Emergence of heartbeat frailty in advanced age I: perspectives from life-long EKG recordings in adult mice

Abstract

The combined influences of sinoatrial nodal (SAN) pacemaker cell automaticity and its response to autonomic input determine the heart’s beating interval variability and mean beating rate. To determine the intrinsic SAN and autonomic signatures buried within EKG RR interval time series change in advanced age, we measured RR interval variability before and during double autonomic blockade at 3-month intervals from 6 months of age until the end of life in long-lived (those that achieved the total cohort median life span of 24 months and beyond) C57/BL6 mice. Prior to 21 months of age, time-dependent changes in intrinsic RR interval variability and mean RR interval were relatively minor. Between 21 and 30 months of age, however, marked changes emerged in intrinsic SAN RR interval variability signatures, pointing to a reduction in the kinetics of pacemaker clock mechanisms, leading to reduced synchronization of molecular functions within and among SAN cells. This loss of high-frequency signal processing within intrinsic SAN signatures resulted in a marked increase in the mean intrinsic RR interval. The impact of autonomic signatures on RR interval variability were net sympathetic and partially compensated for the reduced kinetics of the intrinsic SAN RR interval variability signatures, and partially, but not completely, shifted the EKG RR time series intervals to a more youthful pattern. Cross-sectional analyses of other subsets of C57/BL6 ages indicated that at or beyond the median life span of our longitudinal cohort, noncardiac, constitutional, whole-body frailty was increased, energetic efficiency was reduced, and the respiratory exchange ratio increased. We interpret the progressive reduction in kinetics in intrinsic SAN RR interval variability signatures in this context of whole-body frailty beyond 21 months of age to be a manifestation of “heartbeat frailty.”

What makes the sinoatrial node tick? A question not for the faint of heart

“…The long- and short-term variability in the intervals between cardiac APs, in the range of milliseconds around the mean beating rate, is indicative of the Ca 2+ - and phosphorylation-dependent memory encoded within the clock proteins and manifest as variable coupling between the clocks [27]. This is consistent with the understanding that higher beating rates, known to correspond to higher clock-coupling, are also correlated with lower heart rate variability, and lower beating rates with higher variability [47]. Thus, the body influences the rate and rhythm of SAN pacemaking via autonomic receptor activation, which impacts on the activation states and coupling of the same proteins that are involved in the coupled-clock system in the absence of autonomic neurotransmitter input (figure 1 a ).…”

“…Ultimately, new instructions from the brain are broadcast throughout the autonomic neuro-visceral surveillance network to maintain coordinated resonance of blood pressure, heartbeats and breathing rates and rhythms. As a result, a beautifully tuned resonant coregulation of heart rate and rhythm, respiration rate and blood pressure at different time intervals emerges from the heart–brain autonomic surveillance network, informing on the health status of the body [47]. Disease states, and advancing age, even in the absence of disease [47], induce alterations in either the ‘heart's SAN brain' molecular machinery (coupled-clock system) or the efficacy of autonomic modulation of this machinery that become manifest as altered heart-rate variability [47], which creates discordance within the harmony that resonates throughout the autonomic neuro-visceral surveillance network.…”

The alterations in multiple neurophysiological procedures are associated with frailty phenotype in older adults

“…Additionally, numerous studies showed that this complexity metric, which characterizing the dynamics of a given neurophysiological procedure [e.g., the heartbeat fluctuation ( Toosizadeh et al, 2021 )] over multiple scales of time or space, can better capture subtle changes in this system that cannot be appropriately captured by traditional single-scale measures (e.g., mean or variability) ( Lipsitz, 2002 ; Thijssen et al, 2011 ; Manor and Lipsitz, 2013 ; Jiang et al, 2021 , 2022b ). This complexity metric can thus provide insights into the pathology of health conditions [e.g., frailty, the absence of autonomic surveillance of the cardiovascular system ( Moen et al, 2022 )]. Taken together, the results suggest that in addition to the functionality of one given procedure itself, the multiscale interactions across neurophysiological procedures are one critical factor contributing to the pathology of frailty, which should be carefully considered in future studies.…”

Using beat-to-beat heart signals for age-independent biometric verification

“…The original dataset was comprised of 58 C57/BL6 mouse ECG recordings and their extracted heartbeat signals published in Moen et al 15 The recordings were collected in accordance with the Guide for the Care and Use of Laboratory 102 Animals published by the National Institutes of Health (NIH Publication no. 85–23, revised 1996).…”

“…All of the 30 mice lived at least 24 months. Moen et al 15 calculated the Kaplan–Meier survival curve 16 on the total 58 mice and found that 50% did not reach the age of 24 months. Thus, the recordings used here are equivalent to ~ 20 to 75 human years since 75 is approximately the current median life expectancy in the western world 17 .…”