Modeling cortisol dynamics in the neuro-endocrine axis distinguishes normal, depression, and post-traumatic stress disorder (PTSD) in humans

Cortisol: Biosensing and detection strategies

Cortisol, a crucial steroid hormone synthesized by the adrenal glands, has diverse impacts on multiple physiological processes, such as metabolism, immune function, and stress management. Disruption in cortisol levels can result in conditions like Cushing's syndrome and Addison's disease. This review provides an in-depth exploration of cortisol, covering its structure, various forms in the body, detection methodologies, and emerging trends in cancer treatment and detection. Various techniques for cortisol detection, including electrochemical, chromatographic, and immunoassay methods were discussed and highlighted for their merits and applications. Electrochemical immunosensing emerges as a promising approach, which offered high sensitivity and low detection limits. Moreover, the review delves into the intricate relationship between cortisol and cancer, emphasizing cortisol's role in cancer progression and treatment outcomes. Lastly, the utilization of biomarkers, in-silico modeling, and machine learning for electrochemical cortisol detection were explored, which showcased innovative strategies for stress monitoring and healthcare advancement.

Systematic Quantitative Analysis of Fetal Dexamethasone Exposure and Fetal Lung Maturation in Pregnant Animals: Model Informed Dexamethasone Precision Dose Study

Dexamethasone (DEX) was applied in neonatal respiratory distress syndrome treatment of pregnant women. We established a pharmacokinetics (PK)/pharmacodynamics(PD)/end point model of pregnant animals based on published data and then extrapolated to simulate fetal exposure and lung maturation in pregnant women. We first established the PK/PD/end point model for DEX in pregnant sheep. We considered the competitive effect of cortisol (Cort) and DEX binding with glucocorticoid receptor and then used the indirect response model to describe disaturated-phosphatidylcholine (DSPC) dynamics. Based on that, we established a regression relationship between DSPC and fetal lung volume (V40). We then extrapolated the PD/end point model of pregnant sheep to pregnant monkeys by corrected stages of morphologic lung maturation in two species. Finally, we utilized the interspecies extrapolation strategy to simulate fetal exposure (AUC0-48h) and V40 relationship in pregnant women. The current model could well describe the maternal-fetal PK of DEX in pregnant animals. Simulated DEX AUC0-24h values of the umbilical venous to maternal plasma ratio in pregnant sheep and monkeys were 0.31 and 0.27, respectively. The simulated Cort curve and V40 in pregnant sheep closely matched the observed data within a 2-fold range. For pregnant monkeys, model-simulated V40 were well fitted with external verification data, which showed good interspecies extrapolation performance. Finally, we simulated fetal exposure-response relationship in pregnant women, which indicated that the fetal AUC0-48h of DEX should not be less than 300 and 100 ng/mL·hr at GW28 and GW34 to ensure fetal lung maturity. The current model preliminarily provided support for clinical DEX dose optimization.

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.

The Psychedelic Future of Post-Traumatic Stress Disorder Treatment

Post-traumatic stress disorder (PTSD) is a mental health condition that can occur following exposure to a traumatic experience. An estimated 12 million U.S. adults are presently affected by this disorder. Current treatments include psychological therapies (e.g., exposure-based interventions) and pharmacological treatments (e.g., selective serotonin reuptake inhibitors (SSRIs)). However, a significant proportion of patients receiving standard-of-care therapies for PTSD remain symptomatic, and new approaches for this and other trauma-related mental health conditions are greatly needed. Psychedelic compounds that alter cognition, perception, and mood are currently being examined for their efficacy in treating PTSD despite their current status as Drug Enforcement Administration (DEA)- scheduled substances. Initial clinical trials have demonstrated the potential value of psychedelicassisted therapy to treat PTSD and other psychiatric disorders. In this comprehensive review, we summarize the state of the science of PTSD clinical care, including current treatments and their shortcomings. We review clinical studies of psychedelic interventions to treat PTSD, trauma-related disorders, and common comorbidities. The classic psychedelics psilocybin, lysergic acid diethylamide (LSD), and N,N-dimethyltryptamine (DMT) and DMT-containing ayahuasca, as well as the entactogen 3,4-methylenedioxymethamphetamine (MDMA) and the dissociative anesthetic ketamine, are reviewed. For each drug, we present the history of use, psychological and somatic effects, pharmacology, and safety profile. The rationale and proposed mechanisms for use in treating PTSD and traumarelated disorders are discussed. This review concludes with an in-depth consideration of future directions for the psychiatric applications of psychedelics to maximize therapeutic benefit and minimize risk in individuals and communities impacted by trauma-related conditions.

Dietary Marine Hydrolysate Improves Memory Performance and Social Behavior through Gut Microbiota Remodeling during Aging

Aging is characterized by a decline in social behavior and cognitive functions leading to a decrease in life quality. In a previous study, we show that a fish hydrolysate supplementation prevents age-related decline in spatial short-term memory and long-term memory and anxiety-like behavior and improves the stress response in aged mice. The aim of this study was to determine the effects of a fish hydrolysate enriched with EPA/DHA or not on the cognitive ability and social interaction during aging and the biological mechanisms involved. We showed for the first time that a fish hydrolysate enriched with EPA/DHA or not improved memory performance and preference for social novelty that were diminished by aging. These changes were associated with the modulation of the gut microbiota, normalization of corticosterone, and modulation of the expression of genes involved in the mitochondrial respiratory chain, circadian clock, neuroprotection, and antioxidant activity. Thus, these changes may contribute to the observed improvements in social behavior and memory and reinforced the innovative character of fish hydrolysate in the prevention of age-related impairments.

Proportional-Derivative Control of Cortisol for Treatment of PTSD

Mental illnesses, such as depression or post-traumatic stress disorder (PTSD), often impact an individual's physiological reaction to stress via their cortisol response. We examine the regulation of cortisol within the hypothalamic-pituitary-adrenal (HPA) axis as a dynamic biosystem. We investigate the difference between the cortisol regulation of people with PTSD and healthy controls. Additionally, we investigate models for potential therapies based on proportional-derivative (PD) control to normalize and improve the stress response of those with PTSD. Such a design may be relevant to improving the treatment of PTSD, as current medical interventions are frequently imprecise and may result in unwanted side effects. The use of a PD controller in administration of hormone therapy, in contrast, can be highly measurable and patient specific.Clinical Relevance- This paper offers an approach to treating post-traumatic stress disorder (PTSD) via stabilizing an individual's endocrinal regulation as a potential future alternative to current pharmaceutical practices.

VeVaPy, a Python Platform for Efficient Verification and Validation of Systems Biology Models with Demonstrations Using Hypothalamic-Pituitary-Adrenal Axis Models

In order for mathematical models to make credible contributions, it is essential for them to be verified and validated. Currently, verification and validation (V&V) of these models does not meet the expectations of the system biology and systems pharmacology communities. Partially as a result of this shortfall, systemic V&V of existing models currently requires a lot of time and effort. In order to facilitate systemic V&V of chosen hypothalamic-pituitary-adrenal (HPA) axis models, we have developed a computational framework named VeVaPy-taking care to follow the recommended best practices regarding the development of mathematical models. VeVaPy includes four functional modules coded in Python, and the source code is publicly available. We demonstrate that VeVaPy can help us efficiently verify and validate the five HPA axis models we have chosen. Supplied with new and independent data, VeVaPy outputs objective V&V benchmarks for each model. We believe that VeVaPy will help future researchers with basic modeling and programming experience to efficiently verify and validate mathematical models from the fields of systems biology and systems pharmacology.

Pharmacological Implications of Adjusting Abnormal Fear Memory: Towards the Treatment of Post-Traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a unique clinical mental abnormality presenting a cluster of symptoms in which patients primarily experience flashbacks, nightmares and uncontrollable thoughts about the event that triggered their PTSD. Patients with PTSD may also have comorbid depression and anxiety in an intractable and long-term course, which makes establishing a comprehensive treatment plan difficult and complicated. The present article reviews current pharmacological manipulations for adjusting abnormal fear memory. The roles of the central monoaminergic systems (including serotonin, norepinephrine and dopamine) within the fear circuit areas and the involvement of the hypothalamic-pituitary-adrenal (HPA) axis and glucocorticoid receptor (GR) are explored based on attempts to integrate current clinical and preclinical basic studies. In this review, we explain how these therapeutic paradigms function based on their connections to stages of the abnormal fear memory process from condition to extinction. This may provide useful translational interpretations for clinicians to manage PTSD.

The biobehavioural effectiveness of spiritual-hypnosis-assisted therapy in PTSD with childhood trauma

Background

Posttraumatic Stress Disorder (PTSD) is a serious psychological trauma disorder. Treatment of psychological trauma tends to focus on patients' memory. Clinical Spiritual-Hypnosis Assisted Therapy is a culturally sensitive treatment that combines elements of psychodynamic hypnosis, cognitive–behavioral and humanistic therapies.

Methods

The current interventional single-blind randomized control study assessed the biobehavioural effectiveness of spiritual-hypnosis on cortisol and PTSD symptomatology in adults with childhood trauma. Participants were divided into spiritual hypnosis (n = 15) and a control group (n = 14) that received fluoxetine. This study used PCL-C & CTQ to screen the presence and severity of PTSD symptoms.

Results

Spiritual hypnosis was significantly better than fluoxetine at reducing PTSD symptoms, while both treatments had similar effects on cortisol modification.

Conclusions

Spiritual-Hypnosis Assisted Therapy for PTSD patients with childhood trauma appears to have a noteworthy effect in reducing PTSD clinical symptoms and results in a comparable to the pharmacological treatment modification of the HPA axis cortisol markers.

Understanding virtual patients efficiently and rigorously by combining machine learning with dynamical modelling

Individual biological organisms are characterized by daunting heterogeneity, which precludes describing or understanding populations of ‘patients’ with a single mathematical model. Recently, the field of quantitative systems pharmacology (QSP) has adopted the notion of virtual patients (VPs) to cope with this challenge. A typical population of VPs represents the behavior of a heterogeneous patient population with a distribution of parameter values over a mathematical model of fixed structure. Though this notion of VPs is a powerful tool to describe patients’ heterogeneity, the analysis and understanding of these VPs present new challenges to systems pharmacologists. Here, using a model of the hypothalamic–pituitary–adrenal axis, we show that an integrated pipeline that combines machine learning (ML) and bifurcation analysis can be used to effectively and efficiently analyse the behaviors observed in populations of VPs. Compared with local sensitivity analyses, ML allows us to capture and analyse the contributions of simultaneous changes of multiple model parameters. Following up with bifurcation analysis, we are able to provide rigorous mechanistic insight regarding the influences of ML-identified parameters on the dynamical system’s behaviors. In this work, we illustrate the utility of this pipeline and suggest that its wider adoption will facilitate the use of VPs in the practice of systems pharmacology.

Light-induced synchronization of the SCN coupled oscillators and implications for entraining the HPA axis

The suprachiasmatic nucleus (SCN) synchronizes the physiological rhythms to the external light-dark cycle and tunes the dynamics of circadian rhythms to photoperiod fluctuations. Changes in the neuronal network topologies are suggested to cause adaptation of the SCN in different photoperiods, resulting in the broader phase distribution of neuron activities in long photoperiods (LP) compared to short photoperiods (SP). Regulated by the SCN output, the level of glucocorticoids is elevated in short photoperiod, which is associated with peak disease incidence. The underlying coupling mechanisms of the SCN and the interplay between the SCN and the HPA axis have yet to be fully elucidated. In this work, we propose a mathematical model including a multiple-cellular SCN compartment and the HPA axis to investigate the properties of the circadian timing system under photoperiod changes. Our model predicts that the probability-dependent network is more energy-efficient than the distance-dependent network. Coupling the SCN network by intra-subpopulation and inter-subpopulation forces, we identified the negative correlation between robustness and plasticity of the oscillatory network. The HPA rhythms were predicted to be strongly entrained to the SCN rhythms with a pro-inflammatory high-amplitude glucocorticoid profile under SP. The fast temporal topology switch of the SCN network was predicted to enhance synchronization when the synchronization is not complete. These synchronization and circadian dynamics alterations might govern the seasonal variation of disease incidence and its symptom severity.

Teaching computational systems biology with an eye on quantitative systems pharmacology at the undergraduate level: Why do it, who would take it, and what should we teach?

Computational systems biology (CSB) is a field that emerged primarily as the product of research activities. As such, it grew in several directions in a distributed and uncoordinated manner making the area appealing and fascinating. The idea of not having to follow a specific path but instead creating one fueled innovation. As the field matured, several interdisciplinary graduate programs emerged attempting to educate future generations of computational systems biologists. These educational initiatives coordinated the dissemination of information across student populations that had already decided to specialize in this field. However, we are now entering an era where CSB, having established itself as a valuable research discipline, is attempting the next major step: Entering undergraduate curricula. As interesting as this endeavor may sound, it has several difficulties, mainly because the field is not uniformly defined. In this manuscript, we argue that this diversity is a significant advantage and that several incarnations of an undergraduate-level CSB biology course could, and should, be developed tailored to programmatic needs. In this manuscript, we share our experiences creating a course as part of a Biomedical Engineering program.

A Modeling and Machine Learning Pipeline to Rationally Design Treatments to Restore Neuroendocrine Disorders in Heterogeneous Individuals

Heterogeneity among individual patients presents a fundamental challenge to effective treatment, since a treatment protocol working for a portion of the population often fails in others. We hypothesize that a computational pipeline integrating mathematical modeling and machine learning could be used to address this fundamental challenge and facilitate the optimization of individualized treatment protocols. We tested our hypothesis with the neuroendocrine systems controlled by the hypothalamic–pituitary–adrenal (HPA) axis. With a synergistic combination of mathematical modeling and machine learning (ML), this integrated computational pipeline could indeed efficiently reveal optimal treatment targets that significantly contribute to the effective treatment of heterogeneous individuals. What is more, the integrated pipeline also suggested quantitative information on how these key targets should be perturbed. Based on such ML revealed hints, mathematical modeling could be used to rationally design novel protocols and test their performances. We believe that this integrated computational pipeline, properly applied in combination with other computational, experimental and clinical research tools, can be used to design novel and improved treatment against a broad range of complex diseases.

Light entrainment of the SCN circadian clock and implications for personalized alterations of corticosterone rhythms in shift work and jet lag

The suprachiasmatic nucleus (SCN) functions as the central pacemaker aligning physiological and behavioral oscillations to day/night (activity/inactivity) transitions. The light signal entrains the molecular clock of the photo-sensitive ventrolateral (VL) core of the SCN which in turn entrains the dorsomedial (DM) shell via the neurotransmitter vasoactive intestinal polypeptide (VIP). The shell converts the VIP rhythmic signals to circadian oscillations of arginine vasopressin (AVP), which eventually act as a neurotransmitter signal entraining the hypothalamic–pituitary–adrenal (HPA) axis, leading to robust circadian secretion of glucocorticoids. In this work, we discuss a semi-mechanistic mathematical model that reflects the essential hierarchical structure of the photic signal transduction from the SCN to the HPA axis. By incorporating the interactions across the core, the shell, and the HPA axis, we investigate how these coupled systems synchronize leading to robust circadian oscillations. Our model predicts the existence of personalized synchronization strategies that enable the maintenance of homeostatic rhythms while allowing for differential responses to transient and permanent light schedule changes. We simulated different behavioral situations leading to perturbed rhythmicity, performed a detailed computational analysis of the dynamic response of the system under varying light schedules, and determined that (1) significant interindividual diversity and flexibility characterize adaptation to varying light schedules; (2) an individual’s tolerances to jet lag and alternating shift work are positively correlated, while the tolerances to jet lag and transient shift work are negatively correlated, which indicates trade-offs in an individual’s ability to maintain physiological rhythmicity; (3) weak light sensitivity leads to the reduction of circadian flexibility, implying that light therapy can be a potential approach to address shift work and jet lag related disorders. Finally, we developed a map of the impact of the synchronization within the SCN and between the SCN and the HPA axis as it relates to the emergence of circadian flexibility.

Pathophysiology of Major Depression by Clinical Stages

The comprehension of the pathophysiology of the major depressive disorder (MDD) is essential to the strengthening of precision psychiatry. In order to determine the relationship between the pathophysiology of the MDD and its clinical progression, analyzed by severity of the depressive symptoms and sleep quality, we conducted a study assessing different peripheral molecular biomarkers, including the levels of plasma C-reactive protein (CRP), serum mature brain-derived neurotrophic factor (mBDNF), serum cortisol (SC), and salivary cortisol awakening response (CAR), of patients with MDD (n = 58) and a control group of healthy volunteers (n = 62). Patients with the first episode of MDD (n = 30) had significantly higher levels of CAR and SC than controls (n = 32) and similar levels of mBDNF of controls. Patients with treatment-resistant depression (TRD, n = 28) presented significantly lower levels of SC and CAR, and higher levels of mBDNF and CRP than controls (n = 30). An increased severity of depressive symptoms and worse sleep quality were correlated with levels low of SC and CAR, and with high levels of mBDNF. These results point out a strong relationship between the stages clinical of MDD and changes in a range of relevant biological markers. This can assist in the development of precision psychiatry and future research on the biological tests for depression.

Modeling the Influence of Chronic Sleep Restriction on Cortisol Circadian Rhythms, with Implications for Metabolic Disorders

Chronic sleep deficiency is prevalent in modern society and is associated with increased risk of metabolic and other diseases. While the mechanisms by which chronic sleep deficiency induces pathophysiological changes are yet to be elucidated, the hypothalamic–pituitary–adrenal (HPA) axis may be an important mediator of these effects. Cortisol, the primary hormone of the HPA axis, exhibits robust circadian rhythmicity and is moderately influenced by sleep and wake states and other physiology. Several studies have explored the effects of acute or chronic sleep deficiency (i.e., usually from self-selected chronic sleep restriction, CSR) on the HPA axis. Quantifying long-term changes in the circadian rhythm of cortisol under CSR in controlled conditions is inadequately studied due to practical limitations. We use a semi-mechanistic mathematical model of the HPA axis and the sleep/wake cycle to explore the influence of CSR on cortisol circadian rhythmicity. In qualitative agreement with experimental findings, model simulations predict that CSR results in physiologically relevant disruptions in the phase and amplitude of the cortisol rhythm. The mathematical model presented in this work provides a mechanistic framework to further explore how CSR might lead to HPA axis disruption and subsequent development of chronic metabolic complications.

Mathematical analysis of the role of pituitary-adrenal interactions in ultradian rhythms of the HPA axis

The hypothalamic-pituitary-adrenal (HPA) axis is a biological system in the human body that plays an important role in controlling stress and regulating various physiological elements, including the immune system, emotions, and moods in tense situations. Over the past two decades, several ordinary or delay differential equations models of the HPA axis have been proposed. In the majority of studies presented so far, corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and cortisol are among the main variables employed to build the HPA axis models. In the present study, based on a previously introduced hypothesis which asserts that ultradian rhythms in the HPA axis are produced by the pituitary-adrenal network alone and these rhythms can endure in the absence of CRH secretion, a simple two-dimensional delayed dynamical model of the HPA axis based on only ACTH and cortisol is introduced. The model is shown to be able to capture the ultradian (low frequency) rhythms of ACTH and cortisol released into the bloodstream. By mathematical analysis of the model using the Hopf bifurcation theorem, it is also demonstrated how oscillating solutions can emerge. Also, the model employs physiologically reasonable parameter values to exhibit how in the absence of CRH secretion, a simple model of the pituitary-adrenal interaction can be used to produce ultradian rhythms of both cortisol and ACTH hormones.

Stress, memory, and implications for major depression

The stress response comprises a phylogenetically conserved set of cognitive, physiological, and behavioral responses that evolved as a survival strategy. In this context, the memory of stressful events would be adaptive as it could avoid re-exposure to an adverse event, otherwise the event would be facilitated in positively stressful or non-distressful conditions. However, the interaction between stress and memory comprises complex responses, some of them which are not yet completely understood, and which depend on several factors such as the memory system that is recruited, the nature and duration of the stressful event, as well as the timing in which this interaction takes place. In this narrative review, we briefly discuss the mechanisms of the stress response, the main memory systems, and its neural correlates. Then, we show how stress, through the action of its biochemical mediators, influences memory systems and mnemonic processes. Finally, we make use of major depressive disorder to explore the possible implications of non-adaptive interactions between stress and memory to psychiatric disorders, as well as possible roles for memory studies in the field of psychiatry.

The role of childhood trauma, HPA axis reactivity and FKBP5 genotype on cognition in healthy individuals

Cognitive impairment has been associated with both childhood adversity and abnormalities of hypothalamic-pituitary-adrenal (HPA) axis function. An interaction exists between the functional polymorphism rs1360780 in the FKBP5 gene and childhood maltreatment, influencing a variety of clinical outcomes. Our goal was to study the relationship between different types of childhood trauma, HPA axis functionality, rs1360780 genotype and cognitive function in 198 healthy individuals who participated in the study. We obtained clinical data, childhood maltreatment scores and neurocognitive performance by clinical assessment; HPA negative feedback was analysed using the dexamethasone suppression test ratio (DSTR) after administration of 0.25 mg of dexamethasone; and the FKBP5 rs1360780 polymorphism was genotyped in DNA obtained from blood samples. The results showed a significant influence of physical neglect on measures of neurocognition as well as an interaction between the DSTR and physical and emotional neglect. Regarding social cognition, a significant association was found with sexual and physical abuse as well as with rs1360780 risk-allele carrier status. Moreover, an interaction between the rs1360780 genotype and the presence of physical abuse was significantly associated with social cognition results. Our results suggest a specific impact of different kinds of childhood maltreatment on measures of neurocognition and social cognition, which might be influenced by HPA axis reactivity and genetic variants in HPA axis-related genes such as FKBP5. Disentangling the relationship between these elements and their influence on cognitive performance might help identify susceptible individuals with higher stress vulnerability and develop preventive interventions.

Circadian rhythms and the HPA axis: A systems view

The circadian timing system comprises a network of time-keeping clocks distributed across a living host whose responsibility is to allocate resources and distribute functions temporally to optimize fitness. The molecular structures generating these rhythms have evolved to accommodate the rotation of the earth in an attempt to primarily match the light/dark periods during the 24-hr day. To maintain synchrony of timing across and within tissues, information from the central clock, located in the suprachiasmatic nucleus, is conveyed using systemic signals. Leading among those signals are endocrine hormones, and while the hypothalamic-pituitary-adrenal axis through the release of glucocorticoids is a major pacesetter. Interestingly, the fundamental units at the molecular and physiological scales that generate local and systemic signals share critical structural properties. These properties enable time-keeping systems to generate rhythmic signals and allow them to adopt specific properties as they interact with each other and the external environment. The purpose of this review is to provide a broad overview of these structures, discuss their functional characteristics, and describe some of their fundamental properties as these related to health and disease. This article is categorized under: Immune System Diseases > Computational Models Immune System Diseases > Biomedical Engineering.

Stress-induced alterations of social behavior are reversible by antagonism of steroid hormones in C57/BL6 mice

Various disturbances of social behavior, such as autism, depression, or posttraumatic stress disorder, have been associated with an altered steroid hormone homeostasis and a dysregulation of the hypothalamus-pituitary-adrenal axis. A link between steroid hormone antagonists and the treatment of stress-related conditions has been suggested. We evaluated the effects of stress induction on social behavior in the three chambers and its potential reversibility upon specific steroid hormone antagonism in mice. C57BL/6 mice were stressed twice daily for 8 days by chronic swim testing. Social behavior was evaluated by measuring, first, the preference for sociability and, second, the preference for social novelty in the three-chamber approach before and after the chronic swim test. The reversibility of behavior upon stress induction was analyzed after applying steroid hormone antagonists targeting glucocorticoids with etomidate, mineralocorticoids with potassium canrenoate, and androgens with cyproterone acetate and metformin. In the chronic swim test, increased floating time from 0.8 ± 0.2 min up to 4.8 ± 0.25 min was detected (p < 0.01). In the three-chamber approach, increased preference for sociability and decreased preference for social novelty was detected pre- versus post-stress induction. These alterations of social behavior were barely affected by etomidate and potassium canrenoate, whereas the two androgen antagonists metformin and cyproterone acetate restored social behavior even beyond baseline conditions. The alteration of social behavior was better reversed by the androgen as compared with the glucocorticoid and mineralocorticoid antagonists. This suggests that social behavior is primarily controlled by androgen rather than by glucocorticoid or mineralocorticoid action. The stress-induced changes in preference for sociability are incompletely explained by steroid hormone action alone. As the best response was related to metformin, an effect via glucose levels might confound the results and should be subject to future research.

Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions

The hypothalamus-pituitary-adrenal (HPA) axis is a key neuroendocrine system implicated in stress response, major depression disorder, and post-traumatic stress disorder. We present a new, compact dynamical systems model for the response of the HPA axis to external stimuli, representing stressors or therapeutic intervention, in the presence of a circadian input. Our work builds upon previous HPA axis models where hormonal dynamics are separated into slow and fast components. Several simplifications allow us to derive an effective model of two equations, similar to a multiplicative-input FitzHugh-Nagumo system, where two stable states, a healthy and a diseased one, arise. We analyze the effective model in the context of state transitions driven by external shocks to the hypothalamus, but also modulated by circadian rhythms. Our analyses provide mechanistic insight into the effects of the circadian cycle on input driven transitions of the HPA axis and suggest a circadian influence on exposure or cognitive behavioral therapy in depression, or post-traumatic stress disorder treatment.

Timescales of Human Hair Cortisol Dynamics

Cortisol is a major human stress hormone, secreted within minutes of acute stress. Cortisol also has slower patterns of variation: a strong circadian rhythm and a seasonal rhythm. However, longitudinal cortisol dynamics in healthy individuals over timescales of months has rarely been studied. Here, we measured longitudinal cortisol in 55 healthy participants using 12 cm of hair, which provides a retrospective measurement over one year. Individuals showed (non-seasonal) fluctuations averaging about 22% around their baseline. Fourier analysis reveals dominant slow frequencies with periods of months to a year. These frequencies can be explained by a mathematical model of the hormonal cascade that controls cortisol, the HPA axis, when including the slow timescales of tissue turnover of the glands. Measuring these dynamics is important for understanding disorders in which cortisol secretion is impaired over months, such as mood disorders, and to test models of cortisol feedback control.

Role of enhanced glucocorticoid receptor sensitivity in inflammation in PTSD: insights from computational model for circadian-neuroendocrine-immune interactions

Although glucocorticoid resistance contributes to increased inflammation, individuals with posttraumatic stress disorder (PTSD) exhibit increased glucocorticoid receptor (GR) sensitivity along with increased inflammation. It is not clear how inflammation coexists with a hyperresponsive hypothalamic-pituitary-adrenal (HPA) axis. To understand this better, we developed and analyzed an integrated mathematical model for the HPA axis and the immune system. We performed mathematical simulations for a dexamethasone (DEX) suppression test and IC₅₀-dexamethasone for cytokine suppression by varying model parameters. The model analysis suggests that increasing the steepness of the dose-response curve for GR activity may reduce anti-inflammatory effects of GRs at the ambient glucocorticoid levels, thereby increasing proinflammatory response. The adaptive response of proinflammatory cytokine-mediated stimulatory effects on the HPA axis is reduced due to dominance of the GR-mediated negative feedback on the HPA axis. To verify these hypotheses, we analyzed the clinical data on neuroendocrine variables and cytokines obtained from war-zone veterans with and without PTSD. We observed significant group differences for cortisol and ACTH suppression tests, proinflammatory cytokines TNFα and IL6, high-sensitivity C-reactive protein, promoter methylation of GR gene, and IC_50-DEX for lysozyme suppression. Causal inference modeling revealed significant associations between cortisol suppression and post-DEX cortisol decline, promoter methylation of human GR gene exon 1F (NR3C1-1F), IC_50-DEX, and proinflammatory cytokines. We noted significant mediation effects of NR3C1-1F promoter methylation on inflammatory cytokines through changes in GR sensitivity. Our findings suggest that increased GR sensitivity may contribute to increased inflammation; therefore, interventions to restore GR sensitivity may normalize inflammation in PTSD.

A new model for the HPA axis explains dysregulation of stress hormones on the timescale of weeks

Stress activates a complex network of hormones known as the hypothalamic-pituitary-adrenal (HPA) axis. The HPA axis is dysregulated in chronic stress and psychiatric disorders, but the origin of this dysregulation is unclear and cannot be explained by current HPA models. To address this, we developed a mathematical model for the HPA axis that incorporates changes in the total functional mass of the HPA hormone-secreting glands. The mass changes are caused by HPA hormones which act as growth factors for the glands in the axis. We find that the HPA axis shows the property of dynamical compensation, where gland masses adjust over weeks to buffer variation in physiological parameters. These mass changes explain the experimental findings on dysregulation of cortisol and ACTH dynamics in alcoholism, anorexia, and postpartum. Dysregulation occurs for a wide range of parameters and is exacerbated by impaired glucocorticoid receptor (GR) feedback, providing an explanation for the implication of GR in mood disorders. These findings suggest that gland-mass dynamics may play an important role in the pathophysiology of stress-related disorders.

Our natural "makeup" reveals more than it hides: Modeling the skin and its microbiome

Skin is our primary interface with the environment. A structurally and functionally complex organ that hosts a dynamic ecosystem of microbes, and synthesizes many compounds that affect our well-being and psychosocial interactions. It is a natural platform of signal exchange between internal organs, skin resident microbes, and the environment. These interactions have gained a great deal of attention due to the increased prevalence of atopic diseases, and the co-occurrence of multiple allergic diseases related to allergic sensitization in early life. Despite significant advances in experimentally characterizing the skin, its microbial ecology, and disease phenotypes, high-levels of variability in these characteristics even for the same clinical phenotype are observed. Addressing this variability and resolving the relevant biological processes requires a systems approach. This review presents some of our current understanding of the skin, skin-immune, skin-neuroendocrine, skin-microbiome interactions, and computer-based modeling approaches to simulate this ecosystem in the context of health and disease. The review highlights the need for a systems-based understanding of this sophisticated ecosystem. This article is categorized under: Infectious Diseases > Computational Models.

Modeling inter-sex and inter-individual variability in response to chronopharmacological administration of synthetic glucocorticoids

Endogenous glucocorticoids have diverse physiological effects and are important regulators of metabolism, immunity, cardiovascular function, musculoskeletal health and central nervous system activity. Synthetic glucocorticoids have received widespread attention for their potent anti-inflammatory activity and have become an important class of drugs used to augment endogenous glucocorticoid activity for the treatment of a host of chronic inflammatory conditions. Chronic use of synthetic glucocorticoids is associated with a number of adverse effects as a result of the persistent dysregulation of glucocorticoid sensitive pathways. A failure to consider the pronounced circadian rhythmicity of endogenous glucocorticoids can result in either supraphysiological glucocorticoid exposure or severe suppression of endogenous glucocorticoid secretion, and is thought be a causal factor in the incidence of adverse effects during chronic glucocorticoid therapy. Furthermore, given that synthetic glucocorticoids have potent feedback effects on the hypothalamic-pituitary-adrenal (HPA) axis, physiological factors which can give rise to individual variability in HPA axis activity such as sex, age, and disease state might also have substantial implications for therapy. We use a semi-mechanistic mathematical model of the rodent HPA axis to study how putative sex differences and individual variability in HPA axis regulation can influence the effects of long-term synthetic exposure on endogenous glucocorticoid circadian rhythms. Model simulations suggest that for the same drug exposure, simulated females exhibit less endogenous suppression than males considering differences in adrenal sensitivity and negative feedback to the hypothalamus and pituitary. Simulations reveal that homeostatic regulatory variability and chronic stress-induced regulatory adaptations in the HPA axis network can result in substantial differences in the effects of synthetic exposure on the circadian rhythm of endogenous glucocorticoids. In general, our results provide insight into how the dosage and exposure profile of synthetic glucocorticoids could be manipulated in a personalized manner to preserve the circadian dynamics of endogenous glucocorticoids during chronic therapy, thus potentially minimizing the incidence of adverse effects associated with long-term use of glucocorticoids.

Transitioning from acute to chronic pain: a simulation study of trajectories of low back pain

Background

Identifying how pain transitions from acute to chronic is critical in designing effective prevention and management techniques for patients’ well-being, physically, psychosocially, and financially. There is an increasingly pressing need for a quantitative and predictive method to evaluate how low back pain trajectories are classified and, subsequently, how we can more effectively intervene during these progression stages.

Methods

In order to better understand pain mechanisms, we investigated, using computational modeling, how best to describe pain trajectories by developing a platform by which we studied the transition of acute chronic pain.

Results

The present study uses a computational neuroscience-based method to conduct such trajectory research, motivated by the use of hypothalamic–pituitary–adrenal (HPA) axis activity-history over a time-period as a way to mimic pain trajectories. A numerical simulation study is presented as a “proof of concept” for this modeling approach.

Conclusions

This model and its simulation results have highlighted the feasibility and the potential of developing such a broader model for patient evaluations.

Reframing PTSD for computational psychiatry with the active inference framework

Introduction: Recent advances in research on stress and, respectively, on disorders of perception, learning, and behaviour speak to a promising synthesis of current insights from (i) neurobiology, cognitive neuroscience and psychology of stress and post-traumatic stress disorder (PTSD), and (ii) computational psychiatry approaches to pathophysiology (e.g. of schizophrenia and autism). Methods: Specifically, we apply this synthesis to PTSD. The framework of active inference offers an embodied and embedded lens through which to understand neuronal mechanisms, structures, and processes of cognitive function and dysfunction. In turn, this offers an explanatory model of how healthy mental functioning can go awry due to psychopathological conditions that impair inference about our environment and our bodies. In this context, auditory phenomena-known to be especially relevant to studies of PTSD and schizophrenia-and traditional models of auditory function can be viewed from an evolutionary perspective based on active inference. Results: We assess and contextualise a range of evidence on audition, stress, psychosis, and PTSD, and bring some existing partial models of PTSD into multilevel alignment. Conclusions: The novel perspective on PTSD we present aims to serve as a basis for new experimental designs and therapeutic interventions that integrate fundamentally biological, cognitive, behavioural, and environmental factors.

Allostatic adaptation and personalized physiological trade-offs in the circadian regulation of the HPA axis: A mathematical modeling approach

The hypothalamic-pituitary-adrenal (HPA) axis orchestrates the physiological response to unpredictable acute stressors. Moreover, the HPA axis exhibits prominent circadian activity and synchronizes peripheral circadian clocks to daily environmental cycles, thereby promoting homeostasis. Persistent disruption of homeostatic glucocorticoid circadian rhythmicity due to chronic stress exposure is correlated with the incidence of various pathological conditions including depression, diabetes and cancer. Allostatic habituation of the HPA axis, such that glucocorticoid levels retain homeostatic levels upon chronic exposure to stress, can therefore confer fitness advantages by preventing the sustained dysregulation of glucocorticoid-responsive signaling pathways. However, such allostatic adaptation results in a physiological cost (allostatic load) that might impair the homeostatic stress-responsive and synchronizing functions of the HPA axis. We use mathematical modeling to characterize specific chronic stress-induced allostatic adaptations in the HPA network. We predict the existence of multiple individualized regulatory strategies enabling the maintenance of homeostatic glucocorticoid rhythms, while allowing for flexible HPA response characteristics. We show that this regulatory variability produces a trade-off between the stress-responsive and time-keeping properties of the HPA axis. Finally, allostatic regulatory adaptations are predicted to cause a time-of-day dependent sensitization of the acute stress response and impair the entrainability of the HPA axis.

