Multiscale Variability In Human Endotoxemia: Circadian, Ultradian, and Higher Frequency Rhythms In Heart Rate Variability

Tuesday, October 18, 2011: 8:50 AM
Conrad C (Hilton Minneapolis)
Jeremy D. Scheff1, Steven E. Calvano2, Stephen F. Lowry2 and Ioannis P. Androulakis3, (1)Biomedical Engineering, Rutgers University, Piscataway, NJ, (2)Department of Surgery, UMDNJ-Robert Wood Johnson Medical School, New Brunswick, NJ, (3)Biomedical Engineering, Chemical & Biochemical Engineering, Rutgers University, Piscataway, NJ

Homeostasis exhibits rich variability, from the discrete activation of gene expression in individual cells to rhythms in hormone concentrations that regulate entire organs. Heart rate variability (HRV), the quantification of the distribution of time intervals between heartbeats, is one such variable physiological signal with particular clinical importance. Changes in HRV reflect alterations in autonomic function, which is potentially a useful predictor of outcome in myocardial infarction, congestive heart failure, diabetic neuropathy, and neonatal sepsis. Dysregulated autonomic function as assessed by HRV has been observed in intensive care units and has been hypothesized to have value as a marker of recovery from critical illness (Lowry and Calvano 2008). Due to this clinical relevance, dynamic characteristics of HRV have been assessed by time domain, frequency domain, and nonlinear metrics. The majority of HRV research has thus far focused on the interpretation of the patterns of HRV rather than linking cellular-level mechanisms to patterns. The realization that health may be characterized by a certain degree of variability of human heart signals motivates the hypothesis that appropriate physiologic variability is the manifestation of robust dynamics of control signals whose fluctuations equip the host with the ability to anticipate external and internal disturbances. We hypothesize that these variable dynamics are driven by the convergence of rhythmic physiological signals on the heart via autonomic modulation.

Studying the effects of critical illness on HRV requires a clinical model that can be experimentally evaluated in great detail. Human endotoxemia, the injection of lipopolysaccharides (LPS or endotoxin, used interchangeable herein) into healthy human subjects, has been extensively used as a model of systemic inflammation due to qualitatively similar responses in systemic physiologic and metabolic processes, including changes in leukocyte abundance and behavior, hormonal secretion, and cardiac function. Responses observed in human endotoxemia experiments mimic observed responses in systemic inflammation in ICU patients, albeit over different timescales, thus making the human endotoxemia model an excellent platform for exploring mechanistic underpinnings of the systemic inflammatory response. A key component in the response to endotoxemia is a decrease in HRV, concomitant with imbalances in autonomic activity reflected by perturbed autonomic oscillatory responses in HR.

Despite an understanding of the importance of inflammation in a wide variety of disorders and a large number of experiments elucidating the details of the inflammatory response, novel treatments aimed at controlling inflammation remain elusive. The complexity of the interacting, redundant pathways involved in the inflammatory response necessitate a systems-level understanding of inflammation, thus leading to interest in the inflammatory response from a systems biology perspective. The dynamic signals evoked in an inflammatory response are propagated to the sinoatrial (SA) node of the heart to assess how HRV is perturbed in endotoxemia. Previously, endotoxemia-induced changes in HR and HRV have been described by physicochemical relations which begin to elucidate the signals that give rise to altered phenotypes (Foteinou, Calvano et al. 2010). However, this neglects that HR and HRV are both derived from the same physiological process, the beats of the heart, and that the contraction of the heart as initiated by firing neurons at the SA node is a noisy, discrete process. This motivates the development of a more mechanistic model to produce discrete heartbeat signals that can then be used to calculate HR and HRV, providing a basis for the development of autonomic dysfunction in endotoxemia. We propose a semi-mechanistic mathematical model linking endotoxemia to cardiac function through an integral pulse frequency modulation (IPFM) model that produces discrete heartbeats as output based on autonomic modulation of the heart. Outputs of the model, namely HR and HRV, are shown to accurately capture experimentally-observed phenomena in human endotoxemia studies.

In this work, we further explore how physiologic variability outside the heart influences HRV. Therefore, based on the framework described above, we study how physiologic variability at multiple levels culminates in perturbing the host towards a dysregulated autonomic state in inflammation. Circadian rhythms, both in the suprachiasmatic nucleus (SCN) and in peripheral circadian oscillators, play a key role in the dynamics of inflammation. Many components of the inflammatory response are under circadian regulation (Scheff, Calvano et al. 2010), and it has been shown that endotoxemia suppresses the expression of clock genes that comprise the peripheral circadian oscillators in leukocytes (Haimovich, Calvano et al. 2010). The interplay between peripheral circadian rhythms and inflammatory cytokines perturbs the state of the host in an acute response to endotoxemia.

Ultradian rhythms in the secretion of cortisol, a key anti-inflammatory hormone, also play an important role in maintaining homeostasis systems that respond to glucocorticoids (Lightman and Conway-Campbell 2010). Glucocorticoid responsive genes are expressed at appropriate levels in the presence of ultradian rhythms, but when these rhythms are lost a large number of genes are dysregulated. As glucocorticoids are known to regulate the expression of key inflammatory genes, including pro-inflammatory and anti-inflammatory cytokines, and as pulsatility in hormone secretion may be lost in stress, the incorporation of ultradian rhythms into our integrated model alters the state of the inflammatory system as a whole in endotoxemia, which is reflected in HRV.

Our model is motivated and validated by data at multiple scales. The human endotoxemia response (Lowry 2005) is well characterized from the perspective of hormonal and cytokine measurements. Gene expression data is also available, which we leverage to model the evolving transcriptional response to endotoxemia. To study model responses under a variety of experimental conditions, we use data from experiments where hormone treatment is given prior to endotoxin. Furthermore, model subsystems, such as the ultradian release of glucocorticoids by the HPA axis, can be studied in isolation based on the wide range of experimental data on glucocorticoid release and action.

Understanding the loss of variability of cardiac function in endotoxemia serves as a step towards gaining insight into similar changes in HRV observed clinically in response to stress. This work builds towards translational applications of systems biology by moving towards an understanding of the relationship between fundamental biological processes and clinical outcomes.


  • Foteinou, P. T., S. E. Calvano, et al. (2010). "Multiscale model for the assessment of autonomic dysfunction in human endotoxemia." Physiol Genomics 42(1): 5-19.
  • Haimovich, B., J. Calvano, et al. (2010). "In vivo endotoxin synchronizes and suppresses clock gene expression in human peripheral blood leukocytes." Crit Care Med 38(3): 751-8.
  • Lightman, S. L. and B. L. Conway-Campbell (2010). "The crucial role of pulsatile activity of the HPA axis for continuous dynamic equilibration." Nat Rev Neurosci 11(10): 710-8.
  • Lowry, S. F. (2005). "Human endotoxemia: a model for mechanistic insight and therapeutic targeting." Shock 24 Suppl 1: 94-100.
  • Lowry, S. F. and S. E. Calvano (2008). "Challenges for modeling and interpreting the complex biology of severe injury and inflammation." J Leukoc Biol 83(3): 553-7.
  • Scheff, J. D., S. E. Calvano, et al. (2010). "Modeling the influence of circadian rhythms on the acute inflammatory response." J Theor Biol 264(3): 1068-76.

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