Identification of pivotal genes and regulatory networks associated with SAH based on multi-omics analysis and machine learning.

ABSTRACT: Subarachnoid hemorrhage (SAH) is a disease with high mortality and morbidity, and its pathophysiology is complex but poorly understood. To investigate the potential therapeutic targets post-SAH, the SAH-related feature genes were screened by the combined analysis of transcriptomics and metabolomics of rat cortical tissues following SAH and proteomics of cerebrospinal fluid from SAH patients, as well as WGCNA and machine learning. The competitive endogenous RNAs (ceRNAs) and transcription factors (TFs) regulatory networks of the feature genes were constructed and further validated by molecular biology experiments. A total of 1336 differentially expressed proteins were identified, including 729 proteins downregulated and 607 proteins upregulated. The immune microenvironment changed after SAH

SUBMITTER: Lu H 

PROVIDER: S-EPMC12022295 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature