Yuan Xiaoli, Song Yancheng, Xin Hai, Zhang Lu, Liu Bingyu, Ma Jianmin, Sun Ruicong, Guan Xiaomei, Jiang Zhirong
Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China.
Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Eur J Med Res. 2023 Sep 22;28(1):368. doi: 10.1186/s40001-023-01354-6.
Autophagy plays essential roles in abdominal aortic aneurysm (AAA) development and progression. The objective of this study was to verify the autophagy-related genes (ARGs) underlying AAA empirically and using bioinformatics analysis.
Two gene expression profile datasets GSE98278 and GSE57691 were downloaded from the Gene Expression Omnibus (GEO) database, and principal component analysis was performed. Following, the R software (version 4.0.0) was employed to analyze potentially differentially expressed genes related with AAA and autophagy. Subsequently, the candidate genes were screened using protein-protein interaction (PPI), gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, quantitative real-time polymerase chain reaction (RT-qPCR) was performed to detect the RNA expression levels of the top five selected abnormal ARGs in clinical samples obtained from the normal and AAA patients.
According to the information contained (97 AAA patients and 10 healthy controls) in the two datasets, a total of 44 differentially expressed autophagy-related genes (6 up-regulated genes and 38 down-regulated genes) were screened. GO enrichment analysis of differentially expressed autophagy-related genes (DEARGs) demonstrated that some enrichment items were associated with inflammation, and PPI analysis indicated interaction between these genes. RT-qPCR results presented that the expression levels of IL6, PPARG, SOD1, and MAP1LC3B were in accordance with the bioinformatics prediction results acquired from the mRNA chip.
Bioinformatics analysis identified 44 potential autophagy-related differentially expressed genes in AAA. Further verification by RT- qPCR presented that IL6, PPARG, SOD1, and MAP1LC3B may affect the development of AAA by regulating autophagy. These findings might help explain the pathogenesis of AAA and be helpful in its diagnosis and treatment.
自噬在腹主动脉瘤（AAA）的发生和发展中起重要作用。本研究的目的是通过实验和生物信息学分析来验证AAA潜在的自噬相关基因（ARG）。
从基因表达综合数据库（GEO）下载两个基因表达谱数据集GSE98278和GSE57691，并进行主成分分析。随后，使用R软件（版本4.0.0）分析与AAA和自噬相关的潜在差异表达基因。接着，利用蛋白质-蛋白质相互作用（PPI）、基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）富集分析筛选候选基因。最后，进行定量实时聚合酶链反应（RT-qPCR）以检测从正常人和AAA患者获得的临床样本中前五个选定的异常ARG的RNA表达水平。
根据两个数据集中包含的信息（97例AAA患者和10例健康对照），共筛选出44个差异表达的自噬相关基因（6个上调基因和38个下调基因）。对差异表达的自噬相关基因（DEARG）进行GO富集分析表明，一些富集条目与炎症相关，PPI分析表明这些基因之间存在相互作用。RT-qPCR结果显示，IL6、PPARG、SOD1和MAP1LC3B的表达水平与从mRNA芯片获得的生物信息学预测结果一致。
生物信息学分析在AAA中鉴定出44个潜在的自噬相关差异表达基因。RT-qPCR进一步验证表明，IL6、PPARG、SOD1和MAP1LC3B可能通过调节自噬影响AAA的发展。这些发现可能有助于解释AAA的发病机制，并有助于其诊断和治疗。
