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Background Multiply injured patients (MIPs) are at risk of complications including infections, and acute and prolonged organ dysfunction. The immunologic response to injury has been shown to affect outcomes. Recent advances in computational capabilities have shown that early dynamic coordination of the immunologic response is associated with improved outcomes after trauma. We hypothesized that patients who were sensitive or tolerant of hemorrhage would demonstrate differences in dynamic immunologic orchestration within hours of injury. Methods We identified two groups of MIPs who demonstrated distinct clinical tolerance to hemorrhage (n = 10) or distinct clinical sensitivity to hemorrhage (n = 9) from a consecutive cohort of 100 MIPs. Hemorrhage was quantified by integrating elevated shock index values for 24 hours after injury (shock volume). Clinical outcomes were quantified by average Marshall Organ Dysfunction Scores from days 2 to 5 after injury. Shock-sensitive patients had high cumulative organ dysfunction after lower magnitude hemorrhage. Shock-tolerant (ST) patients had low cumulative organ dysfunction after higher magnitude hemorrhage. Computational methods were used to analyze a panel of 20 immunologic mediators collected serially over the initial 72 hours after injury. Results Dynamic network analysis demonstrated the ST patients had increased orchestration of cytokines that are reparative and protective including interleukins 9, 17E/25, 21, 22, 23, and 33 during the initial 0- to 8-hour and 8- to 24-hour intervals after injury. Shock-sensitive patients had delayed immunologic orchestration of a network of largely proinflammatory and anti-inflammatory mediators. Elastic net linear regression demonstrated that a group of five mediators could discriminate between shock-sensitive and ST patients. Conclusions Preliminary evidence from this study suggests that early immunologic orchestration discriminates between patients who are notably tolerant or sensitive to hemorrhage. Early orchestration of a group of reparative/protective mediators was amplified in shock-tolerant patients. Level of evidence Prospective clinical outcomes study, level III.

Acute illness is a complex constellation of responses involving dysregulated inflammatory and immune responses, which are ultimately associated with multiple organ dysfunction. Gene association studies have associated single-nucleotide polymorphisms (SNPs) with clinical and pharmacological outcomes in a variety of disease states, including acute illness. With approximately 4–5 million SNPs in the human genome and recent studies suggesting that a large portion of SNP studies are not reproducible, we suggest that the ultimate clinical utility of SNPs in acute illness depends on validation and quality control measures. To investigate this issue, in December 2018 and January 2019 we searched the literature for peer-reviewed studies reporting data on associations between SNPs and clinical outcomes and between SNPs and pharmaceuticals (i.e. pharmacogenomics) published between January 2011 to February 2019. We review key methodologies and results from a variety of clinical and pharmacological gene association studies, including trauma and sepsis studies, as illustrative examples on current SNP association studies. In this review article, we have found three key points which strengthen the potential accuracy of SNP association studies in acute illness and other diseases: 1) providing evidence of following a protocol quality control method such as the one in Nature Protocols (22) or the OncoArray QC Guidelines (21); 2) enrolling enough patients to have large cohort groups; and 3) validating the SNPs using an independent technique such as a second study using the same SNPs with new patient cohorts. Our survey suggests the need to standardize validation methods and SNP quality control measures in medicine in general, and specifically in the context of complex disease states such as acute illness.

Sepsis is characterized by an overactive, dysregulated inflammatory response that drives organ dysfunction and often results in death. Mathematical modeling has emerged as an essential tool for understanding the underlying complex biological processes. A system of four ordinary differential equations (ODEs) was developed to simulate the dynamics of bacteria, the pro- and anti-inflammatory responses, and tissue damage (whose molecular correlate is damage-associated molecular pattern [DAMP] molecules and which integrates inputs from the other variables, feeds back to drive further inflammation, and serves as a proxy for whole-organism health status). The ODE model was calibrated to experimental data from E. coli infection in genetically identical rats and was validated with mortality data for these animals. The model demonstrated recovery, aseptic death, or septic death outcomes for a simulated infection while varying the initial inoculum, pathogen growth rate, strength of the local immune response, and activation of the pro-inflammatory response in the system. In general, more septic outcomes were encountered when the initial inoculum of bacteria was increased, the pathogen growth rate was increased, or the host immune response was decreased. The model demonstrated that small changes in parameter values, such as those governing the pathogen or the immune response, could explain the experimentally observed variability in mortality rates among septic rats. A local sensitivity analysis was conducted to understand the magnitude of such parameter effects on system dynamics. Despite successful predictions of mortality, simulated trajectories of bacteria, inflammatory responses, and damage were closely clustered during the initial stages of infection, suggesting that uncertainty in initial conditions could lead to difficulty in predicting outcomes of sepsis by using inflammation biomarker levels.

While bulk and single cell transcriptomic patterns in circulating leukocytes from trauma patients have been reported, how these relate to changes in open chromatin patterns remain unstudied. Here, we investigated whether single-cell ATAC-seq would provide further resolution of transcriptomic patterns that align with patient outcomes.We performed scATAC-seq on peripheral blood mononuclear cells from four trauma patients at4 h, 24 h, 72 h post-injury and four matched healthy controls, and extracted the features associated with the global epigenetic alterations. Three large-scale bulk transcriptomic datasets from trauma, burn and sepsis patients were used to validate the scATAC-seq derived signature, explore patient epigenetic heterogeneity (Epigenetic Groups: EG_hi vs. EG_lo), and associate patterns with clinical outcomes in critical illness.Patient subsets with gene expression patterns in blood leukocytes representative of a high global epigenetic signature (EG_hi) had worse outcomes across three etiologies of critical illness. EG_hi designation contributed independent of the known immune leukocyte transcriptomic responses to patient prognosis (Trauma: HR=0.62 [95% CI: 0.43-0.89, event set as recovery], p=0.01, n=167; Burns: HR=4.35 [95% CI: 0.816-23.2, event set as death], p=0.085, n=121; Sepsis: HR=1.60 [95% CI: 1.10-2.33, event set as death], p=0.013, n=479; Cox proportional hazards regression).The inclusion of gene expression patterns that associate with global epigenetic changes in circulating leukocytes improves the resolution of transcriptome-based patient classification in acute critical illnesses. Early detection of both the global epigenetic signature and the known immune transcriptomic patterns associates with the worse prognosis in trauma, burns and sepsis.This project was supported by an R35 grant from National Institutes of Health: 1R35GM127027-01 (T.B.).

Immune dysfunction is an important factor driving mortality and adverse outcomes after trauma but remains poorly understood, especially at the cellular level. To deconvolute the trauma-induced immune response, we applied single-cell RNA sequencing to circulating and bone marrow mononuclear cells in injured mice and circulating mononuclear cells in trauma patients. In mice, the greatest changes in gene expression were seen in monocytes across both compartments. After systemic injury, the gene expression pattern of monocytes markedly deviated from steady state with corresponding changes in critical transcription factors, which can be traced back to myeloid progenitors. These changes were largely recapitulated in the human single-cell analysis. We generalized the major changes in human CD14+ monocytes into 6 signatures, which further defined 2 trauma patient subtypes (SG1 vs. SG2) identified in the whole-blood leukocyte transcriptome in the initial 12 hours after injury. Compared with SG2, SG1 patients exhibited delayed recovery, more severe organ dysfunction, and a higher incidence of infection and noninfectious complications. The 2 patient subtypes were also recapitulated in burn and sepsis patients, revealing a shared pattern of immune response across critical illness. Our data will be broadly useful to further explore the immune response to inflammatory diseases and critical illness.

Trauma is the leading cause of death and disability for individuals under age 55. Many severely injured trauma patients experience complicated clinical courses despite appropriate initial therapy. We sought to identify novel circulating metabolomic signatures associated with clinical outcomes following trauma.Untargeted metabolomics and circulating plasma immune mediator analysis was performed on plasma collected during 3 post-injury time periods (6 hours [h], 6 h-24h, day 2-day 5) in critically ill trauma patients enrolled between April 2004 and May 2013 at UPMC Presbyterian Hospital in Pittsburgh, PA. Inclusion criteria were age ≥ 18 years, blunt mechanism, ICU admission, and expected survival ≥ 24 h. Exclusion criteria were isolated head injury, spinal cord injury, and pregnancy. Exploratory endpoints included length of stay (overall and ICU), ventilator requirements, nosocomial infection, and Marshall organ dysfunction (MOD) score. The top 50 metabolites were isolated using repeated measures ANOVA and multivariate empirical Bayesian analysis for further study.Eighty-six patients were included for analysis. Sphingolipids were enriched significantly (chi-square, p10Metabolomic analysis identified broad alterations in circulating plasma sphingolipids after blunt trauma. Circulating sphingolipid signatures and their association with both clinical outcomes and circulating inflammatory mediators suggest a possible link between sphingolipid metabolism and the immune response to trauma.

Trauma is the leading cause of death worldwide for individuals under the age of 55. Interpatient genomic differences, in the form of candidate single-nucleotide polymorphisms (SNPs), have been associated previously with adverse outcomes after trauma. However, the utility of these SNPs to predict outcomes based on a meaningful endpoint such as survival is as yet undefined. We hypothesized that specific SNP haplotypes could segregate trauma survivors from non-survivors. Genomic DNA samples were obtained from 453 blunt trauma patients, for whom complete daily clinical and biomarker data were available for 397. Of these, 13 patients were non-survivors and the remaining 384 were survivors. All 397 DNA samples were amplified, fragmented, and examined for 551,839 SNPs using the Illumina Infinium CoreExome-24 v1.1 BeadChip (Illumina). To enrich for likely important SNPs, we initially compared SNPs of the 13 non-survivors versus 13 matched survivors, who were matched algorithmically for injury severity score (ISS), age, and gender ratio. This initial enrichment yielded 126 SNPs; a further comparison to the haplotypes of the remaining 371 survivors yielded a final total of 7 SNPs that distinguished survivors from non-survivors. Furthermore, severely injured survivors with the same seven SNPs as non-survivor exhibited distinct inflammatory responses from similarly injured survivors without those SNPs, and specifically had evidence of altered Th17 cell phenotypes based on computational modeling. These studies suggest an interaction among genetic polymorphism, injury severity, and initial inflammatory responses in driving trauma outcomes.

Summary Trauma is a leading cause of death and morbidity worldwide. Here, we present the analysis of a longitudinal multi-omic dataset comprising clinical, cytokine, endotheliopathy biomarker, lipidome, metabolome, and proteome data from severely injured humans. A “systemic storm” pattern with release of 1,061 markers, together with a pattern suggestive of the “massive consumption” of 892 constitutive circulating markers, is identified in the acute phase post-trauma. Data integration reveals two human injury response endotypes, which align with clinical trajectory. Prehospital thawed plasma rescues only endotype 2 patients with traumatic brain injury (30-day mortality: 30.3 versus 75.0%; p = 0.0015). Ubiquitin carboxy-terminal hydrolase L1 (UCHL1) was identified as the most predictive circulating biomarker to identify endotype 2-traumatic brain injury (TBI) patients. These response patterns refine the paradigm for human injury, while the datasets provide a resource for the study of critical illness, trauma, and human stress responses., Graphical abstract, Highlights An integrated longitudinal multi-omic analysis of the human response to trauma Systemic storm and massive consumption patterns are related to early mortality Unique resolution and non-resolution signatures across multiple “omics” platforms Only endotype 2-TBI patients with high UCHL1 levels benefit from early plasma, Wu et al. report a longitudinal multi-omic analysis of the circulation in trauma patients. Cross-platform data integration reveals a massive systemic release of cellular contents (“systemic storm”) and simultaneous consumption of blood constituents. Also defined are patient endotypes that differ in outcomes and responses to early plasma administration.

Purpose: We sought to identify a MODS score parameter that highly correlates with adverse outcomes and then use this parameter to test the hypothesis that multiple severity-based MODS clusters could be identified after blunt trauma. Methods: MOD score across days (D) 2–5 was subjected to Fuzzy C-means Clustering Analysis (FCM) followed by eight Clustering Validity Indices (CVI) to derive organ dysfunction patterns among 376 blunt trauma patients admitted to the intensive care unit (ICU) who survived to discharge. Thirty-one inflammation biomarkers were assayed (Luminex™) in serial blood samples (3 samples within the first 24 h and then daily up to D 5) and were analyzed using Two-Way ANOVA and Dynamic Network analysis (DyNA). Results: The FCM followed by CVI suggested four distinct clusters based on MOD score magnitude between D2 and D5. Distinct patterns of organ dysfunction emerged in each of the four clusters and exhibited statistically significant differences with regards to in-hospital outcomes. Interleukin (IL)-6, MCP-1, IL-10, IL-8, IP-10, sST2, and MIG were elevated differentially over time across the four clusters. DyNA identified remarkable differences in inflammatory network interconnectivity. Conclusion: These results suggest the existence of four distinct organ failure patterns based on MOD score magnitude in blunt trauma patients admitted to the ICU who survive to discharge.

Circadian oscillations of immunity and inflammation have been characterized, and animal studies suggest that the time of day is a determinant of the immunological response to both injury and infection. We hypothesized that due to this diurnal variation, time of injury can affect the systemic inflammatory response and outcomes post-trauma and tested this hypothesis by examining the dynamics of circulating inflammatory mediators in blunt trauma patients injured during daytime vs. nighttime. From a cohort of 472 blunt trauma survivors, two stringently matched sub-cohorts of moderately/severely injured patients [injury severity score (ISS) >20] were identified. Fifteen propensity-matched, daytime-inured (“mDay”) patients (age 43.6 ± 5.2, M/F 11/4, ISS 22.9 ± 0.7) presented during the shortest local annual period (8:00 am-5:00 pm), and 15 propensity-matched “mNight” patients (age 43 ± 4.3, M/F 11/4, ISS 24.5 ± 2.5) presented during the shortest night period (10:00 pm-5:00 am). Serial blood samples were obtained (3 samples within the first 24 h and daily from days 1-7) from all patients. Thirty-two plasma inflammatory mediators were assayed. Two-way Analysis of Variance (ANOVA) was used to compare groups. Dynamic Network Analysis (DyNA) and Dynamic Bayesian Network (DyBN) inference were utilized to infer dynamic interrelationships among inflammatory mediators. Both total hospital and intensive care unit length of stay were significantly prolonged in the mNight group, despite a greater need for surgical interventions in mDay group. Circulating IL-17A was elevated significantly in the mNight group from 24 h – 7 days post-injury. Circulating MIP-1alpha, IL-7, IL-15, GM-CSF, and sST2 were elevated in the mDay group. DyNA demonstrated elevated network complexity in the mNight vs. the mDay group. DyBN suggested that cortisol and sST2 were central nodes upstream of TGF-beta1, chemokines, and Th17/protective mediators in both groups, with IL-6 being an additional downstream node in the mNight group only. Our results suggest that time of injury affects the clinical outcomes in severely injured patients in a manner associated with an altered systemic inflammation program, possibly implying a role for circadian variation in the response to traumatic injury.

Trauma is a leading cause of morbidity and mortality. It is unclear why some trauma victims follow a complicated clinical course and die, while others, with apparently similar injury characteristics, do not. Interpatient genomic differences, in the form of single nucleotide polymorphisms (SNPs), have been associated previously with adverse outcomes after trauma. Recently, we identified seven novel SNPs associated with mortality following trauma. The aim of the present study was to determine if one or more of these SNPs was also associated with worse clinical outcomes and altered inflammatory trajectories in trauma survivors. Accordingly, of 413 trauma survivors, DNA samples, full blood samples, and clinical data were collected at multiple time points in the first 24 h and then daily over 7 days following hospital admission. Subsequently, single-SNP groups were created and outcomes, such as hospital length of stay (LOS), ICU LOS, and requirement for mechanical ventilation, were compared. Across a broad range of Injury Severity Scores (ISS), patients carrying the rs2065418 TT SNP in the metallophosphoesterase domain-containing 2 (MPPED2) gene exhibited higher Marshall MODScores vs. the control group of rs2065418 TG/GG patients. In patients with high-severity trauma (ISS ≥ 25, n = 94), those carrying the rs2065418 TT SNP in MPPED2 exhibited higher Marshall MODScores, longer hospital LOS (21.8 ± 2 days), a greater requirement for mechanical ventilation (9.2 ± 1.4 days on ventilator, DOV), and higher creatinine plasma levels over 7 days vs. the control group of rs2065418 TG/GG high-severity trauma patients (LOS: 15.9 ± 1.2 days, p = 0.03; DOV: 5.7 ± 1 days, p = 0.04; plasma creatinine; p < 0.0001 MODScore: p = 0.0003). Furthermore, rs2065418 TT patients with ISS ≥ 25 had significantly different plasma levels of nine circulating inflammatory mediators and elevated dynamic network complexity. These studies suggest that the rs2065418 TT genotype in the MPPED2 gene is associated with altered systemic inflammation, increased organ dysfunction, and greater hospital resource utilization. A screening for this specific SNP at admission might stratify severely injured patients regarding their lung and kidney function and clinical complications.

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’s 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 hours 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

Critical illness, a constellation of interrelated inflammatory and physiological derangements occurring subsequent to severe infection or injury, affects a large number of individuals in both developed and developing countries. The prototypical complex system embodied in critical illness has largely defied therapy beyond supportive care. We have focused on the utility of data-driven and mechanistic computational modelling to help address the complexity of critical illness and provide pathways towards discovering potential therapeutic options and combinations. Herein, we review recent progress in this field, with a focus on both animal and computational models of critical illness. We suggest that therapy for critical illness can be posed as a model-based dynamic control problem, and discuss novel theoretical and experimental approaches involving biohybrid devices aimed at reprogramming inflammation dynamically. Together, these advances offer the potential for Model-based Precision Medicine for critical illness.

Purpose We hypothesized that early inflammation can drive, or impact, later multiple organ dysfunction syndrome (MODS), that patient-specific principal component analysis (PCA) of circulating inflammatory mediators could reveal conserved dynamic responses which would not be apparent from the unprocessed data, and that this computational approach could segregate trauma patients with regard to subsequent MODS. Methods From a cohort of 472 blunt trauma survivors, 2 separate subcohorts of moderately/severely injured patients were studied. Multiple inflammatory mediators were assessed in serial blood samples in the first 24 hours postinjury. PCA of these time course data was used to derive patient-specific “inflammation barcodes,” followed by hierarchical clustering to define patient subgroups. To define the generalizability of this approach, 2 different but overlapping Luminex kits were used. Results PCA/hierarchical clustering of 24-hour Luminex data segregated the patients into 2 groups that differed significantly in their Marshall multiple organ dysfunction score on subsequent days, independently of the specific set of inflammatory mediators analyzed. Multiple inflammatory mediators and their dynamic networks were significantly different in the 2 groups in both patient cohorts, demonstrating that the groups were defined based on “core” early responses exhibit truly different dynamic inflammatory trajectories. Conclusion Identification of patient-specific “core responses” can lead to early segregation of diverse trauma patients with regard to later MODS. Hence, we suggest that a focus on dynamic inflammatory networks rather than individual biomarkers is warranted.

Background Severe injury initiates a complex physiologic response encompassing multiple systems and varies phenotypically between patients. Trauma-induced coagulopathy may be an early warning of a poorly coordinated response at the molecular level, including a deleterious immunologic response and worsening of shock states. The onset of trauma-induced coagulopathy (TIC) may be subtle however. In previous work, we identified an early warning sign of coagulopathy from the admission thromboelastogram, called the MAR ratio. We hypothesized that a low MAR ratio would be associated with specific derangements in the inflammatory response. Methods In this prospective, observational study, 88 blunt trauma patients admitted to the intensive care unit (ICU) were identified. Concentrations of inflammatory mediators were recorded serially over the course of a week and the MAR ratio was calculated from the admission thromboelastogram. Correlation analysis was used to assess the relationship between MAR and inflammatory mediators. Dynamic network analysis was used to assess coordination of immunologic response. Results Seventy-nine percent of patients were male and mean age was 37 years (SD 12). The mean ISS was 30.2 (SD 12) and mortality was 7.2%. CRITICAL patients (MAR ratio ≤14.2) had statistically higher shock volumes at three time points in the first day compared to NORMAL patients (MAR ratio >14.2). CRITICAL patients had significant differences in IL-6 (P=0.0065), IL-8 (P=0.0115), IL-10 (P=0.0316) and MCP-1 (P=0.0039) concentrations compared to NORMAL. Differences in degree of expression and discoordination of immune response continued in CRITICAL patients throughout the first day. Conclusions The admission MAR ratio may be the earliest warning signal of a pathologic inflammatory response associated with hypoperfusion and TIC. A low MAR ratio is an early indication of complicated dysfunction of multiple molecular processes following trauma.

Soluble suppression of tumorigenicity 2 (sST2), a decoy receptor for interleukin (IL)-33, has emerged as a novel biomarker in various disease processes. Recent studies have elucidated the role of the sST2/IL-33 complex in modulating the balance of Th1/Th2 immune responses after tissue stress. However, the role of sST2 as a biomarker after traumatic injury remains unclear. To address this, we evaluated serum sST2 correlations with mortality and in-hospital adverse outcomes as endpoints in blunt trauma patients.We retrospectively analyzed clinical and biobank data of 493 blunt trauma victims 472 survivors (mean age: 48.4 ± 0.87; injury severity score [ISS]: 19.6 ± 0.48) and 19 nonsurvivors (mean age: 58.8 ± 4.5; ISS: 23.3 ± 2.1) admitted to the intensive care unit. Given the confounding impact of age on the inflammatory response, we derived a propensity-matched survivor subgroup (n = 19; mean age: 59 ± 3; ISS: 23.4 ± 2) using an IBM SPSS case-control matching algorithm. Serial blood samples were obtained from all patients (3 samples within the first 24 h and then once daily from day [D] 1 to D5 after injury). sST2 and twenty-nine inflammatory biomarkers were assayed using enzyme-linked immunosorbent assay and Luminex, respectively. Two-way analysis of variance on ranks was used to compare groups (P 0.05). Spearman rank correlation was performed to determine the association of circulating sST2 levels with biomarker levels and in-hospital clinical outcomes.Circulating sST2 levels of the nonsurvivor cohort were statistically significantly elevated at 12 h after injury and remained elevated up to D5 when compared either to the overall 472 survivor cohort or a matched 19 survivor subcohort. Admission sST2 levels obtained from the first blood draw after injury in the survivor cohort correlated positively with admission base deficit (correlation coefficient [CC] = 0.1; P = 0.02), international normalized ratio (CC = 0.1, P = 0.03), ISS (CC = 0.1, P = 0.008), and the average Marshall multiple organ dysfunction score between D2 and D5 (CC = 0.1, P = 0.04). Correlations with ISS revealed a positive correlation of ISS with plasma sST2 levels across the mild ISS (CC = 0.47, P 0.001), moderate ISS (CC = 0.58, P 0.001), and severe ISS groups (CC = 0.63, P 0.001). Analysis of biomarker correlations in the matched survivor group over the initial 24 h after injury showed that sST2 correlates strongly and positively with IL-4 (CC = 0.65, P = 0.002), IL-5 (CC = 0.57, P = 0.01), IL-21 (CC = 0.52, P = 0.02), IL-2 (CC = 0.51, P = 0.02), soluble IL-2 receptor-α (CC = 0.5, P = 0.02), IL-13 (CC = 0.49, P = 0.02), and IL-17A (CC = 0.48, P = 0.03). This was not seen in the matched nonsurvivor group. sST2/IL-33 ratios were significantly elevated in nonsurvivors and patients with severe injury based on ISS ≥ 25.Elevations in serum sST2 levels are associated with poor clinical trajectories and mortality after blunt trauma. High sST2 coupled with low IL-33 associates with severe injury, mortality, and worse clinical outcomes. These findings suggest that sST2 could serve as an early prognostic biomarker in trauma patients and that sustained elevations of sST2 could contribute to a detrimental suppression of IL-33 bioavailability in patients with high injury severity.

To define the impact of prehospital hypotension on the dynamic, systemic acute inflammatory response to blunt trauma.Retrospective study.Tertiary care institution.Twenty-two hypotensive blunt trauma patients matched with 28 normotensive blunt trauma patients.None.From a cohort of 472 blunt trauma survivors studied following institutional review board approval, two stringently matched subcohorts were derived. Twenty-two patients who sustained prehospital hypotension following blunt trauma (15 males and 7 females; age, 45 ± 3.8; Injury Severity Score, 20.7 ± 1.8) were matched with 28 normotensive trauma patients (20 males and 8 females; age, 46.1 ± 2.5; Injury Severity Score, 20.8 ± 1.3). Serial blood samples (three samples within the first 24 hr and then from days 1 to 7 postinjury) were assessed for 24 inflammatory mediators using Luminex, and No2-/No3- was measured using the nitrate reductase/Griess assay. Two-way analysis of variance was used to compare groups. Dynamic Bayesian Network inference was used to infer causal relationships based on probabilistic measures. Statistically significant differences were observed in ICU length of stay, total length of stay, days on mechanical ventilator, and Marshall Multiple Organ Dysfunction score between hypotensive and normotensive patients. Shock markers (shock index, pH, lactate, and base deficit) were significantly altered in hypotensive patients. Plasma levels of chemokines (monocyte chemotactic protein-1/CCL2, inducible protein-10/CXCL10, macrophage inflammatory protein-1α/CCL3, and interleukin-8/CCL8) and cytokines (interleukin-6, interleukin-10, interleukin-17, granulocyte-macrophage colony-stimulating factor, interleukin-1β, and interleukin-7) as well as soluble interleukin-2 receptor-α were significantly elevated over the first 7 days postinjury in the hypotensive versus normotensive patients. Dynamic Bayesian Network suggested that the chemokines monocyte chemotactic protein-1/CCL2 and monokine induced by gamma interferon/CXCL9 in the hypotensive and normotensive patients, respectively, affect plasma interleukin-6 levels differentially in the initial 24 hours postinjury.Studies in stringently matched patient cohorts suggest that an episode of prehospital hypotension post trauma leads to early, dynamic reprogramming of systemic inflammation (including differential upstream regulation of interleukin-6), which is associated with worse outcomes.

Clinical research characterizing the mechanisms responsible for sex-based outcome differences after injury remains conflicting. Currently lacking is an understanding of the early sex hormone milieu of the injured patient and the effects these early hormone differences have on clinical outcomes and the innate immune response following injury.A prospective cohort study was performed over a 20-month period. Blunt injury patients requiring intensive care unit admission were enrolled. Samples were collected within 6 hours and at 24 hours after injury and were analyzed for total testosterone (TT) and estradiol concentrations. Outcomes of interest included multiple-organ failure (MOF; Marshall Multiple Organ Dysfunction Score [MODScore]5), nosocomial infection (NI), mortality, and serial cytokine/chemokine measurements. Multivariate logistic regression was used to determine the independent risks associated with early sex hormone measurements.In 288 prospectively enrolled patients, 69% were male, with a median Injury Severity Score (ISS) of 16 (interquartile range 10-21). Elevated TT levels at 6 hours were associated with elevated interleukin 6 levels and cytokine/chemokine measurements (18 of 24 measured). Rising TT levels were significantly associated with more than a fivefold and twofold higher independent risk of MOF and NI, respectively (odds ratio [OR], 5.2; p = 0.02; 95% confidence interval [CI], 1.2-22.3; and OR, 2.1; p = 0.03; 95% CI, 1.02-4.2). At 24 hours, TT levels were no longer associated with poor outcome, while estradiol levels were significantly associated with nearly a fourfold higher independent risk of MOF (OR, 3.9; p = 0.04, 95% CI, 1.05-13).Early elevations and increasing testosterone levels over initial 24 hours after injury are associated with an exaggerated inflammatory response and a significantly greater risk of MOF and NI. High estrogen levels at 24 hours are independently associated with an increased risk of MOF. The current analysis suggests that an early evolving testosterone to estrogen hormonal environment is associated with a significantly higher independent risk of poor outcome following traumatic injury.Prognostic/epidemiologic study, level II.

Background The immunosuppression and immune dysregulation that follows severe injury includes type 2 immune responses manifested by elevations in interleukin (IL) 4, IL5, and IL13 early after injury. We hypothesized that IL33, an alarmin released early after tissue injury and a known regulator of type 2 immunity, contributes to the early type 2 immune responses after systemic injury. Methods and findings Blunt trauma patients admitted to the trauma intensive care unit of a level I trauma center were enrolled in an observational study that included frequent blood sampling. Dynamic changes in IL33 and soluble suppression of tumorigenicity 2 (sST2) levels were measured in the plasma and correlated with levels of the type 2 cytokines and nosocomial infection. Based on the observations in humans, mechanistic experiments were designed in a mouse model of resuscitated hemorrhagic shock and tissue trauma (HS/T). These experiments utilized wild-type C57BL/6 mice, IL33-/- mice, B6.C3(Cg)-Rorasg/sg mice deficient in group 2 innate lymphoid cells (ILC2), and C57BL/6 wild-type mice treated with anti-IL5 antibody. Severely injured human blunt trauma patients (n = 472, average injury severity score [ISS] = 20.2) exhibited elevations in plasma IL33 levels upon admission and over time that correlated positively with increases in IL4, IL5, and IL13 (P < 0.0001). sST2 levels also increased after injury but in a delayed manner compared with IL33. The increases in IL33 and sST2 were significantly greater in patients that developed nosocomial infection and organ dysfunction than similarly injured patients that did not (P < 0.05). Mechanistic studies were carried out in a mouse model of HS/T that recapitulated the early increase in IL33 and delayed increase in sST2 in the plasma (P < 0.005). These studies identified a pathway where IL33 induces ILC2 activation in the lung within hours of HS/T. ILC2 IL5 up-regulation induces further IL5 expression by CXCR2+ lung neutrophils, culminating in early lung injury. The major limitations of this study are the descriptive nature of the human study component and the impact of the potential differences between human and mouse immune responses to polytrauma. Also, the studies performed did not permit us to make conclusions about the impact of IL33 on pulmonary function. Conclusions These results suggest that IL33 may initiate early detrimental type 2 immune responses after trauma through ILC2 regulation of neutrophil IL5 production. This IL33–ILC2–IL5–neutrophil axis defines a novel regulatory role for ILC2 in acute lung injury that could be targeted in trauma patients prone to early lung dysfunction., In a reverse translation study from a human cohort to a mouse trauma model, Timothy Billiar and colleagues investigate the factors mediating immune dysregulation after severe injury., Author summary Why was this study done? The factors that initiate immune dysregulation after severe injury, including the skewing of the immune system towards type 2 responses, are unknown. Our aim was to determine if interleukin (IL) 33, an alarmin released after tissue injury and a regulator of type 2 immunity, contributes to the early type 2 immune responses after systemic injury. What did the researchers do and find? We measured IL33 and its soluble receptor, soluble suppression of tumorigenicity 2 (sST2), an endogenous antagonist of IL33, in the blood of 472 multiply injured trauma patients. IL33 levels were already markedly elevated on the first blood draw after injury and correlated with increases in IL4, IL5, and IL13 as well as nosocomial infections. Reverse translation experiments using a mouse model of hemorrhagic shock and tissue trauma were carried out to understand the functional link between IL33 and the type 2 cytokine, IL5. IL33 was shown to activate a resident set of innate lymphocytes (group 2 innate lymphoid cells [ILC2]) in the lungs to produce IL5, further leading to neutrophil IL5 production. What do these findings mean? These findings demonstrate the utility of using reverse translation of observations made in humans into mechanistic experimental models that recapitulate key components of the clinical response. IL33 and one of its target cells, ILC2, are identified for the first time as regulators of the early type 2 immune responses after severe injury. The findings include a previously unsuspected role for ILC2 in the regulation of neutrophils and acute lung injury. The findings identify IL33, IL5, or their receptors as potential targets to block early lung injury after polytrauma.

Clinical research characterizing the mechanisms responsible for sex-based outcome differences postinjury remain conflicting. We sought to characterize an X chromosome-linked IRAK-1 (IL-1 receptor-associated kinase) polymorphism as an alternative mechanism responsible for sex differences postinjury. IRAK-1 is key intermediate in the toll-like receptor (TLR) pathway thought to drive inflammation postinjury.A prospective cohort study was performed over a 24-month period. Bluntly injured patients requiring intensive care unit admission were enrolled, whereas patients with isolated brain and spinal cord injuries were excluded. Outcomes of interest included multiple organ failure (MOF, Marshall MOD score5) and mortality. Logistic regression was utilized to determine the independent risk of poor outcome associated with the IRAK-1 variant after controlling for important differences.In an enrolled cohort of 321 patients, the IRAK-1 variant was common (12.5%). Patients with and without the variant were similar in age, injury severity, and 24hr blood transfusion. After controlling for important confounders, the IRAK1 variant was independently associated with more than eightfold (OR = 8.4, P = 0.005, 95% CI: 1.9-37.1) and 11-fold (OR = 11.8, P = 0.037, 95% CI: 1.1-121) greater risk of MOF and mortality, respectively. These differences were most prominent in men, whereas women heterozygous for the variant demonstrated worse outcome in a dose-dependent fashion.The IRAK1 polymorphism is a strong independent predictor of MOF and mortality postinjury and represents a common variant with prognostic potential. These data demonstrate the importance of TLR signaling postinjury and supports that a genetic mechanism may drive sex outcome differences postinjury.

Extremity and soft tissue injuries contribute significantly to inflammation and adverse in-hospital outcomes for trauma survivors; accordingly, we examined the complex association between clinical outcomes inflammatory responses in this setting using in silico tools. Two stringently propensity-matched, moderately/severely injured (Injury Severity Score > 16) patient sub-cohorts of ~30 patients each were derived retrospectively from a cohort of 472 blunt trauma survivors and segregated based on their degree of extremity injury severity (above or below 3 on the Abbreviated Injury Scale). Serial blood samples were analyzed for 31 plasma inflammatory mediators. In addition to standard statistical analyses, Dynamic Network Analysis (DyNA) and Principal Component Analysis (PCA) were used to model systemic inflammation following trauma. Patients in the severe extremity injury sub-cohort experienced longer intensive care unit length of stay (LOS), total LOS, and days on a mechanical ventilator, with higher Marshall Multiple Organ Dysfunction (MOD) Scores over the first 7 days post-injury as compared to the mild/moderate extremity injury sub-cohort. The higher severity cohort had statistically significant elevated lactate, base deficit, and creatine phosphokinase on first blood draw, along with significant changes in multiple circulating inflammatory mediators. DyNA pointed to a sustained role for type 17 immunity in both sub-cohorts, along with IFN-γ in the severe extremity injury group. DyNA network complexity increased over 7 days post-injury in the severe injury group, while generally decreasing over this same time period in the mild/moderate injury group. PCA suggested a more robust activation of multiple pathways in the severe extremity injury group as compared to the mild/moderate injury group. These studies thus point to the possibility of self-sustaining inflammation following severe extremity injury vs. resolving inflammation following less severe extremity injury.

Sepsis is undoubtedly the most clinically challenging disease encountered in critically ill patients. The common consensus defines sepsis as a dysregulated host inflammatory response to an infectious agent (1). Sepsis is associated with mortality rates of around 30%, although these vary according to geographical location (2). There is no specific treatment for patients with sepsis, and management therefore relies on infection control—with source removal and effective antibiotics—along with organ function support (3).

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.Retrospective clinical study and experimental study in mice.Level 1 trauma center and experimental laboratory.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).None in patients. Neutralizing anti-interleukin-17A antibody in mice.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.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.

Extracellular β-nicotinamide adenine dinucleotide (NAD+) is anti-inflammatory. We hypothesized that NAD+ would modulate the anti-inflammatory cytokine Transforming Growth Factor (TGF)-β1. Indeed, NAD+ led to increases in both active and latent cell-associated TGF-β1 in RAW 264.7 mouse macrophages as well as in primary peritoneal macrophages isolated from both C3H/HeJ (TLR4-mutant) and C3H/HeOuJ (wild-type controls for C3H/HeJ) mice. NAD+ acts partially via cyclic ADP-ribose (cADPR) and subsequent release of Ca2+. Treatment of macrophages with the cADPR analog 3-deaza-cADPR or Ca2+ ionophores recapitulated the effects of NAD+ on TGF-β1, whereas the cADPR antagonist 8-Br-cADPR, Ca2+ chelation, and antagonism of L-type Ca2+ channels suppressed these effects. The time and dose effects of NAD+ on TGF-β1 were complex and could be modeled both statistically and mathematically. Model-predicted levels of TGF-β1 protein and mRNA were largely confirmed experimentally but also suggested the presence of other mechanisms of regulation of TGF-β1 by NAD+. Thus, in vitro and in silico evidence points to NAD+ as a novel modulator of TGF-β1.

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.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.

Red blood cell (RBC) transfusion is associated with alterations in systemic concentrations of IL-8/CXCL8 functional homologs in a murine model. Whether RBC transfusion alters systemic neutrophil chemokine concentrations in individuals sustaining traumatic injury is not known. We conducted a retrospective, single-center study of severely injured trauma patients presenting within 12 h of injury with a base deficit greater than 6 and hypotension in the field. Plasma concentrations of 25 chemokines, cytokines, and growth factors were obtained from both transfused (n = 22) and nontransfused (n = 33) groups in the first 48 h following admission. The transfused group (mean RBC units, 2.7 [SD, 1.7]) tended to be older (49.9 [SD, 21.1] vs. 40.4 [SD, 19.9] years, P = 0.10), with a higher percentage of females (40.9% vs. 18.2%, P = 0.06) and a higher Injury Severity Score (27.1 [SD, 12.7] vs. 21.4 [SD, 10.2], P = 0.07). In univariate and multivariate analyses, transfusion was associated with increased hospital and intensive care unit length of stay but not ventilator-free days. Plasma CXCL8 concentrations were higher in the transfused (84 [SD, 88] pg/mL) than the nontransfused group (31 [SD, 21] pg/mL, P = 0.003). Using a linear prediction model to calculate bioanalyte concentrations standardized for age, sex, Injury Severity Score, and admission SBP, we observed that CXCL8 concentrations diverged within 12 h following injury, with the transfused group showing persistently elevated CXCL8 concentrations by contrast to the decay observed in the nontransfused group. Other bioanalytes showed no differences across time. Red blood cell transfusion is associated with persistently elevated neutrophil chemokine CXCL8 concentrations following traumatic injury.

Properly regulated inflammation facilitates recognition and reaction to injury or infection, but inadequate or overly robust inflammation can lead to disease. Sepsis is an inflammatory disease that accounts for nearly 10% of total U.S. deaths, costing more than $17 billion. Acute inflammation in sepsis may evolve too rapidly to be modulated appropriately, and we suggest that therapies should focus not on abolishing inflammation, but rather on attenuating the positive feedback cycle of inflammation/damage/inflammation. In Gram-negative sepsis, bacterial endotoxin causes inflammation and is driven and regulated by the cytokine tumor necrosis factor-α (TNF-α), which is, in turn, negatively regulated via its endogenous inhibitor, soluble TNF-α receptor (sTNFR). We generated stably gene-modified variants of human HepG2 hepatocytes, using lentiviral constructs coding for mouse sTNFR driven by the constitutive cytomegalovirus promoter, and seeded them in a scaled-down, experimental liver bioreactor. When connected to anesthetized, cannulated rats subjected to endotoxin infusion and maintained solely by the animals’ circulation, this biohybrid device elevated circulating sTNFR, reduced the levels of TNF-α and other key inflammatory mediators, alleviated hypotension, and reduced circulating markers of organ damage. This novel class of biohybrid devices may bemodified for patient- and disease-specific application, and, thus, may represent a disruptive strategy that offers the potential for rational inflammation reprogramming.

Sepsis is a clinical entity in which complex inflammatory and physiological processes are mobilized, not only across a range of cellular and molecular interactions, but also in clinically relevant physiological signals accessible at the bedside. There is a need for a mechanistic understanding that links the clinical phenomenon of physiologic variability with the underlying patterns of the biology of inflammation, and we assert that this can be facilitated through the use of dynamic mathematical and computational modeling. An iterative approach of laboratory experimentation and mathematical/computational modeling has the potential to integrate cellular biology, physiology, control theory, and systems engineering across biological scales, yielding insights into the control structures that govern mechanisms by which phenomena, detected as biological patterns, are produced. This approach can represent hypotheses in the formal language of mathematics and computation, and link behaviors that cross scales and domains, thereby offering the opportunity to better explain, diagnose, and intervene in the care of the septic patient.

Background Aging is accompanied by alterations in immune functions. How these changes translate into levels of circulating inflammatory mediators and network expression after severe trauma is not well characterized. To address this, we compared time-dependent changes in the levels of an extensive biomarker panel in cohorts of severely injured young and aged adults. Study Design Cohorts of young (18 to 30 years old, n = 115) and aged (65 to 90 years old, n = 101) blunt trauma patients admitted to the ICU with plasma sampled 3 times within the first 24 hours and daily from day 1 to day 7 were assayed for 30 inflammatory biomarkers using Luminex analyzer. Stringently matched groups controlling for sex ratio and Injury Severity Score (n = 56 young vs n = 56 aged) were generated. Data were analyzed using 2-way ANOVA, area under the curve analysis, Dynamic Bayesian Network inference, and Dynamic Network Analysis. Results In the overall cohorts, the young group had a significantly higher Injury Severity Score, which was associated with higher circulating levels of 18 inflammatory mediators from admission to day 7. The aged group had higher levels of C-X-C motif chemokine ligand 10/interferon gamma-induced protein 10 and C-X-C motif chemokine ligand 9/monokine induced by gamma interferon. In groups that were matched for Injury Severity Score, the significantly higher levels of interferon gamma-induced protein 10 and monokine induced by gamma interferon persisted in the aged. Dynamic Bayesian Network revealed interferon gamma-induced protein 10 and monokine induced by gamma interferon as key mediators in the aged, and Dynamic Network Analysis revealed higher network complexity in the aged. Conclusions These findings indicate that differences in the early inflammatory networks between young and aged trauma patients are not simply a suppression of pro-inflammatory responses in the aged, but are characterized by a major shift in the mediator profile patterns with high levels of CXC chemokines in the aged.

Trauma-induced critical illness is driven by acute inflammation, and elevated systemic interleukin-6 (IL-6) after trauma is a biomarker of adverse outcomes. We constructed a multicompartment, ordinary differential equation model that represents a virtual trauma patient. Individual-specific variants of this model reproduced both systemic inflammation and outcomes of 33 blunt trauma survivors, from which a cohort of 10,000 virtual trauma patients was generated. Model-predicted length of stay in the intensive care unit, degree of multiple organ dysfunction, and IL-6 area under the curve as a function of injury severity were in concordance with the results from a validation cohort of 147 blunt trauma patients. In a subcohort of 98 trauma patients, those with high-IL-6 single-nucleotide polymorphisms (SNPs) exhibited higher plasma IL-6 levels than those with low IL-6 SNPs, matching model predictions. Although IL-6 could drive mortality in individual virtual patients, simulated outcomes in the overall cohort were independent of the propensity to produce IL-6, a prediction verified in the 98-patient subcohort. In silico randomized clinical trials suggested a small survival benefit of IL-6 inhibition, little benefit of IL-1β inhibition, and worse survival after tumor necrosis factor-α inhibition. This study demonstrates the limitations of extrapolating from reductionist mechanisms to outcomes in individuals and populations and demonstrates the use of mechanistic simulation in complex diseases.

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.—Wang, J., Vodovotz, Y., Fan, L., Li, Y., Liu, Z., Namas, R., Barclay, D., Zamora, R., Billiar, T. R., Wilson, M. A., Fan, J., Jiang, Y. Injury-induced MRP8/MRP14 stimulates IP-10/CXCL10 in monocytes/macrophages.

Blunt trauma and traumatic spinal cord injury induce systemic inflammation that contributes to morbidity. Dysregulated neural control of systemic inflammation postinjury is likely exaggerated in patients with traumatic spinal cord injury. We used in silico methods to discern dynamic inflammatory networks that could distinguish systemic inflammation in traumatic spinal cord injury from blunt trauma.Retrospective study.Tertiary care institution.Twenty-one severely injured thoracocervical traumatic spinal cord injury patients and matched 21 severely injured blunt trauma patients without spinal cord injury.None.Serial blood samples were obtained from days 1 to 14 postinjury. Twenty-four plasma inflammatory mediators were quantified. Statistical significance between the two groups was determined by two-way analysis of variance. Dynamic Bayesian network inference was used to suggest dynamic connectivity and central inflammatory mediators. Circulating interleukin-10 was significantly elevated in thoracocervical traumatic spinal cord injury group versus non-spinal cord injury group, whereas interleukin-1β, soluble interleukin-2 receptor-α, interleukin-4, interleukin-5, interleukin-7, interleukin-13, interleukin-17, macrophage inflammatory protein 1α and 1β, granulocyte-macrophage colony-stimulating factor, and interferon-γ were significantly reduced in traumatic spinal cord injury group versus non-spinal cord injury group. Dynamic Bayesian network suggested that post-spinal cord injury interleukin-10 is driven by inducible protein-10, whereas monocyte chemotactic protein-1 was central in non-spinal cord injury dynamic networks. In a separate validation cohorts of 356 patients without spinal cord injury and 85 traumatic spinal cord injury patients, individuals with plasma inducible protein-10 levels more than or equal to 730 pg/mL had significantly prolonged hospital and ICU stay and days on mechanical ventilator versus patients with plasma inducible protein-10 level less than 730 pg/mL.This is the first study to compare the dynamic systemic inflammatory responses of traumatic spinal cord injury patients versus patients without spinal cord injury, suggesting a key role for inducible protein-10 in driving systemic interleukin-10 and morbidity and highlighting the potential utility of in silico tools to identify key inflammatory drivers.

Extracellular β-nicotinamide adenine dinucleotide (NAD(+)) is anti-inflammatory. We hypothesized that NAD(+) would modulate the anti-inflammatory cytokine Transforming Growth Factor (TGF)-β1. Indeed, NAD(+) led to increases in both active and latent cell-associated TGF-β1 in RAW 264.7 mouse macrophages as well as in primary peritoneal macrophages isolated from both C3H/HeJ (TLR4-mutant) and C3H/HeOuJ (wild-type controls for C3H/HeJ) mice. NAD(+) acts partially via cyclic ADP-ribose (cADPR) and subsequent release of Ca(2+). Treatment of macrophages with the cADPR analog 3-deaza-cADPR or Ca(2+) ionophores recapitulated the effects of NAD(+) on TGF-β1, whereas the cADPR antagonist 8-Br-cADPR, Ca(2+) chelation, and antagonism of L-type Ca(2+) channels suppressed these effects. The time and dose effects of NAD(+) on TGF-β1 were complex and could be modeled both statistically and mathematically. Model-predicted levels of TGF-β1 protein and mRNA were largely confirmed experimentally but also suggested the presence of other mechanisms of regulation of TGF-β1 by NAD(+). Thus, in vitro and in silico evidence points to NAD(+) as a novel modulator of TGF-β1.

The translation of in vitro findings to clinical outcomes is often elusive. Trauma/hemorrhagic shock (T/HS) results in hepatic hypoxia that drives inflammation. We hypothesize that in silico methods would help bridge in vitro hepatocyte data and clinical T/HS, in which the liver is a primary site of inflammation. Primary mouse hepatocytes were cultured under hypoxia (1% O2) or normoxia (21% O2) for 1–72 h, and both the cell supernatants and protein lysates were assayed for 18 inflammatory mediators by Luminex™ technology. Statistical analysis and data-driven modeling were employed to characterize the main components of the cellular response. Statistical analyses, hierarchical and k-means clustering, Principal Component Analysis, and Dynamic Network Analysis suggested MCP-1/CCL2 and IL-1α as central coordinators of hepatocyte-mediated inflammation in C57BL/6 mouse hepatocytes. Hepatocytes from MCP-1-null mice had altered dynamic inflammatory networks. Circulating MCP-1 levels segregated human T/HS survivors from non-survivors. Furthermore, T/HS survivors with elevated early levels of plasma MCP-1 post-injury had longer total lengths of stay, longer intensive care unit lengths of stay, and prolonged requirement for mechanical ventilation vs. those with low plasma MCP-1. This study identifies MCP-1 as a main driver of the response of hepatocytes in vitro and as a biomarker for clinical outcomes in T/HS, and suggests an experimental and computational framework for discovery of novel clinical biomarkers in inflammatory diseases.

We combined in silico, in vivo, and in vitro studies to gain insights into age-dependent changes in acute inflammation in response to bacterial endotoxin (LPS). Time-course cytokine, chemokine, and NO2 (-/)NO3 (-) data from "middle-aged" (6-8 months old) C57BL/6 mice were used to re-parameterize a mechanistic mathematical model of acute inflammation originally calibrated for "young" (2-3 months old) mice. These studies suggested that macrophages from middle-aged mice are more susceptible to cell death, as well as producing higher levels of pro-inflammatory cytokines, vs. macrophages from young mice. In support of the in silico-derived hypotheses, resident peritoneal cells from endotoxemic middle-aged mice exhibited reduced viability and produced elevated levels of TNF-α, IL-6, IL-10, and KC/CXCL1 as compared to cells from young mice. Our studies demonstrate the utility of a combined in silico, in vivo, and in vitro approach to the study of acute inflammation in shock states, and suggest hypotheses with regard to the changes in the cytokine milieu that accompany aging.

13 Combined network and mathematical modeling suggests novel inflammation positive feedback circuit and role for IL-1 in experimental trauma/hemorrhage and hepatocyte hypoxia Nabil Azhar, Rami Namas, Bahiyyah Jefferson, Derek Barclay, Ruben Zamora, Yoram Vodovotz University of Pittsburgh, Pittsburgh, PA, USA Objectives: Trauma/hemorrhagic shock (T/HS) is the most common cause of death for young people in the United States, costing more than $400 billion annually. Most deaths from T/HS occur due to the multiple organ dysfunction syndrome. Multiple organ dysfunction syndrome is thought to be due, in part, to dysregulated inflammation. We have used computational modeling to define key networks and mechanisms of post-T/HS acute inflammation. We used a Dynamic Bayesian Network (DBN) algorithm (adapted from Grzegorczyk and Husmeier, Bioinformatics 2010;27:693). Given time-series data, DBNs provide a way of inferring causal relationships based on probabilistic measures. This approximation helps to suggest the overall network structure, including central nodes that exhibit feedback. Methods: C57Bl/6 mice were subjected to T/HS for 0 to 4 hours. Separately, C57Bl/6 hepatocytes were subjected to an in vitro surrogate of T/HS, namely, hypoxia (culture at 1% O2 for 1 to 72 hours). Cytokines/chemokines were assayed in the plasma (in vivo T/HS) as well as supernatants and lysates (in vitro hypoxia) by Luminex (MiraiBio, Alameda, CA), and the data were subjected to DBN analysis. Results: Dynamic Bayesian Network analysis suggested a core network that involves the cytokines IL-10 and IL-1α, as well as the chemokines IP-10 and MIG. Assigning biologically plausible functions to directed edges of the network resulted in a so-called incoherent type I feed forward loop that predicted pulsatile, “gatekeeper” behavior for the cytokine IL-1α—a behavior that was indeed observed in preliminary studies in mice subjected to T/ HS. An initial ordinary differential equation (ODE) model was constructed to analyze this behavior in further detail. Simulated trajectories of cytokines and chemokines in the ODE model corresponded closely with the data. Conclusions: Data-driven (DBN) and mechanistic (ODE) analyses suggest a novel inflammatory circuit with a central role for IL-1α in T/HS and hepatocyte hypoxia. http://dx.doi.org/10.1016/j.jcrc.2012.10.029

Sepsisis a clinical syndrome characterized by a multi-system response to a microbial pathogenic insult consisting of a mosaic of interconnected biochemical, cellular, and organ-organ interaction networks. A central thread that connects these responses is inflammation, which, while attempting to defend the body and prevent further harm, causes further damage through the feed-forward, pro-inflammatory effects of damage-associated molecular pattern molecules. In this review, we address the epidemiology and current definitions of sepsis, and focus specifically on the biological cascades that comprise the inflammatory response to sepsis. We suggest that attempts to improve clinical outcomes by targeting specific components of this network have been unsuccessful due to the lack of an integrative, predictive, and individualized systems-based approach to define the time-varying, multi-dimensional state of the patient. We highlight the translational impact of computational modeling and other complex systems approaches as applied to sepsis, including in silico clinical trials, patient-specific models, and complexity-based assessments of physiology.

Results: Sevoflurane pharmacodynamic was in close agreement with a sigmoid dose-response relationship for SEF95 (correlation coefficient r = 0.62 ± 0.17), FD (r = 0.73 ± 0.11), and H (r = 0.78 ± 0.12). The probability of H to predict sevoflurane effectside concentration (Pk = 0.86 ± 0.05) was significantly higher (P b .05) as compared with FD (Pk = 0.81 ± 0.06) or SEF95 (Pk = 0.76 ± 0.08). Conclusions: The Hurst coefficient is superior to fractal dimension and spectral edge frequency in predicting the depth of sevoflurane anesthesia. Nonlinear EEG analysis seems to be a promising tool to improve the monitoring of anesthetic depth and to investigate anesthesia-related EEG decomplexification.