Mid‐life crisis or mid‐life gains: 2 years of high‐intensity exercise is highly beneficial for the middle‐aged heart

High‐intensity exercise has long been shown to induce beneficial adaptations of the cardiovascular (CV) system, including reducing heart rate (HR) and its regulation by the autonomic nervous system. A number of parameters are typically employed to quantify the effects of exercise or disease on the CV system, including HR variability (Okazaki et al. 2005); however, using HR variability to assess CV health is complicated by the complexity in both neural and non‐neural control mechanisms that contribute to overall CV variability. Specifically, multiple input and output CV and respiratory control mechanisms exist, with the interrelationships between changes in central respiratory control mechanisms, left ventricular (LV) end‐diastolic pressures (LVEDPs), stroke volume (SV), arterial distension, and the arterial–cardiac baroreflex all contributing, at least in part, to short‐term measurements of HR variability. Therefore, HR variability is the output variable of this complicated cascade of neural and non‐neural control mechanisms. Thus, using this parameter to quantify the impact of health and disease on CV regulatory systems requires determination of both the individual and the combined effects of CV and respiratory control systems in order to provide a more comprehensive insight into integrated CV regulation.

In a recent article in The Journal of Physiology, Hieda et al. (2019) developed an innovative three‐component cascade model to assess the effects of 2 years of high‐intensity exercise training on CV variability in 61 healthy, yet previously sedentary, middle‐aged adults (45–64 years). Using a transfer function analysis, their model, which incorporates the dynamic Starling mechanism (i.e. changes in SV induced by changes in LVEDP), dynamic arterial elastance (i.e. changes in systolic blood pressure (sBP) induced by changes in SV) and arterial–cardiac baroreflex function (i.e. changes in HR induced by changes in BP), allowed the authors to eloquently quantify the individual and combined beat‐to‐beat haemodynamic relationships between the input and output of each of these sequential components in the frequency domain at a controlled respiratory frequency (0.2 Hz). The authors found that compared to age‐matched controls, both the dynamic Starling mechanism gain and arterial–cardiac baroreflex gain, but not dynamic arterial elastance, were increased with high‐intensity training under steady‐state conditions, resulting in a 1.34‐fold larger integrated CV regulation gain (gain pulmonary artery diastolic (PAD)‐RR interval) after the intervention. Taken together, these findings provide novel insight into the individual and combined effects of exercise training on the integrated regulation of CV, suggesting high‐intensity training augments total CV function in middle‐aged adults through enhancements in LV compliance and arterial baroreflex sensitivity.

The use of an integrated three‐component cascade model by Hieda et al. (2019) builds upon previous work from their group (Shibata et al. 2006), providing a more comprehensive assessment of the CV and respiratory control mechanisms on integrated CV function by building in the dynamic Starling mechanism. This was an important and necessary adaptation of their previous model, given the gain of the relationship between LVEDP and sBP is dependent on LV output (i.e. SV), which itself is modulated by LV compliance. Similarly, the authors controlled the breathing frequency of the subjects while measuring their CV parameters, which is a notable strength of the study as it controls for the initial input into their cascade model. As changes in intrathoracic pressures during respiration may modify individual components of their three‐cascade model, using a controlled respiratory frequency removed a potential confounding variable from their analysis. Moreover, by using transfer function analyses, the authors were able to quantify the beat‐to‐beat haemodynamic relationships between the input and output of each component of their cascade model in the frequency domain. This has important clinical implications in terms of the application of this model as it would enable investigators to identify both the individual and integrated contributions of each component to CV disease progression or improvement with physiological or pharmacological interventions.

The application of this novel cascade model may be far reaching in studying changes in CV regulation, such as the deterioration of cardiac health seen with ageing and/or disease. This is clearly relevant in middle‐aged adults, in which age‐related decline in cardiac compliance and diastolic function may be an initial change that this model may be particularly sensitive to detect, leading to earlier exercise interventions while there is still plasticity to the CV system. Thus, application of the three‐component cascade model to middle‐aged individuals was an important aspect of the study, as it is well documented that ageing is associated with reduced LV compliance and lower LV end‐diastolic volumes (Fujimoto et al. 2012). The present study proves that their middle‐age subjects were in the ‘sweet spot’ for cardiac plasticity as vigorous exercise training enhanced LV compliance and SV augmentation, which is the primary factor for their increase of integrated CV regulation gain. Furthermore, we speculate that this model could also allow for earlier detection of ‘responders’ and ‘non‐responders’ to exercise and pharmacological CV interventions, which would allow for a more individualized approach to treatment. In addition, the findings from this study have caused us to re‐evaluate findings from our own group (Lakin et al. 2018), in which 6 weeks of high‐intensity swim or voluntary free wheel exercise resulted in increases in cardiac vagal nerve activity and HR variability in mice. Based on these findings we are motivated to investigate the role of non‐neural CV factors, specifically the cardiac–arterial baroreflex, which might contribute to the enhanced HR variability and the beneficial effects of exercise training in our model.

The main finding of the study that 2 years of vigorous exercise training increases integrated CV function through augmenting dynamic Starling mechanism and dynamic arterial–cardiac baroreflex gain is intriguing, but whether these findings extend beyond steady‐state conditions is currently unclear. In order to fully understand the behaviour of the CV system, it is important to study it in response to stressors or in the context of disease. For example, while the current study provides evidence of steady‐state improvements in integrated CV regulation with exercise training, it would be interesting to see how each component of the cascade model changes to augment CV function during moderate‐ or high‐intensity endurance exercise. Alternatively, the independent contributions of neural and non‐neural input and output variables to integrated CV regulation could be measured under controlled conditions in response to pharmacological interventions that alter CV homeostasis, including isoproterenol, nitroprusside, phenylephrine, and/or atropine. These studies would be particularly relevant given many high‐level endurance athletes experience central hypovolaemia, orthostatic hypotension and an attenuation of arterial–cardiac baroreflex sensitivity during orthostatic stress (Ogoh et al. 2003), which would be contradictory to the finding of enhanced dynamic arterial–cardiac baroreflex gain at steady‐state in response to high‐intensity training in the current study. Thus, it would be interesting to apply the three‐component cascade model of integrated CV regulation developed by Hieda et al. (2019) to high‐level endurance athletes with orthostatic hypotension as this finding suggests there may be a disconnect between steady‐state and non‐steady‐state responses to haemodynamic stressors such as central hypovolaemia. Nonetheless, it is clear that application of the three‐component cascade model beyond steady‐state conditions requires further study.

The study of Hieda et al. (2019) is not without its limitations, but it is clear that the authors could use this as an opportunity to refine the model moving forward. As the authors note, measurements of augmentation index and pulse wave velocity would have been more appropriate and sensitive to study changes in dynamic arterial elastance and, more importantly, central and peripheral adaptations to 2 years of vigorous endurance training using their three‐component cascade model. Nonetheless, the authors could use their measures of arterial elastance gain to further interrogate the relationship to arterial structure and function, especially in those individuals in which dynamic arterial elastance was significantly reduced. In addition, the decision to use PAD pressure as a surrogate of pulmonary capillary wedge pressure (PCWP) or LVEDP is unclear, especially given the routine use of PCWP measurements in exercise studies (Wright et al. 2016); this might enhance the comparability of their findings to studies examining the effects of exercise, ageing, and/or CV disease on LVEDPs. Lastly, while the authors did a pre–post comparison of their three‐component cascade model to determine the effects of 2 years of high‐intensity exercise, it would be interesting to determine the time course of the adaptations throughout training, especially given the exercise programme remained stable for the final 14 months. This could have important clinical implications, especially given changes in cardiac plasticity with ageing as well as CV disease progression. Thus, the three‐component cascade model may impact on individualized exercise prescription and how we track CV disease progression and improvements moving forward.

In conclusion, Hieda et al. (2019) have developed a novel three‐component cascade model to demonstrate that 2 years of high‐intensity exercise training results in an increase in dynamic Starling and arterial–cardiac baroreflex gain as well as integrated CV gain in middle‐aged adults. The use of this innovative model to address the complex and interconnected nature of the neural and non‐neural components of CV regulation has tremendous clinical potential, which will be an invaluable tool moving forward to monitor not only the progression of exercise interventions, but that of ageing and disease on integrated CV health.