Translational applications of evaluating physiologic variability in human endotoxemia

The Physiological and Pharmacological Significance of the Circadian Timing of the HPA Axis: A Mathematical Modeling Approach

As a potent endogenous regulator of homeostasis, the circadian time-keeping system synchronizes internal physiology to periodic changes in the external environment to enhance survival. Adapting endogenous rhythms to the external time is accomplished hierarchically with the central pacemaker located in the suprachiasmatic nucleus (SCN) signaling the hypothalamus-pituitary-adrenal (HPA) axis to release hormones, notably cortisol, which help maintain the body's circadian rhythm. Given the essential role of HPA-releasing hormones in regulating physiological functions, including immune response, cell cycle, and energy metabolism, their daily variation is critical for the proper function of the circadian timing system. In this review, we focus on cortisol and key fundamental properties of the HPA axis and highlight their importance in controlling circadian dynamics. We demonstrate how systems-driven, mathematical modeling of the HPA axis complements experimental findings, enhances our understanding of complex physiological systems, helps predict potential mechanisms of action, and elucidates the consequences of circadian disruption. Finally, we outline the implications of circadian regulation in the context of personalized chronotherapy. Focusing on the chrono-pharmacology of synthetic glucocorticoids, we review the challenges and opportunities associated with moving toward personalized therapies that capitalize on circadian rhythms.

Detecting Pathogen Exposure During the Non-symptomatic Incubation Period Using Physiological Data: Proof of Concept in Non-human Primates

Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First, we seek to determine the upper limits of early warning detection through physiological measurements. Second, we investigate whether the detected physiological response is specific to the pathogen. Third, we explore the feasibility of extending early warning detection with wearable devices.

Research Methods: For the first objective, we developed a supervised random forest algorithm to detect pathogen exposure in the asymptomatic period prior to overt symptoms (fever). We used high-resolution physiological telemetry data (aortic blood pressure, intrathoracic pressure, electrocardiograms, and core temperature) from non-human primate animal models exposed to two viral pathogens: Ebola and Marburg (N = 20). Second, to determine reusability across different pathogens, we evaluated our algorithm against three independent physiological datasets from non-human primate models (N = 13) exposed to three different pathogens: Lassa and Nipah viruses and Y. pestis. For the third objective, we evaluated performance degradation when the algorithm was restricted to features derived from electrocardiogram (ECG) waveforms to emulate data from a non-invasive wearable device.

Results: First, our cross-validated random forest classifier provides a mean early warning of 51 ± 12 h, with an area under the receiver-operating characteristic curve (AUC) of 0.93 ± 0.01. Second, our algorithm achieved comparable performance when applied to datasets from different pathogen exposures – a mean early warning of 51 ± 14 h and AUC of 0.95 ± 0.01. Last, with a degraded feature set derived solely from ECG, we observed minimal degradation – a mean early warning of 46 ± 14 h and AUC of 0.91 ± 0.001.

Conclusion: Under controlled experimental conditions, physiological measurements can provide over 2 days of early warning with high AUC. Deviations in physiological signals following exposure to a pathogen are due to the underlying host’s immunological response and are not specific to the pathogen. Pre-symptomatic detection is strong even when features are limited to ECG-derivatives, suggesting that this approach may translate to non-invasive wearable devices.

A Personalized Signature and Chronotherapy-Based Platform for Improving the Efficacy of Sepsis Treatment

Sepsis remains a major therapeutic challenge and is associated with a high rate of morbidity and mortality. It is a dynamic condition in which multiple parameters change over time, rendering it difficult to overcome the various injurious responses, which worsen the prognosis in these patients. The prognosis of sepsis is associated with a disbalance of compensatory responses to infectious triggers, part of which can be deleterious. Marked inter- and intra-patient variability characterizes the mechanisms that underlie sepsis progression and determine the response to therapy. In this paper, we review some of the data on the use of chronopharmacological approaches for the treatment of patients with sepsis and discuss the role of the autonomic nervous system in the mechanisms associated with immune response and chronotherapy in these patients. We describe the implementation of an individualized platform that is based on the personalized autonomic nervous system, immune, and chronobiology-derived parameters for generating a patient-tailored therapeutic regimen. The notion of overcoming the deleterious compensatory response in a highly dynamic system in sepsis is presented to ensure an improved response to current therapies.

Asymmetry in Signal Oscillations Contributes to Efficiency of Periodic Systems

Oscillations are an important feature of cellular signaling that result from complex combinations of positive- and negative-feedback loops. The encoding and decoding mechanisms of oscillations based on amplitude and frequency have been extensively discussed in the literature in the context of intercellular and intracellular signaling. However, the fundamental questions of whether and how oscillatory signals offer any competitive advantages-and, if so, what-have not been fully answered. We investigated established oscillatory mechanisms and designed a study to analyze the oscillatory characteristics of signaling molecules and system output in an effort to answer these questions. Two classic oscillators, Goodwin and PER, were selected as the model systems, and corresponding no-feedback models were created for each oscillator to discover the advantage of oscillating signals. Through simulating the original oscillators and the matching no-feedback models, we show that oscillating systems have the capability to achieve better resource-to-output efficiency, and we identify oscillatory characteristics that lead to improved efficiency.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Natural small molecule FMHM inhibits lipopolysaccharide-induced inflammatory response by promoting TRAF6 degradation via K48-linked polyubiquitination

TNF receptor-associated factor 6 (TRAF6) is a key hub protein involved in Toll-like receptor-dependent inflammatory signaling pathway, and it recruits additional proteins to form multiprotein complexes capable of activating downstream NF-κB inflammatory signaling pathway. Ubiquitin-proteasome system (UPS) plays a crucial role in various protein degradations, such as TRAF6, leading to inhibitory effects on inflammatory response and immunologic function. However, whether ubiquitination-dependent TRAF6 degradation can be used as a novel anti-inflammatory drug target still remains to be explored. FMHM, a bioactive natural small molecule compound extracted from Chinese herbal medicine Radix Polygalae, suppressed acute inflammatory response by targeting ubiquitin protein and inducing UPS-dependent TRAF6 degradation mechanism. It was found that FMHM targeted ubiquitin protein via Lys48 site directly induced Lys48 residue-linked polyubiquitination. This promoted Lys48 residue-linked polyubiquitin chain formation on TRAF6, resulting in increased TRAF6 degradation via UPS and inactivation of downstream NF-κB inflammatory pathway. Consequently, FMHM down-regulated inflammatory mediator levels in circulation, protected multiple organs against inflammatory injury in vivo, and prolong the survival of endotoxemia mouse models. Therefore, FMHM can serve as a novel lead compound for the development of TRAF6 scavenging agent via ubiquitination-dependent mode, which represents a promising strategy for treating inflammatory diseases.

Does heart rate variability reflect the systemic inflammatory response in a fetal sheep model of lipopolysaccharide-induced sepsis?

Fetal inflammatory response occurs during chorioamnionitis, a frequent and often subclinical inflammation associated with increased risk for brain injury and life-lasting neurologic deficits. No means of early detection exist. We hypothesized that systemic fetal inflammation without septic shock will be reflected in alterations of fetal heart rate (FHR) variability (fHRV) distinguishing baseline versus inflammatory response states. In chronically instrumented near-term fetal sheep (n = 24), we induced an inflammatory response with lipopolysaccharide (LPS) injected intravenously (n = 14). Ten additional fetuses served as controls. We measured fetal plasma inflammatory cytokine IL-6 at baseline, 1, 3, 6, 24 and 48 h. 44 fHRV measures were determined continuously every 5 min using continuous individualized multi-organ variability analysis (CIMVA). CIMVA creates an fHRV measures matrix across five signal-analytical domains, thus describing complementary properties of fHRV. Using principal component analysis (PCA), a widely used technique for dimensionality reduction, we derived and quantitatively compared the CIMVA fHRV PCA signatures of inflammatory response in LPS and control groups. In the LPS group, IL-6 peaked at 3 h. In parallel, PCA-derived fHRV composite measures revealed a significant difference between LPS and control group at different time points. For the LPS group, a sharp increase compared to baseline levels was observed between 3 h and 6 h, and then abating to baseline levels, thus tracking closely the IL-6 inflammatory profile. This pattern was not observed in the control group. We also show that a preselection of fHRV measures prior to the PCA can potentially increase the difference between LPS and control groups, as early as 1 h post LPS injection. We propose a fHRV composite measure that correlates well with levels of inflammation and tracks well its temporal profile. Our results highlight the potential role of HRV to study and monitor the inflammatory response non-invasively over time.

