A systems model for immune cell interactions unravels the mechanism of inflammation in human skin

Dynamics of a network mediated by IL-36 and involved in the pathogenesis of psoriasis

The pathogenesis of the inflammatory, chronic, and common skin disease psoriasis involves immune cells, skin cells (keratinocytes), and the cytokines they secrete. Hyperproliferation and abnormal differentiation of keratinocytes are hallmarks of the disease. The roles of cytokines such as TNFα, IL-15, IL-17, and IL-23 in psoriasis have been studied through mathematical/computational models as well as experiments. However, the role of proinflammatory cytokine IL-36 in the onset and progression of psoriasis is still elusive. To explore the role of IL-36, we construct a network embodying indirect cell-cell interactions of a few immune and skin cells mediated by IL-36 based on existing knowledge. We also develop a mathematical model for the network and perform a global sensitivity analysis. Our results suggest that the model is most sensitive to a parameter that represents the level of cytokine IL-36. In addition, a steady-state analysis of the model suggests that an increase in the level of IL-36 could lead to the hyperproliferation of keratinocytes and, thus, psoriasis. Our analysis also highlights that the plaque formation and progression of psoriasis could occur through either a gradual or a switch-like increase in the keratinocyte population. We propose that the switch-like increase would be due to a bistable behavior of the network toward either a psoriatic or healthy state and could be used as a novel treatment strategy.

Mathematical modeling in autoimmune diseases: from theory to clinical application

The research & development (R&D) of novel therapeutic agents for the treatment of autoimmune diseases is challenged by highly complex pathogenesis and multiple etiologies of these conditions. The number of targeted therapies available on the market is limited, whereas the prevalence of autoimmune conditions in the global population continues to rise. Mathematical modeling of biological systems is an essential tool which may be applied in support of decision-making across R&D drug programs to improve the probability of success in the development of novel medicines. Over the past decades, multiple models of autoimmune diseases have been developed. Models differ in the spectra of quantitative data used in their development and mathematical methods, as well as in the level of "mechanistic granularity" chosen to describe the underlying biology. Yet, all models strive towards the same goal: to quantitatively describe various aspects of the immune response. The aim of this review was to conduct a systematic review and analysis of mathematical models of autoimmune diseases focused on the mechanistic description of the immune system, to consolidate existing quantitative knowledge on autoimmune processes, and to outline potential directions of interest for future model-based analyses. Following a systematic literature review, 38 models describing the onset, progression, and/or the effect of treatment in 13 systemic and organ-specific autoimmune conditions were identified, most models developed for inflammatory bowel disease, multiple sclerosis, and lupus (5 models each). ≥70% of the models were developed as nonlinear systems of ordinary differential equations, others - as partial differential equations, integro-differential equations, Boolean networks, or probabilistic models. Despite covering a relatively wide range of diseases, most models described the same components of the immune system, such as T-cell response, cytokine influence, or the involvement of macrophages in autoimmune processes. All models were thoroughly analyzed with an emphasis on assumptions, limitations, and their potential applications in the development of novel medicines.

Diffusive mediator feedbacks control the health-to-disease transition of skin inflammation

The spatiotemporal dynamics of inflammation provide vital insights into the understanding of skin inflammation. Skin inflammation primarily depends on the regulatory feedback between pro- and anti-inflammatory mediators. Healthy skin exhibits fading erythema. In contrast, diseased skin exhibits expanding erythema with diverse patterns, which are clinically classified into five types: circular, annular, arcuate, gyrate, and polycyclic. Inflammatory diseases with expanding erythema are speculated to result from the overproduction of pro-inflammatory mediators. However, the mechanism by which feedback selectively drives the transition from a healthy fading erythema to each of the five types of diseased expanding erythema remains unclear. This study theoretically elucidates the imbalanced production between pro- and anti-inflammatory mediators and prospective treatment strategies for each expanding pattern. Our literature survey showed that eleven diseases exhibit some of the five expanding erythema, thereby suggesting a common spatiotemporal regulation underlying different patterns and diseases. Accordingly, a reaction-diffusion model incorporating mediator feedback reproduced the five observed types of diseased expanding and healthy fading patterns. Importantly, the fading pattern transitioned to the arcuate, gyrate, and polycyclic patterns when the productions of anti-inflammatory and pro-inflammatory mediators were lower and higher, respectively than in the healthy condition. Further depletion of anti-inflammatory mediators caused a circular pattern, whereas further overproduction of pro-inflammatory mediators caused an annular pattern. Mechanistically, the bistability due to stabilization of the diseased state exhibits circular and annular patterns, whereas the excitability exhibits the gyrate, polycyclic, arcuate, and fading patterns as the threshold of pro-inflammatory mediator concentration relative to the healthy state increases. These dynamic regulations of diffusive mediator feedback provide effective treatment strategies for mediator production wherein skins recover from each expanding pattern toward a fading pattern. Thus, these strategies can estimate disease severity and risk based on erythema patterns, paving the way for developing noninvasive and personalized treatments for inflammatory skin diseases.

Immunity-on-a-Chip: Integration of Immune Components into the Scheme of Organ-on-a-Chip Systems

Studying the immune system in vitro aims to understand how, when, and where the immune cells migrate/differentiate and respond to the various triggering events and the decision points along the immune response journey. It becomes evident that organ-on-a-chip (OOC) technology has a superior capability to recapitulate the cell-cell and tissue-tissue interaction in the body, with a great potential to provide tools for tracking the paracrine signaling with high spatial-temporal precision and implementing in situ real-time, non-destructive detection assays, therefore, enabling extraction of mechanistic information rather than phenotypic information. However, despite the rapid development in this technology, integration of the immune system into OOC devices stays among the least navigated tasks, with immune cells still the major missing components in the developed models. This is mainly due to the complexity of the immune system and the reductionist methodology of the OOC modules. Dedicated research in this field is demanded to establish the understanding of mechanism-based disease endotypes rather than phenotypes. Herein, we systemically present a synthesis of the state-of-the-art of immune-cantered OOC technology. We comprehensively outlined what is achieved and identified the technology gaps emphasizing the missing components required to establish immune-competent OOCs and bridge these gaps.

The effect of muscle length on post-tetanic potentiation of C57BL/6 and skMLCK-/- mouse EDL muscles

Post-tetanic potentiation of fast-twitch skeletal muscle is dependent on muscle length, with greater potentiation observed at shorter compared to longer lengths. The structural effects of the primary potentiation mechanism, phosphorylation of the regulatory light chain (RLC) of myosin, are thought to explain this relationship. The purpose of these experiments was to determine whether the length-dependence of potentiation would be attenuated in the absence of RLC phosphorylation. To this end, we compared isometric twitch potentiation of mouse extensor digitorum longus (EDL) muscles with (wildtype, WT) and without (skeletal myosin light chain kinase knockout, skMLCK^-/-) phosphorylation. Force was measured at five muscle lengths (0.90 L_o, 0.95 L_o, L_o, 1.05 L_o, 1.10 L_o, where L_o refers to optimal length) prior to and following a tetanic train. In accordance with prior findings, potentiation was dependent on muscle length, with greater values observed at short (e.g., 44.3 ± 4.6% for WT, 33.5 ± 6.2% for skMLCK^-/-, at 0.90 L_o) compared to long lengths (e.g., 16.9 ± 1.3% for WT, 9.1 ± 1.8% for skMLCK^-/-, at 1.10 L_o) in both genotypes. WT muscles displayed greater potentiation compared to their skMLCK^-/- counterparts across lengths (e.g., 16.9 ± 1.6% vs 7.3 ± 1.5% at L_o). However, the relationship between potentiation and muscle length was not different between genotypes. Thus, the alternative mechanisms of potentiation, present in the skMLCK^-/- EDL, display a length-dependence of post-tetanic potentiation similar to RLC phosphorylation-dominant potentiation. Additional mechanisms may be required to explain the length-dependence of potentiation.

Traveling wave of inflammatory response to regulate the expansion or shrinkage of skin erythema

Many skin diseases show circular red lesions on the skin, called erythema. Erythema is characterized by the expansion of its circular area solely from local stimulation. A pathological inflammatory response caused by the stimulation persistently increases inflammatory mediators in the dermis, whereas a normal inflammatory response transiently increases mediators, resulting in the shrinkage of the erythema. Although the diffusion of mediators theoretically reproduces the expansion, how the inflammatory response expands or shrinks the erythema remains unknown. A possibility is positive feedback, which affects mediator production and can generate two distinct stable states (i.e., inflamed and noninflamed), referred to as bistability. Bistability causes a state transition either from the noninflamed to inflamed state or the reverse direction by suprathreshold stimulation. Additionally, the diffusion selectively causes state transition in either direction, resulting in spatial spread of the transited state, known as the traveling wave. Therefore, we hypothesize that the traveling wave of the inflammatory response can account for both the expansion and shrinkage. Using a reaction-diffusion model with bistability, we theoretically show a possible mechanism in which the circular inflamed area expands via the traveling wave from the noninflamed to the inflamed state. During the expansion, the boundary between the inflamed and noninflamed areas moves at a constant velocity while maintaining its concentration gradient. Moreover, when the positive feedback is weak, the traveling wave selectively occurs from the inflamed to noninflamed state, shrinking the inflamed area. Whether the inflamed area expands or shrinks is mainly controlled by the balance of mediator concentration between the noninflamed and inflamed states, relative to the threshold. The traveling wave of the inflammatory response provides an experimentally testable framework for erythema expansion and shrinkage, thereby contributing to the development of effective treatments, including probiotics.

Role of subnetworks mediated by [Formula: see text], IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis

Psoriasis is a chronic inflammatory skin disease clinically characterized by the appearance of red colored, well-demarcated plaques with thickened skin and with silvery scales. Recent studies have established the involvement of a complex signalling network of interactions between cytokines, immune cells and skin cells called keratinocytes. Keratinocytes form the cells of the outermost layer of the skin (epidermis). Visible plaques in psoriasis are developed due to the fast proliferation and unusual differentiation of keratinocyte cells. Despite that, the exact mechanism of the appearance of these plaques in the cytokine-immune cell network is not clear. A mathematical model embodying interactions between key immune cells believed to be involved in psoriasis, keratinocytes and relevant cytokines has been developed. The complex network formed of these interactions poses several challenges. Here, we choose to study subnetworks of this complex network and initially focus on interactions involving [Formula: see text], IL-23/IL-17, and IL-15. These are chosen based on known evidence of their therapeutic efficacy. In addition, we explore the role of IL-15 in the pathogenesis of psoriasis and its potential as a future drug target for a novel treatment option. We perform steady state analyses for these subnetworks and demonstrate that the interactions between cells, driven by cytokines could cause the emergence of a psoriasis state (hyper-proliferation of keratinocytes) when levels of [Formula: see text], IL-23/IL-17 or IL-15 are increased. The model results explain and support the clinical potentiality of anti-cytokine treatments. Interestingly, our results suggest different dynamic scenarios underpin the pathogenesis of psoriasis, depending upon the dominant cytokines of subnetworks. We observed that the increase in the level of IL-23/IL-17 and IL-15 could lead to psoriasis via a bistable route, whereas an increase in the level of [Formula: see text] would lead to a monotonic and gradual disease progression. Further, we demonstrate how this insight, bistability, could be exploited to improve the current therapies and develop novel treatment strategies for psoriasis.

ImmunoGlobe: enabling systems immunology with a manually curated intercellular immune interaction network

BACKGROUND

While technological advances have made it possible to profile the immune system at high resolution, translating high-throughput data into knowledge of immune mechanisms has been challenged by the complexity of the interactions underlying immune processes. Tools to explore the immune network are critical for better understanding the multi-layered processes that underlie immune function and dysfunction, but require a standardized network map of immune interactions. To facilitate this we have developed ImmunoGlobe, a manually curated intercellular immune interaction network extracted from Janeway's Immunobiology textbook.

RESULTS

ImmunoGlobe is the first graphical representation of the immune interactome, and is comprised of 253 immune system components and 1112 unique immune interactions with detailed functional and characteristic annotations. Analysis of this network shows that it recapitulates known features of the human immune system and can be used uncover novel multi-step immune pathways, examine species-specific differences in immune processes, and predict the response of immune cells to stimuli. ImmunoGlobe is publicly available through a user-friendly interface at www.immunoglobe.org and can be downloaded as a computable graph and network table.

CONCLUSION

While the fields of proteomics and genomics have long benefited from network analysis tools, no such tool yet exists for immunology. ImmunoGlobe provides a ground truth immune interaction network upon which such tools can be built. These tools will allow us to predict the outcome of complex immune interactions, providing mechanistic insight that allows us to precisely modulate immune responses in health and disease.

Monitoring transient cell-to-cell interactions in a multi-layered and multi-functional allergy-on-a-chip system

We have developed a highly integrated lab-on-a-chip containing embedded electrical microsensors, μdegassers and pneumatically-actuated micropumps to monitor allergic hypersensitivity. Rapid antigen-mediated histamine release (e.g. s to min) and resulting muscle contraction (<30 min) is detected by connecting an immune compartment containing sensitized basophile cells to a vascular co-culture model.

Integrating Immunology and Microfluidics for Single Immune Cell Analysis

The field of immunoengineering aims to develop novel therapies and modern vaccines to manipulate and modulate the immune system and applies innovative technologies toward improved understanding of the immune system in health and disease. Microfluidics has proven to be an excellent technology for analytics in biology and chemistry. From simple microsystem chips to complex microfluidic designs, these platforms have witnessed an immense growth over the last decades with frequent emergence of new designs. Microfluidics provides a highly robust and precise tool which led to its widespread application in single-cell analysis of immune cells. Single-cell analysis allows scientists to account for the heterogeneous behavior of immune cells which often gets overshadowed when conventional bulk study methods are used. Application of single-cell analysis using microfluidics has facilitated the identification of several novel functional immune cell subsets, quantification of signaling molecules, and understanding of cellular communication and signaling pathways. Single-cell analysis research in combination with microfluidics has paved the way for the development of novel therapies, point-of-care diagnostics, and even more complex microfluidic platforms that aid in creating in vitro cellular microenvironments for applications in drug and toxicity screening. In this review, we provide a comprehensive overview on the integration of microsystems and microfluidics with immunology and focus on different designs developed to decode single immune cell behavior and cellular communication. We have categorized the microfluidic designs in three specific categories: microfluidic chips with cell traps, valve-based microfluidics, and droplet microfluidics that have facilitated the ongoing research in the field of immunology at single-cell level.

Modeling Procedures

Being concerned by the understanding of the mechanism underlying chronic degenerative diseases , we presented in the previous chapter the medical systems biology conceptual framework that we present for that purpose in this volume. More specifically, we argued there the clear advantages offered by a state-space perspective when applied to the systems-level description of the biomolecular machinery that regulates complex degenerative diseases. We also discussed the importance of the dynamical interplay between the risk factors and the network of interdependencies that characterizes the biochemical, cellular, and tissue-level biomolecular reactions that underlie the physiological processes in health and disease. As we pointed out in the previous chapter, the understanding of this interplay (articulated around cellular phenotypic plasticity properties, regulated by specific kinds of gene regulatory networks) is necessary if prevention is chosen as the human-health improvement strategy (potentially involving the modulation of the patient's lifestyle). In this chapter we provide the medical systems biology mathematical and computational modeling tools required for this task.

The competitive nature of signal transducer and activator of transcription complex formation drives phenotype switching of T cells

Signal transducers and activators of transcription (STATs) are key molecular determinants of T-cell fate and effector function. Several inflammatory diseases are characterized by an altered balance of T-cell phenotypes and cytokine secretion. STATs, therefore, represent viable therapeutic targets in numerous pathologies. However, the underlying mechanisms by which the same STAT proteins regulate both the development of different T-cell phenotypes and their plasticity during changes in extracellular conditions remain unclear. In this study, we investigated the STAT-mediated regulation of T-cell phenotype formation and plasticity using mathematical modelling and experimental data for intracellular STAT signalling proteins. The close fit of our model predictions to the experimental data allows us to propose a potential mechanism for T-cell switching. According to this mechanism, T-cell phenotype switching is the result of the relative redistribution of STAT dimer complexes caused by the extracellular cytokine-dependent STAT competition effects. The developed model predicts that the balance between the intracellular STAT species defines the amount of the produced cytokines and thereby T-cell phenotypes. The model predictions are consistent with the experimentally observed interferon-γ to interleukin-10 switching that regulates human T helper type 1/type 1 regulatory T-cell responses. The proposed model is applicable to a number of STAT signalling circuits.

Serum and cerebrospinal fluid immune mediators in children with autistic disorder: a longitudinal study

BACKGROUND

The causes of autism likely involve genetic and environmental factors that influence neurobiological changes and the neurological and behavioral features of the disorder. Immune factors and inflammation are hypothesized pathogenic influences, but have not been examined longitudinally.

METHODS

In a cohort of 104 participants with autism, we performed an assessment of immune mediators such as cytokines, chemokines, or growth factors in serum and cerebrospinal fluid (n = 67) to determine potential influences of such mediators in autism.

RESULTS

As compared with 54 typically developing controls, we found no evidence of differences in the blood profile of immune mediators supportive of active systemic inflammation mechanisms in participants with autism. Some modulators of immune function (e.g., EGF and soluble CD40 ligand) were increased in the autism group; however, no evidence of group differences in traditional markers of active inflammation (e.g., IL-6, TNFα, IL-1β) were observed in the serum. Further, within-subject stability (measured by estimated intraclass correlations) of most analytes was low, indicating that a single measurement is not a reliable prospective indicator of concentration for most analytes. Additionally, in participants with autism, there was little correspondence between the blood and CSF profiles of cytokines, chemokines, and growth factors, suggesting that peripheral markers may not optimally reflect the immune status of the central nervous system. Although the relatively high fraction of intrathecal production of selected chemokines involved in monocyte/microglia function may suggest a possible relationship with the homeostatic role of microglia, control data are needed for further interpretation of its relevance in autism.

CONCLUSIONS

These longitudinal observations fail to provide support for the hypothesized role of disturbances in the expression of circulating cytokines and chemokines as an indicator of systemic inflammation in autism. ClinicalTrials.gov, NCT00298246.

