Unknown

Dataset Information

Identification of transcriptomics biomarkers for the early prediction of the prognosis of septic shock from pneumopathies.


ABSTRACT:

Background

Identifying the biological subclasses of septic shock might provide specific targeted therapies for the treatment and prognosis of septic shock. It might be possible to find biological markers for the early prediction of septic shock prognosis.

Methods

The data were obtained from the Gene Expression Omnibus databases (GEO) in NCBI. GO enrichment and KEGG pathway analyses were performed to investigate the functional annotation of up- and downregulated DEGs. ROC curves were drawn, and their areas under the curves (AUCs) were determined to evaluate the predictive value of the key genes.

Results

117 DEGs were obtained, including 36 up- and 81 downregulated DEGs. The AUC for the MME gene was 0.879, as a key gene with the most obvious upregulation in septic shock

SUBMITTER: Shi S 

PROVIDER: S-EPMC8619650 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature