclusions: Skiers favored a long, traditional WU approach for both the sprint and distance events, performing less high-intensity and more moderate-intensity exercise during their WUs than planned. In addition, elements likely relevant to successful performance in cross-country skiing were missing from WU plans.

Purpose: To provide a descriptive account of the warm up strategies (WU) employed by cross country skiers prior to distance and sprint competitions at a national championship; analyze the skiers’ planned WU; compare skiers’ planned and actual WUs carried out prior to the respective  competitions.

Methods: Twenty-one national- and international-level skiers (11 females and 10 males) participated. Skiers submitted WU plans prior to the competitions and reported any deviations from the plans after the respective competitions. Participants used personal hear rate (HR) monitors to record HR and were instructed to start the recording upon starting the WU and end the data collection following their cool down after the competition.

Results: Skiers’ planned WU for the distance and sprint competitions were of similar content and planned time in HR derived intensity zones. Skiers spent similar durations within the lowest zone (A1, 60–74% peak HR) as planned for distance and sprint competitions. Prior to the sprint competition skiers spent significantly (p < 0.05) less time than planned in the highest intensity domain (A3+, >95% peak HR). Forty five % of female and 20% of male skiers reported their WU was not carried out as planned.

Conclusions: Planned WU were not sufficiently tailored for the differing demands of distance and sprint competition. Prior to the sprint competition skiers failed to accumulate the planned volume of high intensity work (time in A3+).

Practical applications: Skiers examined here would benefit from more bespoke WU, tailored to the specific demands of distance and sprint competition.

Intensive training periods may negatively influence immune function, but the immunological consequences of specific high-intensity training (HIT) prescriptions are not well defined. Purpose: This study explored whether three different HIT prescriptions influence multiple health-related biomarkers and whether biomarker responses to HIT were associated with upper respiratory illness (URI) risk. Methods: Twenty-five male cyclists and triathleteswere randomised to three HIT groups and completed twelve HIT sessions over four weeks. Peak oxygen consumption (V̇O2peak) was determined using an incremental cycling protocol, while resting serum biomarkers (cortisol, testosterone, 25(OH)D and ferritin), salivary immunoglobulin-A (s-IgA) and energy availability (EA) were assessed before and after the training intervention. Participants self-reported upper respiratory symptoms during the interventionand episodes of URI were identified retrospectively. Results: Fourteen athletes reported URIs, but there were no differences in incidence, duration or severity between groups. Increased risk of URI was associated with higher s-IgA secretion rates (odds ratio=0.90, 90% CI:0.83-0.97). Lower pre-intervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher V̇O2peak reported higher total symptom scores (incidence rate ratio=1.07, 90% CI:1.01-1.13). Conclusions: Although multiple biomarkers wereweakly associated with risk of URI, the direction of associations between s-IgA, cortisol, EA and URI risk were inverse to previous observations and physiological rationale. There was a cluster of URIs within the first week of the training intervention, but no samples were collected at this time-point. Future studies should incorporate more frequent sample time-points, especially around the onset of new training regimes, and include athletes with suspected or known nutritional deficiencies.

This study investigated the energy, macronutrient and fluid intakes, as well as hydration status (urine specific gravity; USG), in elite cross-country skiers during a typical day of training (day one) and a sprint skiing competition the following day (day two). Thirty-one (18 male and 13 female) national team skiers recorded their food and fluid intakes and USG was measured on days one and two. In addition, the females completed the Low Energy Availability in Females-Questionnaire (LEAF-Q) to assess their risk of long-term energy deficiency. Energy intake for males was 65+/-9 kcal/kg on day one versus 58+/-9 kcal/kg on day two (P=0.002), and for females was 57+/-10 on day one versus 55+/-5 kcal/kg on day two (P=0.445). Carbohydrate intake recommendations of 10-12 g/kg/day were not met by 89% of males and 92% of females. All males and females had a protein intake above the recommended 1.2-2.0 g/kg on both days, and a post-exercise protein intake above the recommended 0.3 g/kg. Of the females, 31% were classified as being at risk of long-term energy deficiency. In the morning of day one, 50% of males and 46% of females were dehydrated; on day two this was the case for 56% of males and 38% of females. In conclusion, these data suggest that elite cross-country skiers ingested more protein and less carbohydrate than recommended, and one third of the females were considered at risk for long-term energy deficiency. Furthermore, many of the athletes were dehydrated prior to training and competition.

Purpose: This study aimed to compare performance and pacing strategies between elite male and female cross-country skiers during a sprint competition on snow using the skating technique.

Methods: Twenty male and 14 female skiers completed an individual time-trial prolog (TT) and three head-to-head races (quarter, semi, and final) on the same 1,572-m course, which was divided into flat, uphill and downhill sections. Section-specific speeds, choice of sub-technique (i.e., gear), cycle characteristics, heart rate and post-race blood lactate concentration were monitored. Power output was estimated for the different sections during the TT, while metabolic demand was estimated for two uphill camera sections and the final 50-m flat camera section.

Results: Average speed during the four races was ∼12.5% faster for males than females (P < 0.001), while speeds on the flat, uphill and downhill sections were ∼11, 18, and 9% faster for the males than females (all P< 0.001 for terrain, sex, and interaction). Differences in uphill TT speed between the sexes were associated with different sub-technique preferences, with males using a higher gear more frequently than females (P < 0.05). The estimated metabolic demand relative to maximal oxygen uptake (V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; outline: 0px !important;">V˙V˙O2max) was similar for both sexes during the two uphill camera sections (∼129% of V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; outline: 0px !important;">V˙V˙O2max) and for the final 50-m flat section (∼153% of V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; outline: 0px !important;">V˙V˙O2max). Relative power output during the TT was 18% higher for males compared to females (P < 0.001) and was highly variable along the course for both sexes (coefficient of variation [CV] between sections 4–9 was 53%), while the same variation in heart rate was low (CV was ∼3%). The head-to-head races were ∼2.4% faster than the TT for both sexes and most race winners (61%) were positioned first already after 30 m of the race. No sex differences were observed during any of the races for heart rate or blood lactate concentration.

Conclusion: The average sex difference in sprint skiing performance was ∼12.5%, with varying differences for terrain-specific speeds. Moreover, females skied relatively slower uphill (at a lower gear) and thereby elicited more variation in their speed profiles compared to the males.

This study investigated whether commercially available compression garments (COMP) exerting a moderate level of pressureand/or neuromuscular electrical stimulation (NMES) accelerate recovery following a cross-country sprint skiing competitioncompared with a control group (CON) consisting of active recovery only. Twenty-one senior (12 males, 9 females) and 11junior (6 males, 5 females) Swedish national team skiers performed an outdoor sprint skiing competition involving foursprints lasting ∼3–4 min. Before the competition, skiers were matched by sex and skiing level (senior versus junior) andrandomly assigned to COMP (n = 11), NMES (n = 11) or CON (n = 10). Creatine kinase (CK), urea, countermovementjump (CMJ) height, and perceived muscle pain were measured before and 8, 20, 44 and 68 h after competition. NeitherCOMP nor NMES promoted the recovery of blood biomarkers, CMJ or perceived pain post-competition compared withCON (all P > .05). When grouping all 32 participants, urea and perceived muscle pain increased from baseline, peaking at8 h (standardised mean difference (SMD), [95% confidence intervals (CIs)]): 2.8 [2.3, 3.2]) and 44 h (odds ratio [95%CI]: 3.3 [2.1, 5.1]) post-competition, respectively. Additionally, CMJ was lower than baseline 44 and 68 h postcompetitionin both males and females (P < .05). CK increased from baseline in males, peaking at 44 h (SMD: 1.4 [−0.4,0.9]), but was decreased in females at 20 h post-competition (SMD: −0.8 [−1.4, −0.2]). In conclusion, cross-countrysprint skiing induced symptoms of exercise-induced muscle damage peaking 8–44 h post-competition. However, neitherCOMP nor NMES promoted physiological or perceptual recovery compared with CON.

Intensified training periods may increase incidence of upper respiratory illness (URI) in athletes (Meeusen et al., 2013,Medicine and Science in Sports and Exercise, 45(1), 186–205). Many physiological and nutritional risk factors have beenassociated with increased risk of URI (Bermon et al., 2017, Exercise Immunology Review, 23, 8–50), including reductionsin salivary IgA (sIgA), elevated cortisol, vitamin D insufficiency, iron deficiency and low energy availability (EA). However, few studies have explored the relative importance of each of thesehealth-related biomarkers in a multivariate model. Our aimwas therefore to investigate the relationship between multiplebiological risk factors for illness and incidence, duration andseverity of URIs that present during intensified training. 3815Twenty-five well-trained male cyclists and triathletes (age 30 ± 9 y, VO2peak 64 ± mL· kg−1· min−1) performed one ofthree different high-intensity interval training (HIT) programmes for three sessions per week over four weeks in November-December. The study received local ethical approval and participants provided written, informed consentto participate. Participants performed each HIT session at “isoeffort” intensity and sessions were matched for total accumulated work duration. Participants logged upper respiratorysymptoms (URS) daily using the Jackson Common Cold Scale; episodes of URI were identified retrospectively using the followinga priori criteria: weekly symptom score > 14 or selfreportedcommon cold for > 2 consecutive days (Jacksonet al., 1958, American Medical Association Archives of Internal Medicine, 101, 267–278). Before commencing the training period, VO2peak was determined using an incremental maximal cycling protocol and participants provided rested, fasted blood and saliva samples prior to the training period foranalysis of plasma 25(OH)D, ferritin, cortisol, testosterone and sIgA secretion rate. EA was calculated based on a 3-day registration of energy intake and expenditure relative to fat-free mass measured in a rested, fasted state using indirect calorimetry (Torstveit et al., 2018 February, International Journal of Sport Nutrition and Exercise Metabolism, 1–28). We used a zero-inflated negative binomial model to investigate the relationship between baseline VO2peak, health-related biomarkers and URI incidence/duration/global URS severity. Fourteen athletes(56%) reported an episode of URI during the four-week monitoring period. Higher sIgA was associated with reduced risk of URI (odds ratio = 0.90, 90% confidence interval (CI): [0.83,0.97]). Lower plasma cortisol (P = 0.02) and higher EA (P = 0.02) were associated with longer URI duration; holding cortisol constant, the incidence risk ratio (IRR) for a one-unit increase in EA was 1.04 (90% CI: [1.01, 1.07]). Participants with higher VO2peak reported higher total symptom scores during the intervention period (P = 0.03, IRR = 1.07, 90% CI: [1.01,1.13]). Several health-related biomarkers and physiological parameters may therefore be associated with risk and severityof URI, including sIgA, cortisol, EA and VO2peak.

The integrity of the athlete biological passport (ABP) is underpinned by understanding normal fluctuations of its biomarkers to environmental or medical conditions, for example, altitude training or iron deficiency. The combined impact of altitude and iron supplementation on the ABP was evaluated in endurance-trained athletes (n = 34) undertaking 3 weeks of simulated live-high: train-low (14 h.d(-1), 3000 m). Athletes received either oral, intravenous (IV) or placebo iron supplementation, commencing 2 weeks prior and continuing throughout hypoxic exposure. Venous blood was sampled twice prior, weekly during, and up to 6 weeks after altitude. Individual ABP thresholds for haemoglobin concentration ([Hb]), reticulocyte percentage (%retic), and OFF score were calculated using the adaptive model and assessed at 99% and 99.9% specificity. Eleven athletes returned values outside of the calculated reference ranges at 99%, with 8 at 99.9%. The percentage of athletes exceeding the thresholds in each group was similar, but IV returned the most individual occurrences. A similar frequency of abnormalities occurred across the 3 biomarkers, with abnormal [Hb] and OFF score values arising mainly during-, and %retic values mainly post-altitude. Removing samples collected during altitude from the model resulted in 10 athletes returning abnormal values at 99% specificity, 2 of whom had not triggered the model previously. In summary, the abnormalities observed in response to iron supplementation and hypoxia were not systematic and mostly in line with expected physiological adaptations. They do not represent a uniform weakness in the ABP. Nevertheless, altitude training and iron supplementation should be carefully considered by experts evaluating abnormal ABP profiles.

High-intensity interval training (HIT) encompasses a wide range of training prescriptions where up to nine variables can be manipulated (Buchheit and Laursen, 2013, Sports Medicine, 43(5), 313–338). Four weeks of HIT with longer intervals and accumulated work durations (AWD) has been shown to elicit greater improvements in peak oxygen consumption (V O 2peak ) despite more modest physiological, hormonal and perceptual responses (Sylta et al., 2017, Medicine & Science in Sports & Exercise, 49(6), 1137–1146). However, immunological responses to different HIT pre- scriptions have rarely been investigated. The purpose of this study was to compare the cumulative effects of a four-week HIT intervention, performed either as short or long intervals with the same AWD, on V O 2peak , the immunological biomarker salivary secretory IgA (s-IgA) and upper respiratory illness (URI) incidence. In addition, we explored the influence of HIT on serum cortisol, testosterone, 25(OH)D and ferritin as biomarkers related to immune competence. Following local ethics committee approval, twenty-five well-trained male cyclists and triath- letes provided written consent to take part and were randomised to one of three HIT groups (Long Intervals [LI]: 4 × 8min; Short Intervals 1 [SI1]: 4×[12 × 40/20s]; Short Intervals 2 [SI2]: 4×[8 ×40/20s]). Participants per- formed three cycling HIT sessions per week for four weeks at maximal session effort (“isoeffort”) intensity, supplemented with ad libitumlow-intensity training. Participants recorded upper respiratory symptoms (URS) daily using the Jackson Common Cold Scale; episodes of URI were identified retrospectively. V O 2peak as well as rested saliva and blood biomarkers were analysed before and after the training period. Fourteen of twenty-five participants reported an episode of URI (LI: 4/8, SI1: 4/8, SI2: 6/9) but there were no differences in URI incidence, severity or duration between groups. Following the train- ing intervention, we observed a moderate increase in V O 2peak across the cohort (mean± SD: 4.75 ± 0.42 to 4.86 ± 0.43 L· min−1 ,Cohen’s d= 0.65, 90% confidence intervals: [0.16, 1.13]) but the change in V O 2peak was not different between groups. Serum cortisol displayed a moderate increase (367 ± 98 to 415 ± 108 nmol· L −1 ,d=0.60 [0.12, 1.08]) and 25(OH)D a large decrease (79.2 ± 17.1 to 70.4 ± 17.6 nmol· L −1 ,d= -0.87 [−1.36,−0.37]) from pre- to post-training, but there were no differences in the magnitude of the responses between groups. Four weeks’HIT did not influence s-IgA secretion rate, serum testosterone or ferritin. We conclude that four weeks’ AWD-matched HIT performed as short- or long-intervals at isoeffort intensity does not differentially influence ill- ness incidence, immunological responses to training nor other immune-related biomarkers. This observation can be viewed as a positive finding for training planning, since it could allow coaches some flexibility in constructing AWD-matched isoeffort HIT sessions to achieve performance goals, without concern about detrimental effects on athletes’ immune status.