Bioinformatics-based identification of lipid- and immune-related biomarkers in abdominal aortic aneurysms

Abstract

BackgroundAbdominal aortic aneurysm (AAA) manifest as a natural inflammatory process with permanent dilation and terminal rupture. Nevertheless, the pathogenesis of AAA remains a mystery, and treatment is still controversial. Lipid metabolism and immune system are involved in AAA progression, which has been well documented. However, lipid- and immune-related (LIR) biomarkers need to be further elucidated. MethodsThe AAA-related datasets were retrieved from the GEO database, and the datasets were analyzed for differential gene expression by NetworkAnalyst. GO and KEGG pathway enrichment analysis of differentially expressed mRNA (DE-mRNA) was performed using Metscape, and LIR DE-mRNA was further screened. AAA rat model was constructed using porcine pancreatic elastase to verify the differential expression of LIR DE-mRNA. ResultsThe GSE47472 and GSE57691 datasets respectively identified 614 (containing 381 down-regulated and 233 up-regulated DE-mRNAs) and 384 (containing 218 down-regulated and 164 up-regulated DE-mRNAs) DE-mRNAs. Intersection and union of DE-mRNAs were 13 and 983, respectively. The main terms involved in the union of DE-mRNAs included “immune system process”, “metabolic process”, “Chemokine signaling pathway”, “hematopoietic cell lineage” and “Cholesterol metabolism”. In vivo experiments revealed that LIR DE-mRNAs of PDIA3, TYROBP, and HSPA1A were significantly low expression in AAA abdominal aortic tissues, and HCK and SERPINE1 were significantly high expression, which is consistent with the bioinformatics analysis. ConclusionsPDIA3, TYROBP, HSPA1A, HCK and SERPINE1 may serve as LIR biomarkers of AAA, which provides new insights and theoretical guidance for the future treatment, early prevention and progression of AAA.