Sepsis diagnostics using MinION
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB28340 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2752910.fastq.gz | Fastqsanger.gz | |||
| ERR2752911.fastq.gz | Fastqsanger.gz | |||
| ERR2752912.fastq.gz | Fastqsanger.gz | |||
| ERR2752913.fastq.gz | Fastqsanger.gz | |||
| ERR2752914.fastq.gz | Fastqsanger.gz |
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Project description:Enhanced performance of next-generation sequencing diagnostics compared to standard of care microbiological diagnostics in patients suffering from septic shock
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Project description:Molecular Diagnostics in Sepsis: from Bedside to Bench
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Project description:Background: Severe septic syndromes deeply impair innate and adaptive immunity. While neutrophils represent the first line of defense against infection, little is known about their phenotype and functions during sepsis-induced immunosuppression. The objective of this study was thus to perform for the first time a global evaluation of neutrophil alterations in immunosuppressed septic patients based on phenotypic, functional and transcriptomic studies. In addition, the potential association of these parameters and deleterious outcomes was assessed. Methods: Peripheral blood was collected from 9 septic shock patients at D3-4 and D6-8 presenting with features of sepsis-induced immunosuppression and compared to 8 healthy controls. Results: In order to get on overview of potential neutrophil alterations after sepsis, we performed transcriptomic analyses on purified neutrophils from 9 septic shock patients and 8 healthy volunteers. For each time point, comparisons were made between patients and controls. Venn diagrams indicated that 364 up-regulated genes and 328 down-regulated genes were common between the two analyses (Supplementary Tables 1 and 2). Interestingly, most of the differentially expressed genes are involved in cell maturation (CD177), apoptosis (STK4, Caspase 8), cell recruitment and chemotaxis (CD44, TPST, MMP9, CREB1), and antimicrobial properties (ARG1, STOM, ADAM9, CD63, YKL40) of neutrophils. Conclusions: The aim of the current study was to perform an extensive investigation of neutrophil alterations during sepsis-induced immunosuppression through phenotypic, functional and transcriptomic studies. Notably, transcriptomic study on purified neutrophils revealed differentially expressed genes between septic patients and healthy volunteers.
2015-12-28 | GSE64457 | GEO
Project description:Normal children, children with SIRS, children with sepsis, and children with septic shock. Objectives: To advance our biological understanding of pediatric septic shock, we measured the genome-level expression profiles of critically ill children representing the systemic inflammatory response syndrome (SIRS), sepsis, and septic shock spectrum. Experiment Overall Design: Prospective observational study involving microarray-based bioinformatics.
2009-01-05 | E-GEOD-13904 | biostudies-arrayexpress
Project description:Mobile And Real-time PLant disEase (MARPLE) diagnostics for strain-level identification of wheat yellow rust
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Project description:Using the highly sensitive miRNA array, we screened 40 miRNAs were differentially expressed among the three groups and we explored the functions of these miRNAs in the serum by Gene Ontology and Kyoto Encyclopedia of Genes annotation. The enrichment results indicated that these miRNAs mainly participated in the oxidative stress and mitochondrial dysfunction pathways. Furthermore, the quantitative real-time polymerase chain reaction showed the different expression of miRNA might potentially be used to discriminate septic AKI from sepsis-non AKI and they were correlated with the regulation of mitochondrial oxidative stress and dysfunction, including PGC-1α, SIRT1, mTOR, OXSR1 and NOX5.
2017-02-10 | GSE94717 | GEO
Project description:Urinary tract infections (UTIs) are the second most common infections encountered in the pediatric population, second only to respiratory tract infections. UTIs are also a major cause of morbidity and mortality. UTIs can often ascend causing infection in the upper urinary tract or even progress to bacteremia or urosepsis. Urosepsis accounts for 10-30% of septic shock cases and Uropathogenic E.coli (UPEC) is responsible for almost 75% of cases. Therefore, increased understanding of the effects of urosepsis at the cellular and organ specific level will provide the foundation for improvements in clinical care.
2020-10-26 | GSE160038 | GEO
Project description:Accuracy of sepsis prediction was obtained using cross-validation of gene expression data from 12 human spleen samples and from 16 mouse spleen samples. For blood studies, classifiers were constructed using data from a training data set of 26 microarrays. The error rate of the classifiers was estimated on seven de-identified microarrays, and then on a subsequent cross-validation for all 33 blood microarrays. Estimates of classification accuracy of sepsis in human spleen were 67.1%; in mouse spleen, 96%; and in mouse blood, 94.4% (all estimates were based on nested cross-validation). Lists of genes with substantial changes in expression between study and control groups were used to identify nine mouse common inflammatory response genes, six of which were mapped into a single pathway using contemporary pathway analysis tools. Keywords: genomics, diagnosis, microarray, calprotectin
2006-08-29 | GSE5663 | GEO
Project description:OBJECTIVE:In response to a need for better sepsis diagnostics, several new gene expression classifiers have been recently published, including the 11-gene "Sepsis MetaScore," the "FAIM3-to-PLAC8" ratio, and the Septicyte Lab. We performed a systematic search for publicly available gene expression data in sepsis and tested each gene expression classifier in all included datasets. We also created a public repository of sepsis gene expression data to encourage their future reuse. DATA SOURCES:We searched National Institutes of Health Gene Expression Omnibus and EBI ArrayExpress for human gene expression microarray datasets. We also included the Glue Grant trauma gene expression cohorts. STUDY SELECTION:We selected clinical, time-matched, whole blood studies of sepsis and acute infections as compared to healthy and/or noninfectious inflammation patients. We identified 39 datasets composed of 3,241 samples from 2,604 patients. DATA EXTRACTION:All data were renormalized from raw data, when available, using consistent methods. DATA SYNTHESIS:Mean validation areas under the receiver operating characteristic curve for discriminating septic patients from patients with noninfectious inflammation for the Sepsis MetaScore, the FAIM3-to-PLAC8 ratio, and the Septicyte Lab were 0.82 (range, 0.73-0.89), 0.78 (range, 0.49-0.96), and 0.73 (range, 0.44-0.90), respectively. Paired-sample t tests of validation datasets showed no significant differences in area under the receiver operating characteristic curves. Mean validation area under the receiver operating characteristic curves for discriminating infected patients from healthy controls for the Sepsis MetaScore, FAIM3-to-PLAC8 ratio, and Septicyte Lab were 0.97 (range, 0.85-1.0), 0.94 (range, 0.65-1.0), and 0.71 (range, 0.24-1.0), respectively. There were few significant differences in any diagnostics due to pathogen type. CONCLUSIONS:The three diagnostics do not show significant differences in overall ability to distinguish noninfectious systemic inflammatory response syndrome from sepsis, though the performance in some datasets was low (area under the receiver operating characteristic curve, < 0.7) for the FAIM3-to-PLAC8 ratio and Septicyte Lab. The Septicyte Lab also demonstrated significantly worse performance in discriminating infections as compared to healthy controls. Overall, public gene expression data are a useful tool for benchmarking gene expression diagnostics.
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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