Identification of immune-related endoplasmic reticulum stress genes in sepsis using bioinformatics and machine learning.

ABSTRACT:

Background

Sepsis-induced apoptosis of immune cells leads to widespread depletion of key immune effector cells. Endoplasmic reticulum (ER) stress has been implicated in the apoptotic pathway, although little is known regarding its role in sepsis-related immune cell apoptosis. The aim of this study was to develop an ER stress-related prognostic and diagnostic signature for sepsis through bioinformatics and machine learning algorithms on the basis of the differentially expressed genes (DEGs) between healthy controls and sepsis patients.

Methods

The transcriptomic datasets that include gene expression profiles of sepsis patients and healthy controls were downloaded from the GEO database. The immune-related endoplasmic reticulum stress hub genes associated with sepsis patients w

SUBMITTER: Gong T 

PROVIDER: S-EPMC9530749 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature