Cardiovascular disease (CVD) is the leading cause of death among adults in developed countries. Among CVDs, abdominal aortic aneurysm (AAA) and aortic occlusive disease (AOD) are of great public health importance because of the high mortality rate in the elderly population. Despite significant molecular insights into AAA and AOD, the molecular mechanisms of these diseases remain unclear, and the current lack of robust diagnostic and prognostic biomarkers requires novel approaches to biomarker discovery and molecular targeting. In this study, we performed a comparative analysis of genome-wide expression data from patients with large AAA (n = 29), small AAA (n = 20), AOD (n = 9), and controls (n = 10). Specifically, we identified the differentially expressed genes and associated molecular pathways and biological processes (BPs) in each disease. Using a systems science approach, these data were linked to comprehensive human biological networks (i.e., protein-protein interaction, transcriptional regulatory, and metabolic networks) to identify molecular signatures of the salient mechanisms of AAA and AOD. Significant alterations in lipid metabolism and valine, leucine, and isoleucine metabolism, as well as neurodegenerative diseases and sex differences in the pathogenesis of AAA and AOD were identified. In the presence of aneurysm, size-dependent changes in lipid metabolism were observed. In addition, molecules and signaling pathways related to immunity, inflammation, infectious disease, and oxidative phosphorylation were identified in common. The results of the comparative and integrative analyzes revealed important clues to disease mechanisms and reporter molecules at various levels that warrant future development as potential prognostic biomarkers and putative therapeutic targets.
Keywords: abdominal aortic aneurysm; aortic occlusive disease; big data; biomarker; omics; protein-protein interaction.