Abstract
Background
Recent studies have begun to identify the molecular determinants of
inter-individual variability of cardiorespiratory fitness (CRF) in
response to exercise training programs. However, we still have an
incomplete picture of the molecular mechanisms underlying trainability
in response to exercise training.
Objective
We investigated baseline serum and skeletal muscle metabolomics profile
and its associations with maximal power output (MPO) gains in response
to 8-week of continuous endurance training (ET) and high-intensity
interval training (HIIT) programs matched for total units of exercise
performed (the TIMES study).
Methods
Eighty healthy sedentary young adult males were randomized to one of
three groups and 70 were defined as completers (> 90% of sessions): ET
(n = 30), HIIT (n = 30) and control (CO, n = 10). For the CO,
participants were asked to not exercise for 8 weeks. Serum and skeletal
muscle samples were analyzed by 1H-NMR spectroscopy. The targeted
screens yielded 43 serum and 70 muscle reproducible metabolites
(intraclass > 0.75; coefficient of variation < 25%). Associations of
baseline metabolites with MPO trainability were explored within each
training program via three analytical strategies: (1) correlations with
gains in MPO; (2) differences between high and low responders to ET and
HIIT; and (3) metabolites contributions to the most significant
pathways related to gains in MPO. The significance level was set at P <
0.01 or false discovery rate of 0.1.
Results
The exercise programs generated similar gains in MPO (ET = 21.4 ± 8.0%;
HIIT = 24.3 ± 8.5%). MPO associated baseline metabolites supported by
all three levels of evidence were: serum glycerol, muscle alanine,
proline, threonine, creatinine, AMP and pyruvate for ET, and serum
lysine, phenylalanine, creatine, and muscle glycolate for HIIT. The
most common pathways suggested by the metabolite profiles were
aminoacyl-tRNA biosynthesis, and carbohydrate and amino acid
metabolism.
Conclusion
We suggest that MPO gains in both programs are potentially associated
with metabolites indicative of baseline amino acid and translation
processes with additional evidence for carbohydrate metabolism in ET.
Introduction
Cardiorespiratory fitness (CRF) is commonly assessed by the measurement
of maximal oxygen uptake (
[MATH:
V˙O2MAX :MATH]
) or maximum power output (MPO) in incremental exercise tests leading
to exhaustion. CRF is the most widely examined human physiological
functional capacity [[44]1]. Higher levels of CRF are strongly
associated with lower all-cause and cardiovascular disease mortality
[[45]2, [46]3].
Current physical activity guidelines focused on health outcomes
recommend that adults engage in continuous endurance exercise at
moderate-intensity for ≥ 150 min wk^-1 or at vigorous-intensity for 75
min wk^-1 or more [[47]4]. Although it is well known that regular
exercise is associated with improvements in CRF [[48]4], there is a
large body of animal and human data demonstrating that there is
considerable inter-individual variability in CRF response to a
standardized dose of exercise [[49]5–[50]9]. Typically, individual
responses to standardized continuous endurance training (ET) program
have ranged from no gain up to 100% increase in
[MATH:
V˙O2MAX :MATH]
[[51]5, [52]7, [53]10] and to 60% for MPO [[54]11, [55]12] in groups of
previously sedentary heathy adults. Furthermore, inter-individual
variability in CRF training responses has also been shown with exposure
to high-intensity interval training (HIIT) [[56]13–[57]16]. HIIT is
characterized by repeated intense bouts interspersed by short periods
of recovery and it generally differs substantially in exercise
intensity and metabolic demands from ET [[58]17]. HIIT has been found
to produce CRF gains comparable or superior to traditional ET exposure
[[59]18]. However, little is known on the relationships between the
baseline metabolomics profile and the CRF response patterns to ET or
HIIT programs.
It has been previously reported that genomics and muscle transcriptomic
profiles were associated with exercise response variability to ET
programs [[60]19–[61]21]. In this context, recently, metabolomics has
emerged as an “omics” family of technologies with the potential to
illuminate biomarkers and metabolic pathways related to complex
phenotypes [[62]22, [63]23]. Metabolomics involves the systematic
quantification of small-molecules (metabolites) which provide
complementary information to epigenetic events and posttranslational
modifications [[64]22]. A metabolite profile (from blood, muscle,
adipose tissue, etc) represents a dynamic signature of cellular
biochemical activity reflecting the end product of interactions among
the genome, transcriptome, proteome and the cellular and tissue
environment, which can provide unique insights on phenotypes of
interest and their perturbations.
Metabolomics has already been used in a range of exercise studies as
recently reviewed [[65]24]. For example, changes in serum and plasma
metabolites have been described in response to acute and chronic
adaptation to ET or HIIT programs [[66]25–[67]27], as well as
differences in metabolite profile in relation to variable
cross-sectional CRF levels, but not investigating MPO [[68]28, [69]29].
To our knowledge, no previous study has investigated the relationships
between baseline serum or skeletal muscle metabolites with CRF or MPO
trainability. Understanding the association between the baseline
metabolite profile and MPO trainability has the potential to generate
new biomarkers and clarify the biology of adaptation to regular
exercise. In this study, MPO is the dependent variable. MPO as a
surrogate of CRF is known to have a high test-retest reliability level
and low technical error [[70]11].
Therefore, the present study aimed at investigating baseline serum and
skeletal muscle metabolomics profile and related metabolic pathways
associated with MPO gains in sedentary young male adults in response to
ET and HIIT (TraInability and MEtabolomicS study or TIMES study).
Methods
Participants
Young sedentary healthy Caucasian men (18–31 years old) were recruited
through local advertisement in Campinas, Brazil to participate in a
longitudinal randomized controlled study. Recruitment started in
September 2016 and the last post-training assessment was performed in
June 2017. Participants were sedentary and did not engage in regular
exercise defined as 30 min wk^-1 at an energy expenditure of 6 METS or
more in the previous 4 months. All participants provided a detailed
medical history and received a medical examination that included an
electrocardiogram at rest. Participants were excluded if they were
smoker, hypertensive (blood pressure > 140/90 mm Hg), diabetic (fasting
glucose > 7.0 mmol L^-1), obese (defined as body mass index > 33 kg
m^-2), dyslipidemic (based on medication), or presented evidence of
heart diseases, metabolic disorders, significant chronic respiratory
conditions or musculoskeletal problems interfering with exercise.
Initially, a total of 108 young men showed interest and were screened
by interview ([71]Fig 1 and [72]S1 Checklist). Of those, 84 underwent a
medical examination. Among them, 80 were found to be eligible and were
randomized via computer-generated random numbers, after completing all
baseline tests, to one of three arms: high-intensity interval training
(HIIT; n = 34), continuous endurance training (ET; n = 35) and control
(CO; n = 11). An unequal randomization strategy with an approximately
3:1 ratio of subjects between the intervention vs. control arms was
used to ensure adequate sample size for correlation analysis and
analysis of high and low responders in the intervention groups.
Subsequently, 6 participants dropped out early in their treatment arm
for personal reasons and 74 completed the intervention, including
post-tests. Finally, since the experiment study focuses primarily on
mechanisms and is not an effectiveness study, four participants were
discarded from analysis due to invalid maximal tests, as objectively
determined by failure to attain maximal exertion and associated maximal
heart rate. Thus, a total of 70 participants were available for
metabolomics explorations.
Fig 1. CONSORT flow diagram of participants in the TIMES study.
[73]Fig 1
[74]Open in a new tab
The sample size was calculated using G*Power 3.2.1 software [[75]30]
and determined for MPO in terms of gains expected (~20% or ~50 W) after
8 weeks of intervention, based on data of our laboratory [[76]31],
assuming moderate effects of Cohen’s ƒ = 0.3 for within-between
interaction design [Group (ET, HIIT and CO) vs. Time (Pre and Post
intervention)], r = 0.5 for correlation design, and type I error of
0.05 for a two side-test to reach a statistical power of at least 80%
[[77]32].
The experimental procedures and possible risks associated with the
study were explained to all subjects, who provided written informed
consent before participation. The study was approved by the Research
Ethics Committee from University of Campinas (CAAE:
52997216.8.0000.5404, April 2016) and conducted in conformity with the
standards set by the Declaration of Helsinki [[78]33]. This study was
included in the Brazilian Clinical Trials Registry
([79]ensaiosclinicos.gov.br; RBR-3rh38g; [80]S1 Clinical trial). The
study has been registered after enrolment of participants, because
trial registration was not required by the ethics committee at the time
the trial started. The authors confirm that all ongoing and related
trials for this intervention are registered.
Experimental design
Prior to intervention, resting blood and skeletal muscle biopsy samples
were obtained in the fasted state (12 h). After > 72 h, body mass and
composition were measured followed by a maximal exercise test on a
cycle ergometer designed to measure MPO. The MPO test was repeated 48 h
later. About one week later, participants started the eight-week
intervention protocol in their assigned arm. Maximal exercise tests
were repeated after 4 weeks (to adjust training loads if necessary) and
5 days after the last exercise session. Similarly, in the control
group, resting and fasted blood and muscle biopsies were drawn at the
beginning of week 8 and the MPO test was performed 3 days later. The
MPO and metabolites concentrations were used as our primary and
secondary outcomes, respectively.
Maximal exercise test
Participants were requested to remain sedentary before the MPO test and
were instructed to abstain from consuming alcohol (for 48 h), caffeine
(for 12 h) and food (for 3 h) before the test. The MPO test and retest
was carried out on a cycle ergometer with electromagnetic braking
(Corival 400, Lode BV, Groningen, Netherlands). After 5 min of rest on
the bike, each participant performed a 3 min warm-up at 50 W followed
by workload increments of 25 W every min at a pedaling cadence of 70–80
rpm until exhaustion [[81]34]. Exhaustion was defined as the incapacity
to maintain a cadence of at least 70 rpm despite verbal encouragement
or being unable to keep with the current workload. Heart rate (HR) was
measured during the whole test with a cardiac monitor (S810, Polar,
Kepler, Finland) and maximal heart rate (HR[MAX]) was defined as the
highest value over 10 s reached at MPO as described below. During the
last 15 s of each exercise stage, perceived exertion was recorded with
the Borg’s scale [[82]35]. All participants reported ratings of
perceived exertion ≥ 17 at end of the test. MPO was calculated as
[MATH:
Wcompleted+[25·(t/60)] :MATH]
, where W[completed] is the last fully completed workload level and t
is the number of valid seconds in the final workload [[83]11]. All
tests were performed under controlled conditions of temperature
(21–23°C) and relative humidity (50–70%).
The validity of each maximal exercise test was determined based on the
achieved HR[MAX] in relation to the expected HR[MAX] taking into
account all the MPO tests performed by each subject. As reported
earlier, the within-subject standard deviation of HR[MAX] derived from
repeated measurements reached about 4 beats min^-1 [[84]36]. We opted
to use 2 x within-subject standard deviation or 8 beats min^-1 as the
cutoff value. Thus, in the case of the pre-training tests, the highest
MPO was retained. In the post-training, for the MPO test be valid, the
attained HR[MAX] needed be within 8 beats min^-1 of the HR[MAX]
associated with the pre-test MPO retained.
Exercise training
Prior to the main study, a pilot experiment was conducted with 6
subjects who performed the initial ET and then the initial HIIT
training session in order to verify their comparability by quantifying
the total amount of work performed and the total volume of exercise
executed per week in each program. The total amount of work in Joules
performed was quite similar between the two exercise sessions (HIIT:
250.2 ± 31.3 J; ET: 250.9 ± 48.5 J) as was the total exercise volume
per program calculated as [intensity (% heart rate reserve) x duration
(minutes per session) x frequency (sessions per week) x (number of
weeks) [[85]37]. The exercise volume is reported in “Units of Exercise”
and it reached 816 Units for ET and HIIT, with no difference between
the two programs.
The training programs were performed on cycle ergometers, 40 min per
session, for 8 weeks. The intensity of training was customized for each
individual based on the heart rate reserve (HRR) calculated as the
difference between resting and maximum HR values [[86]38]. For ET,
participants exercised at 70% HRR for 40 min, three times a week in the
first four weeks; and at 75% HRR for 40 min, 4 times a week in the last
four weeks. For HIIT, participants exercised at 50% HRR for 5 min,
followed by 5 intervals of 4 min at 90% HRR (work phase) interspersed
with 3 min at 50% HRR (recovery phase), three days a week, in the first
4 weeks training: and at 60% HRR for 5 min, followed by 5 intervals of
4 min at 90% HRR and 3 min at 60% HRR, 4 days a week in the final four
weeks of training. For the CO, participants were asked to not exercise
for 8 weeks. Control subjects were contacted after 4 weeks to remind
them of the importance of remaining sedentary and to plan for the post
program testing visits. Additionally, after four- and eight-weeks,
control participants were asked if they have changed their physical
activity level. No change involving an increase in walking time greater
30 min a week was recorded.
All exercise sessions were supervised to ensure that the target HR
(monitored by the Polar watch and band) and cycling cadence (70–80 rpm)
were maintained. The power output of the cycle ergometer was adjusted
manually in response to HR variability of each participant at all
training sessions. In each exercise session, subjects were required to
reach the target HR in less than 90 s. For the first series of
exercise, after warming up, we set workload at a power output that
elicited 90% of heart rate reserve for HIIT or 70–75% of heart rate
reserve for ET, based on cardiorespiratory test. If heart rate appeared
to be stable and under the target, additional increments of 10–30 W
were applied until the targeted heart rate was reached. For the
subsequent sets of exercise sessions, we set the last workload used to
reach targeted heart rate, with workload adjustment if heart rate did
not meet the target. All subjects trained in target intensity zone in
all exercise sessions.
Participants received constant visual feedback on pedal frequency,
power output and elapsed time. To minimize possible cardiovascular
drift effects due to dehydration and increased body temperature all
subjects were encouraged to drink water which was offered ad libitum
during each exercise session whereas environmental temperature was kept
the same throughout all training sessions (21–23°C). There was no
airflow provided for cooling.
Participants were asked to remain sedentary outside of the supervised
training program, to maintain their current eating patterns, and to
report important changes in their daily life routine and their use of
new medications during the intervention period. No substantive changes
were recorded [i.e.none affecting hours of sleep (± 1 h per day for a
week) and walking time (> 30 min at a week)].
Body composition
Participants were asked to drink only water and not to eat or exercise
for 2 h prior to the assessment. Height and body mass were recorded
using a stadiometer and digital scale (BOD POD; Cosmed, Chicago, USA)
calibrated according to manufacturer guidelines with participants
without shoes or outer garments. Next, body density was assessed using
air displacement plethysmography (BOD POD Body Composition Tracking
System; Cosmed, Chicago, USA) calibrated according to manufacturer
guidelines. Body density was converted to body fat percentage using the
Siri equation [[87]39].
Blood and muscle tissue collection
Blood samples and muscle biopsies were collected pre-training between
7:00 and 10:00 am, after 12 h of overnight fast. Participants were
instructed to refrain from exercise and alcohol consumption for the
preceding 48 h from caffeine consumption for a minimum of 12 h. In
preparation for the first laboratory visit, participants consumed a
standardized prepacked meal containing 30% of estimated daily energy
needs with the following macronutrient composition: 55–60%
carbohydrate, 15–20% protein and 20–25% fat. Blood samples were
collected from the antecubital vein in serology tubes (Vacuette, 8 ml),
centrifuged at 956 g for 10 min, and then serum was stored at -80°C
until analysis. Muscle biopsies were obtained from the vastus lateralis
of the dominant leg under local anaesthetic [2–3 ml of 2% lidocaine
(Xylestesin)] using the percutaneous biopsy technique combined with
suction [[88]40]. Muscle tissue was quickly dissected free from blood
and connective tissue, and then samples were immediately frozen in
liquid nitrogen and stored at –80°C until further analyses.
Sample preparation for NMR analysis
Serum samples were centrifuged at 20817 g for 45 min at 4°C with a
clean 3 kDa membrane centrifuge filter (Amicon Ultra 0.5 ml,
Millipore). Filtered serum (250 μL) was diluted in a deuterium oxide
solution (D[2]O, 99.9%; Cambridge Isotope Laboratories Inc., USA)
containing phosphate buffer (0.1 M, pH 7.4) and 0.5 mM TMSP-d4
(3-(trimethylsilyl)-2,2',3,3'-tetradeuteropropionic acid from
Sigma-Aldrich) to a 600 uL final solution, and then transferred to a 5
mm NMR tube (Wilmad Standard Series 5 mm, Sigma-Aldrich) for immediate
NMR acquisition [[89]41].
Muscle samples were processed based as described earlier [[90]42,
[91]43]. Briefly, muscle tissue fragments (~40 mg) were weighed, added
to a cold methanol/chloroform solution (2:1 v/v, total of 2.5 mL),
homogenized on ice (3 times of 30 s each, interspaced by 10 s pause)
and sonicated for 3 min with a 10 s pause each minute. A cold
chloroform/ultrapure water solution (1:1 v/v, a total of 2.5 mL) was
then added to the samples. Samples were briefly vortexed to emulsion
and centrifuged (2000 g, 30 min, at 4°C). The upper phase containing
methanol, water, and polar metabolites was collected and evaporated in
a vacuum concentrator (miVac Duo Concentrator, GeneVac, UK). The
remaining solid phase was rehydrated in 0.6 mL of D[2]O-containing
phosphate buffer (0.1 M, pH 7.4) and 0.5 mM of TMSPd4. Samples were
added to a 5-mm NMR tube for immediate scanning.
NMR data acquisition and metabolite identification
Each spectrum was acquired using a Proton (^1H) NMR Varian Inova ^1H
NMR spectrometer (Agilent Technologies Inc., Santa Clara, USA) equipped
with a triple cold resonance probe operating at a ^1H resonance
frequency of 599.89 MHz and a constant temperature of 298 K (25°C). A
total of 256 free induction decays were collected with 32-k data points
over a spectral width of 8000 Hz. An acquisition time of 4 s and
relaxation delay intervals of 1.5 s were implemented between scans
[[92]41]. After all spectra had been acquired, phase adjustment,
baseline correction, removal of water signal (4.6–5.1 ppm), spectral
calibration and quantification were conducted following the parameters
for profiling as defined in Chenomx NMR Suite software 8.31 (Chenomx
Inc., Edmonton, Canada) [[93]44]. All spectra were processed with a
line broadening (lb) of 0.5 Hz. Metabolites (methanol and ethanol) that
were biased due to reagents used in the collection and preparation of
samples were not considered for further analysis.
Determination of technical error of measurement
Only metabolites with satisfactory reproducibility and coefficient of
variation (CV) characteristics were retained for the study. In the
present research, reproducibility was assessed by the within-subject
standard deviation for repeated measures, commonly referred to as the
technical error (TE) of measurement [[94]45], and the intraclass
correlation (ICC) coefficient. In the case of MPO and HR[MAX], the
values obtained at two tests performed within 48 h at baseline were
used for the calculation of TE and CV (n = 59). For metabolomics, data
obtained on a sample of subjects recruited for the purpose of
quantifying TE and CV were used (n = 11; age = 22 ± 4 years; BMI = 23 ±
3). The subjects met the same inclusion criteria as the main study. Two
blood samples were collected at a 15-min interval in order to quantify
the stability of each serum metabolite measurement. Reproducibility and
coefficient of variation measurements were not performed for muscle
tissue samples.
Briefly, TE was calculated by computing the within-subject standard
deviation from repeated measures divided by √2 [[95]46] while CV was
derived from TE divided by its measurement mean multiplied by 100
[[96]45]. Reliability of measurement was further examined with the
computation of the ICC based on a mixed model analysis of variance
[[97]47]. To minimize potential biases due to short-term, unstable
metabolites or poorly reproducible assays, we considered for further
analysis only serum metabolites that exhibited ICC ≥ 0.75 and CV < 25%.
Statistical analysis
For all variables, the distributions of scores were checked for major
deviation from normality. When appropriate (skewness values > 3.0),
logarithmic transformations (log[2]) were used to improve normality of
distributions. However, all transformed data are presented herein in
their original scale for ease of interpretation.
To compare MPO and other traits as well as metabolite concentrations
among the three groups (ET, HIIT and CO) at baseline and their changes
with the interventions, we used a one-way ANOVA followed by a Sidak’s
adjustment for multiple comparisons. Additionally, a two-way ANOVA
(Mixed Linear Model) with a scaled identity covariance matrix structure
was used to assess whether there were group (ET, HIIT and CO), time
(Pre- and Post-training) and interaction group*time effects with time
as a repeated measure effect, and assuming subjects as a random factor.
Whenever a significant F-value was obtained, Sidak’s adjustment was
performed to verify where the differences reside. In another series of
comparisons, the lowest (1^st; low responders—LRE) and highest (3^rd;
high responders—HRE) tertiles of gains in MPO in response to ET and
HIIT were compared for baseline metabolite concentrations using a
Student unpaired t test. To identify baseline metabolites and other
traits associated with MPO, reproducible serum and skeletal muscle
metabolites were correlated to gains in MPO (W) in response to each
intervention program (ET and HIIT) using Pearson correlation
coefficient. These analyses were carried out using the PASW statistics
software version 18.0 (SPSS, Chicago, IL).
For this exploratory and hypothesis-generating study, a large number of
statistical tests were performed. We therefore adjusted the
significance level threshold at a nominal value of P < 0.01,
recognizing that a full Bonferroni adjustment is likely to be too
conservative, leading to reduced discovery from greater number of false
negative observations. To supplement the above, we calculated the 95%
confidence intervals of the effect size (ES: mean difference divided by
pooled SD from all subjects) of each baseline metabolite concentration
between LRE and HRE. If the confidence intervals did not cross zero,
the difference was considered significant [[98]48].
To identify the most relevant baseline metabolic pathways related to
MPO gains for each program, the set of serum and skeletal muscle
metabolites that had correlation coefficients of 0.2 and above
(separately in ET and HIIT) were retained for pathway
over-representation and pathway topology analyses using the web-based
tool MetaboAnalyst 4.0 ([99]http://www.metaboanalyst.ca). The pathway
analysis was based on ‘Homo Sapiens’ library using Hypergeometric Test
for Over Representation Analysis and Relative-Betweeness Centrality for
Test Pathway Topology Analysis [[100]49]. For the pathway enrichment
analysis, we used a false discovery rate of 0.1 [[101]50] to account
for multiple tests while allowing for hypothesis generation to provide
good balance between controlling for false positives and being able to
identify true effects [[102]51]. The threshold for correlation
coefficient was selected on the basis of the range of effects expected
for molecular predictors of CRF trainability (0.07 ≤ r ≤ 0.26) as
observed in previous studies [[103]19, [104]20].
Finally, the baseline metabolites most associated with MPO trainability
were those that scored highly among the three levels of evidences used
in the present analytical strategy: (1) correlations with gains in MPO
(r ≥ 0.2); (2) differences between LRE and HRE; and (3) metabolites
contributions to the most significant pathways related to gains in MPO.
Results
Reproducibility analysis
Both MPO and HR[MAX] showed excellent reproducibility in the
test-retest (48 h) situation, with CVs lower than 3% and ICCs higher
than 0.95 ([105]Table 1). Furthermore, for the 52 serum metabolites
tested in a related pilot study of TIMES with blood samples obtained
15-min apart, ICCs and CVs were in a range of 0.79 to 1.00 and 3–23%,
respectively, for all but 9 metabolites (2-Aminobutyrate,
2-Hydroxybutyrate, 2-Oxoglutarate, Acetate, Acetoacetate, Fumarate,
Glucose, Methylamine and Oxypurinol) which had ICCs below 0.75 and CVs
above 25% ([106]S1 Table). These latter metabolites were judged to be
of low reproducibility and not considered for further analysis.
Table 1. Reproducibility of MPO and HR[MAX] based on test-retest within 48 h
(n = 59) in TIMES.
Variables Mean SD TE CV% ICC
MPO (W) 236.9 ± 36.2 6.54 2.8 0.98
HR[MAX] (bpm min^-1) 192 ± 9 2.85 1.5 0.95
[107]Open in a new tab
Mean and standard deviation (SD) were calculated from the data of both
tests. MPO: Maximal power output; HR[MAX]: Maximal heart rate; TE:
Technical error defined as the within-subject standard deviation
calculated from repeated measurements; CV: Coefficient of variation
derived from the technical error and the measurement mean, expressed as
a percentage; ICC: Intraclass correlation coefficient.
Baseline characteristics
The ET, HIIT and CO groups were comparable for age, height, body mass,
body fat percentage, body mass index (BMI), fasting glucose, systolic
blood pressure, diastolic blood pressure, HR at rest, HR[MAX] and
estimated cardiorespiratory fitness in METS ([108]Table 2), MPO
([109]Table 3), serum metabolite concentration levels ([110]S2 Table)
and skeletal muscle metabolite concentrations ([111]S3 Table) at
baseline.
Table 2. Baseline characteristics of subjects in TIMES.
Variables ET (n = 30) HIIT (n = 30) CO (n = 10)
Mean ± SD Mean ± SD Mean ± SD
Age (years) 23.3 ± 3.4 23.5 ± 2.6 23.6 ± 3.5
Height (m) 1.7 ± 0.1 1.7 ± 0.1 1.7 ± 0.0
Body mass (kg) 72.1 ± 12.1 72.1 ± 10.3 76.5 ± 8.4
Body fat percentage (%) 20.3 ± 7.3 21.3 ± 7.6 21.6 ± 5.7
BMI (kg m^2) 23.9 ± 3.4 23.8 ± 2.7 25.0 ± 2.6
Fasting glucose (mmol L^-1)[112]^a 4.0 ± 0.4 4.2 ± 0.6 3.9 ± 0.3
Systolic BP (mm Hg) 114.1 ± 13.1 116.1 ± 11.2 118.7 ± 11.0
Diastolic BP (mm Hg) 71.8 ± 10.1 74.2 ± 9.3 71.2 ± 10.5
HR at rest (beats min^-1) 71 ± 9 70 ± 7 71 ± 9
HR[MAX] (beats min^-1) 192 ± 9 192 ± 8 195 ± 9
Cardiorespiratory fitness (METS) 12.3 ± 1.9 12.3 ± 1.8 12.1 ± 1.1
[113]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; CO: Control; BMI: Body mass index; BP: Blood pressure; HR:
Heart rate; HR[MAX]: Maximal heart rate.
^a Serum glucose was obtained from the metabolomics assay; at
posteriori, no subject exhibited a serum glucose > 7 mmol L^-1 at
baseline. There were no significant differences between groups for any
variables (P > 0.01 for all one-way ANOVA tests).
Table 3. MPO and HR[MAX] pre and post-intervention in TIMES.
Variables ET (n = 30) HIIT (n = 30) CO (n = 10)
Mean ± SD Mean ± SD Mean ± SD
MPO (W)[114]^a[115]^b[116]^c Pre 237.5 ± 38.4 237.6 ± 32.4 249.5 ± 28.7
Post 286.5 ± 37.6[117]^*[118]^† 294.2 ± 35.3[119]^*[120]^† 239.5 ± 26.3
∆ MPO (W)[121]^a 49.0 ± 15.3[122]^† 56.6 ± 17.2[123]^† -10.0 ± 9.3
∆ MPO (%)[124]^a 21.4 ± 8.0[125]^† 24.3 ± 8.5[126]^† -3.9 ± 3.4
HR[MAX] (beats min^-1)[127]^b Pre 192 ± 9 192 ± 8 195 ± 9
Post 192 ± 7 191 ± 7 195 ± 12
∆ HR[MAX] (beats min^-1)[128]^a 0 ± 5 -1 ± 4 0 ± 5
∆ HR[MAX] (%)[129]^a -0.1 ± 2.6 -0.3 ± 2.2 -0.1 ± 2.7
[130]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; CO: Control; MPO: Maximal power output; HR[MAX]: Maximal
heart rate; ∆: Change pre to post-intervention.
^a Baseline values and changes were analysed by one-way ANOVA.
^b Interactions group*time were analysed by two-way ANOVA (Mixed Linear
Model);
^c Significant interaction group*time.
* Difference from pre (P < 0.01).
^† Difference from CO group (P < 0.01).
Intervention effects
Adherence to training was similar between ET and HIIT programs (97.6 ±
3.0% vs. 97.3 ± 3.5% of training sessions completed, respectively, P =
0.681). There was no difference between the two training programs for
the total amount of work performed on the cycle ergometer across all
sessions (P > 0.01). The total amount of work performed in each
training program was as follows: 8711.7 ± 1740.9 kJ for ET and 7667.0 ±
1402.7 for HIIT.
The main gain in MPO in response to ET reached 49.9 ± 15.3 W (21.4 ±
8.0%) and to HIIT 56.6 ± 17.2 W (24.3 ± 8.5%) with wide ranges from 20
to 77 W (8.3 to 39.3%) for ET and from 31 to 94 W (12.9 to 44.6%) for
HIIT ([131]Table 3 and [132]S1 Fig). There was a significant group*time
interaction effect (P < 0.001), where ET and HIIT groups increased MPO
similarly from baseline to post-training (P < 0.001 for both) while the
CO group experienced no change in MPO (P > 0.01). There were no
significant differences in absolute (W), and relative (%) gains in MPO
between ET and HIIT programs, and both exercise programs registered
higher gains in MPO compared to CO group (P < 0.001 for all
comparisons). There were no significant interactions or main effects
for HR[MAX] ([133]Table 3). Additionally, no cardiovascular drift
across the duration of training sessions were observed for either
training program ([134]S2 Fig).
Associations between baseline values and MPO gains
There were no significant correlations between baseline characteristics
(age, body mass, body fat percentage, BMI, and MPO) and MPO gains with
ET and HIIT programs (P > 0.01 for all, [135]Table 4). In the ET
program, baseline serum metabolite concentration levels that were
correlated with the gains in MPO at r ≥ 0.2 and better included were
o-acetylcarnitine, 3-hydroxybutyrate, propyleneglycol and others as
summarized in [136]Table 5. In the case of baseline skeletal muscle
metabolites, alanine, glutamate, histidine, phenylalanine, proline,
threonine, creatinine, glutathione, isobutyrate, 3-methylxanthine, AMP,
2-phosphoglycerate, histamine and pyruvate concentrations among others
were correlated with the ET gains in MPO ([137]Table 6). In the HIIT
program, the most correlated serum metabolites included lysine,
asparagine, and tyrosine ([138]Table 5), while baseline skeletal muscle
τ-methylhistidine and glycolate were the best correlates of the gains
in MPO ([139]Table 6).
Table 4. Correlation coefficients (r) between gains (∆) in MPO (W) and
baseline characteristics.
Variables ET (n = 30) HIIT (n = 30)
∆ MPO (W) ∆ MPO (W)
MPO (W) -0.255 -0.091
Age (years) -0.226 0.061
Body mass (kg) -0.018 -0.090
Fat mass (%) -0.166 -0.078
BMI (kg m^2) -0.183 -0.191
[140]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; CO: Control; MPO: Maximal power output. BMI: Body mass index.
No correlation reached statistical significance (P > 0.01).
Table 5. Pearson correlation coefficients (r) between gains (∆) in MPO (W)
and baseline serum metabolites concentration levels in TIMES.
Serum metabolites[141]^# ET (n = 30) HIIT (n = 29)
∆ MPO ∆ MPO
Amino acids
Alanine -0.02 -0.09
Asparagine 0.36 -0.33
Glutamine 0.28 -0.11
Glycine 0.15 0.02
Histidine 0.13 -0.20
Isoleucine 0.01 0.12
Lysine -0.08 -0.36
Methionine 0.24 -0.21
Phenylalanine 0.18 -0.29
Proline -0.05 0.12
Threonine 0.29 0.02
Tyrosine 0.05 -0.35
Valine 0.09 ^LT 0.03
Carboxylic acids
Betaine -0.13 -0.10
Creatinine 0.22 -0.19
Guanidoacetate 0.15 0.23
N,N-Dimethylglycine -0.14 -0.22
Ornithine 0.26 0.01
Succinate 0.14 -0.13
Creatine -0.06 0.21
Creatinephosphate -0.01 0.25
Formate -0.19 -0.09
Fatty acids
2-Hydroxyisocaproate 0.16 ^LT 0.18
2-Hydroxyisovalerate 0.05 -0.05
Methylsuccinate 0.21 -0.03
O-Acetylcarnitine 0.42 0.11
Hydroxy acids
3-Hydroxybutyrate 0.42 0.24
Lactate 0.11 -0.22
Glycolate 0.21 0.07
Imidazopyrimidines
Hypoxanthine 0.21 -0.17
Xanthine -0.02 -0.10
Organic carbonic acids
N-Methylhydantoin -0.17 0.23
Urea -0.08 0.27
Organic oxygen compounds
Glycerol 0.33 -0.20
Carnitine 0.15 0.06
Choline 0.06 -0.10
Citrate 0.18 -0.11
Dimethyl-sulfone -0.01 0.13
Trimethylamine 0.12 -0.21
Propyleneglycol 0.42 -0.07
Unclustered
Dimethylamine 0.15 -0.21
Inosine -0.05 -0.02
Pyruvate -0.02 -0.10
[142]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; MPO: Maximal power output; ∆: Change pre to post
intervention. ^LT Data log transformed before analysis. Bold values are
correlation coefficients (r) ≥ 0.2.
^# Metabolites chemical taxonomy was based on class and sub-class from
Human Metabolome Database.
Table 6. Pearson correlation coefficients (r) between gains in MPO and
baseline muscle metabolites levels in TIMES.
Skeletal muscle metabolites[143]^# ET (n = 29) HIIT (n = 28)
∆ MPO ∆ MPO
Alcohols and polyols
Ethyleneglycol 0.19 -0.06
Myo-Inositol 0.24 -0.04
Amino acids
Alanine 0.40 ^LT 0.01
Anserine 0.18 ^LT -0.24
β-Alanine 0.20 ^LT -0.02
Glutamate 0.40 ^LT 0.05
Glutamine 0.34 ^LT -0.04
Glycine 0.36 ^LT -0.08
Histidine 0.40 ^LT -0.06
Isoleucine 0.30 0.17
Leucine 0.13 ^LT 0.20
Phenylalanine 0.46 0.00
Proline 0.38 ^LT 0.19
Threonine 0.46 ^LT -0.12
Tyrosine 0.12 ^LT 0.11
Valine -0.12 0.11
Carboxylic acids
Acetate 0.35 0.14
Betaine 0.07 -0.16
Citrate 0.08 -0.01
Creatine 0.35 ^LT 0.13
Creatinephosphate -0.04 ^LT -0.14
Creatinine 0.38 0.02
Formate 0.23 ^LT 0.06
Fumarate 0.21 0.05
Glutathione 0.40 ^LT -0.25
Isobutyrate 0.45 ^LT 0.09
Isocitrate 0.26 -0.29
Maleate 0.01 0.10
Malonate 0.19 ^LT 0.09
N,N-Dimethylglycine 0.33 -0.12
N-Acetylaspartate 0.33 -0.20
N-Acetylglutamine 0.23 -0.19
Nicotinurate 0.18 0.00
Ornithine 0.30 ^LT -0.19
Succinate 0.20 ^LT 0.15
π-Methylhistidine 0.21 ^LT 0.04
τ-Methylhistidine -0.28 0.35 ^LT
Fatty acids
2-Hydroxyisocaproate 0.34 ^LT -0.04
3-Hydroxyisovalerate 0.33 ^LT 0.23
O-Acetylcarnitine 0.26 ^LT 0.12
Hydroxy acids
Glycolate -0.09 -0.42
Lactate 0.30 0.04
Imidazopyrimidines
3-Methylxanthine 0.38 -0.25
Oxypurinol 0.26 ^LT -0.06
Theophylline 0.36 -0.15
Nucleosides and nucleotides
ADP 0.31 -0.01
AMP 0.38 -0.04
ATP 0.28 ^LT -0.03
NAD+ 0.23 ^LT -0.16
NADP+ 0.11 ^LT -0.23
Organic oxygen compounds
2-Phosphoglycerate 0.37 0.15
Glucose 0.22 ^LT -0.19
Glycerol 0.01 0.08
Organic nitrogen compounds
Carnitine 0.29 0.02
Choline -0.16 -0.12
Dimethylamine 0.36 ^LT 0.05
Histamine 0.45 ^LT 0.13
Methylamine 0.29 ^LT 0.30
N-Nitrosodimethylamine 0.22 -0.02
Trimethylamine 0.17 ^LT -0.15
Trimethylamine-N-oxide 0.31 ^LT -0.15
Tartrate -0.04 0.04
Unclustered
2-Hydroxyphenylacetate 0.36 0.07
Acetamide 0.16 -0.30
Carnosine 0.11 -0.06
Dimethylsulfone 0.24 -0.24
Niacinamide 0.32 -0.01
Pyrimidine 0.11 ^LT 0.04
Pyruvate 0.42 -0.18
Taurine 0.18 ^LT -0.03
[144]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; MPO: Maximal power output; ∆: Change pre to post
intervention. ^LT Data log transformed before analysis. Bold values are
correlation coefficients (r) ≥ 0.2.
^# Metabolites chemical taxonomy was based on class and sub-class from
Human Metabolome Database.
Differences between high and low responders (HRE and LRE)
There were no significant baseline differences between HRE (upper
tertile) and LRE (lower tertile) in ET and HIIT programs for age,
height, body mass, body fat percentage, BMI, HR[MAX] and MPO (P > 0.01
for all, [145]S4 Table). As expected, in both exercise programs, HRE
presented higher absolute and relative MPO gains compared to LRE (P <
0.0001 for both).
For ET program, HRE presented higher baseline serum concentration
levels than LRE for 3-hydroxybutyrate (P = 0.062), glycerol (P =
0.035), methylsuccinate (P = 0.041), O-acetylcarnitine (P = 0.019) as
revealed by the pattern of findings summarized as effect sizes and 95%
confidence intervals in [146]Table 7. For skeletal muscle metabolites,
higher concentration levels were observed in HRE for alanine (P =
0.049), AMP (P = 0.051), creatinine (P = 0.035), proline (P = 0.041),
pyruvate (P = 0.035), threonine (P = 0.044), but lower concentrations
of isobutyrate (P = 0.044) when compared to LRE ([147]Table 8). In the
case of the HIIT program, HRE subjects showed higher baseline serum
concentrations of creatine (P = 0.049) and lower concentration levels
of lysine (P = 0.054), and phenylalanine (P = 0.048) compared to LRE
([148]Table 7). As for skeletal muscle metabolites, HRE displayed lower
concentrations of glycolate compared to LRE ([149]Table 8).
Table 7. Baseline differences in serum metabolites concentration levels
between low responders (LRE) and high responders (HRE) to ET and HIIT
programs in TIMES.
Data are mean ± standard deviation, plus confidence intervals of the
effect size (ES) of differences.
Serum metabolites (mM)^# ET ES 95% CI Serum metabolites (mM)[150]^#
HIIT ES 95% CI
LRE (n = 10) HRE (n = 10) LRE (n = 9) HRE (n = 10)
3-Hydroxybutyrate 0.0364 ± 0.0337 0.1097 ± 0.1063[151]^* -0.93 -1.85
-0.01 3-Hydroxybutyrate 0.0830 ± 0.0641 0.1169 ± 0.1648 -0.27 -1.17
0.64
Asparagine 0.0333 ± 0.0109 0.0414 ± 0.0143 -0.64 -1.54 0.26 Asparagine
0.0402 ± 0.0115 0.0336 ± 0.0125 0.55 -0.37 1.47
Creatinine 0.0658 ± 0.0147 0.0783 ± 0.0217 -0.67 -1.57 0.23 Creatine
0.0091 ± 0.0072 0.0180 ± 0.0105[152]^* -0.97 -1.93 -0.02
Glutamine 0.3342 ± 0.0648 0.4093 ± 0.1909 -0.53 -1.42 0.37
Creatinephosphate 0.0033 ± 0.0020 0.0049 ± 0.0029 -0.65 -1.58 0.27
Glycerol 0.1797 ± 0.0382 0.2352 ± 0.0670[153]^* -1.02 -1.95 -0.09
Dimethylamine 0.0055 ± 0.0041 0.0044 ± 0.0043 0.26 -0.64 1.17
Glycolate 0.0146 ± 0.0020 0.0174 ± 0.0069 -0.54 -1.44 0.35
Guanidoacetate 0.0311 ± 0.0191 0.0456 ± 0.0203 -0.73 -1.66 0.20
Hypoxanthine 0.0031 ± 0.0007 0.0037 ± 0.0011 -0.56 -1.46 0.33 Glycerol
0.2253 ± 0.0679 0.1838 ± 0.0665 0.62 -0.30 1.54
Methionine 0.0223 ± 0.0061 0.0247 ± 0.0064 -0.39 -1.28 0.49 Histidine
0.0950 ± 0.0166 0.0876 ± 0.0106 0.54 -0.38 1.46
Methylsuccinate 0.0107 ± 0.0046 0.0145 ± 0.0030[154]^* -0.99 -1.92
-0.06 Lactate 1.9549 ± 0.5674 1.6320 ± 0.3145 0.71 -0.21 1.64
O-Acetylcarnitine 0.0040 ± 0.0025 0.0073 ± 0.0031[155]^* -1.16 -2.11
-0.22 Lysine 0.1066 ± 0.0239 0.0832 ± 0.0252[156]^* 0.95 0.00 1.90
Ornithine 0.0248 ± 0.0095 0.0350 ± 0.0170 -0.74 -1.65 0.17 Methionine
0.0212 ± 0.0092 0.0181 ± 0.0049 0.43 -0.48 1.34
Propylene glycol 0.0143 ± 0.0047 0.0188 ± 0.0049 -0.92 -1.85 0.00
N.N-Dimethylglycine 0.0032 ± 0.0005 0.0028 ± 0.0007 0.57 -0.35 1.49
Threonine 0.1164 ± 0.0140 0.1371 ± 0.0450 -0.62 -1.52 0.28
N-Methylhydantoin 0.0012 ± 0.0005 0.0016 ± 0.0008 -0.66 -1.59 0.26
Phenylalanine 0.0651 ± 0.0146 0.0545 ± 0.0058[157]^* 0.98 0.03 1.93
Trimethylamine 0.0020 ± 0.0007 0.0018 ± 0.0006 0.32 -0.59 1.22
Tyrosine 0.0758 ± 0.0164 0.0640 ± 0.0079 0.94 -0.01 1.89
Urea 0.5102 ± 0.1680 0.6089 ± 0.2848 -0.42 -1.33
0.49
[158]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; LRE and HRE were stratified by the 1^st and 3^rd tertiles,
respectively, from the gains in maximal power output (MPO) in response
to ET and HIIT. ES: Effect size calculated as the standardized
difference between HRE and LRE in standard deviation units; CI:
Confidence intervals.
^# Set of metabolites with correlation coefficients (r) between
baseline values and (MPO) gains higher than 0.2.
*Difference from LRE (as determined by the 95% CI for ES that did not
cross zero), bold values.
Table 8. Baseline differences in skeletal muscle metabolites concentration
levels between low responders (LRE) and high responders (HRE) to ET and HIIT
programs at baseline in TIMES.
Data are mean ± standard deviation.
Skeletal muscle
metabolites (mM g^-1) ET ES 95% CI Skeletal muscle metabolites
(mM.g^-1) HIIT ES 95% CI
LRE (n = 10) HRE (n = 10) LRE (n = 9) HRE (n = 10)
2-Hydroxyisocaproate^LT 0.0333 ± 0.0174 0.1208 ± 0.2262 -0.64 -1.54
0.26 3-Hydroxyisovalerate 0.0916 ± 0.0224 0.1217 ± 0.0574 -0.68 -1.60
0.25
2-Hydroxyphenylacetate 0.0467 ± 0.0229 0.0761 ± 0.0596 -0.62 -1.52 0.28
3-Methylxanthine 0.0820 ± 0.0465 0.0570 ± 0.0262 0.67 -0.26 1.60
2-Phosphoglycerate 1.1580 ± 0.8462 3.0567 ± 3.4077 -0.76 -1.67 0.14
Acetamide 0.0515 ± 0.0181 0.0336 ± 0.0211 0.90 -0.04 1.85
3-Hydroxyisovalerate^LT 0.0911 ± 0.0210 0.2880 ± 0.5351 -0.52 -1.41
0.37 Anserine 0.0819 ± 0.0621 0.0544 ± 0.0401 0.53 -0.38 1.45
3-Methylxanthine 0.0642 ± 0.0424 0.1111 ± 0.0707 -0.81 -1.72 0.11
Dimethylsulfone 0.0218 ± 0.0107 0.0147 ± 0.0045 0.88 -0.06 1.82
Acetate 0.3637 ± 0.1309 0.6021 ± 0.4515 -0.72 -1.62 0.19 Glutathione
0.1651 ± 0.0822 0.1241 ± 0.0766 0.52 -0.40 1.43
ADP 0.0203 ± 0.0144 0.0319 ± 0.0259 -0.56 -1.45 0.34 Glycolate 0.8198 ±
0.3807 0.4438 ± 0.4032[159]^* 0.96 0.01 1.91
Alanine^LT 1.5874 ± 0.4245 2.7646 ± 2.1839[160]^* -0.95 -1.87 -0.02
Isocitrate 0.2628 ± 0.1744 0.1488 ± 0.0635 0.89 -0.06 1.83
AMP 0.0608 ± 0.0416 0.1152 ± 0.0711[161]^* -0.93 -1.86 -0.01 Leucine
0.1394 ± 0.0866 0.1817 ± 0.1195 -0.40 -1.31 0.51
ATPLT 0.0526 ± 0.0246 0.0914 ± 0.1154 -0.50 -1.38 0.39 Methylamine
0.0568 ± 0.0251 0.0757 ± 0.0592 -0.41 -1.32 0.50
β-Alanine^LT 0.1182 ± 0.0655 0.2497 ± 0.4442 -0.26 -1.14 0.62
N.N-Dimethylglycine 0.036 ± 0.014 0.031 ± 0.0135 0.34 -0.56 1.25
Carnitine 1.4222 ± 1.0910 2.0486 ± 1.1493 -0.56 -1.45 0.33 NADP+ 0.0188
± 0.0083 0.0139 ± 0.0114 0.49 -0.42 1.41
Creatine^LT 12.587 ± 3.6706 22.869 ± 22.243 -0.78 -1.68 0.25
τ-Methylhistidine 0.4473 ± 0.3936 0.9128 ± 1.1093 -0.55 -1.46 0.37
Creatinine 0.1051 ± 0.0587 0.2069 ± 0.1287[162]^* -1.02 -1.95 -0.09
Dimethylamine^LT 0.0197 ± 0.0113 0.0506 ± 0.0801 -0.72 -1.62 0.35
Dimethylsulfone 0.0193 ± 0.0079 0.0262 ± 0.0204 -0.45 -1.33 0.44
Formate^LT 0.8568 ± 0.5706 1.3886 ± 1.3546 -0.50 -1.39 0.38
Fumarate 0.0442 ± 0.0134 0.0574 ± 0.0412 -0.43 -1.32 0.46
Glucose^LT 0.6620 ± 0.3043 0.8370 ± 0.7496 -0.18 -1.06 0.70
Glutamate^LT 0.6019 ± 0.3278 1.2540 ± 1.8610 -0.69 -1.59 0.21
Glutamine^LT 6.4535 ± 2.1208 11.689 ± 11.399 -0.88 -1.80 0.04
Glutathione^LT 0.0807 ± 0.0464 0.1832 ± 0.2377 -0.72 -1.62 0.19
Glycine^LT 0.5711 ± 0.2411 1.0937 ± 1.0838 -0.90 -1.82 0.02
Histamine^LT 0.0956 ± 0.0739 0.3303 ± 0.5266 -0.70 -1.60 0.20
Histidine^LT 0.2220 ± 0.0991 0.5340 ± 0.5839 -0.86 -1.77 0.06
Isobutyrate^LT 0.0373 ± 0.0137 0.2084 ± 0.2820[163]^* -1.02 -1.95 -0.09
Isocitrate 0.1945 ± 0.1482 0.3513 ± 0.2428 -0.78 -1.69 0.13
Isoleucine 0.1003 ± 0.0439 0.2211 ± 0.2751 -0.61 -1.51 0.28
Lactate 3.5887 ± 0.8784 4.8606 ± 3.0539 -0.57 -1.46 0.33
Methylamine^LT 0.0473 ± 0.0478 0.0973 ± 0.1462 -0.68 -1.58 0.22
Myo-Inositol 0.5446 ± 0.3353 0.7324 ± 0.7103 -0.34 -1.22 0.54
N,N-Dimethylglycine 0.0287 ± 0.0177 0.0431 ± 0.0341 -0.53 -1.42 0.36
N-Acetylaspartate 0.0570 ± 0.0233 0.0684 ± 0.0233 -0.49 -1.38 0.40
N-Acetylglutamine 0.0465 ± 0.0212 0.0539 ± 0.0213 -0.35 -1.23 0.53
NAD+^LT 0.1206 ± 0.0631 0.1676 ± 0.1685 -0.37 -1.25 0.51
Niacinamide 0.1062 ± 0.0626 0.1883 ± 0.1918 -0.58 -1.47 0.32
N-Nitrosodimethylamine 0.0624 ± 0.0151 0.0730 ± 0.0494 -0.29 -1.17 0.59
O-Acetylcarnitine^LT 0.5165 ± 0.3459 0.8350 ± 1.2147 -0.26 -1.14 0.62
Ornithine^LT 0.1196 ± 0.0275 0.2086 ± 0.2090 -0.39 -1.27 0.50
Oxypurinol 0.6912 ± 0.5124 1.3503 ± 1.8772 -0.48 -1.37 0.41
Phenylalanine 0.0698 ± 0.0154 0.1372 ± 0.1236 -0.76 -1.67 0.14
π-Methyhistidine^LT 0.1140 ± 0.1634 0.1388 ± 0.2073 -0.34 -1.23 0.54
Proline^LT 0.2829 ± 0.1480 1.1477 ± 2.1528[164]^* -0.98 -1.91 -0.06
Pyruvate 0.1137 ± 0.0482 0.2426 ± 0.1721[165]^* -1.02 -1.95 -0.09
Succinate^LT 0.0816 ± 0.0169 0.1120 ± 0.0973 -0.38 -1.26 0.51
Theophylline 0.1515 ± 0.0958 0.2477 ± 0.2231 -0.56 -1.45 0.33
Threonine^LT 0.2113 ± 0.0911 0.4581 ± 0.5168[166]^* -0.97 -1.89 -0.04
Trimethylamine-N-oxide^LT 0.1011 ± 0.0990 0.2611 ± 0.3509 -0.73 -1.63
0.18
τ-Methylhistidine 0.5810 ± 0.4570 0.3394 ± 0.3076 0.62 -0.28 1.52
[167]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; LRE and HRE were stratified by the 1^st and 3^rd tertiles,
respectively, from the gains in maximal power output (MPO) in response
to ET and HIIT. ES: Effect size calculated as the standardized
difference between HRE and LRE in standard deviation units; CI:
Confidence intervals. ^LT Data log transformed before analysis,
including ES when necessary.
^# Set of metabolites with correlation coefficients (r) between
baseline values and (MPO) gains higher than 0.2.
*Difference from LRE (as determined by the 95% CI for ES that did not
cross zero), bold values.
Pathway analysis
For pathway analysis, baseline metabolites that were correlated at r ≥
0.2 with MPO gains were used, separately for serum (ET: 13 metabolites;
HIIT: 17 metabolites) and skeletal muscle (ET: 49 metabolites; HIIT: 13
metabolites) in each exercise program. We relied on MetaboAnalyst 3.0,
‘Homo Sapiens’ library, and used the test for Over Representation
Analysis and the test for Pathway Topology Analysis to explore pathway
enrichment as suggested by the profile of MPO associated metabolite
concentrations.
We observed multiple pathways significantly related to MPO gains for
each exercise program ([168]Fig 2). Here, we report on pathways that
were first retained at false discovery rate threshold of 0.1 together
with their “impact” score defined as the sum of connections for matched
metabolites normalized by the sum of all metabolite connections within
the relevant significant pathway [[169]49]. The complete list of
significant pathaways and related metabolites for each training
programs are sumarized in details in [170]Fig 2.
Fig 2. Summary of baseline serum and skeletal muscle pathways suggested to be
related to MPO gains under continuous endurance training (ET) and
high-intensity interval training (HIIT) programs in TIMES.
[171]Fig 2
[172]Open in a new tab
The numbers in the figure panels refer to pathways that were most
enriched. Pathway numbers refer to the same pathways across all 4
panels. All pathways represented in the figure had a false discovery
rate of 0.1 (see text for details). The pathway impact on the
horizontal axis is a score representing the relative contribution of
all matched metabolites in relation to all metabolites in the given
pathway. (1) Arginine and proline metabolism (A: glutamine, ornithine,
and creatinine; B: glutamine, ornithine, proline, creatine, and
creatinine; C: guanidoacetate, creatine, phosphocreatine,
N-methylhydantoin, and urea); (2) Aminoacyl-tRNA biosynthesis (A:
asparagine, glutamine, methionine and threonine; B: histidine,
phenylalanine, glutamine, glycine, alanine, isoleucine, threonine, and
proline; C: asparagine, histidine, phenylalanine, methionine, lysine,
and tyrosine); (3) Glycine, serine and threonine metabolism (B:
dimethylglycine, glycine, threonine, creatine, and pyruvate; C:
guanidoacetate, N,N-dimethylglycine, and creatine); (4) Nitrogen
metabolism (A: asparagine and glutamine; B: phenylalanine, glutamine,
histidine, glycine, formate, and AMP; C: phenylalanine, tyrosine,
asparagine, and histidine); (5) Phenylalanine metabolism (B:
phenylalanine, pyruvate, succinate, and fumarate); (6) Alanine,
aspartate and glutamate metabolism (A: asparagine and glutamine; B:
N-acetylaspartate, alanine, pyruvate, glutamine, fumarate, and
succinate); (7) Glyoxylate and dicarboxylate metabolism (B: isocitrate,
formate, pyruvate, and succinate; D: isocitrate and glycolate); (8)
Methane metabolism (B: glycine, formate, trimethylamine N-oxide,
dimethylamine, and methylamine; C: trimethylamine and dimethylamine);
(9) Histidine metabolism (D: anserine and τ-methylhistidine); (10)
Glutathione metabolism (D: Glutathione and NADP+); (11) Pyruvate
metabolism (B: pyruvate, lactate, formate, and acetate); (12) Glutamine
and glutamate metabolism (B: glutamate and glutamine); (13)
Glycerolipid metabolism (A: glycerol and propylene glycol); (14)
Citrate cycle (B: succinate, isocitrate, pyruvate, and fumarate); (15)
Purine metabolism (B: glutamine, ATP, ADP, and AMP); (16) Glycolysis or
Gluconeogenesis (B: pyruvate, lactate, glucose, and acetate); (17)
Propanoate metabolism (B: succinate, lactate, and β-alanine); (18)
Taurine and hypotaurine metabolism (B: alanine, pyruvate, and acetate);
(19) Nicotinate and nicotinamide metabolism (B: niacinamide, NAD+,
pyruvate, and fumarate); (20) Valine, leucine and isoleucine
biosynthesis (B: pyruvate, threonine, and isoleucine); (21)
Phenylalanine, tyrosine and tryptophan biosynthesis (C: phenylalanine
and tyrosine).
From the 21 observed significant pathways, five were related to MPO
gains in both exercise programs ([173]Fig 2), including metabolites
supported by all the three levels of evidence, such as: arginine and
proline metabolism ([174]Fig 2A, [175]2B and 2C), aminoacyl-tRNA
biosynthesis ([176]Fig 2A, [177]2B and 2C), glycine, serine and
threonine metabolism ([178]Fig 2B and 2C), nitrogen metabolism
([179]Fig 2A, [180]2B and 2C) and glyoxylate and dicarboxylate
metabolism ([181]Fig 2B and 2D).
Summary of metabolites and pathways associated with MPO gains
The baseline metabolites most associated with MPO trainability were
identified from the three levels of evidences described above: (1)
correlations with gains in MPO (r ≥ 0.2); (2) differences between LRE
and HRE and (3) contributions of the most significant pathways related
to gains in MPO.
The baseline metabolites supported by all three levels of evidence
were: serum glycerol (a c) ([182]Table 9), skeletal muscle alanine (b),
proline (c), threonine (d), creatinine (e), AMP (f) and pyruvate (g)
for ET ([183]Table 10). In case of HIIT, metabolites were: serum lysine
(h), phenylalanine (i) and creatine (j) ([184]Table 9), and skeletal
muscle glycolate (k) ([185]Table 10).
Table 9. Summary of evidence for baseline serum metabolites related to MPO
gains in response to ET and HIIT in TIMES.
Serum metabolites[186]^# [187]^$ ET HIIT
Baseline association with MPO gains Baseline difference between LRE and
HRE Baseline pathways associated with MPO gains Baseline association
with MPO gains Baseline difference between LRE and HRE Baseline
pathways associated with MPO gains
Amino Acids
Asparagine X AtRNAB; Nitrogen metabolism; AAGMB X AtRNABs; Nitrogen
metabolism
Glutamine X AtRNAB;
Nitrogen metabolism;
AAGMB; APM
Histidine X AtRNABs;
Nitrogen metabolism
Isoleucine
Lysine X LRE < HRE AtRNABs
Methionine X AtRNABs X AtRNAB
Phenylalanine X LRE > HRE AtRNABs; PTTB
Nitrogen metabolism;
Phenylalanine metabolism
Threonine X AtRNABs
Tyrosine X AtRNABs; PTTB;
Nitrogen metabolism;
Phenylalanine metabolism
Carboxylic Acids
Creatinine X APM
Guanidoacetate X APM; GSTM
N,N-Dimethylglycine X GSTM
Ornithine X APM
Creatine X LRE < HRE APM; GSTM
Phosphocreatine X APM
Fatty Acids
Methylsuccinate X LRE < HRE
O-Acetylcarnitine X LRE < HRE
Hydroxy Acids
3-Hydroxybutyrate X LRE < HRE SDKB X SDKB
Lactate X
Glycolate X
Imidazopyrimidines
Hypoxanthine X
Organic Carbonic Acids
N-Methylhydantoin X APM
Urea X APM
Organic Oxygen Compounds
Glycerol X LRE < HRE Glycerolipid metabolism X
Trimethylamine X Methane metabolism
Propyleneglycol X Glycerolipid metabolism
Unclustered
Dimethylamine X Methane metabolism
[188]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training: MPO: Maximal power output; AAGM: Alanine, aspartate and
glutamate metabolism biosynthesis; AtRNAB: Aminoacyl-tRNA biosynthesis:
SDKB: Synthesis and degradation of ketone bodies; APM: Arginine and
proline metabolism; GSTM: Glycine, serine and threonine metabolism;
PTTB: Phenylalanine, tyrosine and tryptophan biosynthesis.
#Metabolites chemical taxonomy was based on class and sub-class from
Human Metabolome Database.
^$ Set of metabolites with correlation coefficients (r) between
baseline values and changes in MPO higher than 0.2 at least one of the
exercise training programs.
Table 10. Summary of evidence for baseline skeletal muscle metabolites
related to MPO gains in response to ET and HIIT in TIMES.
Skeletal muscle[189]^#[190]^$ ET HIIT
Baseline association with MPO gains Baseline difference between LRE and
HRE Baseline pathways associated with MPO gains Baseline association
with MPO gains Baseline difference between LRE and HRE Baseline
pathways associated with MPO gains
Alcohols and Polyols
Myo-Inositol X
Amino Acids
Alanine X LRE < HRE AAGM; AtRNAB; THM
Anserine X Histidine metabolism
β-Alanine X Propanoate metabolism
Glutamate X GGM
Glutamine X AAGM; AtRNAB; APM;
Nitrogen metabolism;
GGM; Purine metabolism
Glycine X AtRNAB; GSTM;
Nitrogen metabolism;
Methane metabolism;
Glutathione metabolism
Histidine X AtRNAB;
Nitrogen metabolism;
Histidine metabolism
Isoleucine X AtRNAB; VLIB;
Leucine X
Phenylalanine X AtRNAB;
Phenylalanine metabolism;
Nitrogen metabolism
Proline X LRE < HRE AAGM; AtRNAB; APM
Threonine X LRE < HRE AtRNAB; GSTM; VLIB
Carboxylic Acids
Acetate X Glycolysis or
Gluconeogenesis;
Pyruvate metabolism;
THM
Creatine X APM; GSTM
Creatinine X LRE < HRE APM
Formate X Nitrogen metabolism;
Methane metabolism;
Pyruvate metabolism;
GDM
Fumarate X AAGM; Citrate cycle; NNM;
Butanoate metabolism;
Phenylalanine metabolism
Glutathione X Glutathione metabolism X Glutathione metabolism
Isobutyrate X LRE > HRE
Isocitrate X Citrate cycle; Glyoxylate X Glyoxylate and dicarboxylate
metabolism
and dicarboxylate
metabolism
N,N-Dimethylglycine X GSTM
N-Acetylaspartate X AAGM X
N-Acetylglutamine X
Ornithine X APM;
Glutathione metabolism
Succinate X GDM; AAGM;
Citrate cycle;
Phenylalanine metabolism;
Butanoate metabolism;
Propanoate metabolism
π-Methylhistidine X Histidine metabolism
τ-Methylhistidine X Histidine metabolism X Histidine metabolism
Fatty Acids
2-Hydroxyisocaproate X
3-Hydroxyisovalerate X X
O-Acetylcarnitine X
Hydroxy Acids
Glycolate X LRE < HRE Glyoxylate and LRE > HRE
dicarboxylate metabolism
Lactate X Glycolysis or
Gluconeogenesis;
Pyruvate metabolism;
Propanoate metabolism
Imidazopyrimidines
3-Methylxanthine X X
Oxypurinol X
Theophylline X
Nucleosides and Nucleotides
ADP X Purine metabolism
AMP X Purine metabolism; LRE < HRE
Nitrogen metabolism
ATP X Purine metabolism
NAD+ X NNM
NADP+ X Glutathione metabolism
Organic Oxygen Compounds
2-Phosphoglycerate X
Glucose X Glycolysis or Gluconeogenesis
Organic Nitrogen Compounds
Carnitine X
Dimethylamine X Methane metabolism
Histamine X Histidine metabolism
Methylamine X X
N-Nitrosodimethylamine X
Trimethylamine-N-oxide X Methane metabolism
Unclustered
2-Hydroxyphenylacetate X
Acetamide X
Dimethylsulfone X X
Niacinamide X NNM
Pyruvate X LRE < HRE AAGM; Citrate cycle; GSTM; Glycolysis or
Gluconeogenesis; Pyruvate metabolism; THM; Phenylalanine metabolism;
GDM; VLIB; Butanoate metabolism
[191]Open in a new tab
ET: Continuous endurance training; HIIT: High-intensity interval
training; MPO: Maximal power output; AAGM: Alanine, aspartate and
glutamate metabolism; GSTM: Glycine, serine and threonine metabolism;
GDM: Glyoxylate and dicarboxylate metabolism; AtRNAB: Aminoacyl-tRNA
biosynthesis; GGM: Glutamine and glutamate metabolism; NNM: Nicotinate
and nicotinamide metabolism; APM: Arginine and proline metabolism; THM:
Taurine and hypotaurine metabolism; VLIB: Valine, leucine and
isoleucine biosynthesis.
^#Metabolites chemical taxonomy was based on class and sub-class from
Human Metabolome Database.
^$Set of metabolites with correlation coefficients (r) between baseline
values and changes in MPO higher than 0.2 at least one of the exercise
training programs.
The most significant pathways associated with MPO gains suggested by
the metabolites for all three levels of evidence were: aminoacyl-tRNA
biosynthesis (b, c, d, h, i); alanine, aspartate and glutamate
metabolism (b, c, g); glycine, serine and threonine metabolism (d, g,
j), arginine and proline metabolism (c, e, j); valine, leucine and
isoleucine biosynthesis (d, g); taurine and hypotaurine metabolism (b,
g); nitrogen metabolism (f, i), glyoxylate and dicarboxylate metabolism
(g, k), phenylalanine metabolism (g, h); glycerolipid metabolism (a);
phenylalanine, tyrosine and tryptophan biosynthesis (i); purine
metabolism (f), pyruvate metabolism/glycolysis or
gluconeogenesis/nicotinate and nicotinamide metabolism/citrate cycle
(g) ([192]S5 Table).
Discussion
In this study, we report on baseline targeted blood and muscle
metabolites in relation to MPO trainability in response to two
different exercise training programs. Our key findings can be
summarized as follows: (i) significant and similiar improvement in MPO
with ET and HIIT programs matched for total units of exercise
performed; (ii) presence of considerable inter-individual response
variability to both training programs; (iii) distinct baseline serum
and skeletal muscle metabolic profile associated with MPO gains within
each training program as well as differences between MPO high and low
responders (HRE vs LRE); (iv) specific baseline metabolites associated
with MPO gains such as serum glycerol, and skeletal muscle alanine,
AMP, creatinine, proline, pyruvate and threonine for ET; serum lysine,
phenylalanine and creatine for HIIT as well as skeletal muscle
glycolate; and (v) pathways in baseline state arguably associated with
MPO trainability, involved in the metabolism of amino acids,
carbohydrates and perhaps translation processes.
In TIMES, the average gains in MPO was about 21% and 24% of the
baseline values after eight weeks of ET and HIIT, respectively, with
the range of responses extending from 8% to 45%. Our findings agree
with those of previous studies involving untrained young adults, in
which MPO gains 24% (5–65%) after 6 weeks of ET [[193]11]; and 21%
after 6 weeks of HIIT [[194]52]. Our finding of similar MPO gains after
ET and HIIT programs stands in contrast to other reports which have
suggested that HIIT generates higher CRF (and by extension MPO) gains
compared to moderate intensity ET [[195]18, [196]53]. However, the two
exercise programs of the present study were perfectly matched for time,
work per session, and total program units of exercise, which is not
always the case in previous studies. This suggests that ET programs
performed at moderate to high intensities in sedentary people (as in
the present study) have the potential to induce as much improvement in
cardiorespiratory fitness and exercise capacity as HIIT-based programs.
In case of ET, we observed higher baseline serum concentrations of
glycerol and skeletal muscle alanine, proline, threonine and pyruvate
in HRE compared to LRE. Glycerol is the backbone of triglyceride
molecules, and its fasting blood levels are strongly influenced by
adipose tissue lipolysis [[197]54, [198]55]. High blood concentrations
of glycerol during endurance exercise are thought to contribute to
thermoregulatory and cardiovascular physiology, attenuating dehydration
and favoring better endurance performance [[199]56]. In TIMES, we
observed consistent relationships between baseline glycerol levels and
a glycerolipid metabolism pathway with MPO trainability in ET. On the
other hand, we found higher baseline muscle concentrations of pyruvate
in HRE. Pyruvate stands at the crossroad between cytosolic and
mitochondrial metabolism and is key in the carbon flux to the citrate
cycle [[200]57, [201]58]. Significant associations between baseline
muscle pyruvate metabolism, citrate cycle, glycolysis pathway,
glyoxylate and dicarboxylate metabolism and phenylalanine metabolism
with MPO trainability in ET were suggested from the metabolite profile.
HRE in the ET program were also characterized by higher concentrations
of alanine, threonine, proline and creatinine. Alanine, threonine and
proline are blood glucose precursors as they can be converted to
pyruvate or citrate cycle intermediates [[202]59] while creatinine is
partly derived from degradation of phosphocreatine, a fast source of
energy for skeletal muscle contraction [[203]60]. Interestingly, in the
ET program, other pathways were suggested from the exploration of the
baseline metabolite profile: glycine, serine and threonine metabolism;
arginine and proline metabolism; taurine and hypotaurine metabolism;
valine, leucine and isoleucine biosynthesis; and aminoacyl-tRNA
biosynthesis, all seemed to be contributing to MPO trainability. All
three levels of evidence also provided support for the notion that
higher baseline muscle AMP (adenosine monophosphate) concentration was
associated with the gains in MPO, whereas the pathway analysis revealed
that baseline purine metabolism and nitrogen metabolism also associated
with MPO gains. AMP is derived from ATP and ADP hydrolysis [[204]61].
In a state of decreased energy levels (i.e., muscle contraction or
fasting), AMP concentration increases activating AMP-activated protein
kinase (AMPK), which stimulates pathways involved in carbohydrate and
fatty acid catabolism to restore ATP levels [[205]62, [206]63].
Previous studies have shown that AMPK activation is related to
increased mitochondrial biogenesis and muscle adaptation to continuous
endurance training [[207]64, [208]65].
In the case of exposure to the HIIT program, the three lines of
evidence indicated that higher concentrations of serum creatine and
lower concentrations of serum lysine and phenylalanine as well as lower
skeletal muscle glycolate were associated with higher MPO gains. Fasted
serum creatine can be attributed mainly to liver synthesis from
glycine, arginine and methionine. Skeletal muscle creatine is converted
to phosphocreatine, which is a source of high-energy phosphate used to
produce ATP [[209]60]. Our pathway analysis emphasized that creatine is
involved in arginine and proline metabolism and the glycine, serine and
threonine metabolism which were both associated with MPO gains.
Previous studies have reported that increased availability of blood and
skeletal muscle creatine through supplementation can improve
ventilatory threshold and submaximal power output with HIIT programs
[[210]66, [211]67]. Lysine is an essential amino acid converted to
acetyl CoA and a precursor of carnitine, which contributes to the
transportation of long-chain fatty acids into the mitochondria
[[212]68]. Phenylalanine is another essential amino acid, and its flux
provides some indication of whole body protein breakdown in the
postabsorptive state [[213]69]. Previous studies have demonstrated
lower plasma phenylalanine and lysine and high creatinine (derived from
creatine) concentrations in healthy subjects with high CRF compared to
low CRF [[214]29]. Here, we showed that pathways in which lysine and
phenylalanine participate (such as phenylalanine tyrosine and
tryptophan biosynthesis, nitrogen metabolism, and aminoacyl-tRNA
biosynthesis) were related to MPO trainability in HIIT. Glycolate is a
hydroxy monocarboxylic acid anion that is oxidized to glyoxylate which
is a precursor of oxalate [[215]70, [216]71]. It has been shown that
the activity of the calcium dependent ATPase which activates the
transport of calcium is itself inhibited by oxalate [[217]72, [218]73].
It is tempting to speculate that lower levels of glycolate may be
associated with reduced inhibition of calcium dependent ATPase, perhaps
contributing to CRF regulation. Furthermore, the lower skeletal muscle
glycolate and its association with higher MPO gains suggested the
involvement of glyoxylate and dicarboxylate metabolism pathway.
Although the glycolate function in skeletal muscle is largely unknown,
one recent study has shown increased glyoxylate and dicarboxylate
metabolism in plantaris muscle of trained rats (5 h after last exercise
training) compared to sedentary controls [[219]74].
Our findings suggest that MPO training response to ET is influenced by
baseline metabolite levels reflecting metabolism of carbohydrates,
amino acids and lipids, with pyruvate playing a pivotal role. On the
other hand, for HIIT, baseline and fasting levels of amino acids were
associated with MPO gains, potentially reflecting a reduced protein
breakdown in high MPO responders compared to low responders. Pathway
analysis revealed that there were 5 pathways derived from baseline
metabolite profiling that were associated with MPO gains in both
exercise programs: aminoacyl-tRNA biosynthesis, arginine and proline
metabolism, glycine, serine and threonine metabolism, glyoxylate and
dicarboxylate metabolism, and nitrogen metabolism. These pathways are
related mainly to amino acid metabolism and exhibit connectivity with
aminoacyl-tRNA biosynthesis. These observations confirm the importance
of both amino acid metabolism and translation processes to MPO
trainability regardless of exercise program in young men. Future
studies are encouraged to investigate baseline serum and skeletal
muscle metabolites predicitve of CRF trainability in other populations
including women and different age groups.
The present study has considerable strengths but also some limitations.
Even though the study was well powered to detect the main effect of
either ET or HIIT on MPO, it is based on small sample sizes for
metabolomics study. Nonetheless, the current study is comparable in
size to previously reported studies on an aspect or another of this
topic [[220]26, [221]27, [222]29]. An important limitation of the
present research design is that it is comparing two training programs
that were only 8 weeks in duration. From other research, we understand
that 8 weeks of training is generally not sufficient to achieve the
maximal training response for a given exercise dose [[223]75]. Thus our
findings are impacted in an unknown manner by the fact that subjects
may not all have reached their maximal training response with our ET or
HIIT training programs in spite of the fact that programs were matched
for total unit of exercise and total work accomplished. We also
speculate that because the intensity of exercise reached substantially
higher peaks in the HIIT exercise sessions compared to the ET sessions,
the association of baseline metabolite with the MPO training gain may
be different perhaps due to specific time-course patterns of
physiological adaptations in each training modality [[224]17, [225]75,
[226]76] and biological sample [[227]77]. This would provide an
explanation for the differences observed in the direction of the
correlations between a number of baseline serum or muscle metabolites
with MPO training response (e.g. positive correlation in one tissue but
negative in the other) and observed contrast between ET and HIIT
metabolic profile. A strength of the study is that it was based on the
metabolite profiles in both serum and muscle. As our metabolomics
exploration was targeted, a limited number of metabolites were
considered. However, a major effort was made to base the metabolite and
pathway analyses solely on those metabolites that exhibited excellent
reproducibility. Low to moderate reproducibility of the excluded
metabolites were attributed mainly to spectrum areas overlapping with
other metabolites or possibly to dynamic changes in fasting metabolism
and ketone body metabolism. We aimed at parsimonious solutions by
focusing primarily on metabolites and pathways that were supported by
all types of analytical strategies employed in this report. The
discussion of our findings and conclusions are essentially based on the
commonality among three lines of evidence as defined herein. Total
control over diet is almost impossible to acnhieve in free-living
subjects participating in exercise training studies. A strenght of the
present study is that diet was controlled in the hours preceding
baseline blood and muscle sampling procedures with subjects receiving a
standardized evening meal and then coming to the laboratory after a
12-hour fast.
We conclude that in young sedentary men, ET programs performed at
moderate to high intensities have the potential to induce as much
improvement in MPO and exercise capacity as HIIT-based programs.
However, the baseline serum and skeletal muscle metabolomics profile
and pathways associated with MPO trainability differ between ET and
HIIT programs. We observed that inter-individual response variability
of MPO is associated with baseline metabolites reflecting amino acid
metabolism and translation processes in both exercise programs with
further associations to metabolites suggesting involvement of
carbohydrate metabolism in ET program. Replication studies are
warranted.
Supporting information
S1 Checklist. CONSORT checklist.
(PDF)
[228]Click here for additional data file.^ (67.8KB, pdf)
S1 Clinical trial
(PDF)
[229]Click here for additional data file.^ (871.3KB, pdf)
S1 Protocol. Within ethics application (in Portuguese).
(PDF)
[230]Click here for additional data file.^ (395.5KB, pdf)
S1 Translation. Of relevant parts of protocol.
(PDF)
[231]Click here for additional data file.^ (168.8KB, pdf)
S1 Changes. Changes to the protocol.
(PDF)
[232]Click here for additional data file.^ (143KB, pdf)
S1 Fig. Heterogeneity of maximal power output (MPO) gains (absolute and
relative) in response to continuous endurance training (ET) and
high-intensity interval training (HIIT) in TIMES.
(TIF)
[233]Click here for additional data file.^ (108KB, tif)
S2 Fig. Mean ± standard deviation of the workloads performed during all
exercise sessions for both training programs in TIMES.
A) Continuous endurance training, (n = 30; B) High-intensity interval
training (n = 30). * Difference from 10 min in A or set 1 in B (P <
0.01).
(TIF)
[234]Click here for additional data file.^ (40.1KB, tif)
S1 Table. Reproducibility of serum metabolite concentrations from
assays obtained from two samples drawn 15-min apart in TIMES (n = 11).
SD: Standard Deviation; TE: Technical Error defined by the
within-subject standard deviation calculated from repeated
measurements; CV: Coefficient of variation derived from the technical
error and the measurement mean, expressed as a percentage; ICC:
Intraclass Correlation Coefficient. ^‡ Metabolites not considered for
further analysis.
(DOCX)
[235]Click here for additional data file.^ (40.6KB, docx)
S2 Table. Baseline serum metabolites levels for each of the three
groups in TIMES.
Data are mean ± standard deviation (SD) and skewness. ET: Continuous
endurance training; HIIT: High-intensity interval training; CO:
Control. There were no significant differences between groups. P-values
from ANOVA one-way were adjusted by false discovery rate [[236]50].
^LTData log transformed before analysis.
(DOCX)
[237]Click here for additional data file.^ (49KB, docx)
S3 Table. Baseline skeletal muscle metabolites levels for each of the
three groups in TIMES.
Data are mean ± standard deviation (SD) and skewness. ET: Continuous
endurance training; HIIT: High-intensity interval training; CO:
Control. There were no significant differences between arms. P-values
from ANOVA one-way were adjusted by false discovery rate (Benjamini &
Hochberg, 1995). ^LT Data log transformed before analysis.
(DOCX)
[238]Click here for additional data file.^ (59.3KB, docx)
S4 Table. Baseline characteristics of participants stratified by the
1^st and 3^nd tertiles of MPO (W) gains in response to ET and HIIT in
TIMES.
Data are mean ± standard deviation (SD) and skewness. ET: Continuous
endurance training; HIIT: High-intensity interval training; MPO:
Maximal power output; HR[MAX]: Maximal heart rate; ∆: Change Pre to
Post intervention. * Difference from LRE (P < 0.0001 by unpaired t
Test).
(DOCX)
[239]Click here for additional data file.^ (36.7KB, docx)
S5 Table. Summary of serum and skeletal muscle metabolites supported by
all 3 levels of evidence and related pathways associated to MPO gains
in response to ET and HIIT in TIMES.
MPO: Maximal power output; ET: Continuous endurance training; HIIT:
High-intensity interval training.
(DOCX)
[240]Click here for additional data file.^ (37.7KB, docx)
Acknowledgments