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

Background: Abdominal 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.Methods: The 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.Results: The 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.Conclusions: PDIA3, 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.