Sagulkoo Pakorn, Chuntakaruk Hathaichanok, Suratanee Apichat, Plaimas Kitiporn, Teerakulkittipong Nuttinee
Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.
Center of Biomedical Informatics, Department of Family Medicine, Faculty of Medicine, Chiang Mai University, 50200, Chaing Mai, Thailand.
Sci Rep. 2025 Jul 1;15(1):22331. doi: 10.1038/s41598-025-07989-1.
Abdominal aortic aneurysm (AAA) is a non-communicable disease (NCD) with high morbidity and mortality, commonly observed worldwide. Understanding its molecular mechanisms and identifying potential therapeutic targets are crucial for disease screening, diagnosis, and treatment. In this study, we conducted a meta-analysis of multiple genome-wide association studies (GWASs) to identify genetic variants associated with AAA and explored the functional implications of these variants in disease pathology. We identified differentially expressed genes (DEGs) based on significant single nucleotide polymorphisms (SNPs) from expression quantitative trait loci (eQTL) and transcriptome-wide association study (TWAS) analyses. Using these DEGs, we constructed an AAA-related protein-protein interaction (PPI) network and prioritized key genes for further analysis. Furthermore, we performed drug repurposing by identifying drug-gene and drug-protein interactions in existing databases and validated potential candidates through molecular docking. Our findings reveal 42 novel disease-associated SNPs and 52 previously unreported disease-related genes. Some residual confounding factors cannot be fully ruled out and may represent a limitation of our study. However, it is worth noting that only a minority of SNPs exhibited heterogeneity. Functional pathways analysis highlighted key processes, including lipid and cholesterol metabolism, tissue remodeling, and acetylcholine activation. We identified 74 DEGs through eQTL and TWAS analyses, with PPI network analysis highlighting CD40 and LRP1 as key proteins. Drug repurposing and molecular docking suggested abciximab and paclitaxel as potential therapeutic agents targeting CD40, while ivermectin emerged as a strong candidate for LRP1 binding. In conclusion, our integrative bioinformatics frameworks links genomics and transcriptomics with network biology and structural modeling, providing valuable insights into the molecular mechanisms of AAA and potential therapeutic strategies.
腹主动脉瘤(AAA)是一种发病率和死亡率都很高的非传染性疾病(NCD),在全球范围内普遍存在。了解其分子机制并确定潜在的治疗靶点对于疾病的筛查、诊断和治疗至关重要。在本研究中,我们对多项全基因组关联研究(GWAS)进行了荟萃分析,以确定与AAA相关的基因变异,并探讨这些变异在疾病病理学中的功能意义。我们基于来自表达定量性状位点(eQTL)和全转录组关联研究(TWAS)分析的显著单核苷酸多态性(SNP)鉴定了差异表达基因(DEG)。利用这些DEG,我们构建了一个与AAA相关的蛋白质-蛋白质相互作用(PPI)网络,并对关键基因进行了优先级排序以进行进一步分析。此外,我们通过在现有数据库中识别药物-基因和药物-蛋白质相互作用来进行药物再利用,并通过分子对接验证了潜在的候选药物。我们的研究结果揭示了42个新的疾病相关SNP和52个以前未报道的疾病相关基因。一些残留的混杂因素无法完全排除,这可能是我们研究的一个局限性。然而,值得注意的是,只有少数SNP表现出异质性。功能通路分析突出了关键过程,包括脂质和胆固醇代谢、组织重塑和乙酰胆碱激活。我们通过eQTL和TWAS分析鉴定了74个DEG,PPI网络分析突出了CD40和LRP1作为关键蛋白。药物再利用和分子对接表明阿昔单抗和紫杉醇是靶向CD40的潜在治疗药物,而伊维菌素是与LRP1结合的有力候选药物。总之,我们的综合生物信息学框架将基因组学和转录组学与网络生物学和结构建模联系起来,为AAA的分子机制和潜在治疗策略提供了有价值的见解。