(376a) A Multi-Scale Model for the Assessment of Autonomic Dysfunction in Human Endotoxemia | AIChE

(376a) A Multi-Scale Model for the Assessment of Autonomic Dysfunction in Human Endotoxemia

Authors 

Foteinou, P. - Presenter, Rutgers University
Androulakis, I. P. - Presenter, Rutgers University
Calvano, S. E. - Presenter, UMDNJ-Robert Wood Johnson Medical School
Lowry, S. F. - Presenter, UMDNJ-Robert Wood Johnson Medical School


Severe injury and infection are leading causes of morbidity and mortality evoking both pro-inflammatory and anti-inflammatory responses at the systemic and tissue levels[1]. Mechanisms aiming at the regulation of the inflammatory response involve not only the local release of anti-inflammatory cytokines but also hormonal and autonomic influences. Recent studies indicate that the central nervous system (CNS) is a pivotal regulator of the immune response and its autonomic divisions control inflammation at various levels. In particular, the neuro-immune bidirectional network is comprised of a descending pathway that links CNS to peripheral immune tissues and a parallel afferent arm linking the immune system with the CNS[2]. The integrity of this loop allows for communication between the CNS and the peripheral immune system, integrating neuronal and immune signals in the periphery as well as in the CNS. Such reciprocal communication pathways between the immune and central nervous systems are now considered to be major components of the integrated homeostatic network of the host and involve all areas of medulla, hypothalamic regions and autonomic system[3]. It is therefore becoming evident that disruptions may occur at any level of these adaptive functions and thereby predispose a host to excessive inflammatory responses.

Heart rate variability (HRV), assessed by evaluating the standard deviation of normal to normal interbeat intervals, is a noninvasive means of quantifying the cardiac autonomic input. Assessment of HRV has been extensively used to evaluate autonomic modulation of the sinus node and as a predictor of the severity of illness[4]. It has been hypothesized that the reduction in HRV, i.e., increases in regularity, suggests an increased isolation of the heart with other organs that behave like biological oscillators coupled to one another. Loss of high level signal variability reflects detectable systemic-level loss of adaptability and fitness[5]. As a potential surrogate marker for system decomplexification, diminished HRV and autonomic dysfunction have received increasing attention in the mathematical modeling of critical illness. Thus, the development of surrogate multi-scale, nonlinear, dynamic, complex models gains ever increasing acceptance as a means of deciphering the intricacies of critical illness emphasizing the emerging loss (?decomplexification?) of rich variability, observed in normal physiology, in critically ill patients[6].

Understanding the relevance of neuro-immunomodulation in controlling inflammatory processes would require a model that simulates critical aspects of the multi-scale interplay between the central nervous system (CNS) and the immune response. A vital enabler in that respect is the development of a systems-based approach that integrates clinical data across multiple scales and subsequently models the emerging host response as the outcome of orchestrated interactions of critical modules. To meet this challenge, an integrated host response model is proposed to connect the (cellular) inflammatory response with neural based pathways that account for modulations in autonomic activity assessed by physiologic variables including HRV. Specifically, the data used in this study span various scales from the cellular to the systemic host response level.

Based on our prior work[7-9], a physicochemical model of human endotoxemia, as a prototype model of systemic inflammation in humans, will be used as template for connecting extracellular signals and intracellular signaling cascades eventually leading to the emergent transcriptional dynamics. However, one of the simplifying hypotheses made in this model is that the immunomodulatory role of autonomic (hormonal) influences is not accounted for. Driven by the premise that a characteristically enhanced endocrine hormone profile is elicited during the early-phase response to endotoxin injury[10], the additional scale we wish to explore is associated with critical aspects of the neuro-endocrine immune crosstalk. In particular, essential modules associated with the release of neuro-endocrine stress hormones including endogenous cortisol and catecholamines are further incorporated. Accordingly, a signal transduction model is developed to establish implicit interaction among these signaling molecules and thereby quantify the bi-directional link between the neuro-endocrine axis and peripheral inflammation. Clinical observables such as HRV will be further incorporated to assess disruptions in autonomic activities which reflect the manifestation of systemic decomplexification and correlate with the severity of the host. In order to quantify the relevant system parameters and functions, data associated with plasma cortisol and catecholamine levels recorded before and after the endotoxin infusion are employed. Of particular relevance are also data associated with vital signs including heart rate and mean arterial blood pressure. Such modeling effort will be evaluated through its ability to not only reproduce available experimental data but also to assess the implications of endocrine hormone influence upon autonomic activity. Thus, the proposed work intends to associate acquired endocrine dysfunction with diminished HRV making it a critical enabler for the assessment of neuro-endocrine activity at both the cellular and systemic (autonomic) levels[11].

The overall goal of this study is to demonstrate the feasibility of a clinically relevant, mechanistic-based, multi-level human inflammation model that couples essential aspects of the bi-directional relationship between the CNS and inflammation. Specifically, the proposed modeling effort bridges the initiating signal and macroscopic phenotypic expressions (HRV) through semi-mechanistic models that include transcriptional dynamics, signaling cascades and physiological components. Such systems level approach could potentially offer significant insight on how interacting inflammatory responses and neural based mechanisms influence the host's ability to regulate inflammation; thus making it a critical enabler for clarifying the clinical contexts in which disruptions of these bidirectional communications contribute to morbidity and mortality to severely stressed patients.

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