Recent advances in the neurobiology of posttraumatic stress disorder: A review of possible mechanisms underlying an effective pharmacotherapy

Recent progress in the field of neurobiology supported by clinical evidence gradually reveals the mystery of human brain functioning. So far, many psychiatric disorders have been described in great detail, although there are still plenty of cases that are misunderstood. These include posttraumatic stress disorder (PTSD), which is a unique disease that combines a wide range of neurobiological changes, which involve disturbances of the hypothalamic-pituitary-adrenal gland axis, hyperactivation of the amygdala complex, and attenuation of some hippocampal and cortical functions. Such multiplicity results in differential symptomatology, including elevated anxiety, nightmares, fear retrieval episodes that may trigger delusions and hallucinations, sleep disturbances, and many others that strongly interfere with the quality of the patient's life. Because of widespread neurological changes and the disease manifestation, the pharmacotherapy of PTSD remains unclear and requires a multidimensional approach and involvement of polypharmacotherapy. Hopefully, more and more neuroscientists and clinicians will study PTSD, which will provide us with new information that would possibly accelerate establishment of well-tolerated and effective pharmacotherapy. In this review, we have focused on neurobiological changes regarding PTSD, addressing the most disturbed brain structures and neurotransmissions, as well as discussing in detail the recently taken and novel therapeutic paths.

Posttraumatic stress disorder following the 2008 Wenchuan earthquake: A 10-year systematic review among highly exposed populations in China

BACKGROUND

The 2008 Wenchuan earthquake was unprecedented in Chinese history both in terms of the magnitude of the quake itself and the scale of human suffering. Following the disaster, researchers reported on a wide range of mental health outcomes, especially posttraumatic stress disorder (PTSD). In this review, we assess the cumulative body of research evidence about PTSD across the first 10 years following the earthquake.

METHODS

We searched the literature in the PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI) databases (from May 2008 to February 2018) using Wenchuan earthquake and PTSD as keywords.

RESULTS

We selected 58 relevant studies. Published findings from the selected period suggested a substantial burden of PTSD on highly exposed survivors. Studies have found that symptoms of PTSD have been associated with a range of risk factors, including sociodemographic factors, trauma exposure characteristics, post-disaster cognitive and emotional states, and social support. Studies have explored the factor structure of PTSD in the affected Chinese population, and researchers have developed a Chinese self-report measure of PTSD symptoms. Several treatments for PTSD have been evaluated, including some indigenous intervention methods.

LIMITATIONS

Only a relatively small number of the studies used longitudinal assessments, and the consistency and effectiveness of measurement tools for PTSD require further exploration. More rigorous investigations of the effectiveness of interventions for the prevention and treatment of PTSD are needed.

CONCLUSION

The 10-year body of literature is important for the future deployment of disaster relief and an increased understanding of PTSD in China.

Modeling the influence of chronopharmacological administration of synthetic glucocorticoids on the hypothalamic-pituitary-adrenal axis

Natural glucocorticoids, a class of cholesterol-derived hormones, modulate an array of metabolic, anti-inflammatory, immunosuppressive and cognitive signaling. The synthesis of natural glucocorticoids, largely cortisol in humans, is regulated by the hypothalamic-pituitary-adrenal (HPA) axis and exhibits pronounced circadian variation. Considering the central regulatory function of endogenous glucocorticoids, maintenance of the circadian activity of the HPA axis is essential to host survival and chronic disruption of such activity leads to systemic complications. There is a great deal of interest in synthetic glucocorticoids due to the immunosuppressive and anti-inflammatory properties and the development of novel dosing regimens that can minimize the disruption of endogenous activity, while still maintaining the pharmacological benefits of long-term synthetic glucocorticoid therapy. Synthetic glucocorticoids are associated with an increased risk of developing the pathological disorders related to chronic suppression of cortisol rhythmicity as a result of the potent negative feedback by synthetic glucocorticoids on the HPA axis precursors. In this study, a mathematical model was developed to explore the influence of chronopharmacological dosing of exogenous glucocorticoids on the endogenous cortisol rhythm considering intra-venous and oral dosing. Chronic daily dosing resulted in modification of the circadian rhythmicity of endogenous cortisol with the amplitude and acrophase of the altered rhythm dependent on the administration time. Simulations revealed that the circadian features of the endogenous cortisol rhythm can be preserved by proper timing of administration. The response following a single dose was not indicative of the response following long-term, repeated chronopharmacological dosing of synthetic glucocorticoids. Furthermore, simulations revealed the inductive influence of long-term treatment was only associated with low to moderate doses, while high doses generally led to suppression of endogenous activity regardless of the chronopharmacological dose. Finally, chronic daily dosing was found to alter the responsiveness of the HPA axis, such that a decrease in the amplitude of the cortisol rhythm resulted in a partial loss in the time-of-day dependent response to CRH stimulation, while an increase in the amplitude was associated with a more pronounced time-of-day dependence of the response.

A mathematical model of type 1 diabetes involving leptin effects on glucose metabolism

Leptin, a hormone released from fat cells in adipose tissues, was recently found to be capable of normalizing glucose metabolism in animals. Clinical data on patients with lipodystrophy indicates that leptin may have a positive effect on glucose metabolism in individuals with diabetes. There are growing expectations that leptin can improve the current insulin treatment for patients with type 1 diabetes. We investigated this possibility through in silico experiments based on a mathematical model of diabetes, which is currently the only mode of research that eliminates human risk. A model of the brain-centered glucoregulatory system, in which leptin plays a central role, was constructed and integrated within a conventional model of insulin/glucose dynamics. The model has been validated using experimental data from animal studies. The in silico combination experiments showed excellent therapeutic performance over insulin monotherapy.

Assessment and Management of Posttraumatic Stress Disorder

PURPOSE

The goal of this article is to increase clinicians' understanding of posttraumatic stress disorder (PTSD) and improve skills in assessing risk for and diagnosing PTSD. The importance and sequelae of lifetime trauma burden are discussed, with reference to trends in prevention, early intervention, and treatment.

RECENT FINDINGS

PTSD has different clinical phenotypes, which are reflected in the changes in Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria. PTSD is almost always complicated by comorbidity. Treatment requires a multimodal approach, usually including medication, different therapeutic techniques, and management of comorbidity. Interest is growing in the neurobiology of childhood survivors of trauma, intergenerational transmission of trauma, and long-term impact of trauma on physical health. Mitigation of the risk of PTSD pretrauma in the military and first responders is gaining momentum, given concerns about the cost and disability associated with PTSD. Interest is also growing in screening for PTSD in medical populations, with evidence of improved clinical outcomes. Preliminary research supports the treatment of PTSD with repetitive transcranial magnetic stimulation.

SUMMARY

PTSD is a trauma-related disorder with features of fear and negative thinking about the trauma and the future. Untreated, it leads to ongoing disruption of life due to avoidance, impaired vocational and social functioning, and other symptoms, depending on the phenotype. Despite a theoretical understanding of underlying mechanisms, PTSD remains challenging to treat, although evidence exists for benefit of pharmacologic agents and trauma-focused therapies. A need still remains for treatments that are more effective and efficient, with faster onset.

Perturbing the Hypothalamic-Pituitary-Adrenal Axis: A Mathematical Model for Interpreting PTSD Assessment Tests

We use a dynamical systems model of the hypothalamic-pituitary-adrenal (HPA) axis to understand the mechanisms underlying clinical protocols used to probe patient stress response. Specifically, we address dexamethasone (DEX) and ACTH challenge tests, which probe pituitary and adrenal gland responses, respectively. We show that some previously observed features and experimental responses can arise from a bistable mathematical model containing two steady-states, rather than relying on specific and permanent parameter changes due to physiological disruption. Moreover, we show that the timing of a perturbation relative to the intrinsic oscillation of the HPA axis can affect challenge test responses. Conventional mechanistic hypotheses supported and refuted by the challenge tests are reexamined by varying parameters in our mathematical model associated with these hypotheses. We show that (a) adrenal hyposensitivity can give rise to the responses seen in ACTH challenge tests and (b) enhanced cortisol-mediated suppression of the pituitary in subjects with PTSD is not necessary to explain the responses observed in DEX stress tests. We propose a new two-stage DEX/external stressor protocol to more clearly distinguish between the conventional hypothesis of enhanced suppression of the pituitary and bistable dynamics hypothesized in our model.

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.

Modeling the Sex Differences and Interindividual Variability in the Activity of the Hypothalamic-Pituitary-Adrenal Axis

Significant sex differences exist in the activity of the hypothalamic-pituitary-adrenal (HPA) axis. These differences are thought to contribute to the disparity in the prevalence of various autoimmune and infectious diseases between males and females. We used a mathematical model of the HPA axis to evaluate the hypothesis that differential sensitivity and negative feedback of the HPA axis network are causal factors for the observed sex differences in its activity. In doing so, we implicitly accounted for the differential influence of gonadal hormones on the HPA axis. Furthermore, we determined whether the putative mechanisms responsible for differences in basal HPA axis activity might also contribute to the observed differences in its stimulus-driven response. Model simulations predicted that the female HPA axis has greater adrenal sensitivity and weaker negative feedback. We identified two distinct sex-specific parameter spaces that generate corticosterone profiles in qualitative agreement with experimental results. We propose that these parameter subspaces indicate the interindividual variability in the regulatory mechanisms of the HPA axis. Furthermore, the model predicts that the maintenance of homeostatic rhythms in response to chronic stress requires specific regulatory adaptations resulting in a phenotype of allostatically driven chronic stress-sensitization. We propose that these adaptations indicate a physiological cost of adaptation to chronic stress. Model simulations suggest that individuals with high adrenal sensitivity are more vulnerable to chronic stress sensitization and might be more susceptible to the development of neuropsychiatric disorders. These results contribute to the study of sex differences in physiological feedback systems within a quantitative framework.

Early life adversity influences stress response association with smoking relapse

RATIONALE

We examined the hypothesis that stress-related blunting of cortisol in smokers is particularly pronounced in those with a history of severe life adversity.

OBJECTIVES

The two aims of this study were first to examine hormonal, craving, and withdrawal symptoms during ad libitum smoking and after the first 24 h of abstinence in smokers who experienced high or low levels of adversity. Second, we sought to examine the relationship between adversity and hypothalamic-pituitary-adrenal (HPA) hormones to predict relapse during the first month of a smoking cessation attempt.

METHODS

Hormonal and self-report measures were collected from 103 smokers (49 women) during ad libitum smoking and after the first 24 h of abstinence. HPA hormones were measured during baseline rest and in response to acute stress in both conditions. All smokers were interested in smoking cessation, and we prospectively used stress response measures to predict relapse during the first 4 weeks of the smoking cessation attempt.

RESULTS

The results showed that high adversity was associated with higher distress and smoking withdrawal symptoms. High level of early life adversity was associated with elevated HPA activity, which was found in both salivary and plasma cortisol. Enhanced adrenocorticotropic hormone (ACTH) stress response was evident in high-adversity but not in low-adversity relapsers.

CONCLUSIONS

This study demonstrated that early life adversity is associated with stress-related HPA responses. The study also demonstrated that, among smokers who experienced a high level of life adversity, heightened ACTH and cortisol responses were linked with increased risk for smoking relapse.

The Hepato-Hypothalamic-Pituitary-Adrenal-Renal Axis: Mathematical Modeling of Cortisol’s Production, Metabolism, and Seasonal Variation

Cortisol dynamics are governed by the integration of influences from the suprachiasmatic nucleus (SCN), the hypothalamic-pituitary-adrenal (HPA) axis, and metabolic enzymes, such as the 11β–hydroxysteroid dehydrogenase (HSD) family, which are highly expressed in hepatic and renal tissue. The coordinated regulation of cortisol dynamics is essential for the maintenance of a healthy state, and aberrant cortisol circadian rhythms are associated with various pathophysiological conditions. The duration of the light-dark cycle, or photoperiod, which regulates SCN activity, varies seasonally, and the shorter photoperiod winter season is associated with elevated cortisol levels, peak inflammatory disease incidence, and symptom exacerbation. Elevated expression and activity of 11β-HSD1 protein, assumed to also occur during the winter, have been allied with numerous inflammatory conditions. A comprehensive understanding of the communication between the underlying regulatory mechanisms of cortisol as well as how changes in their activity could lead to the development of disease is yet to be elucidated. In this work, we propose the use of a semimechanistic mathematical model to explore the impact of the hepato-hypothalamic-pituitary-adrenal-renal axis in modulating neuroendocrine-immune system dynamics. Our model predicts the predominance of a winter proinflammatory state and that genetic variations could alter 11β-HSD enzyme functionality, rendering certain subpopulations more susceptible to disease as a consequence of HPA axis dysregulation.

Common Marmosets: A Potential Translational Animal Model of Juvenile Depression

Major depression is a psychiatric disorder with high prevalence in the general population, with increasing expression in adolescence, about 14% in young people. Frequently, it presents as a chronic condition, showing no remission even after several pharmacological treatments and persisting in adult life. Therefore, distinct protocols and animal models have been developed to increase the understanding of this disease or search for new therapies. To this end, this study investigated the effects of chronic social isolation and the potential antidepressant action of nortriptyline in juvenile Callithrix jacchus males and females by monitoring fecal cortisol, body weight, and behavioral parameters and searching for biomarkers and a protocol for inducing depression. The purpose was to validate this species and protocol as a translational model of juvenile depression, addressing all domain criteria of validation: etiologic, face, functional, predictive, inter-relational, evolutionary, and population. In both sexes and both protocols (IDS and DPT), we observed a significant reduction in cortisol levels in the last phase of social isolation, concomitant with increases in autogrooming, stereotyped and anxiety behaviors, and the presence of anhedonia. The alterations induced by chronic social isolation are characteristic of the depressive state in non-human primates and/or in humans, and were reversed in large part by treatment with an antidepressant drug (nortriptyline). Therefore, these results indicate C. jacchus as a potential translational model of juvenile depression by addressing all criteria of validation.

The implications of war captivity and long-term psychopathology trajectories for telomere length

BACKGROUND

Previous findings have demonstrated the link between trauma, its psychopathological aftermath and cellular aging, as reflected in telomere length. However, as long-term examinations of psychopathology following trauma are scarce, very little is known regarding the repercussions of depression and PTSD trajectories of psychopathology for telomeres. The current study examined the implications of war captivity and depression/PTSD trajectories on telomere length.

METHODS

Ninety-nine former prisoners of war (ex-POWs) from the 1973 Yom Kippur War were evaluated for depression and PTSD at 18, 30, 35 and 42 years after the war. Data on leukocyte telomere length of ex-POWs and 79 controls was collected 42 years after the war.

RESULTS

Ex-POWs had shorter telomeres compared to controls (Cohen's d=.5 indicating intermediate effect). Ex-POWs with chronic depression had shorter telomeres compared to those with delayed onset of depression (Cohen's d=4.89), and resilient ex-POWs (Cohen's d= 3.87), indicating high effect sizes. PTSD trajectories were not implicated in telomere length (Partial eta²=.16 and p=.11).

CONCLUSION

The findings suggest that the detrimental ramifications of war captivity are extensive, involving premature cellular senesces. These findings further point to the wear-and-tear effect of long-term depression, but not PTSD, on telomere length. Explanations for the findings are discussed.

Dynamic genome-scale metabolic modeling of the yeast Pichia pastoris

BACKGROUND

Pichia pastoris shows physiological advantages in producing recombinant proteins, compared to other commonly used cell factories. This yeast is mostly grown in dynamic cultivation systems, where the cell's environment is continuously changing and many variables influence process productivity. In this context, a model capable of explaining and predicting cell behavior for the rational design of bioprocesses is highly desirable. Currently, there are five genome-scale metabolic reconstructions of P. pastoris which have been used to predict extracellular cell behavior in stationary conditions.

RESULTS

In this work, we assembled a dynamic genome-scale metabolic model for glucose-limited, aerobic cultivations of Pichia pastoris. Starting from an initial model structure for batch and fed-batch cultures, we performed pre/post regression diagnostics to ensure that model parameters were identifiable, significant and sensitive. Once identified, the non-relevant ones were iteratively fixed until a priori robust modeling structures were found for each type of cultivation. Next, the robustness of these reduced structures was confirmed by calibrating the model with new datasets, where no sensitivity, identifiability or significance problems appeared in their parameters. Afterwards, the model was validated for the prediction of batch and fed-batch dynamics in the studied conditions. Lastly, the model was employed as a case study to analyze the metabolic flux distribution of a fed-batch culture and to unravel genetic and process engineering strategies to improve the production of recombinant Human Serum Albumin (HSA). Simulation of single knock-outs indicated that deviation of carbon towards cysteine and tryptophan formation improves HSA production. The deletion of methylene tetrahydrofolate dehydrogenase could increase the HSA volumetric productivity by 630%. Moreover, given specific bioprocess limitations and strain characteristics, the model suggests that implementation of a decreasing specific growth rate during the feed phase of a fed-batch culture results in a 25% increase of the volumetric productivity of the protein.

CONCLUSION

In this work, we formulated a dynamic genome scale metabolic model of Pichia pastoris that yields realistic metabolic flux distributions throughout dynamic cultivations. The model can be calibrated with experimental data to rationally propose genetic and process engineering strategies to improve the performance of a P. pastoris strain of interest.

Mathematical modeling of the circadian dynamics of the neuroendocrine-immune network in experimentally induced arthritis

The circadian dynamics of important neuroendocrine-immune mediators have been implicated in progression of rheumatoid arthritis pathophysiology, both clinically as well as in animal models. We present a mathematical model that describes the circadian interactions between mediators of the hypothalamic-pituitary-adrenal (HPA) axis and the proinflammatory cytokines. Model predictions demonstrate that chronically elevated cytokine expression results in the development of adrenal insufficiency and circadian variability in paw edema. Notably, our model also predicts that an increase in mean secretion of corticosterone (CST) after the induction of the disease is accompanied by a decrease in the amplitude of the CST oscillation. Furthermore, alterations in the phase of circadian oscillation of both cytokines and HPA axis mediators are observed. Therefore, by incorporating the circadian interactions between the neuroendocrine-immune mediators, our model is able to simulate important features of rheumatoid arthritis pathophysiology.

Onset, timing, and exposure therapy of stress disorders: mechanistic insight from a mathematical model of oscillating neuroendocrine dynamics

BACKGROUND

The hypothalamic-pituitary-adrenal (HPA) axis is a neuroendocrine system that regulates numerous physiological processes. Disruptions in the activity of the HPA axis are correlated with stress-related diseases such as post-traumatic stress disorder (PTSD) and major depressive disorder. In this paper, we characterize "normal" and "diseased" states of the HPA axis as basins of attraction of a dynamical system describing the inhibition of peptide hormones such as corticotropin-releasing hormone (CRH) and adrenocorticotropic hormone (ACTH) by circulating glucocorticoids such as cortisol (CORT).

RESULTS

In addition to including key physiological features such as ultradian oscillations in cortisol levels and self-upregulation of CRH neuron activity, our model distinguishes the relatively slow process of cortisol-mediated CRH biosynthesis from rapid trans-synaptic effects that regulate the CRH secretion process. We show that the slow component of the negative feedback allows external stress-induced reversible transitions between "normal" and "diseased" states in novel intensity-, duration-, and timing-dependent ways.

CONCLUSION

Our two-step negative feedback model suggests a mechanism whereby exposure therapy of stress disorders such as PTSD may act to normalize downstream dysregulation of the HPA axis. Our analysis provides a causative rationale for improving treatments and guiding the design of new protocols.

Dynamic transitions in a model of the hypothalamic-pituitary-adrenal axis

Dynamic properties of a nonlinear five-dimensional stoichiometric model of the hypothalamic-pituitary-adrenal (HPA) axis were systematically investigated. Conditions under which qualitative transitions between dynamic states occur are determined by independently varying the rate constants of all reactions that constitute the model. Bifurcation types were further characterized using continuation algorithms and scale factor methods. Regions of bistability and transitions through supercritical Andronov-Hopf and saddle loop bifurcations were identified. Dynamic state analysis predicts that the HPA axis operates under basal (healthy) physiological conditions close to an Andronov-Hopf bifurcation. Dynamic properties of the stress-control axis have not been characterized experimentally, but modelling suggests that the proximity to a supercritical Andronov-Hopf bifurcation can give the HPA axis both, flexibility to respond to external stimuli and adjust to new conditions and stability, i.e., the capacity to return to the original dynamic state afterwards, which is essential for maintaining homeostasis. The analysis presented here reflects the properties of a low-dimensional model that succinctly describes neurochemical transformations underlying the HPA axis. However, the model accounts correctly for a number of experimentally observed properties of the stress-response axis. We therefore regard that the presented analysis is meaningful, showing how in silico investigations can be used to guide the experimentalists in understanding how the HPA axis activity changes under chronic disease and/or specific pharmacological manipulations.