Network-based analysis reveals novel gene signatures in the peripheral blood of patients with sporadic nonsyndromic thoracic aortic aneurysm

Abstract

Thoracic aortic aneurysm (TAA), a serious cardiovascular disease that causes morbidity and mortality worldwide. At present, few biomarkers can accurately diagnose the appearance of TAA before dissection or rupture. Our research has the intention to investigate the developing applicable biomarkers for TAA promising clinically diagnostic biomarkers or probable regulatory targets for TAA. In our research, we built correlation networks utilizing the expression profile of peripheral blood mononuclear cell obtained from a public microarray data set (GSE9106). Furthermore, we chose the turquoise module, which has the strongest significance with TAA and was further analyzed. Fourteen genes that overlapped with differentially expressed proteins in the medial aortic layer were obtained. Subsequently, we verified the results applying quantitative polymerase chain reaction (Q-PCR) to our clinical specimen. In general, the Q-PCR results coincide with the majority of the expression profile. Fascinatingly, a notable change occurred in CLU, DES, MYH10, and FBLN5. In summary, using weighted gene coexpression analysis, our study indicates that CLU, DES, MYH10, and FBLN5 were identified and validated to be related to TAA and might be candidate biomarkers or therapeutic targets for TAA.

Keywords: FBLN5; biomarker; gene expression; protein-protein interaction; thoracic aortic aneurysms; weighted gene coexpression network analysis.