Project description:Background: Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. To date, no biomarker has shown sufficient evidence and ease of application in clinical routine to monitor the complexity of the sepsis-related immune alterations. Multiple levels of interaction of human endogenous retroviruses (HERVs) with the immune response led us to hypothesize that they may be relevant candidates both to contribute to the physiopathology of sepsis and to be part of a molecular signature. In this study, we used a recently described high-density microarray which allows exploring HERVs/MaLRs transcriptome in septic shock patients. Results: About 6.9% of the HERVs/MalRs repertoire is transcribed in whole blood. Concerning the functionality of LTRs, the majority of LTRs are silent (62.9%), 7.5% of LTRs present a putative constitutive promoter or polyA functions, while 20.4% of them may shift from silent to active. Evidence was given that a subset of HERVs/MaLRs and genes were modulated in septic shock patients according to the monocyte HLA-DR (mHLA-DR) expression level measured by flow cytometry, as a proxy of immunosuppression. We then identified a large signature consisting of 193 differentially expressed HERVs/MaLRs probesets further reduced to a smaller 10 HERVs/MaLRs signature. Both signatures, validated in an independent septic shock cohort, identified two groups of patients with different severity features including clinical criteria and the CD74 and CX3CR1 sepsis severity molecular markers. Conclusion: This microarray-based approach unveiled the expression of about 87,912 distinct HERV probesets and identified 764 putative promoter LTRs and 642 putative polyA LTRs in whole blood. HERV/MaLR expression was shown to be tightly modulated in septic shock patients according to mHLA-DR expression. We identified a set of potential molecular biomarkers in septic shock patients partially overlapping immunosuppression (mHLA-DR), and the risk of Health Care associated Infections (HAI) (CD74 ratio), complementary to existing molecular markers of a sepsis patients stratification. We identified a HERV/MaLR signature discriminating patients based on their immunosuppression state and severity.

Project description:Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients. Background: We measured gene expression levels and profiles of children with systemic inflammatory response syndrome (SIRS) and septic shock as a means for discovering patient sub-groups and gene signatures that are active in disease-affected individuals and potentially in patients with poor outcomes. Methods: Microarray and bioinformatics analyses of 123 microarray chips representing whole blood derived RNA from controls, children with SIRS, and children with septic shock. Results: A discovery-based filtering approach was undertaken to identify genes whose expression levels were altered in patients with SIRS or septic shock. Clustering of these genes identified 3 Major and several minor sub-groups of patients with SIRS or septic shock. The three groups differed with respect to incidence of septic shock and trended toward differences in mortality. Statistical analyses demonstrated that 6,435 gene probes were differentially regulated between the three patient sub-groups (false discovery rate < 0.001%). Of these gene probes, 623 gene probes within 7 major gene ontologies accounted for the majority of group differentiation. Network analyses of these 623 gene probes demonstrated 5 major gene networks that were differentially expressed between the 3 groups. Statistical comparison of septic shock survivors and non-survivors identified one major gene network that was under expressed in a high fraction of the non-survivors and identified potential biomarkers for poor outcome. Conclusions: This is the first genome-level demonstration of pediatric patient sub-groups with SIRS and septic shock. The sub-groups differ clinically and differentially express 5 major gene networks. We have identified gene signatures and potential biomarkers associated with poor outcome in children with septic shock. These data represent a major advancement in our genome-level understanding of pediatric SIRS and septic shock. Experiment Overall Design: Children < 10 years of age admitted to the pediatric intensive care unit and meeting the criteria for either SIRS or septic shock were eligible for the study. SIRS and septic shock were defined based on pediatric-specific criteria. We did not use separate categories of "sepsis" or "severe sepsis". Patients meeting criteria for "sepsis" or "severe sepsis" were placed in the categories of SIRS and septic shock, respectively, for study purposes. Control patients were recruited from the outpatient or inpatient departments of the participating institutions using the following exclusion criteria: a recent febrile illness (within 2 weeks), recent use of anti-inflammatory medications (within 2 weeks), or any history of chronic or acute disease associated with inflammation. Experiment Overall Design: After obtaining informed consent, blood samples were obtained on Day 1 of the study, and when possible on Day 3 of the study. Blood samples were divided for RNA extraction and isolation of serum. Severity of illness was calculated based on the PRISM III score. Organ failure was defined based on pediatric-specific criteria. Annotated clinical and laboratory data were collected daily while in the intensive care unit. Study patients were placed in the study categories of SIRS or Septic Shock on Day 1 of the study. On Day 3 of the study, patients were classified as SIRS, Septic Shock, or SIRS resolved (no longer meeting criteria for SIRS). All study patients were followed for 28 days to determine mortality or survival. Clinical, laboratory, and biological data were entered and stored using a web-based data base developed locally.

Dataset Information

Polymorphonuclear cells show features of dysfunctional activation during fatal sepsis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets