Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression.

Area of Science:

• Genomics
• Biomarkers
• Neuroscience

Background:

• Ischemic stroke necessitates reliable biomarkers for risk stratification and monitoring.
• Identifying genetic factors and therapeutic targets is crucial for improving patient outcomes.

Purpose of the Study:

• To identify key genes associated with ischemic stroke progression.
• To explore potential therapeutic small molecules for ischemic stroke treatment.

Main Methods:

• Analysis of publicly available microarray datasets (GSE58294, GSE22255, GSE16561) from the Gene Expression Omnibus (GEO) database.
• Identification of differentially expressed genes (DEGs) using Limma, followed by Gene Ontology (GO) and KEGG pathway enrichment analyses.
• Construction of a protein-protein interaction (PPI) network and module analysis using Cytoscape and MCODE, with potential drug targets identified via the Connectivity Map (CMap) database.

Main Results:

• Sixty DEGs were identified, significantly associated with programmed cell death and apoptosis.
• Enrichment analysis highlighted the Fc epsilon RI, MAPK signaling pathways, and Huntington's disease.
• Five high-connectivity DEGs (CYBB, SYK, DUSP1, TNF, SP1) were selected as predictors of stroke progression; ten potential therapeutic small molecules were identified, with mycophenolic acid showing the most promise.

Conclusions:

• The identified genes (CYBB, SYK, DUSP1, TNF, SP1) represent potential therapeutic targets for modifying ischemic stroke progression.
• Mycophenolic acid is a promising small molecule for further investigation as an adjuvant therapy for ischemic stroke.