Transcriptomic profiling of the inflammatory response after trauma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE70311 | GEO | 2015/11/01
SECONDARY ACCESSION(S): PRJNA288295
REPOSITORIES: GEO
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Project description:The study was aimed to identify mechanisms linked to complicated courses after severe trauma by a systems biology approach. In severe trauma, overwhelming systemic inflammation can result in adverse events and the development of complications, including sepsis. In a prospective study, RNA samples from circulating leukocytes from patients with multiple injury (injury severity score ⥠17) were analyzed for dynamic changes in gene expression over a period of 21 days by whole genome screening. Based on their clinical presentation, patients were divided into two subgroups: patients with secondary sepsis after trauma (n=5) and patients with systemic inflammation without infection (n=5). Expression cluster were defined by correlating gene expression data with clinical outcome parameters. Using unsupervised clustering, patients with systemic inflammation only and patients with sepsis showed a distinct expression pattern and the discrimination of clinical presentation was reflected by clustering of the samples. Explorative gene set analysis revealed robust upregulation of genes related to âhemoglobin metabolism/oxygen transportâ and âpathogenic E.coli infectionâ. 10 patients with multi-system trauma (ISS ⥠17 points) admitted to the Division of Trauma Surgery at the University Hospital Zurich were included. Whole blood from trauma patients was collected within the first 6 h after trauma (day 0) and on days 1, 2, 3, 5, 7, 10, 14, and 21. Total cellular RNA from circulating leukocytes was isolated using PaxGene Blood RNA Kit (PreAnalytix) for transcriptome profiling. RNA from blood of trauma patients was extracted and subjected to microarray analysis for comparison of longitudinal transcriptomic responses of patients. RNA samples of circulating leukocytes covering time points directly after admission (D0) and on the consecutive days (D1-D21) were subject to multifactorial microarray data analysis: Differences in dynamics of transcripts were assessed by contrasting time- and individual-resolved changes for sepsis and systemic inflammation without infection.
2015-11-01 | E-GEOD-70311 | biostudies-arrayexpress
Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20). This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. The GEO data represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).
2011-11-01 | E-GEOD-28750 | biostudies-arrayexpress
Project description:To investigate immunologic alterations taking place in patients with nosocomial sepsis, we undertook genomic expression analysis of white blood cells (WBC) using DNA microarrays in a small sample of trauma patients who developed severe sepsis/septic shock during their ICU stay and compared with trauma patients with uncomplicated sepsis. RNA was extracted from blood obtained upon admission (a) and at the onset of the disease (b).
2012-08-01 | E-MEXP-3621 | biostudies-arrayexpress
Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).
2011-11-01 | GSE28750 | GEO
Project description:Early diagnosis of sepsis and discrimination from SIRS is crucial for clinicians to provide appropriate care, management and treatment to critically ill patients. Here, we describe identification of transcriptional mRNA biomarkers able to identify severe systemic inflammation and differentiate Sepsis from SIRS, in adult patients within a multi-center clinical study. All patients were recruited in Intensive Care Units (ICUs) from multiple UK hospitals including 59 patients with abdominal sepsis, 84 patients with pulmonary sepsis, 42 SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), at four time points including 30 healthy control donors. Multiple clinical parameters were measured, including SOFA score etc., with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using PBL mRNA microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools. Nineteen select high-performance, differentially-expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed ‘indicators of inflammation’ (IoI), including CD177, FAM20A and OLAH. Combinations of these were trialed. Best-performing minimal panels e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (ROC/AUC>0.99). Twenty select entities were differentially-expressed between sepsis and SIRS (FC>2.0, p-value<0.05), termed ‘SIRS or Sepsis’ (SoS) biomarkers. Panels of biomarkers able to differentiate sepsis from SIRS were also identified and performance assessed using AUCROC. The best performing panel was CMTM5/CETP/PLA2G7/MIA/MPP3 using our dataset (AUCROC=0.9758). The IoI and SoS signatures were evaluated on other independent gene expression datasets, with some reduced performance observed, which maybe in part due to study/platform technical variation.
2024-01-08 | GSE236713 | GEO
Project description:BACKGROUND: Despite best supportive intensive care, the development of severe sepsis and septic shock after trauma is still associated with a high mortality rate in intensive care units (ICU). Incomplete knowledge of the pathophysiological and biochemical mechanisms that lead to perturbations of the host system is a major cause for this clinical entity. This lack of knowledge is mirrored in a delay in both diagnosis of sepsis and stratification of patients at risk. The current diagnostic and classification methods do not provide an early and reliable evidence for the development of sepsis and consequently lead to uncertainty in the classification and a delay in the initiation of an adequate therapy. Here, we present a prospective study performed with a well-defined patient cohort suffering from severe multiple trauma (n=85), in which we aimed to uncover the biological reasons why patients with multiple trauma can have dramatically different outcomes after suffering similar traumatic insults. METHODS: We used peripheral whole blood obtained with the PaxGene system at the time of admission to the ICU, i.e., 12 hours after trauma, for transcriptome analysis and monitored clinically the sequence of events from the admission to the ICU, to the very onset of sepsis and finally to the full development of multiple organ dysfunction syndrome (MODS). Study protocols and standard operating procedures (SOPs) regarding ethics, patient recruitment, logistics in sample acquisition and storage, microarray experiments, data analysis and data management have been developed and provided for a high feasibility and reproducibility of the investigations. FINDINGS: The transcriptome analysis from peripheral blood revealed a strong host response upon severe injury and demonstrated the suitability of whole blood in the PaxGene system as a surrogate marker in clinical gene expression studies. It was evident that patients who developed sepsis in the course of the disease (3-5 days after admission) showed an imbalance in the TH1/TH2 response towards a pronounced TH2 response, soon after trauma. The imbalanced TH1/TH2 shift along with inactivation of T cells, neutrophils, monocytes and macrophages might be critical factors for the initiation of a septic program seen in these patients 12 hours after trauma. INTERPRETATION: First, in this study, we provide protocols for logistics and infrastructure that can be applied generally to successfully integrate gene expression analysis studies in a clinical routine and demonstrate that by following these protocols, dedicated and reproducible results can be obtained. Second, we showed that peripheral whole blood is a suitable surrogate marker for the host response as it contains lots of “information” and is easily accessible. Third, we identified mechanisms involved in the perturbations of the immune system that lead to sepsis. Keywords: Prospective study 159 consecutive traumatized patients were included in the study upon admission to the intensive care unit (ICU), fulfilling all of the following inclusion criteria: severe injuries to at least two body regions or three major fractures, between 18 and 65 years of age, an estimated Injury Severity Score (ISS) of ?15 points after thorough assessment of injuries, <12 hours between the occurrence of the accident and the time of admission to the ICU, and at least greater than 3 days of survival. None of the patients underwent neuro- or cardiac surgery. We excluded patients with severe intracranial head injuries, coagulation abnormalities known at the day of admission to the ICU, acute renal failure, liver failure, malignant disease, or hemofiltration in the patient`s history. The Patients were divided into two groups depending on their posttraumatic course: Patients not complicatd by sepsis (Group: N) and Patients complicated by sepsis (Group: S). Using the CodeLink UniSet Human 10 K Bioarrays (GE Healthcare, Freiburg, Germany), we searched for early differences in the transcriptome of these two groups. Only whole blood samples drawn upon admission to the ICU were used for this investigation. Microarray results were validated by quantification of mRNA by TaqMan® technology. Each patient sample was hybridized in duplicate or triplicate on microarrays (label-extract technical replicate). A total of 72 arrays (36 group N, 36 group S) were subjected to microarray quality analysis. Of these, 2 arrays (0 group N, 2 group S) were excluded from the data set due to quality reasons and a final set of 70 arrays (36 group N and 34 group S) were subjected to microarray analysis. Since the eliminated 2 arrays belonged to patients with three replicates, they were treated as two replicates in the further analysis. The arrays were designated N_xx_yy_z or S_xx_yy_z, with x for the patient-ID (1,2,3,4..) and z for the technical replicate number (1,2 or 3).
2010-12-22 | E-GEOD-12624 | biostudies-arrayexpress
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress
Project description:There is currently no reliable tool available to measure immune dysfunction in septic patients in the clinical setting. This proof-of-concept study assesses the potential of gene expression profiling of whole blood as a tool to monitor immune dysfunction in critically ill septic patients. Whole blood samples were collected daily for up to 5 days from patients admitted to the intensive care unit with sepsis. RNA isolated from whole blood samples was assayed on Illumina HT-12 gene expression microarrays consisting of 48,804 probes. Microarray analysis identified 3677 genes as differentially expressed across 5 days between septic patients and healthy controls. Of the 3677 genes, biological pathway analysis identified 86 genes significantly down-regulated in the sepsis patients were present in pathways relating to immune response. These 86 genes correspond to known immune pathways implicated in sepsis including lymphocyte depletion, reduced T lymphocyte activation and deficient antigen presentation. Furthermore, expression levels of these genes correlated with clinical severity, with a significantly greater degree of down-regulation found in non-survivors compared to survivors. The results show that whole blood gene-expression analysis can capture systemic immune dysfunctions in septic patients. Our study provides an experimental basis to support further study on the use of a gene expression based assay, to assess immunosuppression and guide immunotherapy in future clinical trials. Daily PAXgene samples for up to 5 days for sepsis survivors (n=26), sepsis nonsurvivors (n=9), and healthy controls (n=18).
2014-02-04 | E-GEOD-54514 | biostudies-arrayexpress
Project description:BACKGROUND: Despite best supportive intensive care, the development of severe sepsis and septic shock after trauma is still associated with a high mortality rate in intensive care units (ICU). Incomplete knowledge of the pathophysiological and biochemical mechanisms that lead to perturbations of the host system is a major cause for this clinical entity. This lack of knowledge is mirrored in a delay in both diagnosis of sepsis and stratification of patients at risk. The current diagnostic and classification methods do not provide an early and reliable evidence for the development of sepsis and consequently lead to uncertainty in the classification and a delay in the initiation of an adequate therapy. Here, we present a prospective study performed with a well-defined patient cohort suffering from severe multiple trauma (n=85), in which we aimed to uncover the biological reasons why patients with multiple trauma can have dramatically different outcomes after suffering similar traumatic insults. METHODS: We used peripheral whole blood obtained with the PaxGene system at the time of admission to the ICU, i.e., 12 hours after trauma, for transcriptome analysis and monitored clinically the sequence of events from the admission to the ICU, to the very onset of sepsis and finally to the full development of multiple organ dysfunction syndrome (MODS). Study protocols and standard operating procedures (SOPs) regarding ethics, patient recruitment, logistics in sample acquisition and storage, microarray experiments, data analysis and data management have been developed and provided for a high feasibility and reproducibility of the investigations. FINDINGS: The transcriptome analysis from peripheral blood revealed a strong host response upon severe injury and demonstrated the suitability of whole blood in the PaxGene system as a surrogate marker in clinical gene expression studies. It was evident that patients who developed sepsis in the course of the disease (3-5 days after admission) showed an imbalance in the TH1/TH2 response towards a pronounced TH2 response, soon after trauma. The imbalanced TH1/TH2 shift along with inactivation of T cells, neutrophils, monocytes and macrophages might be critical factors for the initiation of a septic program seen in these patients 12 hours after trauma. INTERPRETATION: First, in this study, we provide protocols for logistics and infrastructure that can be applied generally to successfully integrate gene expression analysis studies in a clinical routine and demonstrate that by following these protocols, dedicated and reproducible results can be obtained. Second, we showed that peripheral whole blood is a suitable surrogate marker for the host response as it contains lots of “information” and is easily accessible. Third, we identified mechanisms involved in the perturbations of the immune system that lead to sepsis. Keywords: Prospective study
2010-12-22 | GSE12624 | GEO
Project description:Sepsis remains a lethal ailment with imprecise treatment and ill-understood biology. A clinical transcriptomic analysis of sepsis patients was performed for the first time in India and revealed large-scale change in blood gene expression in patients of severe sepsis and septic shock admitted to ICU. Three biological processes were quantified using scores derived from the corresponding transcriptional modules. Comparison of the module scores revealed that genes associated with immune response were more suppressed compared to the inflammation-associated genes. These findings will have great implication in the treatment and prognosis of severe sepsis/septic shock if translated into a bedside tool.
2022-09-12 | GSE137340 | GEO