Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods.

ABSTRACT:

Background

Preeclampsia (PE) is a multisystem progressive disease that occurs during pregnancy. Previous studies have shown that the immune system is involved in the placental trophoblast function and the pathological process of uterine vascular remodeling in PE. However, its molecular mechanism is still unclear. This study aimed to identify critical genes and immune cells involved in the pathological process of PE.

Methods

The PE-related GSE74341 and GSE160888 datasets were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis were combined to screen the PE-related DEGs. Receiver operating characteristic (ROC)

SUBMITTER: Li W 

PROVIDER: S-EPMC11817261 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature