Identification of diagnostic biomarkers and therapeutic targets for abdominal aortic aneurysm via transcriptome sequencing and integrated bioinformatics

Objectives This study aimed to identify key genes and potential therapeutic targets involved in the development of abdominal aortic aneurysm (AAA) through transcriptomic profiling in a rat model. Methods RNA sequencing was performed on abdominal aortic tissues from AAA-induced rats and healthy controls. Differentially expressed genes (DEGs) were identified through bioinformatic analysis, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Protein–protein interaction (PPI) networks were constructed to identify central regulatory genes. Additional analyses included tissue-specific gene expression profiling, Gene Set Enrichment Analysis (GSEA), and molecular docking to predict candidate therapeutic compounds. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was conducted to validate key gene expression. Results A total of 400 DEGs were identified in AAA tissues, including 314 upregulated and 86 downregulated genes. Functional enrichment indicated significant involvement in biological processes such as response to external stimuli, plasma membrane localization, and cell adhesion. KEGG analysis highlighted the PI3K-Akt signaling pathway as prominently associated with AAA. PPI network analysis identified five hub genes— Fcgr2b , Tlr7 , Clec7a , Tlr9 , and Cd53 —which were significantly upregulated in AAA tissues. Tissue-specific expression analysis revealed that these genes were predominantly expressed in immune-related organs such as the spleen and bone marrow. GSEA showed enrichment of Cd53 , Fcgr2b , and Tlr9 in leukocyte transendothelial migration and actin cytoskeleton regulation pathways, while Clec7a and Tlr7 were linked to cell cycle progression and DNA replication. Molecular docking identified diphenylpyraline as a potential therapeutic compound targeting AAA-related pathways. RT-qPCR validation confirmed the differential expression of the five hub genes. Conclusion This integrative transcriptomic and bioinformatic analysis provides novel insights into the molecular mechanisms underlying AAA and identifies promising diagnostic biomarkers and therapeutic targets.