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.

Mathematical modeling of light-mediated HPA axis activity and downstream implications on the entrainment of peripheral clock genes.

In this work we propose a semimechanistic model that describes the photic signal transduction to the hypothalamic-pituitary-adrenal (HPA) axis that ultimately regulates the synchronization of peripheral clock genes (PCGs). Our HPA axis model predicts that photic stimulation induces a type-1 phase response curve to cortisol's profile with increased cortisol sensitivity to light exposure in its rising phase, as well as the shortening of cortisol's period as constant light increases (Aschoff's first rule). Furthermore, our model provides insight into cortisol's phase and amplitude dependence on photoperiods and reveals that cortisol maintains highest amplitude variability when it is entrained by a balanced schedule of light and dark periods. Importantly, by incorporating the links between HPA axis and PCGs we were able to investigate how cortisol secretion impacts the entrainment of a population of peripheral cells and show that disrupted light schedules, leading to blunted cortisol secretion, fail to synchronize a population of PCGs which further signifies the loss of circadian rhythmicity in the periphery of the body.

APOε4 is associated with enhanced in vivo innate immune responses in human subjects.

BACKGROUND: The genetic determinants of the human innate immune response are poorly understood. Apolipoprotein (Apo) E, a lipid-trafficking protein that affects inflammation, has well-described wild-type (ε3) and disease-associated (ε2 and ε4) alleles, but its connection to human innate immunity is undefined. OBJECTIVE: We sought to define the relationship of APOε4 to the human innate immune response. METHODS: We evaluated APOε4 in several functional models of the human innate immune response, including intravenous LPS challenge in human subjects, and assessed APOε4 association to organ injury in patients with severe sepsis, a disease driven by dysregulated innate immunity. RESULTS: Whole blood from healthy APOε3/APOε4 volunteers induced higher cytokine levels on ex vivo stimulation with Toll-like receptor (TLR) 2, TLR4, or TLR5 ligands than blood from APOε3/APOε3 patients, whereas TLR7/8 responses were similar. This was associated with increased lipid rafts in APOε3/APOε4 monocytes. By contrast, APOε3/APOε3 and APOε3/APOε4 serum neutralized LPS equivalently and supported similar LPS responses in Apoe-deficient macrophages, arguing against a differential role for secretory APOE4 protein. After intravenous LPS, APOε3/APOε4 patients had higher hyperthermia and plasma TNF-α levels and earlier plasma IL-6 than APOε3/APOε3 patients. APOE4-targeted replacement mice displayed enhanced hypothermia, plasma cytokines, and hepatic injury and altered splenic lymphocyte apoptosis after systemic LPS compared with APOE3 counterparts. In a cohort of 828 patients with severe sepsis, APOε4 was associated with increased coagulation system failure among European American patients. CONCLUSIONS: APOε4 is a determinant of the human innate immune response to multiple TLR ligands and associates with altered patterns of organ injury in human sepsis.

A genomic storm in critically injured humans.

Human survival from injury requires an appropriate inflammatory and immune response. We describe the circulating leukocyte transcriptome after severe trauma and burn injury, as well as in healthy subjects receiving low-dose bacterial endotoxin, and show that these severe stresses produce a global reprioritization affecting >80% of the cellular functions and pathways, a truly unexpected "genomic storm." In severe blunt trauma, the early leukocyte genomic response is consistent with simultaneously increased expression of genes involved in the systemic inflammatory, innate immune, and compensatory antiinflammatory responses, as well as in the suppression of genes involved in adaptive immunity. Furthermore, complications like nosocomial infections and organ failure are not associated with any genomic evidence of a second hit and differ only in the magnitude and duration of this genomic reprioritization. The similarities in gene expression patterns between different injuries reveal an apparently fundamental human response to severe inflammatory stress, with genomic signatures that are surprisingly far more common than different. Based on these transcriptional data, we propose a new paradigm for the human immunological response to severe injury.

Pulsatile glucocorticoid secretion: origins and downstream effects.

Glucocorticoids are steroid hormones which, among other functions, exert an antiinflammatory effect. Endogenous glucocorticoids are normally secreted by the adrenal gland in discrete bursts. It is becoming increasingly evident that this pulsatile secretion pattern, leading to ultradian rhythms of plasma glucocorticoid levels, may have important downstream regulatory effects on glucocorticoid-responsive genes. Mathematical modeling of this system can compliment recent experimental data and quantitatively evaluate hypothesized mechanistic underpinnings of differential pulsatile signal transduction. In this paper, we describe an integrated model of pulsatile secretion of glucocorticoids by the hypothalamic-pituitary-adrenal (HPA) axis and the pharmacodynamic effect of glucocorticoids. This model is used to investigate the difference in transcriptional responses to pulsatile and constant glucocorticoid exposure. Nonlinearity in ligand-receptor kinetics leads to the differential expression of glucocorticoid-responsive genes in response to different patterns of glucocorticoid secretion, even when the total amount of glucocorticoid exposure is held constant. Understanding the implications of ultradian rhythms in glucocorticoids is important in studying the dysregulation of HPA axis function leading to altered glucocorticoid secretion patterns in disease.

Computational identification of transcriptional regulators in human endotoxemia.

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically 'coregulated' genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes.

Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia.

Heart rate variability (HRV), the quantification of beat-to-beat variability, has been studied as a potential prognostic marker in inflammatory diseases such as sepsis. HRV normally reflects significant levels of variability in homeostasis, which can be lost under stress. Much effort has been placed in interpreting HRV from the perspective of quantitatively understanding how stressors alter HRV dynamics, but the molecular and cellular mechanisms that give rise to both homeostatic HRV and changes in HRV have received less focus. Here, we develop a mathematical model of human endotoxemia that incorporates the oscillatory signals giving rise to HRV and their signal transduction to the heart. Connections between processes at the cellular, molecular, and neural levels are quantitatively linked to HRV. Rhythmic signals representing autonomic oscillations and circadian rhythms converge to modulate the pattern of heartbeats, and the effects of these oscillators are diminished in the acute endotoxemia response. Based on the semimechanistic model developed herein, homeostatic and acute stress responses of HRV are studied in terms of these oscillatory signals. Understanding the loss of HRV in endotoxemia serves as a step toward understanding changes in HRV observed clinically through translational applications of systems biology based on the relationship between biological processes and clinical outcomes.

A dual negative regulation model of Toll-like receptor 4 signaling for endotoxin preconditioning in human endotoxemia.

We discuss a model illustrating how the outcome of repeated endotoxin administration experiments can emerge as a natural consequence of the tightly regulated signaling pathways and also highlight the importance of a dual negative feedback regulation including PI3K/Akt and IRAK-M (IRAK3). We identify the relative time scales of the onset and the magnitude of the stimulus as key determinants of outcome in repeated administration experiments. The results of our simulations involve potentiated response, tolerance, and protective tolerance. Moreover, the knockout of negative regulators shows that IRAK-M is a necessary and sufficient factor for generation of endotoxin tolerance (ET). The effects of the knockout of IRAK-M gene or administration of PI3K inhibitor do yield predictions that have been verified experimentally. Finally, the pretreatment with PI3K inhibitor reveals the interaction between these two negative regulations.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

BACKGROUND: Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. METHODOLOGY/PRINCIPAL FINDINGS: An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. CONCLUSIONS/SIGNIFICANCE: The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.