Impaired signaling intrinsic to sinoatrial node pacemaker cells affects heart rate variability during cardiac disease

Effect of simultaneous physical and auditory stressors on cardiorespiratory response

In occupational medicine, monitoring individual stress-related physiological responses is an effective tool for minimizing health risks at the workplace. From an audiology perspective, this particularly concerns the effects of auditory stress, which leads to increased listening effort with subsequent hearing fatigue. A study was conducted to investigate whether cardio-respiratory responses can detect the effects of a multi-level combination of physical and auditory stressors. To investigate their measurability and determine whether an interaction exists, a selection of cardio-respiratory vital parameters such as heart rate, features in the time and frequency domain of the heart rate variability, breathing rate, respiratory minute volume, and the respiratory quotient were analyzed. The results showed a significant main effect of physical stress on all assessed parameters. Auditory stress demonstrated a significant impact on breathing frequency, root mean square of successive differences of interbeat intervals, and the power components of the low and high frequency bands of the heart rate variability. No interaction between auditory and physical stressors was observed across any of the examined parameters. From these results we conclude that physiological responses to different sources of stress can be recorded within selected vital parameters, independent of external stimuli such as ambient noise. In an occupational context, we see potential in tracking individual auditory stress by monitoring cardio-respiratory parameters, especially breathing patterns. By knowing the individual (auditory) stress level, conclusions could be drawn about the worker's ability to concentrate and further measures could be taken to combat safety risks in the work environment.

Lifelong longitudinal assessment of the contribution of multi-fractal fluctuations to heart rate and heart rate variability in aging mice: role of the sinoatrial node and autonomic nervous system

Aging is a major risk factor for sinoatrial node (SAN) dysfunction, which can impair heart rate (HR) control and heart rate variability (HRV). HR and HRV are determined by intrinsic SAN function and its regulation by the autonomic nervous system (ANS). The purpose of this study was to use multi-scale multi-fractal detrended fluctuation analysis (MSMFDFA; a complexity-based approach to analyze multi-fractal dynamics) to longitudinally assess changes in multi-fractal HRV properties and SAN function in ECG time series recorded repeatedly across the full adult lifespan in mice. ECGs were recorded in anesthetized mice in baseline conditions and after autonomic nervous system blockade every three months beginning at 6 months of age until the end of life. MSMFDFA was used to assess HRV and SAN function every three months between 6 and 27 months of age. Intrinsic HR (i.e. HR during ANS blockade) remained relatively stable until 15 months of age, and then progressively declined until study endpoint at 27 months of age. MSMFDFA revealed sudden and rapid changes in multi-fractal properties of the ECG RR interval time series in aging mice. In particular, multi-fractal spectrum width (MFSW, a measure of multi-fractality) was relatively stable between 6 months and 15 months of age and then progressively increased at 27 months of age. These changes in MFSW were evident in baseline conditions and during ANS blockade. Thus, intrinsic SAN function declines progressively during aging and is manifested by age-associated changes in multi-fractal HRV across the lifespan in mice, which can be accurately quantified by MSMFDFA.

Evaluation of non-linear heart rate variability using multi-scale multi-fractal detrended fluctuation analysis in mice: Roles of the autonomic nervous system and sinoatrial node

Nonlinear analyses of heart rate variability (HRV) can be used to quantify the unpredictability, fractal properties and complexity of heart rate. Fractality and its analysis provides valuable information about cardiovascular health. Multi-Scale Multi-Fractal Detrended Fluctuation Analysis (MSMFDFA) is a complexity-based algorithm that can be used to quantify the multi-fractal dynamics of the HRV time series through investigating characteristic exponents at different time scales. This method is applicable to short time series and it is robust to noise and nonstationarity. We have used MSMFDFA, which enables assessment of HRV in the frequency ranges encompassing the very-low frequency and ultra-low frequency bands, to jointly assess multi-scale and multi-fractal dynamics of HRV signals obtained from telemetric ECG recordings in wildtype mice at baseline and after autonomic nervous system (ANS) blockade, from electrograms recorded from isolated atrial preparations and from spontaneous action potential recordings in isolated sinoatrial node myocytes. Data demonstrate that the fractal profile of the intrinsic heart rate is significantly different from the baseline heart rate in vivo, and it is also altered after ANS blockade at specific scales and fractal order domains. For beating rate in isolated atrial preparations and intrinsic heart rate in vivo, the average fractal structure of the HRV increased and multi-fractality strength decreased. These data demonstrate that fractal properties of the HRV depend on both ANS activity and intrinsic sinoatrial node function and that assessing multi-fractality at different time scales is an effective approach for HRV assessment.

Smart Wearables for Cardiac Autonomic Monitoring in Isolated, Confined and Extreme Environments: A Perspective from Field Research in Antarctica

Antarctica is a space-analog ICE (isolated, cold, and extreme) environment. Cardiovascular and heart autonomic adjustments are key-adaptive physiological responses to Antarctica, both in summer camps and in research stations winter-over. Research fieldwork in ICE environments imposes limitations such as energy restriction, the need for portable and easy-to-handle resources, and resistance of materials to cold and snow/water. Herein, we present the methods we use for cardiac monitoring in the Antarctic field, the limitations of the equipment currently available, and the specific demands for smart wearables to physiological and health tracking in ICE environments, including the increased remote monitoring demand due to COVID-19 restrictions.

Impact of Chronic Fetal Hypoxia and Inflammation on Cardiac Pacemaker Cell Development

Chronic fetal hypoxia and infection are examples of adverse conditions during complicated pregnancy, which impact cardiac myogenesis and increase the lifetime risk of heart disease. However, the effects that chronic hypoxic or inflammatory environments exert on cardiac pacemaker cells are poorly understood. Here, we review the current evidence and novel avenues of bench-to-bed research in this field of perinatal cardiogenesis as well as its translational significance for early detection of future risk for cardiovascular disease.

Arrhythmic Risk in Elderly Patients Candidates to Transcatheter Aortic Valve Replacement: Predictive Role of Repolarization Temporal Dispersion

Background/Aim

Degenerative aortic valve stenosis (AS) is associated to ventricular arrhythmias and sudden cardiac death, as well as mental stress in specific patients. In such a context, substrate, autonomic imbalance as well as repolarization dispersion abnormalities play an undoubted role. Aim of the study was to evaluate the increase of premature ventricular contractions (PVC) and complex ventricular arrhythmias during mental stress in elderly patients candidate to the transcatheter aortic valve replacement (TAVR).

Methods

In eighty-one elderly patients with AS we calculated several short-period RR- and QT-derived variables at rest, during controlled breathing and during mild mental stress, the latter being represented by a mini-mental state evaluation (MMSE).

Results

All the myocardial repolarization dispersion markers worsened during mental stress (p < 0.05). Furthermore, during MMSE, low frequency component of the RR variability increased significantly both as absolute power (LF_RR) and normalized units (LF_{RRN U}) (p < 0.05) as well as the low-high frequency ratio (LF_RR/HF_RR) (p < 0.05). Eventually, twenty-four (30%) and twelve (15%) patients increased significantly PVC and, respectively, complex ventricular arrhythmias during the MMSE administration. At multivariate logistic regression analysis, the standard deviation of QTend (QTe_sd), obtained at rest, was predictive of increased PVC (odd ratio: 1.54, 95% CI 1.14-2.08; p = 0.005) and complex ventricular arrhythmias (odd ratio: 2.31, 95% CI 1.40-3.83; p = 0.001) during MMSE. The QTe_sd showed the widest sensitive-specificity area under the curve for the increase of PVC (AUC: 0.699, 95% CI: 0.576-0.822, p < 0.05) and complex ventricular arrhythmias (AUC: 0.801, 95% CI: 0.648-0.954, p < 0.05).

Conclusion

In elderly with AS ventricular arrhythmias worsened during a simple cognitive assessment, this events being a possible further burden on the outcome of TAVR. QTe_sd might be useful to identify those patients with the highest risk of ventricular arrhythmias. Whether the TAVR could led to a QTe_sd reduction and, hence, to a reduction of the arrhythmic burden in this setting of patients is worthy to be investigated.

Diet-Induced Metabolic Syndrome Reduced Heart Rate Variability and Increased Irregularity and Complexity of Short-Term RR Time Series in Rabbits

Simple Summary

In recent years, obesity and metabolic syndrome (MetS) have become more prevalent, owing to increased unhealthy habits and sedentary lifestyles becoming public health problems. Both conditions are linked with a higher prevalence of sudden cardiac death (SCD), but the exact mechanisms are not known. An autonomic nervous system imbalance can produce atrial and ventricular arrhythmias, which cause SCD, and this can be quantified by analyzing heart rate variability (HRV). We investigated HRV using time-domain, frequency-domain and nonlinear analyses during the development of MetS in rabbits and found HRV modifications that could be associated with the higher prevalence of SCD in this pathological condition.

Abstract

Metabolic syndrome (MetS) has been linked to a higher prevalence of sudden cardiac death (SCD), but the mechanisms are not well understood. One possible underlying mechanism may be an abnormal modulation of autonomic activity, which can be quantified by analyzing heart rate variability (HRV). Our aim was to investigate the modifications of short-term HRV in an experimental rabbit model during the time-course of MetS development. NZW rabbits were randomly assigned to a control (n = 10) or a MetS group (n = 13), fed 28 weeks with control or high-fat, high-sucrose diets. After anesthesia, a 15-min ECG recording was acquired before diet administration and at weeks 14 and 28. We analyzed short RR time series using time-domain, frequency-domain and nonlinear analyses. A mixed-model factorial ANOVA was used for statistical analysis. Time-domain analysis showed a 52.4% decrease in the standard deviation of heart rate in animals from the MetS group at week 28, but no changes in the rest of parameters. In the frequency domain, we found a 9.7% decrease in the very low frequency and a 380.0% increase of the low frequency bands in MetS animals at week 28, whereas high frequency remained unchanged. Nonlinear analyses showed increased complexity and irregularity of the RR time series in MetS animals.

PhysioZoo: A Novel Open Access Platform for Heart Rate Variability Analysis of Mammalian Electrocardiographic Data

Background: The time variation between consecutive heartbeats is commonly referred to as heart rate variability (HRV). Loss of complexity in HRV has been documented in several cardiovascular diseases and has been associated with an increase in morbidity and mortality. However, the mechanisms that control HRV are not well understood. Animal experiments are the key to investigating this question. However, to date, there are no standard open source tools for HRV analysis of mammalian electrocardiogram (ECG) data and no centralized public databases for researchers to access. Methods: We created an open source software solution specifically designed for HRV analysis from ECG data of multiple mammals, including humans. We also created a set of public databases of mammalian ECG signals (dog, rabbit and mouse) with manually corrected R-peaks (>170,000 annotations) and signal quality annotations. The platform (software and databases) is called PhysioZoo. Results: PhysioZoo makes it possible to load ECG data and perform very accurate R-peak detection (F 1 > 98%). It also allows the user to manually correct the R-peak locations and annotate low signal quality of the underlying ECG. PhysioZoo implements state of the art HRV measures adapted for different mammals (dogs, rabbits, and mice) and allows easy export of all computed measures together with standard data representation figures. PhysioZoo provides databases and standard ranges for all HRV measures computed on healthy, conscious humans, dogs, rabbits, and mice at rest. Study of these measures across different mammals can provide new insights into the complexity of heart rate dynamics across species. Conclusion: PhysioZoo enables the standardization and reproducibility of HRV analysis in mammalian models through its open source code, freely available software, and open access databases. PhysioZoo will support and enable new investigations in mammalian HRV research. The source code and software are available on www.physiozoo.com.

The end effector of circadian heart rate variation: the sinoatrial node pacemaker cell

Cardiovascular function is regulated by the rhythmicity of circadian, infradian and ultradian clocks. Specific time scales of different cell types drive their functions: circadian gene regulation at hours scale, activation-inactivation cycles of ion channels at millisecond scales, the heart's beating rate at hundreds of millisecond scales, and low frequency autonomic signaling at cycles of tens of seconds. Heart rate and rhythm are modulated by a hierarchical clock system: autonomic signaling from the brain releases neurotransmitters from the vagus and sympathetic nerves to the heart’s pacemaker cells and activate receptors on the cell. These receptors activating ultradian clock functions embedded within pacemaker cells include sarcoplasmic reticulum rhythmic spontaneous Ca²⁺ cycling, rhythmic ion channel current activation and inactivation, and rhythmic oscillatory mitochondria ATP production. Here we summarize the evidence that intrinsic pacemaker cell mechanisms are the end effector of the hierarchical brain-heart circadian clock system. [BMB Reports 2015; 48(12): 677-684]

The Autonomic Nervous System Regulates the Heart Rate through cAMP-PKA Dependent and Independent Coupled-Clock Pacemaker Cell Mechanisms

Sinoatrial nodal cells (SANCs) generate spontaneous action potentials (APs) that control the cardiac rate. The brain modulates SANC automaticity, via the autonomic nervous system, by stimulating membrane receptors that activate (adrenergic) or inactivate (cholinergic) adenylyl cyclase (AC). However, these opposing afferents are not simply additive. We showed that activation of adrenergic signaling increases AC-cAMP/PKA signaling, which mediates the increase in the SANC AP firing rate (i.e., positive chronotropic modulation). However, there is a limited understanding of the underlying internal pacemaker mechanisms involved in the crosstalk between cholinergic receptors and the decrease in the SANC AP firing rate (i.e., negative chronotropic modulation). We hypothesize that changes in AC-cAMP/PKA activity are crucial for mediating either decrease or increase in the AP firing rate and that the change in rate is due to both internal and membrane mechanisms. In cultured adult rabbit pacemaker cells infected with an adenovirus expressing the FRET sensor AKAR3, PKA activity and AP firing rate were tightly linked in response to either adrenergic receptor stimulation (by isoproterenol, ISO) or cholinergic stimulation (by carbachol, CCh). To identify the main molecular targets that mediate between PKA signaling and pacemaker function, we developed a mechanistic computational model. The model includes a description of autonomic-nervous receptors, post- translation signaling cascades, membrane molecules, and internal pacemaker mechanisms. Yielding results similar to those of the experiments, the model simulations faithfully reproduce the changes in AP firing rate in response to CCh or ISO or a combination of both (i.e., accentuated antagonism). Eliminating AC-cAMP-PKA signaling abolished the core effect of autonomic receptor stimulation on the AP firing rate. Specifically, disabling the phospholamban modulation of the SERCA activity resulted in a significantly reduced effect of CCh and a failure to increase the AP firing rate under ISO stimulation. Directly activating internal pacemaker mechanisms led to a similar extent of changes in the AP firing rate with respect to brain receptor stimulation. Thus, Ca²⁺ and cAMP/PKA-dependent phosphorylation limits the rate and magnitude of chronotropic changes in the spontaneous AP firing rate.

How the vagus nerve produces beat-to-beat heart rate variability; experiments in rabbits to mimic in vivo vagal patterns

BACKGROUND AND AIM

Analysis of heart rate variability (HRV) has recently become the playing field of mathematicians and physicists, losing its relation to physiology and the clinic. To set the record straight, a set of animal experiments is presented here, which was designed to test how vagus nerve traffic might produce beat to beat (b-t-b) heart rate (HR) control, like the baroreflex will do in vivo.

METHODS

The response of HR to vagus nerve stimulation was tested after bilateral vagotomy in rabbits under anesthesia. Three protocols were followed: 1. Single burst stimulation at varying moments in one cardiac cycle; 2. B-t-b stimulation in each cycle, coupled to the P-wave with variable delays; in addition, testing the effects of one increased or decreased burst; 3. Tetanic stimulation, shortly interrupted or increased at varying moments in the cardiac cycle.

RESULTS AND CONCLUSIONS

Sensitivity of the sinoatrial node to the timing of vagal bursts in its cycle from protocol 1 explains most of the observations. A single burst would be most effective when applied in late repolarization or early diastole of the sinoatrial node's action potential. In b-t-b stimulation the longest cardiac cycles occur when bursts are timed just before the end of the 'sensitive period'. Later coming bursts have their (diminished) effect on the next cycle; critically timed bursts induce an unstable HR, alternating between long and short cycles. This ran in synchrony with the respirator, thus producing a large respiratory sinus arrhythmia, even though the vagus nerves had been cut. HR-response to vagal burst activity shows two components: a fast one which is phase-sensitive and a slow one that builds up with longer lasting activity and also disappears slowly. Tetanic stimulation results in prolonged, but variable cycle lengths which are difficult to change by short-lasting manipulation of impulse frequency, be it up or down.

RELEVANCE FOR PATIENTS

Measurement of heart rate variability (HRV) and baroreflex sensitivity (BRS) have become clinical tools in the cardiology clinic and in hypertension research. This study shows how the underlying vagus nerve to heart rate physiology is responsible for moment-to-moment variability in these numbers at almost unchanged underlying physiology. Programmed stimulation of the vagus nerves in acute animals (rabbits) demonstrates that the optimal mode of fast, beat-to-beat heart rate control by these nerves is by means of bursts of impulses arriving in every heart beat at well-timed moments. In vivo this is how the baroreflex stabilizes blood pressure at the expense of HRV.