Computational modeling of cytokine signaling in microglia

Neuroinflammation due to glial activation has been linked to many CNS diseases. We developed a computational model of a microglial cytokine interaction network to study the regulatory mechanisms of microglia-mediated neuroinflammation. We established a literature-based cytokine network, including TNFα, TGFβ, and IL-10, and fitted a mathematical model to published data from LPS-treated microglia. The addition of a previously unreported TGFβ autoregulation loop to our model was required to account for experimental data. Global sensitivity analysis revealed that TGFβ- and IL-10-mediated inhibition of TNFα was critical for regulating network behavior. We assessed the sensitivity of the LPS-induced TNFα response profile to the initial TGFβ and IL-10 levels. The analysis showed two relatively shifted TNFα response profiles within separate domains of initial condition space. Further analysis revealed that TNFα exhibited adaptation to sustained LPS stimulation. We simulated the effects of functionally inhibiting TGFβ and IL-10 on TNFα adaptation. Our analysis showed that TGFβ and IL-10 knockouts (TGFβ KO and IL-10 KO) exert divergent effects on adaptation. TFGβ KO attenuated TNFα adaptation whereas IL-10 KO enhanced TNFα adaptation. We experimentally tested the hypothesis that IL-10 KO enhances TNFα adaptation in murine macrophages and found supporting evidence. These opposing effects could be explained by differential kinetics of negative feedback. Inhibition of IL-10 reduced early negative feedback that results in enhanced TNFα-mediated TGFβ expression. We propose that differential kinetics in parallel negative feedback loops constitute a novel mechanism underlying the complex and non-intuitive pro- versus anti-inflammatory effects of individual cytokine perturbations.

Current knowledge on psoriasis and autoimmune diseases

Psoriasis is a prevalent, chronic inflammatory disease of the skin, mediated by crosstalk between epidermal keratinocytes, dermal vascular cells, and immunocytes such as antigen presenting cells (APCs) and T cells. Exclusive cellular “responsibility” for the induction and maintenance of psoriatic plaques has not been clearly defined. Increased proliferation of keratinocytes and endothelial cells in conjunction with APC/T cell/monocyte/macrophage inflammation leads to the distinct epidermal and vascular hyperplasia that is characteristic of lesional psoriatic skin. Despite the identification of numerous susceptibility loci, no single genetic determinant has been identified as responsible for the induction of psoriasis. Thus, numerous other triggers of disease, such as environmental, microbial and complex cellular interactions must also be considered as participants in the development of this multifactorial disease. Recent advances in therapeutics, especially systemic so-called “biologics” have provided new hope for identifying the critical cellular targets that drive psoriasis pathogenesis. Recent recognition of the numerous co-morbidities and other autoimmune disorders associated with psoriasis, including inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, and systemic lupus erythematosus suggest common signaling elements and cellular mediators may direct disease pathogenesis. In this review, we discuss common cellular pathways and participants that mediate psoriasis and other autoimmune disorders that share these cellular signaling pathways.

Implantable synthetic cytokine converter cells with AND-gate logic treat experimental psoriasis

Psoriasis is a chronic inflammatory skin disease characterized by a relapsing-remitting disease course and correlated with increased expression of proinflammatory cytokines, such as tumor necrosis factor (TNF) and interleukin 22 (IL22). Psoriasis is hard to treat because of the unpredictable and asymptomatic flare-up, which limits handling of skin lesions to symptomatic treatment. Synthetic biology-based gene circuits are uniquely suited for the treatment of diseases with complex dynamics, such as psoriasis, because they can autonomously couple the detection of disease biomarkers with the production of therapeutic proteins. We designed a mammalian cell synthetic cytokine converter that quantifies psoriasis-associated TNF and IL22 levels using serially linked receptor-based synthetic signaling cascades, processes the levels of these proinflammatory cytokines with AND-gate logic, and triggers the corresponding expression of therapeutic levels of the anti-inflammatory/psoriatic cytokines IL4 and IL10, which have been shown to be immunomodulatory in patients. Implants of microencapsulated cytokine converter transgenic designer cells were insensitive to simulated bacterial and viral infections as well as psoriatic-unrelated inflammation. The designer cells specifically prevented the onset of psoriatic flares, stopped acute psoriasis, improved psoriatic skin lesions and restored normal skin-tissue morphology in mice. The antipsoriatic designer cells were equally responsive to blood samples from psoriasis patients, suggesting that the synthetic cytokine converter captures the clinically relevant cytokine range. Implanted designer cells that dynamically interface with the patient's metabolism by detecting specific disease metabolites or biomarkers, processing their blood levels with synthetic circuits in real time, and coordinating immediate production and systemic delivery of protein therapeutics may advance personalized gene- and cell-based therapies.

Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is

Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way.

Regulation of Dendritic Cell Function in Inflammation

Dendritic cells (DC) are professional antigen presenting cells and link the innate and adaptive immune system. During steady state immune surveillance in skin, DC act as sentinels against commensals and invading pathogens. Under pathological skin conditions, inflammatory cytokines, secreted by surrounding keratinocytes, dermal fibroblasts, and immune cells, influence the activation and maturation of different DC populations including Langerhans cells (LC) and dermal DC. In this review we address critical differences in human DC subtypes during inflammatory settings compared to steady state. We also highlight the functional characteristics of human DC subsets in inflammatory skin environments and skin diseases including psoriasis and atopic dermatitis. Understanding the complex immunoregulatory role of distinct DC subsets in inflamed human skin will be a key element in developing novel strategies in anti-inflammatory therapy.

