A computational analysis of dynamic, multi-organ inflammatory crosstalk induced by endotoxin in mice.

Bacterial lipopolysaccharide (LPS) induces an acute inflammatory response across multiple organs, primarily via Toll-like receptor 4 (TLR4). We sought to define novel aspects of the complex spatiotemporal dynamics of LPS-induced inflammation using computational modeling, with a special focus on the timing of pathological systemic spillover. An analysis of principal drivers of LPS-induced inflammation in the heart, gut, lung, liver, spleen, and kidney to assess organ-specific dynamics, as well as in the plasma (as an assessment of systemic spillover), was carried out using data on 20 protein-level inflammatory mediators measured over 0-48h in both C57BL/6 and TLR4-null mice. Using a suite of computational techniques, including a time-interval variant of Principal Component Analysis, we confirm key roles for cytokines such as tumor necrosis factor-α and interleukin-17A, define a temporal hierarchy of organ-localized inflammation, and infer the point at which organ-localized inflammation spills over systemically. Thus, by employing a systems biology approach, we obtain a novel perspective on the time- and organ-specific components in the propagation of acute systemic inflammation.

Data-Driven Modeling for Precision Medicine in Pediatric Acute Liver Failure.

Absence of early outcome biomarkers for Pediatric Acute Liver Failure (PALF) hinders medical and liver transplant decisions. We sought to define dynamic interactions among circulating inflammatory mediators to gain insights into PALF outcome sub-groups. Serum samples from 101 participants in the PALF study, collected over the first 7 days following enrollment, were assayed for 27 inflammatory mediators. Outcomes (Spontaneous survivors [S, n=61], Non-survivors [NS, n=12], and liver transplant patients [LTx, n=28]) were assessed at 21 days post-enrollment. Dynamic interrelations among mediators were defined using data-driven algorithms. Dynamic Bayesian Network inference identified a common network motif with HMGB1 as a central node in all patient sub-groups. The networks in S and LTx were similar, and differed from NS. Dynamic Network Analysis suggested similar dynamic connectivity in S and LTx, but a more highly-interconnected network in NS that increased with time. A Dynamic Robustness Index calculated to quantify how inflammatory network connectivity changes as a function of correlation stringency differentiated all three patient sub-groups. Our results suggest that increasing inflammatory network connectivity is associated with non-survival in PALF, and may ultimately lead to better patient outcome stratification.

Temporal Patterns of Circulating Inflammation Biomarker Networks Differentiate Susceptibility to Nosocomial Infection Following Blunt Trauma in Humans.

BACKGROUND: Severe traumatic injury can lead to immune dysfunction that renders trauma patients susceptible to nosocomial infections (NI) and prolonged intensive care unit (ICU) stays. We hypothesized that early circulating biomarker patterns following trauma would correlate with sustained immune dysregulation associated with NI and remote organ failure. METHODS: In a cohort of 472 blunt trauma survivors studied over an 8-year period, 127 patients (27%) were diagnosed with NI versus 345 trauma patients without NI. To perform a pairwise, case-control study with 1:1 matching, 44 of the NI patients were compared with 44 no-NI trauma patients selected by matching patient demographics and injury characteristics. Plasma obtained upon admission and over time were assayed for 26 inflammatory mediators and analyzed for the presence of dynamic networks. RESULTS: Significant differences in ICU length of stay (LOS), hospital LOS, and days on mechanical ventilation were observed in the NI patients versus no-NI patients. Although NI was not detected until day 7, multiple mediators were significantly elevated within the first 24 hours in patients who developed NI. Circulating inflammation biomarkers exhibited 4 distinct dynamic patterns, of which 2 clearly distinguish patients destined to develop NI from those who did not. Mediator network connectivity analysis revealed a higher, coordinated degree of activation of both innate and lymphoid pathways in the NI patients over the initial 24 hours. CONCLUSIONS: These studies implicate unique dynamic immune responses, reflected in circulating biomarkers that differentiate patients prone to persistent critical illness and infections following injury, independent of mechanism of injury, injury severity, age, or sex.

Computational Analysis Supports an Early, Type 17 Cell-Associated Divergence of Blunt Trauma Survival and Mortality.

OBJECTIVE: Blunt trauma patients may present with similar demographics and injury severity yet differ with regard to survival. We hypothesized that this divergence was due to different trajectories of systemic inflammation and utilized computational analyses to define these differences. DESIGN: Retrospective clinical study and experimental study in mice. SETTING: Level 1 trauma center and experimental laboratory. PATIENTS: From a cohort of 493 victims of blunt trauma, we conducted a pairwise, retrospective, case-control study of patients who survived over 24 hours but ultimately died (nonsurvivors; n = 19) and patients who, after ICU admission, went on to be discharged(survivors; n = 19). INTERVENTIONS: None in patients. Neutralizing anti-interleukin-17A antibody in mice. MEASUREMENTS AND MAIN RESULTS: Data on systemic inflammatory mediators assessed within the first 24 hours and over 7 days were analyzed with computational modeling to infer dynamic networks of inflammation. Network density among inflammatory mediators in nonsurvivors increased in parallel with organ dysfunction scores over 7 days, suggesting the presence of early, self-sustaining, pathologic inflammation involving high-mobility group protein B1, interleukin-23, and the Th17 pathway. Survivors demonstrated a pattern commensurate with a self-resolving, predominantly lymphoid response, including higher levels of the reparative cytokine interleukin-22. Mice subjected to trauma/hemorrhage exhibited reduced organ damage when treated with anti-interleukin-17A. CONCLUSIONS: Variable type 17 immune responses are hallmarks of organ damage, survival, and mortality after blunt trauma and suggest a lymphoid cell-based switch from self-resolving to self-sustaining inflammation.

Injury-induced MRP8/MRP14 stimulates IP-10/CXCL10 in monocytes/macrophages.

Trauma/hemorrhagic shock is associated with morbidity and mortality due to dysregulated inflammation, which is driven in part by monocytes/macrophages stimulated by injury-induced release of damage-associated molecular pattern (DAMP) molecules. MRP8/MRP14 is an endogenous DAMP involved in various inflammatory diseases, though its mechanism of action is unclear. Circulating MRP8/MRP14 levels in human blunt trauma nonsurvivors were significantly lower than those of survivors (P < 0.001). Human monocytic THP-1 cells stimulated with MRP8/MRP14 expressed the chemokine IFN-γ inducible protein 10 (IP-10)/CXCL10. Circulating IP-10 levels in human blunt trauma patients were correlated positively with MRP8/MRP14 levels (r = 0.396, P < 0.001), and were significantly lower in trauma nonsurvivors than in survivors (P < 0.001). We therefore sought to determine the mechanisms by which MRP8/MRP14 stimulates IP-10 in monocytes/macrophages, and found that induction of IP-10 by MRP8/MRP14 required Toll-like receptor 4 and TRIF but not MyD88. Full induction of IP-10 by MRP8/MRP14 required synergy between the transcription factors NF-κB and IFN regulatory factor 3 (IRF3). The receptor for IP-10 is CXCR3, and MRP8/MRP14-induced chemotaxis of CXCR3(+) cells was dependent on the production of IP-10 in monocytes/macrophages. Furthermore, in vivo study with a mouse trauma/hemorrhagic shock model showed that administration of neutralizing antibody against MRP8 prevented activation of NF-κB and IRF3 as well as IP-10 production. Thus, the current study identified a novel signaling mechanism that controls IP-10 expression in monocytes/macrophages by MRP8/MRP14, which may play an important role in injury-induced inflammation.

Implications of an Altered Gut Microbiome in Rat Experimental Vascularized Composite Transplantation.

OBJECTIVES: Vascularized composite allotransplantation is a reconstructive option after severe injury but is fraught with complications, including transplant rejection due to major histocompatibility complex mismatch in the context of allogeneic transplant, which in turn is due to altered immuno-inflammation secondary to transplant. The immunosuppressant tacrolimus can prevent rejection. Because tacrolimus is metabolized predominantly by the gut, this immunosuppressant alters the gut microbiome in multiple ways, thereby possibly affecting immunoinflammation. MATERIALS AND METHODS: We performed either allogeneic or syngeneic transplant with or without tacrolimus in rats. We quantified protein-level inflammatory mediators in the skin, muscle, and plasma and assessed the diversity of the gut microbiome through 16S RNA analysis at several timepoints over 31 days posttransplant. RESULTS: Statistical analysis highlighted a complex interaction between major histocompatibility complex and tacrolimus therapy on the relative diversity of the microbiome. Time-interval principal component analysis indicated numerous significant differences in the tissue characteristics of inflammation and gut microbiome that varied over time and across experimental conditions. Classification and regression tree analysis suggested that both inflammatory mediators in specific tissues and changes in the gut microbiome are useful in characterizing the temporal dynamics of posttransplant inflammation. Dynamic network analysis highlighted unique changes in Methanosphaera that were correlated with Peptococcusin allogeneic transplants with and without tacrolimus versus Prevotella in syngeneic transplant with tacrolimus, suggesting that alterations in Methanosphaera might be a biomarker of vascularized composite allotransplant rejection. CONCLUSIONS: Our results suggest a complex interaction among major histocompatibility complex, local and systemic immuno-inflammation, and tacrolimus therapy and highlight the potential for novel insights into vascularized composite allotransplant from computational approaches.

Unraveling the complex relationship between mRNA and protein abundances: a machine learning-based approach for imputing protein levels from RNA-seq data.

The correlation between messenger RNA (mRNA) and protein abundances has long been debated. RNA sequencing (RNA-seq), a high-throughput, commonly used method for analyzing transcriptional dynamics, leaves questions about whether we can translate RNA-seq-identified gene signatures directly to protein changes. In this study, we utilized a set of 17 widely assessed immune and wound healing mediators in the context of canine volumetric muscle loss to investigate the correlation of mRNA and protein abundances. Our data reveal an overall agreement between mRNA and protein levels on these 17 mediators when examining samples from the same experimental condition (e.g. the same biopsy). However, we observed a lack of correlation between mRNA and protein levels for individual genes under different conditions, underscoring the challenges in converting transcriptional changes into protein changes. To address this discrepancy, we developed a machine learning model to predict protein abundances from RNA-seq data, achieving high accuracy. Our approach also effectively corrected multiple extreme outliers measured by antibody-based protein assays. Additionally, this model has the potential to detect post-translational modification events, as shown by accurately estimating activated transforming growth factor ß1 levels. This study presents a promising approach for converting RNA-seq data into protein abundance and its biological significance.

Augmenter of liver regeneration (ALR) is a novel biomarker of hepatocellular stress/inflammation: in vitro, in vivo and in silico studies.

The liver is a central organ involved in inflammatory processes, including the elaboration of acute-phase proteins. Augmenter of liver regeneration (ALR) protein, expressed and secreted by hepatocytes, promotes liver regeneration and maintains viability of hepatocytes. ALR also stimulates secretion of inflammatory cytokines (tumor necrosis factor [TNF]-α and interleukin [IL]-6) and nitric oxide from Kupffer cells. We hypothesized that ALR may be involved in modulating inflammation induced by various stimuli. We found that hepatic ALR levels are elevated at 24 h, before or about the same time as an increase in the mRNA expression of TNF-α and IL-6, after portacaval shunt surgery in rats. Serum ALR also increased, but significantly only on d 4 when pathological changes in the liver become apparent. In rats, serum ALR was elevated after intraperitoneal administration of lipopolysaccharide alone and in a model of gram-negative sepsis. Serum ALR increased before alanine aminotransferase (ALT) in endotoxemia and in the same general time frame as TNF-α and IL-6 in the bacterial sepsis model. Furthermore, mathematical prediction of tissue damage correlated strongly with alterations in serum ALR in a mouse model of hemorrhagic shock. In vitro, monomethyl sulfonate, TNF-α, actinomycin D and lipopolysaccharide all caused increased release of ALR from rat hepatocytes, which preceded the loss of cell viability and/or inhibition of DNA synthesis. ALR may thus serve as a potential diagnostic marker of hepatocellular stress and/or acute inflammatory conditions.

Peripheral nerve repair is associated with augmented cross-tissue inflammation following vascularized composite allotransplantation.

Introduction: Vascularized composite allotransplantation (VCA), with nerve repair/coaptation (NR) and tacrolimus (TAC) immunosuppressive therapy, is used to repair devastating traumatic injuries but is often complicated by inflammation spanning multiple tissues. We identified the parallel upregulation of transcriptional pathways involving chemokine signaling, T-cell receptor signaling, Th17, Th1, and Th2 pathways in skin and nerve tissue in complete VCA rejection compared to baseline in 7 human hand transplants and defined increasing complexity of protein-level dynamic networks involving chemokine, Th1, and Th17 pathways as a function of rejection severity in 5 of these patients. We next hypothesized that neural mechanisms may regulate the complex spatiotemporal evolution of rejection-associated inflammation post-VCA. Methods: For mechanistic and ethical reasons, protein-level inflammatory mediators in tissues from Lewis rats (8 per group) receiving either syngeneic (Lewis) or allogeneic (Brown-Norway) orthotopic hind limb transplants in combination with TAC, with and without sciatic NR, were compared to human hand transplant samples using computational methods. Results: In cross-correlation analyses of these mediators, VCA tissues from human hand transplants (which included NR) were most similar to those from rats undergoing VCA + NR. Based on dynamic hypergraph analyses, NR following either syngeneic or allogeneic transplantation in rats was associated with greater trans-compartmental localization of early inflammatory mediators vs. no-NR, and impaired downregulation of mediators including IL-17A at later times. Discussion: Thus, NR, while considered necessary for restoring graft function, may also result in dysregulated and mis-compartmentalized inflammation post-VCA and therefore necessitate mitigation strategies. Our novel computational pipeline may also yield translational, spatiotemporal insights in other contexts.

A common single nucleotide polymorphism is associated with inflammation and critical illness outcomes.

Acute inflammation is heterogeneous in critical illness and predictive of outcome. We hypothesized that genetic variability in novel, yet common, gene variants contributes to this heterogeneity and could stratify patient outcomes. We searched algorithmically for significant differences in systemic inflammatory mediators associated with any of 551,839 SNPs in one derivation (n = 380 patients with blunt trauma) and two validation (n = 75 trauma and n = 537 non-trauma patients) cohorts. This analysis identified rs10404939 in the LYPD4 gene. Trauma patients homozygous for the A allele (rs10404939AA; 27%) had different trajectories of systemic inflammation along with persistently elevated multiple organ dysfunction (MOD) indices vs. patients homozygous for the G allele (rs10404939GG; 26%). rs10404939AA homozygotes in the trauma validation cohort had elevated MOD indices, and non-trauma patients displayed more complex inflammatory networks and worse 90-day survival compared to rs10404939GG homozygotes. Thus, rs10404939 emerged as a common, broadly prognostic SNP in critical illness.

Hemoadsorption reprograms inflammation in experimental gram-negative septic peritonitis: insights from in vivo and in silico studies.

UNLABELLED: Improper compartmentalization of the inflammatory response leads to systemic inflammation in sepsis. Hemoadsorption (HA) is an emerging approach to modulate sepsis-induced inflammation. We sought to define the effects of HA on inflammatory compartmentalization in Escherichia coli-induced fibrin peritonitis in rats. HYPOTHESIS: HA both reprograms and recompartmentalizes inflammation in sepsis. Sprague Dawley male rats were subjected to E. coli peritonitis and, after 24 h, were randomized to HA or sham treatment (sepsis alone). Venous blood samples collected at 0, 1, 3 and 6 h (that is, 24-30 h of total experimental sepsis), and peritoneal samples collected at 0 and 6 h, were assayed for 14 cytokines along with NO(2)(-/)NO(3)(-). Bacterial counts were assessed in the peritoneal fluid at 0 and 6 h. Plasma tumor necrosis factor (TNF)-α, interleukin (IL)-6, CXCL-1, and CCL2 were significantly reduced in HA versus sham. Principal component analysis (PCA) suggested that inflammation in sham was driven by IL-6 and TNF-α, whereas HA-associated inflammation was driven primarily by TNF-α, CXCL-1, IL-10 and CCL2. Whereas -peritoneal bacterial counts, plasma aspartate transaminase levels and peritoneal IL-5, IL-6, IL-18, interferon (IFN)-γ and NO(2)(-)/NO(3)(-) were significantly lower, both CXCL-1 and CCL2 as well as the peritoneal-to-plasma ratios of TNF-α, CXCL-1 and CCL2 were significantly higher in HA versus sham, suggesting that HA-induced inflammatory recompartmentalization leads to the different inflammatory drivers discerned in part by PCA. In conclusion, this study demonstrates the utility of combined in vivo/in silico methods and suggests that HA exerts differential effects on mediator gradients between local and systemic compartments that ultimately benefit the host.

A two-compartment mathematical model of endotoxin-induced inflammatory and physiologic alterations in swine.

OBJECTIVE: To gain insights into individual variations in acute inflammation and physiology. DESIGN: Large-animal study combined with mathematical modeling. SETTING: Academic large-animal and computational laboratories. SUBJECTS: Outbred juvenile swine. INTERVENTIONS: Four swine were instrumented and subjected to endotoxemia (100 µg/kg), followed by serial plasma sampling. MEASUREMENTS AND MAIN RESULTS: Swine exhibited various degrees of inflammation and acute lung injury, including one death with severe acute lung injury (PaO(2)/FIO(2) ratio µ200 and static compliance µ10 L/cm H(2)O). Plasma interleukin-1ß, interleukin-4, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-α, high mobility group box-1, and NO(2)/NO(3) were significantly (p µ .05) elevated over the course of the experiment. Principal component analysis was used to suggest principal drivers of inflammation. Based in part on principal component analysis, an ordinary differential equation model was constructed, consisting of the lung and the blood (as a surrogate for the rest of the body), in which endotoxin induces tumor necrosis factor-α in monocytes in the blood, followed by the trafficking of these cells into the lung leading to the release of high mobility group box-1, which in turn stimulates the release of interleukin-1ß from resident macrophages. The ordinary differential equation model also included blood pressure, PaO(2), and FIO(2), and a damage variable that summarizes the health of the animal. This ordinary differential equation model could be fit to both inflammatory and physiologic data in the individual swine. The predicted time course of damage could be matched to the oxygen index in three of the four swine. CONCLUSIONS: The approach described herein may aid in predicting inflammation and physiologic dysfunction in small cohorts of subjects with diverse phenotypes and outcomes.

Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling.

Trauma/hemorrhagic shock followed by resuscitation (T/HS-R) results in multi-system inflammation and organ dysfunction, in part driven by binding of damage-associated molecular pattern molecules to Toll-like Receptor 4 (TLR4). We carried out experimental T/HS-R (pseudo-fracture plus 2 h of shock followed by 0-22 h of resuscitation) in C57BL/6 (wild type [WT]) and TLR4-null (TLR4-/-) mice, and then defined the dynamics of 20 protein-level inflammatory mediators in the heart, gut, lung, liver, spleen, kidney, and systemic circulation. Cross-correlation and Principal Component Analysis (PCA) on data from the 7 tissues sampled suggested that TLR4-/- samples express multiple inflammatory mediators in a small subset of tissue compartments as compared to the WT samples, in which many inflammatory mediators were localized non-specifically to nearly all compartments. We and others have previously defined a central role for type 17 immune cells in human trauma. Accordingly, correlations between IL-17A and GM-CSF (indicative of pathogenic Th17 cells); between IL-17A and IL-10 (indicative of non-pathogenic Th17 cells); and IL-17A and TNF (indicative of memory/effector T cells) were assessed across all tissues studied. In both WT and TLR4-/- mice, positive correlations were observed between IL-17A and GM-CSF, IL-10, and TNF in the kidney and gut. In contrast, the variable and dynamic presence of both pathogenic and non-pathogenic Th17 cells was inferred in the systemic circulation of TLR4-/- mice over time, suggesting a role for TLR4 in efflux of these cells into peripheral tissues. Hypergraph analysis - used to define dynamic, cross compartment networks - in concert with PCA-suggested that IL-17A was present persistently in all tissues at all sampled time points except for its absence in the plasma at 0.5h in the WT group, supporting the hypothesis that T/HS-R induces efflux of Th17 cells from the circulation and into specific tissues. These analyses suggest a complex, context-specific role for TLR4 and type 17 immunity following T/HS-R.

Inflammatory signals and network connections implicate cell-mediated immunity in chronic venous insufficiency.

BACKGROUND: The role of inflammation in superficial venous reflux in varicose veins (VVs) is unknown. Computational network modeling has deduced inflammation in experimental and clinical settings. We measured immune mediators in plasma from competent and incompetent leg veins inferring the role of cellular immunity based on cytokine networks. METHODS: Temperature was assessed using infrared thermography (IRT) to measure inflammation. Blood was obtained during sclerotherapy or endovenous thermal ablation for VVs. Control subjects underwent phlebotomy from saphenous and forearm veins. Vein segments were harvested during surgery. Demographics, clinical, etiology, anatomy and pathophysiology classification, venous clinical severity scores (VCSSs), and body mass index (BMI) were collected. Twenty-five mediators were measured in serum and vein segments. Means were compared using Mann-Whitney U test. Pearson correlations equaling or exceeding a threshold prompted connections among nodes, and mapped as networks. Spearman correlations were performed between interleukin (IL)-17A and both granulocyte macrophage colony stimulation factor, and IL-10 as indicators of pathogenic and nonpathogenic Th17 cell involvement. RESULTS: Age, BMI, and VCSSs differed significantly between groups. Temperatures were higher over diseased veins. Plasma concentrations of 20 cytokines differed between control and patient subjects (P<0.05), and most were lower in patients. C-X-C motif chemokine ligand-9 (aka monokine-induced by gamma interferon), C-X-C motif chemokine ligand 10 (aka IFNγ induced protein 10), and soluble IL-2 receptor-alpha were higher in patients, but not connected to other mediators in networks. In contrast, IL-17A, IL-12p70, and interferon gamma were the only mediators that were more highly interconnected in venous insufficiency. IL-17A and granulocyte macrophage colony stimulating factor (GM-CSF) were highly correlated in chronic venous insufficiency (CVI) but not in controls. In tissue, refluxing VVs significantly higher IL-15 expression than competent saphenous veins. CONCLUSIONS: Venous insufficiency associates with age, BMI, skin temperature, and plasma cytokines associated with interferon gamma and possibly IL-17A signaling. The vein wall may be a source of activation of cellular activation, given elevated IL-15 expression. Correlations between IL-17A and GM-CSF suggested a potential role for pathogenic Th17 cells in VVs. Differentially expressed inflammatory networks induced by venous hypertension may reflect or drive venous damage and ulceration.

Baseline Plasma Inflammatory Profile Is Associated With Response to Neoadjuvant Chemotherapy in Patients With Pancreatic Adenocarcinoma.

Despite its increased application in pancreatic ductal adenocarcinoma (PDAC), complete response to neoadjuvant therapy (NAT) is rare. Given the critical role of host immunity in regulating cancer, we sought to correlate baseline inflammatory profiles to significant response to NAT. PDAC patients receiving NAT were classified as responders (R) or nonresponders (NR) by carbohydrate antigen 19-9 response, pathologic tumor size, and lymph node status in the resected specimen. Baseline (treatment-naive) plasma was analyzed to determine levels of 27 inflammatory mediators. Logistic regression was used to correlate individual mediators with response. Network analysis and Pearson correlation maps were derived to determine baseline inflammatory mediator profiles. Forty patients (20R and 20NR) met study criteria. The R showed significantly higher overall survival (59.4 vs. 21.25 mo, P=0.002) and disease-free survival (50.97 vs. 10.60 mo, P=0.005), compared with NR. soluble interleukin-2 receptor alpha was a significant predictor of no response to NAT (P=0.045). Analysis of inflammatory profiles using the Pearson heat map analysis followed by network analysis depicted increased inflammatory network complexity in NR compared with R (1.69 vs. 1), signifying a more robust baseline inflammatory status of NR. A panel of inflammatory mediators identified by logistic regression and Fischer score analysis was used to create a potential decision tree to predict NAT response. We demonstrate that baseline inflammatory profiles are associated with response to NAT in PDAC, and that an upregulated inflammatory status is associated with a poor response to NAT. Further analysis into the role of inflammatory mediators as predictors of chemotherapy response is warranted.

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation.

Systems-level insights into inflammatory events after vascularized composite allotransplantation (VCA) are critical to the success of immunomodulatory strategies of these complex procedures. To date, the effects of tacrolimus (TAC) immunosuppression on inflammatory networks in VCA, such as in acute rejection (AR), have not been investigated. We used a systems biology approach to elucidate the effects of tacrolimus on dynamic networks and principal drivers of systemic inflammation in the context of dynamic tissue-specific immune responses following VCA. Lewis (LEW) rat recipients received orthotopic hind limb VCA from fully major histocompatibility complex-mismatched Brown Norway (BN) donors or matched LEW donors. Group 1 (syngeneic controls) received LEW limbs without TAC, and Group 2 (treatment group) received BN limbs with TAC. Time-dependent changes in 27 inflammatory mediators were analyzed in skin, muscle, and peripheral blood using Principal Component Analysis (PCA), Dynamic Bayesian Network (DyBN) inference, and Dynamic Network Analysis (DyNA) to define principal characteristics, central nodes, and putative feedback structures of systemic inflammation. Analyses were repeated on skin + muscle data to construct a "Virtual VCA", and in skin + muscle + peripheral blood data to construct a "Virtual Animal." PCA, DyBN, and DyNA results from individual tissues suggested important roles for leptin, VEGF, various chemokines, the NLRP3 inflammasome (IL-1ß, IL-18), and IL-6 after TAC treatment. The chemokines MCP-1, MIP-1α; and IP-10 were associated with AR in controls. Statistical analysis suggested that 24/27 inflammatory mediators were altered significantly between control and TAC-treated rats in peripheral blood, skin, and/or muscle over time. "Virtual VCA" and "Virtual Animal" analyses implicated the skin as a key control point of dynamic inflammatory networks, whose connectivity/complexity over time exhibited a U-shaped trajectory and was mirrored in the systemic circulation. Our study defines the effects of TAC on complex spatiotemporal evolution of dynamic inflammation networks in VCA. We also demonstrate the potential utility of computational analyses to elucidate nonlinear, cross-tissue interactions. These approaches may help define precision medicine approaches to better personalize TAC immunosuppression in VCA recipients.

A putative "chemokine switch" that regulates systemic acute inflammation in humans.

Systemic inflammation is complex and likely drives clinical outcomes in critical illness such as that which ensues following severe injury. We obtained time course data on multiple inflammatory mediators in the blood of blunt trauma patients. Using dynamic network analyses, we inferred a novel control architecture for systemic inflammation: a three-way switch comprising the chemokines MCP-1/CCL2, MIG/CXCL9, and IP-10/CXCL10. To test this hypothesis, we created a logical model comprising this putative architecture. This model predicted key qualitative features of systemic inflammation in patient sub-groups, as well as the different patterns of hospital discharge of moderately vs. severely injured patients. Thus, a rational transition from data to data-driven models to mechanistic models suggests a novel, chemokine-based mechanism for control of acute inflammation in humans and points to the potential utility of this workflow in defining novel features in other complex diseases.

Dynamics of Systemic Inflammation as a Function of Developmental Stage in Pediatric Acute Liver Failure.

The Pediatric Acute Liver Failure (PALF) study is a multicenter, observational cohort study of infants and children diagnosed with this complex clinical syndrome. Outcomes in PALF reflect interactions among the child's clinical condition, response to supportive care, disease severity, potential for recovery, and, if needed, availability of a suitable organ for liver transplantation (LTx). Previously, we used computational analyses of immune/inflammatory mediators that identified three distinct dynamic network patterns of systemic inflammation in PALF associated with spontaneous survivors, non-survivors (NS), and LTx recipients. To date, there are no data exploring age-specific immune/inflammatory responses in PALF. Accordingly, we measured a number of clinical characteristics and PALF-associated systemic inflammatory mediators in daily serum samples collected over the first 7 days following enrollment from five distinct PALF cohorts (all spontaneous survivors without LTx): infants (INF, <1 year), toddlers (TOD, 1-2 years.), young children (YCH, 2-4 years), older children (OCH, 4-13 years) and adolescents (ADO, 13-18 years). Among those groups, we observed significant (P<0.05) differences in ALT, creatinine, Eotaxin, IFN-γ, IL-1RA, IL-1ß, IL-2, sIL-2Rα, IL-4, IL-6, IL-12p40, IL-12p70, IL-13, IL-15, MCP-1, MIP-1α, MIP-1ß, TNF-α, and NO2-/NO3- . Dynamic Bayesian Network inference identified a common network motif with HMGB1 as a central node in all sub-groups, with MIG/CXCL9 being a central node in all groups except INF. Dynamic Network Analysis (DyNA) inferred different dynamic patterns and overall dynamic inflammatory network complexity as follows: OCH>INF>TOD>ADO>YCH. Hypothesizing that systemically elevated but sparsely connected inflammatory mediators represent pathological inflammation, we calculated the AuCon score (area under the curve derived from multiple measures over time divided by DyNA connectivity) for each mediator, and identified HMGB1, MIG, IP-10/CXCl10, sIL-2Rα, and MCP-1/CCL2 as potential correlates of PALF pathophysiology, largely in agreement with the results of Partial Least Squares Discriminant Analysis. Since NS were in the INF age group, we compared NS to INF and found greater inflammatory coordination and dynamic network connectivity in NS vs. INF. HMGB1 was the sole central node in both INF and NS, though NS had more downstream nodes. Thus, multiple machine learning approaches were used to gain both basic and potentially translational insights into a complex inflammatory disease.

Computational Derivation of Core, Dynamic Human Blunt Trauma Inflammatory Endotypes.

Systemic inflammation ensues following traumatic injury, driving immune dysregulation and multiple organ dysfunction (MOD). While a balanced immune/inflammatory response is ideal for promoting tissue regeneration, most trauma patients exhibit variable and either overly exuberant or overly damped responses that likely drive adverse clinical outcomes. We hypothesized that these inflammatory phenotypes occur in the context of severe injury, and therefore sought to define clinically distinct endotypes of trauma patients based on their systemic inflammatory responses. Using Patient-Specific Principal Component Analysis followed by unsupervised hierarchical clustering of circulating inflammatory mediators obtained in the first 24 h after injury, we segregated a cohort of 227 blunt trauma survivors into three core endotypes exhibiting significant differences in requirement for mechanical ventilation, duration of ventilation, and MOD over 7 days. Nine non-survivors co-segregated with survivors. Dynamic network inference, Fisher Score analysis, and correlations of IL-17A with GM-CSF, IL-10, and IL-22 in the three survivor sub-groups suggested a role for type 3 immunity, in part regulated by Th17 and γδ 17 cells, and related tissue-protective cytokines as a key feature of systemic inflammation following injury. These endotypes may represent archetypal adaptive, over-exuberant, and overly damped inflammatory responses.

An Aging-Related Single-Nucleotide Polymorphism is Associated With Altered Clinical Outcomes and Distinct Inflammatory Profiles in Aged Blunt Trauma Patients.

The contribution of individual genetic determinants of aging to the adverse clinical outcomes and altered inflammation mediator networks characteristic of aged trauma patients is unknown. The AA genotype of the aging-related single-nucleotide polymorphism (SNP) rs2075650 in TOMM40 has been associated with longevity, while the AG and GG genotypes are associated with an increased risk of Alzheimer disease. Here, we studied the effect of rs2075650 on clinical outcomes and dynamic biomarker patterns after traumatic injury. Genomic DNA was obtained from blunt trauma patients admitted to the ICU and examined for 551,839 SNPs using an Illumina microarray kit. Plasma was sampled from each patient three times within the first 24 h and daily from day 1 to 7 then assayed for 31 biomarkers using Luminex. Aged patients (65-90 years) were segregated into AA (n = 77) and AG/GG (n = 17) genotypes. Additional comparisons were made with matched groups of young patients (18-30 years), controlling for injury severity score (ISS) and sex ratio, and also segregated into AA (n = 56) and AG/GG (n = 19) genotypes. Aged patients with the AA genotype had a significantly lower requirement for ventilation and fewer days on mechanical ventilation, as well as significantly higher levels of one mediator and lower levels of two mediators. Dynamic Bayesian Network inference revealed IL-23 as a central node in each network regardless of age or genotype, with MIG and IP-10 also as key mediators in the networks of the aged patients. These findings suggest that an aging-related SNP, rs2075650, may influence clinical outcomes and inflammation networks in aged patients following blunt trauma, and thus may serve as a predictive outcome biomarker in the setting of polytrauma.