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Record W4223550137 · doi:10.1113/jp283031

A growing advantage: are cardiovascular adaptations to endurance training in children enhanced following the onset of puberty?

2022· letter· en· W4223550137 on OpenAlexaffabout
Alexa Govette, Adam N. Di Salvo

Bibliographic record

VenueThe Journal of Physiology · 2022
Typeletter
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEndurance trainingStroke volumeMedicineMuscle hypertrophyInternal medicineHeart rateVO2 maxCardiologyAthletesPhysiological AdaptationsCardiac hypertrophyEndocrinologyPsychologyPhysical therapyPhysiologyBiologyBlood pressure

Abstract

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In response to endurance exercise training, common cardiovascular (CV) adaptations include eccentric cardiac remodelling and expansion of haemoglobin (Hb) volume. These training-induced adaptations contribute to enhancing peak exercise performance by efficiently increasing the rate of convective oxygen delivery through elevations in stroke volume (SV) and arterial oxygen carrying capacity, respectively. Following puberty, the influence of growth and sex-related hormones appears to further increase CV adaptations. While research examining CV adaptations in children is limited, recent work identified that left ventricular hypertrophy is less prevalent in pre-pubertal athletes compared to their post-pubertal counterparts despite similar increases in maximal rates of oxygen consumption ( V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ ) (McClean et al. 2018). As such, whether the hormonal environment during puberty provides an opportunity for enhanced cardiac remodelling and haematological adaptation to maximize exercise performance should be explored. In a recent study published in The Journal of Physiology, Perkins et al. (2022) investigated the effect of endurance training on cardiac and haematological adaptations, and whether maturation status (i.e. puberty) had an additional effect on these variables. The relationship between these central variables to convective oxygen delivery and V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ was also examined. One hundred and fifty-four boys and girls were assigned to one of two groups: endurance-trained (ET; n = 87) or untrained (UN; n = 67). Recruitment for ET occurred across various swimming, running, cycling and triathlon clubs. Individuals were deemed ‘endurance-trained’ if they completed at least 3 h of structured endurance training per week, for the past 12 months and were competing within their respective sport. This was in addition to meeting the UK minimum physical activity guidelines (≥60 min of moderate intensity exercise each day). In contrast, untrained participants were characterized as not meeting the minimum physical activity guidelines, as outlined above. The experimental protocol involved two laboratory visits. Within the first visit, anthropometric data were obtained to determine peak height velocity (PHV) – an indirect measure of puberty. Participants were subsequently characterized as pre-pubertal (pre-PHV) or post-pubertal (post-PHV). Resting blood pressure was also assessed prior to the completion of progressive cycling exercise to determine V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ and maximal heart rate (HRmax). During the second visit, body composition was determined using skinfold thickness, and participants performed carbon monoxide rebreathing to quantify haematological variables. Resting transthoracic echocardiography was performed focusing on the left ventricle. While most meaningful cardiac adaptations are structural in nature, given the unique haemodynamic challenge of exercise, functional cardiac adaptations during exercise may also prove to be important. Analyses of functional cardiac measures would provide another valuable point of comparison, particularly when exploring contributors to V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ . Although performing echocardiography is more feasible at rest, it can reliably be completed during submaximal exercise on a specialized stress-echocardiography table ergometer, prior to the fusion of early and late diastolic filling at elevated heart rates (∼110 bpm). Thus, future investigation of differences in cardiac function during exercise may provide additional evidence towards an increased V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ that cannot be ascertained by structural adaptations alone. Perkins et al. (2022) conducted an extensive investigation of the cardiac and haematological adaptations brought about by training status and puberty. Their findings confirm that there are indeed training-related CV adaptations between ET and UN, and furthermore, that these differences in cardiac and haematological adaptations are more pronounced post-PHV. As a result, the authors conclude that the stage of puberty is key for enhancing adaptations to endurance training. In the context of V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ , their findings also highlight an important role of puberty in eliciting a shift towards the central components of oxygen delivery. One interesting observation was that training-induced CV adaptations within the pre-pubertal children differed considerably with respect to biological sex. While training-induced differences in end diastolic volume and SV were present in boys both pre- and post-PHV, they were markedly absent in girls pre-PHV yet present post-PHV. This suggests enhanced cardiac remodelling in boys regardless of maturation stage, whereas in girls, this adaptation appears dependent on puberty. Moreover, while Hb mass, blood volume and plasma volume were enhanced by training in both boys and girls post-PHV, in pre-PHV these adaptations were only observed in girls. This may further suggest that differences in CV adaptations between sexes exist with endurance training even prior to the onset of puberty. While this study was not designed to detect an effect of sex on CV adaptation to endurance training, the differences between boys and girls, particularly within the pre-PHV participants, is surprising given that sex-related differences to exercise training are often reported following puberty when sex steroid concentrations differ. Thus, further investigation into the possible sex-related differences in CV adaptations within pre-pubertal endurance-trained participants may be an avenue for future research. The desire to complete a non-invasive study in a young paediatric cohort is understood and appreciated; however, whether participants were truly matched by maturation status is unclear and may contribute to the finding that in post-PHV there appeared to be a greater magnitude of cardiac remodelling and Hb expansion when compared to pre-PHV. Keeping non-invasive assessments in mind, the authors assessed physical maturity using PHV as a metric of peak growth that is indirectly associated with having reached puberty. Currently, the gold standard for assessing paediatric skeletal muscle maturation is bone age, which can be obtained with X-rays of the hand and wrist using the Tanner–Whitehouse-3 method. This method may provide a better proxy of maturity, but it requires exposure to a small dose of radiation. Alternatively, confirmation of menstrual cycle patterns in the female participants would have been a feasible way to ensure appropriate allocation to each pre- and post-PHV group, without having to obtain blood samples to evaluate sex steroid concentrations. Elevations in oestrogen concentration observed at the onset of menses is known to increase blood flow, cardiac performance and endothelial function while decreasing blood pressure. Given that the girls in this study ranged from 8 to 17 years of age and were within typical menstruating ages in both pubertal subgroups (∼10–15 years old), confirmation that oestrogen was low in pre-PHV and in contrast higher in post-PHV would help to corroborate the main finding that puberty influenced CV adaptations to training. The authors should be commended for recruiting participants from a spectrum of endurance sports like swimming, running, cycling and triathlon clubs. However, exercise modality and intensity may influence training responses, independent of hormonal changes during puberty. The haemodynamic stimulus (e.g. the degree of pressure and volume load) elicited by training modality may be an important determinant of cardiac remodelling. Cyclists represented the greatest proportion of boys in both the pre- (56%) and post- (68%) PHV groups. However, 21% and 17% of pre-PHV boys were swimmers and runners, while post-PHV swimmers and runners were comparatively under-represented, with 0% and 5%, respectively. Importantly, the extent of cardiac adaptation differs by sport modality. Swimmers often elicit a lower degree of cardiac remodelling following training compared to running or cycling (Martinez et al. 2021). Therefore, the authors’ observation that cardiac and haematological measures and their contribution to relative V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ are exacerbated in post-PHV compared to pre-PHV children may be indicative of the variety of sport modalities within pubertal subgroups. Additionally, V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ responses are dependent on exercise modality (Millet et al., 2009). For example, runners often demonstrate a decreased V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ during cycling compared to treadmill running. Interestingly, cyclists can achieve equal V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ values during both cycling and treadmill running. Perkins and colleagues (2022) assessed V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ using a cycle ergometer; however, given the significant proportion of non-cyclist participants in this study (∼30%), it is possible that some were disadvantaged (e.g. swimmers and runners), achieving a lower V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ due to the exercise testing modality. Exercise intensity may be particularly important for eliciting training adaptations in children. Previous work suggests that pre-pubertal children require a greater training stimulus compared to following puberty to elicit improvements in V ̇ O 2 max ${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ (Massicotte & Macnab, 1974). In this study, self-reported training records were collected from participants, but the intensity of training sessions was not well described. Characterization of training intensity using a quantifiable metric such training impulse (the product of session effort and time) would have confirmed whether training stimuli were equal between participants, as this could affect the magnitude of training-induced adaptations. Perkins et al. (2022) sought to understand how puberty may magnify cardiac and haematological adaptations to endurance training in children. The main findings were that puberty enhanced training-induced CV adaptations observed in ET compared to UN. We applaud the authors for conducting a rigorous study, which involved the recruitment and experimental testing of over 150 children from a variety of sports backgrounds. This novel work was executed through a complex but thorough study design which incorporated both boys and girls. Differences in CV adaptations were observed between sexes within each pubertal subgroup. However, these differences may be attributed to indirectly measuring maturity via PHV and the lack of menses information in girls for appropriate matching, or possible differences in training stimuli due to unequal representation of exercise modalities. Nevertheless, we propose that future research should investigate the effect of sex on CV training adaptations within pre-pubertal groups to clarify our understanding of training-induced adaptations within children. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. None. Both authors, A.G. and A.N.D., contributed equally to the writing and reading of this manuscript. Both authors have read and approved the final version of this manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed. None. The authors would like to acknowledge their appreciation for the insightful discussions gained through our participation in KIN5546 at the University of Toronto. Specifically, the authors thank Dr. Robert Bentley for his exceptional guidance and feedback during the preparation of this manuscript.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.254
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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