Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Discovery and validation of urinary molecular signature of early sepsis

ABSTRACT: Discovery and validation of urinary molecular signature of early sepsis

PROVIDER: PRJNA439291 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Discovery and validation of urinary molecular signature of early sepsis (validation cohort)

Project description:Discovery and validation of urinary molecular signature of early sepsis (validation cohort)

| PRJNA439295 | ENA

Discovery and validation of urinary molecular signature of early sepsis (discovery cohort)

Project description:Discovery and validation of urinary molecular signature of early sepsis (discovery cohort)

| PRJNA439296 | ENA

Discovery and validation of urinary molecular signature of early sepsis (validation cohort)

Project description:Sepsis remains a diagnostic challenge with no gold-standard test. Urine provides a readily available, non-invasive biofluid with significant diagnostic potential. Urinary gene expression has been previously used for diagnosis and prognosis of urological malignancies and transplant allograft rejections, but remains unutilized for sepsis diagnosis. In this study, the authors use urinary gene expression profiles to both diagnose sepsis and characterize its pathophysiology. By using differential expression augmented with machine learning ensembles, the authors identify a collection of cellular mRNA from 239 genes in patient urine which show exceptional power in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes the disrupted biological pathways in early sepsis and additionally reveals key molecular networks driving its pathogenesis. This study serves a pioneering step towards expanding the clinical potential of urinary molecular profiles for application to systemic diseases.

2020-02-20 | GSE112098 | GEO

Discovery and validation of urinary molecular signature of early sepsis (discovery cohort)

2020-02-20 | GSE112099 | GEO

Discovery and validation of urinary molecular signature of early sepsis

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-02-20 | GSE112100 | GEO

Discovery and Validation of Urinary Molecular Signature of Early Sepsis.

Project description:Identify alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients. Design:Prospective cohort study. Setting:Quaternary care academic hospital. Patients:A total of 266 sepsis and 82 control patients enrolled between January 2015 and February 2018. Interventions:Whole-genome transcriptomic analysis of messenger RNA isolated from the urinary cells of sepsis patients within 12 hours of sepsis onset and from control subjects. Measurements and Main Results:The differentially expressed probes that map to known genes were subjected to feature selection using multiple machine learning techniques to find the best subset of probes that differentiates sepsis from control subjects. Using differential expression augmented with machine learning ensembles, we identified a set of 239 genes in urine, which show excellent effectiveness in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes disrupted biological pathways in early sepsis and reveal key molecular networks driving its pathogenesis. Conclusions:We identified unique urinary gene expression profile in early sepsis. Future studies need to confirm whether this approach can complement blood transcriptomic approaches for sepsis diagnosis and prognostication.

| S-EPMC7523873 | biostudies-literature

Microarray transcriptomic profiling of patients with sepsis due to faecal peritonitis and pneumonia to identify shared and distinct aspects of the transcriptomic response (validation cohort)

Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 106 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.

2017-05-01 | E-MTAB-5274 | biostudies-arrayexpress

Transcription profiling of human peripheral blood mononuclear cells in sepsis

Project description:To identify signature genes that help distinguish (1) sepsis from non-infectious causes of systemic inflammatory response syndrome, (2) between Gram-positive and Gram-negative sepsis. Experiment Overall Design: A total of 70 critically ill patients (46 sepsis and 24 control) were enrolled in a single-centre observational study. Gene-expression profiling was performed using Affymetrix microarray (U133plus2) with 54,675 transcript. Data was divided into a training set (n=35) and a validation set (n=35). A molecular signature was developed in the training set and was then validated in the validation set.

2009-04-12 | E-GEOD-9960 | biostudies-arrayexpress

Microarray transcriptomic profiling of patients with sepsis due to faecal peritonitis and pneumonia to identify shared and distinct aspects of the transcriptomic response (discovery cohort)

Project description:We assayed leukocyte global gene expression for a prospective validation cohort of 221 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. 10 samples from patients scheduled for elective cardiac surgery were also assayed as non-septic controls. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.

2017-05-01 | E-MTAB-5273 | biostudies-arrayexpress

Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma

Project description:Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma

| PRJNA1071056 | ENA