Day-night variation in heart rate variability changes induced by endotoxaemia in healthy volunteers

BACKGROUND

Morbidity and mortality in response to sepsis may be dependent on clock time for the initiation of sepsis. Endotoxaemia, an experimental model for systemic inflammation, induces alterations in sympatico-vagal balance in the autonomic nervous system (ANS). The activity of sympathetic and parasympathetic activity can be estimated by measuring heart rate variability (HRV). Based on the intimate link between ANS and the inflammatory response, we hypothesized, that HRV changes seen during endotoxaemia would be different based on time of the day the endotoxaemia is initiated. We investigated day/night variation in endotoxaemia-induced changes in HRV.

METHODS

A randomized, crossover study with 12 healthy men (age 18-31) was conducted. Endotoxaemia were induced by lipopolysaccharide (LPS) endotoxin 0.3 ng/kg b.w. in two visits (day visit and night visit). At the day visit, endotoxaemia were induced at 12:00 h, and at the night visit it was induced at 24:00 h. Holter recordings were started 1 h before administration of LPS, and continued for 10 h. Time-domain and frequency-domain parameters of HRV were analysed.

RESULTS

A total of nine persons finished the study with valid recordings. Endotoxaemia at both night and day resulted in a significant depression in HRV parameters high-frequency power (HF), low-frequency power (LF), standard deviation of normal-to-normal (NN) intervals, root mean square of successive differences and proportion of NN50 divided by total number of NNs (P<0.001). The ratio LF/HF and mean heart rate significantly increased by endotoxaemia (P<0.001). At night-time endotoxaemia, a more pronounced depression of LF, HF and SDNN (P<0.01) and a more pronounced increase in the ratio of LF/HF and mean heart rate (P<0.01) occurred compared with day-time endotoxaemia.

CONCLUSION

Endotoxaemia induced changes in HRV exhibit a day-night difference. This difference may have clinical consequences in patients with sepsis.

Human metabolic response to systemic inflammation: assessment of the concordance between experimental endotoxemia and clinical cases of sepsis/SIRS

Introduction

Two recent, independent, studies conducted novel metabolomics analyses relevant to human sepsis progression; one was a human model of endotoxin (lipopolysaccharide (LPS)) challenge (experimental endotoxemia) and the other was community acquired pneumonia and sepsis outcome diagnostic study (CAPSOD). The purpose of the present study was to assess the concordance of metabolic responses to LPS and community-acquired sepsis.

Methods

We tested the hypothesis that the patterns of metabolic response elicited by endotoxin would agree with those in clinical sepsis. Alterations in the plasma metabolome of the subjects challenged with LPS were compared with those of sepsis patients who had been stratified into two groups: sepsis patients with confirmed infection and non-infected patients who exhibited systemic inflammatory response syndrome (SIRS) criteria. Common metabolites between endotoxemia and both these groups were individually identified, together with their direction of change and functional classifications.

Results

Response to endotoxemia at the metabolome level elicited characteristics that agree well with those observed in sepsis patients despite the high degree of variability in the response of these patients. Moreover, some distinct features of SIRS have been identified. Upon stratification of sepsis patients based on 28-day survival, the direction of change in 21 of 23 metabolites was the same in endotoxemia and sepsis survival groups.

Conclusions

The observed concordance in plasma metabolomes of LPS-treated subjects and sepsis survivors strengthens the relevance of endotoxemia to clinical research as a physiological model of community-acquired sepsis, and gives valuable insights into the metabolic changes that constitute a homeostatic response. Furthermore, recapitulation of metabolic differences between sepsis non-survivors and survivors in LPS-treated subjects can enable further research on the development and assessment of rational clinical therapies to prevent sepsis mortality. Compared with earlier studies which focused exclusively on comparing transcriptional dynamics, the distinct metabolomic responses to systemic inflammation with or without confirmed infection, suggest that the metabolome is much better at differentiating these pathophysiologies. Finally, the metabolic changes in the recovering patients shift towards the LPS-induced response pattern strengthening the notion that the metabolic, as well as transcriptional responses, characteristic to the endotoxemia model represent necessary and “healthy” responses to infectious stimuli.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0783-2) contains supplementary material, which is available to authorized users.

Circadian characteristics of permissive and suppressive effects of cortisol and their role in homeostasis and the acute inflammatory response

In this work we explore a semi-mechanistic model that considers cortisol's permissive and suppressive effects through the regulation of cytokine receptors and cytokines respectively. Our model reveals the proactive role of cortisol during the resting period and its reactive character during the body's activity phase. Administration of an acute LPS dose during the night, when cortisol's permissive effects are higher than suppressive, leads to increased cytokine levels compared to LPS administration at morning when cortisol's suppressive effects are higher. Interestingly, our model presents a hysteretic behavior where the relative predominance of permissive or suppressive effects results not only from cortisol levels but also from the previous states of the model. Therefore, for the same cortisol levels, administration of an inflammatory stimulus at cortisol's ascending phase, that follows a time period where cytokine receptor expression is elevated ultimately sensitizing the body for the impending stimulus, leads to higher cytokine expression compared to administration of the same stimulus at cortisol's descending phase.

Oxidative stress and inflammation modulate Rev-erbα signaling in the neonatal lung and affect circadian rhythmicity

AIMS

The response to oxidative stress and inflammation varies with diurnal rhythms. Nevertheless, it is not known whether circadian genes are regulated by these stimuli. We evaluated whether Rev-erbα, a key circadian gene, was regulated by oxidative stress and/or inflammation in vitro and in a mouse model.

RESULTS

A unique sequence consisting of overlapping AP-1 and nuclear factor kappa B (NFκB) consensus sequences was identified on the mouse Rev-erbα promoter. This sequence mediates Rev-erbα promoter activity and transcription in response to oxidative stress and inflammation. This region serves as an NrF2 platform both to receive oxidative stress signals and to activate Rev-erbα, as well as an NFκB-binding site to repress Rev-erbα with inflammatory stimuli. The amplitude of the rhythmicity of Rev-erbα was altered by pre-exposure to hyperoxia or disruption of NFκB in a cell culture model of circadian simulation. Oxidative stress overcame the inhibitory effect of NFκB binding on Rev-erbα transcription. This was confirmed in neonatal mice exposed to hyperoxia, where hyperoxia-induced lung Rev-erbα transcription was further increased with NFκB disruption. Interestingly, this effect was not observed in similarly exposed adult mice.

INNOVATION

These data provide novel mechanistic insights into how key circadian genes are regulated by oxidative stress and inflammation in the neonatal lung.

CONCLUSION

Rev-erbα transcription and circadian oscillation are susceptible to oxidative stress and inflammation in the neonate. Due to Rev-erbα's role in cellular metabolism, this could contribute to lung cellular function and injury from inflammation and oxidative stress.

On heart rate variability and autonomic activity in homeostasis and in systemic inflammation

Analysis of heart rate variability (HRV) is a promising diagnostic technique due to the noninvasive nature of the measurements involved and established correlations with disease severity, particularly in inflammation-linked disorders. However, the complexities underlying the interpretation of HRV complicate understanding the mechanisms that cause variability. Despite this, such interpretations are often found in literature. In this paper we explored mathematical modeling of the relationship between the autonomic nervous system and the heart, incorporating basic mechanisms such as perturbing mean values of oscillating autonomic activities and saturating signal transduction pathways to explore their impacts on HRV. We focused our analysis on human endotoxemia, a well-established, controlled experimental model of systemic inflammation that provokes changes in HRV representative of acute stress. By contrasting modeling results with published experimental data and analyses, we found that even a simple model linking the autonomic nervous system and the heart confound the interpretation of HRV changes in human endotoxemia. Multiple plausible alternative hypotheses, encoded in a model-based framework, equally reconciled experimental results. In total, our work illustrates how conventional assumptions about the relationships between autonomic activity and frequency-domain HRV metrics break down, even in a simple model. This underscores the need for further experimental work towards unraveling the underlying mechanisms of autonomic dysfunction and HRV changes in systemic inflammation. Understanding the extent of information encoded in HRV signals is critical in appropriately analyzing prior and future studies.