Cytokines in psoriasis

Psoriasis is a common inflammatory skin disease with an incompletely understood etiology. The disease is characterized by red, scaly and well-demarcated skin lesions formed by the hyperproliferation of epidermal keratinocytes. This hyperproliferation is driven by cytokines secreted by activated resident immune cells, an infiltrate of T cells, dendritic cells and cells of the innate immune system, as well as the keratinocytes themselves. Psoriasis has a strong hereditary character and has a complex genetic background. Genome-wide association studies have identified polymorphisms within or near a number of genes encoding cytokines, cytokine receptors or elements of their signal transduction pathways, further implicating these cytokines in the psoriasis pathomechanism. A considerable number of inflammatory cytokines have been shown to be elevated in lesional psoriasis skin, and the serum concentrations of a subset of these also correlate with psoriasis disease severity. The combined effects of the cytokines found in psoriasis lesions likely explain most of the clinical features of psoriasis, such as the hyperproliferation of keratinocytes, increased neovascularization and skin inflammation. Thus, understanding which cytokines play a pivotal role in the disease process can suggest potential therapeutic targets. A number of cytokines have been therapeutically targeted with success, revolutionizing treatment of this disease. Here we review a number of key cytokines implicated in the pathogenesis of psoriasis.

Cytokine expression provides clues to the pathophysiology of Gulf War illness and myalgic encephalomyelitis

Gulf War illness (GWI) is a chronic disease of unknown etiology characterized by persistent symptoms such as cognitive impairment, unexplained fatigue, pervasive pain, headaches, and gastrointestinal abnormalities. Current reports suggest that as many as 200,000 veterans who served in the 1990-1991 Persian Gulf War were afflicted. Several potential triggers of GWI have been proposed including chemical exposure, toxins, vaccines, and unknown infectious agents. However, a definitive cause of GWI has not been identified and a specific biological marker that can consistently delineate the disease has not been defined. Myalgic encephalomyelitis (ME) is a disease with similar and overlapping symptomology, and subjects diagnosed with GWI typically fit the diagnostic criteria for ME. For these reasons, GWI is often considered a subgroup of ME. To explore this possibility and identify immune parameters that may help to understand GWI pathophysiology, we measured 77 serum cytokines in subjects with GWI and compared these data to that of subjects with ME as well as healthy controls. Our analysis identified a group of cytokines that identified ME and GWI cases with sensitivities of 92.5% and 64.9%, respectively. The five most significant cytokines in decreasing order of importance were IL-7, IL-4, TNF-α, IL-13, and IL-17F. When delineating GWI and ME cases from healthy controls, the observed specificity was only 33.3%, suggesting that with respect to cytokine expression, GWI cases resemble control subjects to a greater extent than ME cases across a number of parameters. These results imply that serum cytokines are representative of ME pathology to a greater extent than GWI and further suggest that the two diseases have distinct immune profiles despite their overlapping symptomology.

Psoriasis

Psoriasis is a common chronic inflammatory skin disease with a spectrum of clinical phenotypes and results from the interplay of genetic, environmental, and immunological factors. Four decades of clinical and basic research on psoriasis have elucidated many of the pathogenic mechanisms underlying disease and paved the way to effective targeted therapies. Here, we review this progress and identify future directions of study that are supported by a more integrative research approach and aim at further improving the patients' life.

The role of low-grade inflammation and metabolic flexibility in aging and nutritional modulation thereof: a systems biology approach

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems.

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

Senescent fibroblasts in melanoma initiation and progression: an integrated theoretical, experimental, and clinical approach

We present an integrated study to understand the key role of senescent fibroblasts in driving melanoma progression. Based on the hybrid cellular automata paradigm, we developed an in silico model of normal skin. The model focuses on key cellular and microenvironmental variables that regulate interactions among keratinocytes, melanocytes, and fibroblasts, key components of the skin. The model recapitulates normal skin structure and is robust enough to withstand physical as well as biochemical perturbations. Furthermore, the model predicted the important role of the skin microenvironment in melanoma initiation and progression. Our in vitro experiments showed that dermal fibroblasts, which are an important source of growth factors in the skin, adopt a secretory phenotype that facilitates cancer cell growth and invasion when they become senescent. Our coculture experiments showed that the senescent fibroblasts promoted the growth of nontumorigenic melanoma cells and enhanced the invasion of advanced melanoma cells. Motivated by these experimental results, we incorporated senescent fibroblasts into our model and showed that senescent fibroblasts transform the skin microenvironment and subsequently change the skin architecture by enhancing the growth and invasion of normal melanocytes. The interaction between senescent fibroblasts and the early-stage melanoma cells leads to melanoma initiation and progression. Of microenvironmental factors that senescent fibroblasts produce, proteases are shown to be one of the key contributing factors that promoted melanoma development from our simulations. Although not a direct validation, we also observed increased proteolytic activity in stromal fields adjacent to melanoma lesions in human histology. This leads us to the conclusion that senescent fibroblasts may create a prooncogenic skin microenvironment that cooperates with mutant melanocytes to drive melanoma initiation and progression and should therefore be considered as a potential future therapeutic target. Interestingly, our simulations to test the effects of a stroma-targeting therapy that negates the influence of proteolytic activity showed that the treatment could be effective in delaying melanoma initiation and progression.

