Chronobiological Influence Over Cardiovascular Function: The Good, the Bad, and the Ugly

Abstract

Essentially all biological processes fluctuate over the course of the day, observed at cellular (eg, transcription, translation, and signaling), organ (eg, contractility and metabolism), and whole-body (eg, physical activity and appetite) levels. It is, therefore, not surprising that both cardiovascular physiology (eg, heart rate and blood pressure) and pathophysiology (eg, onset of adverse cardiovascular events) oscillate during the 24-hour day. Chronobiological influence over biological processes involves a complex interaction of factors that are extrinsic (eg, neurohumoral factors) and intrinsic (eg, circadian clocks) to cells. Here, we focus on circadian governance of 6 fundamentally important processes: metabolism, signaling, electrophysiology, extracellular matrix, clotting, and inflammation. In each case, we discuss (1) the physiological significance for circadian regulation of these processes (ie, the good); (2) the pathological consequence of circadian governance impairment (ie, the bad); and (3) whether persistence/augmentation of circadian influences contribute to pathogenesis during distinct disease states (ie, the ugly). Finally, the translational impact of chronobiology on cardiovascular disease is highlighted.

Keywords: blood pressure; electrophysiology; extracellular matrix; inflammation; metabolism.

Figure 1.

Factors/processes which fluctuate rhythmically with respect to time that fit to a cosine curve can be defined by the peak (maximal value), trough (minimal value), mesor (midline value), amplitude (peak value minus mesor value), phase (timing of the peak or trough), and periodicity (24-hrs, in the case of circadian rhythms) (A). Alterations in 24-hr fluctuations can manifest at the levels of phase (termed a phase shift), periodicity, mesor, and/or amplitude; the figure illustrates attenuation (i) and augmentation (ii) of amplitude, both of which could hypothetically lead to pathology (B).

Figure 1.

Factors/processes which fluctuate rhythmically with respect to time that fit to a cosine curve can be defined by the peak (maximal value), trough (minimal value), mesor (midline value), amplitude (peak value minus mesor value), phase (timing of the peak or trough), and periodicity (24-hrs, in the case of circadian rhythms) (A). Alterations in 24-hr fluctuations can manifest at the levels of phase (termed a phase shift), periodicity, mesor, and/or amplitude; the figure illustrates attenuation (i) and augmentation (ii) of amplitude, both of which could hypothetically lead to pathology (B).

Figure 2.

Evidence-based model for time-of-day fluctuations of myocardial fatty acid metabolism during physiologic (A) and dyslipidemic (B) states. A) Under physiologic conditions, fatty acids (FA) in excess of β-oxidation requirements are utilized cardiomyocyte triglyceride (TAG) synthesis during the awake period, whereas synthesis of FA-derived signaling molecules (e.g., diacylglycerol [DAG], cholesterol esters [CE], phospholipids [PL]) is low at this time; during the sleep period, rates of lipolysis increase, releasing FA from the TAG pool, which are utilized for both β-oxidation and signaling molecule synthesis. B) Under conditions of FA excess (i.e., dyslipidemia), there is a dramatic expansion of the TAG pool during the awake period (due to clock control of TAG synthesis); during the sleep period, lipolysis of the expanded TAG pool occurs, resulting in excessive synthesis of FA-derived signaling molecules, and subsequent cellular dysfunction (i.e., ‘lipotoxicity’). Illustration depicting 24-hr fluctuations in myocardial levels TAG and lipid-based signaling species during physiologic and dyslipidemic states (C).

Figure 2.

Evidence-based model for time-of-day fluctuations of myocardial fatty acid metabolism during physiologic (A) and dyslipidemic (B) states. A) Under physiologic conditions, fatty acids (FA) in excess of β-oxidation requirements are utilized cardiomyocyte triglyceride (TAG) synthesis during the awake period, whereas synthesis of FA-derived signaling molecules (e.g., diacylglycerol [DAG], cholesterol esters [CE], phospholipids [PL]) is low at this time; during the sleep period, rates of lipolysis increase, releasing FA from the TAG pool, which are utilized for both β-oxidation and signaling molecule synthesis. B) Under conditions of FA excess (i.e., dyslipidemia), there is a dramatic expansion of the TAG pool during the awake period (due to clock control of TAG synthesis); during the sleep period, lipolysis of the expanded TAG pool occurs, resulting in excessive synthesis of FA-derived signaling molecules, and subsequent cellular dysfunction (i.e., ‘lipotoxicity’). Illustration depicting 24-hr fluctuations in myocardial levels TAG and lipid-based signaling species during physiologic and dyslipidemic states (C).

Figure 2.

Evidence-based model for time-of-day fluctuations of myocardial fatty acid metabolism during physiologic (A) and dyslipidemic (B) states. A) Under physiologic conditions, fatty acids (FA) in excess of β-oxidation requirements are utilized cardiomyocyte triglyceride (TAG) synthesis during the awake period, whereas synthesis of FA-derived signaling molecules (e.g., diacylglycerol [DAG], cholesterol esters [CE], phospholipids [PL]) is low at this time; during the sleep period, rates of lipolysis increase, releasing FA from the TAG pool, which are utilized for both β-oxidation and signaling molecule synthesis. B) Under conditions of FA excess (i.e., dyslipidemia), there is a dramatic expansion of the TAG pool during the awake period (due to clock control of TAG synthesis); during the sleep period, lipolysis of the expanded TAG pool occurs, resulting in excessive synthesis of FA-derived signaling molecules, and subsequent cellular dysfunction (i.e., ‘lipotoxicity’). Illustration depicting 24-hr fluctuations in myocardial levels TAG and lipid-based signaling species during physiologic and dyslipidemic states (C).

Figure 3.

Hypothetical circadian influences on arrhythmia risk. During physiologic conditions, oscillations in factors that have the potential to trigger arrhythmias (e.g., adrenergic stimulation) are paralleled with oscillations in protective mechanisms (e.g., heart rate variability; HRV), such that arrhythmia susceptibility is low (the ‘good’). An attenuation in protective mechanisms (e.g., decreased HRV following myocardial infarction) increases arrhythmia susceptibility above the threshold when arrhythmia triggers are present (the ‘bad’). Augmentation of arrhythmia trigger oscillations also have the potential to increase arrhythmia susceptibility above the threshold (the ‘ugly’).

Figure 4.

Summary of circadian influences on cardiovascular-relevant parameters in humans (A) and rodents (B).

Figure 4.

Summary of circadian influences on cardiovascular-relevant parameters in humans (A) and rodents (B).