Fig. 1

Workflow of integrative bioinformatics frameworks for abdominal aortic aneurysm (AAA). AAA genome-wide association study (GWAS) datasets were retrieved from the GWAS Catalog³⁶ and subjected to meta-analysis using METAL⁴³. Summary statistics from the meta-analysis were used to identify independent significant single nucleotide polymorphisms (SNPs) and expression quantitative trait loci (eQTLs) via FUMA²⁹. Gene-set enrichment analysis was conducted using MAGMA⁴⁷. Transcriptome-wide association study (TWAS) was performed using the FUSION pipeline⁴⁹. Differentially expressed genes (DEGs) were determined based on genes that were significant in both the eQTL and TWAS analyses. An AAA-associated protein–protein interaction (PPI) network was constructed using the DEGs and interactome data from the STRING database⁵¹ and visualized with Cytoscape⁵². Key nodes in the network were identified based on high degree and betweenness centrality scores, calculated using the NetworkX package in Python⁵³. Drug repurposing candidates were identified through screening drug–gene and drug–protein interaction databases, such as DrugBank⁵⁷, Therapeutic Target Database (TTD)⁵⁸, Comparative Toxicogenomics Databases (CTD)⁵⁹, GeneCards⁶⁰, and STITCH database⁶¹, and shortlisted drugs were further evaluated via computational structural modeling and molecular docking simulations using the HDOCK server⁷¹. The structural modeling results were visualized by the PDBsum website⁷², Accelrys Discovery Studio 3.0 (Accelrys Inc.)⁷³, and the University of California at San Francisco (UCSF) Chimera package⁷⁴.