Risk factor-dependent dynamics of atopic dermatitis: modelling multi-scale regulation of epithelium homeostasis

Epithelial tissue provides the body with its first layer of protection against harmful environmental stimuli by enacting the regulatory interplay between a physical barrier preventing the influx of external stimuli and an inflammatory response to the infiltrating stimuli. Importantly, this interdependent regulation occurs on different time scales: the tissue-level barrier permeability is regulated over the course of hours, whereas the cellular-level enzymatic reactions leading to inflammation take place within minutes. This multi-scale regulation is key to the epithelium's function and its dysfunction leads to various diseases. This paper presents a mathematical model of regulatory mechanisms in the epidermal epithelium that includes processes on two different time scales at the cellular and tissue levels. We use this model to investigate the essential regulatory interactions between epidermal barrier integrity and skin inflammation and how their dysfunction leads to atopic dermatitis (AD). Our model exhibits a structure of dual (positive and negative) control at both cellular and tissue levels. We also determined how the variation induced by well-known risk factors for AD can break the balance of the dual control. Our model analysis based on time-scale separation suggests that each risk factor leads to qualitatively different dynamic behaviours of different severity for AD, and that the coincidence of multiple risk factors dramatically increases the fragility of the epithelium's function. The proposed mathematical framework should also be applicable to other inflammatory diseases that have similar time-scale separation and control architectures.

Systems approaches to computational modeling of the oral microbiome

Current microbiome research has generated tremendous amounts of data providing snapshots of molecular activity in a variety of organisms, environments, and cell types. However, turning this knowledge into whole system level of understanding on pathways and processes has proven to be a challenging task. In this review we highlight the applicability of bioinformatics and visualization techniques to large collections of data in order to better understand the information that contains related diet—oral microbiome—host mucosal transcriptome interactions. In particular, we focus on systems biology of Porphyromonas gingivalis in the context of high throughput computational methods tightly integrated with translational systems medicine. Those approaches have applications for both basic research, where we can direct specific laboratory experiments in model organisms and cell cultures, and human disease, where we can validate new mechanisms and biomarkers for prevention and treatment of chronic disorders.

A mechanism for controlled access to GWAS data: experience of the GAIN Data Access Committee

The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.

Altered AKT1 and MAPK1 gene expression on peripheral blood mononuclear cells and correlation with T-helper-transcription factors in systemic lupus erythematosus patients

Kinases have been implicated in the immunopathological mechanisms of Systemic Lupus Erythematosus (SLE). v-akt murine-thymoma viral-oncogene-homolog 1 (AKT1) and mitogen-activated-protein-kinase 1 (MAPK1) gene expressions in peripheral mononuclear cells from thirteen SLE patients with inactive or mild disease were evaluated using quantitative real-time reverse-transcription polymerase-chain-reaction and analyzed whether there was any correlation with T-helper (Th) transcription factors (TF) gene expression, cytokines, and S100A8/S100A9-(Calprotectin). Age- and gender-matched thirteen healthy controls were examined. AKT1 and MAPK1 expressions were upregulated in SLE patients and correlated with Th17-(Retinoic acid-related orphan receptor (ROR)-C), T-regulatory-(Treg)-(Transforming Growth Factor Beta (TGFB)-2), and Th2-(interleukin (IL)-5)-related genes. MAPK1 expression correlated with Th1-(IL-12A, T-box TF-(T-bet)), Th2-(GATA binding protein-(GATA)-3), and IL-10 expressions. IL-10 expression was increased and correlated with plasma Tumor Necrosis Factor (TNF)-α and Th0-(IL-2), Th1-(IL-12A, T-bet), GATA3, Treg-(Forkhead/winged-helix transcription factor- (FOXP)-3), and IL-6 expressions. FOXP3 expression, FOXP3/RORC, and FOXP3/GATA3 expression ratios were increased. Plasma IL-1β, IL-12(p70), Interferon-(IFN)-γ, and IL-6 cytokines were augmented. Plasma IL-1β, IL-6, IL-2, IFN-γ, TNF-α, IL-10, and IL-13 correlated with C-reactive protein, respectively. Increased Calprotectin correlated with neutrophils. Conclusion, SLE patients presented a systemic immunoinflammatory activity, augmented AKT1 and MAPK1 expressions, proinflammatory cytokines, and Calprotectin, together with increased expression of Treg-related genes, suggesting a regulatory feedback opposing the inflammatory activity.

Transcriptome classification reveals molecular subtypes in psoriasis

BACKGROUND

Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes.

RESULTS

We present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed.

CONCLUSION

Overall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.

Cutaneous microdialysis: cytokine evidence for altered innate reactivity in the skin of psoriasis patients?

Cutaneous microdialysis demonstrates cytokine production in living human skin. In the present study, microdialysis samples taken from uninvolved and lesional skin in three test subjects with psoriasis over 24 h have been investigated for cytokine content with a bead-based multiplex immunoassay from Luminex. Concentration curves for a set of Th1/Th2 and pro-inflammatory cytokines measured differed from a reference group of ten subjects without psoriasis. The time to return to near baseline values after innate insertion reactivity is between 9 and 16 h. Post-equilibration levels (17-24 h) for the three main cytokines elevated in the reference group were differentially elevated outside the range of the reference group for interleukin-1β (IL1β) and IL8 but not so for IL6. Two further cytokines, granulocyte-macrophage colony-stimulating factor and tumor necrosis factor-α not generally elevated in the reference group, showed elevated values in the test subjects. Multivariate time series analysis (chemometry) showed that cytokine patterns for the individual test subjects often fell outside the 99% confidence intervals of a model generated from the reference group. In a clinical research situation, cutaneous microdialysis is feasible, gives generally higher cytokine levels than in the blood and generates interpretable data on an individual's reactivity compared with a reference group. This may well prove useful in delineation of pathogenetic issues, selection of appropriate therapy and monitoring of subsequent response in inflammatory dermatoses such as psoriasis.

The multitasking organ: recent insights into skin immune function

The skin provides the first line defense of the human body against injury and infection. By integrating recent findings in cutaneous immunology with fundamental concepts of skin biology, we portray the skin as a multitasking organ ensuring body homeostasis. Crosstalk between the skin and its microbial environment is also highlighted as influencing the response to injury, infection, and autoimmunity. The importance of the skin immune network is emphasized by the identification of several skin-resident cell subsets, each with its unique functions. Lessons learned from targeted therapy in inflammatory skin conditions, such as psoriasis, provide further insights into skin immune function. Finally, we look at the skin as an interacting network of immune signaling pathways exemplified by the development of a disease interactome for psoriasis.

Reducing systems biology to practice in pharmaceutical company research; selected case studies

Reviews of the productivity of the pharmaceutical industry have concluded that the current business model is unsustainable. Various remedies for this have been proposed, however, arguably these do not directly address the fundamental issue; namely, that it is the knowledge required to enable good decisions in the process of delivering a drug that is largely absent; in turn, this leads to a disconnect between our intuition of what the right drug target is and the reality of pharmacological intervention in a system such as a human disease state. As this system is highly complex, modelling will be required to elucidate emergent properties together with the data necessary to construct such models. Currently, however, both the models and data available are limited. The ultimate solution to the problem of pharmaceutical productivity may be the virtual human, however, it is likely to be many years, if at all, before this goal is realised. The current challenge is, therefore, whether systems modelling can contribute to improving productivity in the pharmaceutical industry in the interim and help to guide the optimal route to the virtual human. In this context, this chapter discusses the emergence of systems pharmacology in drug discovery from the interface of pharmacokinetic-pharmacodynamic modelling and systems biology. Examples of applications to the identification of optimal drug targets in given pathways, selecting drug modalities and defining biomarkers are discussed, together with future directions.

Computational modelling elucidates the mechanism of ciliary regulation in health and disease

Background

Ciliary dysfunction leads to a number of human pathologies, including primary ciliary dyskinesia, nephronophthisis, situs inversus pathology or infertility. The mechanism of cilia beating regulation is complex and despite extensive experimental characterization remains poorly understood. We develop a detailed systems model for calcium, membrane potential and cyclic nucleotide-dependent ciliary motility regulation.

Results

The model describes the intimate relationship between calcium and potassium ionic concentrations inside and outside of cilia with membrane voltage and, for the first time, describes a novel type of ciliary excitability which plays the major role in ciliary movement regulation. Our model describes a mechanism that allows ciliary excitation to be robust over a wide physiological range of extracellular ionic concentrations. The model predicts the existence of several dynamic modes of ciliary regulation, such as the generation of intraciliary Ca²⁺ spike with amplitude proportional to the degree of membrane depolarization, the ability to maintain stable oscillations, monostable multivibrator regimes, all of which are initiated by variability in ionic concentrations that translate into altered membrane voltage.

Conclusions

Computational investigation of the model offers several new insights into the underlying molecular mechanisms of ciliary pathologies. According to our analysis, the reported dynamic regulatory modes can be a physiological reaction to alterations in the extracellular environment. However, modification of the dynamic modes, as a result of genetic mutations or environmental conditions, can cause a life threatening pathology.