Lactacidosis impairs energy homeostasis of primary vascular smooth muscle cells - possible pathomechanisms during septic vasoplegia
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA937762 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23592679_1.fastq.gz | Fastqsanger.gz | |||
| SRR23592679_2.fastq.gz | Fastqsanger.gz | |||
| SRR23592680_1.fastq.gz | Fastqsanger.gz | |||
| SRR23592680_2.fastq.gz | Fastqsanger.gz | |||
| SRR23592681_1.fastq.gz | Fastqsanger.gz |
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Project description:RNAsequencing was performed for human primary aortic smooth muscle cells (HAoSMCs) from male donors, after incubation at pH 7.4 (control condition or with Na+-Lactate) or at pH 6.8 (ajusted with HCl or lactic acid).
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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.
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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. Keywords: Septic shock, SIRS, pediatrics, outcome, infection, inflammation
2006-04-30 | GSE4607 | GEO
Project description:In an ongoing translational research program involving microarray-based expression profiles in pediatric septic shock, we have now conducted longitudinal studies focused on the temporal expression profiles of canonical signaling pathways and gene networks. Genome-level expression profiles were generated from whole blood-derived RNA samples of children with septic shock (n = 30 individual patients) corresponding to days 1 and 3 of admission to the pediatric intensive care unit. Based on sequential statistical and expression filters, day 1 and day 3 of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to normal control patients. Venn analysis demonstrated 239 unique genes in the day 1 data set, 598 unique genes in the day 3 data set, and 1,906 genes common to both data sets. Analyses targeted toward derivation of biological function from these data sets demonstrated time-dependent, differential regulation of genes involved in multiple canonical signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biological processes were persistently downregulated from day 1 to day 3. Further analyses demonstrated large scale and persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock, which has undergone longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses that can be readily tested at both the experimental and translational levels. Keywords: Inflammation; sepsis; innate immunity; T cells; MHC antigen Keywords: to be updated
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Project description:TLRs are considered important for innate immune responses that combat bacterial infections. Here, the role of TLRs in severe septic peritonitis using the colon ascendens stent peritonitis (CASP) model was examined. We demonstrate that mice deficient for MyD88 and TRIF had markedly reduced bacterial numbers both in peritoneal cavity and peripheral blood, indicating that bacterial clearance in this model is inhibited by TLR signals. Moreover, survival of Myd88-/-;TrifLps2/Lps2 mice was significantly improved. The lack of TLR signals prevented the excessive induction of inflammatory cytokines and of IL 10. Notably, the expression of IFN-gamma, which has an essential protective role in septic peritonitis, and of IFN-regulated genes including several p47 and p65 GTPases as well as IP 10 was independent of TLR signaling. These results provide evidence that, in severe septic peritonitis, TLR deficiency balances the innate immune response in a favorable manner by attenuating deleterious responses such as excessive cytokine release, while leaving intact protective IFN-gamma production. In this dataset, expression data of genes induced by septic peritonitis in spleens from TLR-deficient and wildtype mice are included. 3 groups (septic TLR-deficient mice, septic wildtype mice, and untreated wildtype mice) with 4 replicates each.
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Project description:Background: Septic shock heterogeneity has important implications for the conduct of clinical trials and individual patient management. We previously addressed this heterogeneity by indentifying 3 putative subclasses of children with septic shock based on a 100-gene expression signature corresponding to adaptive immunity and glucocorticoid receptor signaling. Herein we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort. Methods: Gene expression mosaics were generated from the 100 class-defining genes for 82 individual patients in the validation cohort. Patients were classified into 1 of 3 subclasses (“A”, “B”, or “C”) based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. Separate classifications were conducted by 21 individual clinicians and a computer-based algorithm. After subclassification the clinical database was mined for clinical phenotyping. Results: In the final consensus subclassification generated by clinicians, subclass A patients had a higher illness severity, as measured by illness severity scores and maximal organ failure, relative to subclasses B and C. The k coefficient across all possible inter-evaluator comparisons was 0.633. Similar observations were made based on the computer-generated subclassification. Patients in subclass A were also characterized by repression of a large number of genes having functional annotations related to zinc biology. Conclusions: We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses can be indentified by clinicians without formal bioinformatics training, at a clinically relevant time point, and have clinically relevant phenotypic differences. Expression data from 82 children with septic shock and 21 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data from 100 class defining genes to validate the existence of pediatric septic shock subclasses having phenotypic differences.
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