Screening plasma metabolites as potential biomarkers for type B aortic dissection

Background: Aortic dissection (AD) is a serious aortic disease. Although current imaging methods can provide accurate diagnosis for AD, they do not include essential biological information. The aim of this study is to identify plasma metabolites for the risk and severity of type B AD (TBAD). Methods: In this cross-sectional study, we enrolled 16 hypertensive patients with TBAD and 7 hypertensive patients without TBAD in Jieyang People's Hospital between December 2021 and April 2022. After plasma metabolomics analysis, a metabolites risk score (MRS) model was conducted through logistic regression and least absolute shrinkage and selection operator (LASSO) regression to predict the risk of TBAD. Subsequently, TBAD group was divided into uncomplicated and complicated TBAD subgroups for further screening for metabolites related to the severity of TBAD. Results: Three metabolites, including 1,5-anhydro-D-glucitol, D-(+)-sucrose and PC(O-16:0/ 0:0) were related to the risk of TBAD. Compared to hypertensive patients without TBAD, the abundance of 1,5-anhydro-D-glucitol and D-(+)-sucrose were significantly increased while PC(O-16:0/0:0) was significantly reduced in hypertensive patients with TBAD (P<0.001). We subsequently built an MRS model based on these three metabolites. Furthermore, we found that hydrocinnamic acid (r=0.741, P<0.001) was independently correlated with the TBAD severity, while glycine deoxycholic acid (r=-0.53 8, P=0.008) and glycochenodeoxycholic acid (r=-0.538, P=0.008) were inversely correlated with the TBAD severity independently. Conclusions: The present study screened out three plasma metabolites associated with the risk of TBAD, constructed an MRS model, and identified three metabolites that were independently associated with the severity of TBAD. These findings may serve to identify more TBAD-related biomarkers and shed light on exploring potential mechanisms of TBAD.