Annals of vascular surgery · 2023
Biomarker Screening by LCMS and Liquid Chip Technology in Acute Aortic Dissection.
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Ren Yong, Zhang Yue, Li Bin, Liu Juan, Rao Qun, Zhou Qing, Run Qi
Аннотация
BACKGROUND: Aortic dissection (AD) is a serious disease. Previous study, the use of peripheral blood biomarkers to diagnose AD showed strong clinical feasibility, but the possible molecular mechanism is unclear.
METHODS: Sera from 79 healthy subjects, 73 patients with well-established AD, and 74 patients with well-established acute myocardial infarction (AMI) were investigated by Liquid Chromatograph-Mass Spectrometer to detect metabolites (AFMK, Glycerophosphocholine, Inosine, SPH). The cell factor expression in the 3 group were detected by Liquid Chip Technology.
RESULTS: The serum content trends of 4 metabolic indexes in patients with AMI and AD group were used as the diagnostic models, and the effective diagnosis rate was 97.8%. The diagnosis rate is 89.8% in distinguishing patients with AMI from patients with AD. The expression in serum of the 3 groups showed that there were significant differences in the expression of 23 cytokines. By correlation analysis, it was found that miP-1, IL-7, MIP-1β, EGF and other cytokines were significantly correlated with the 4 metabolic molecules.
CONCLUSIONS: AFMK, Glycerophosphocholine, Inosine, Sphingfungin B (SPH) metabolites are potential biomarkers for AD, and the influence of related metabolic process may be related to the expression of miP-1, IL-7, MIP-1β, EGF, and other cytokines.
METHODS: Sera from 79 healthy subjects, 73 patients with well-established AD, and 74 patients with well-established acute myocardial infarction (AMI) were investigated by Liquid Chromatograph-Mass Spectrometer to detect metabolites (AFMK, Glycerophosphocholine, Inosine, SPH). The cell factor expression in the 3 group were detected by Liquid Chip Technology.
RESULTS: The serum content trends of 4 metabolic indexes in patients with AMI and AD group were used as the diagnostic models, and the effective diagnosis rate was 97.8%. The diagnosis rate is 89.8% in distinguishing patients with AMI from patients with AD. The expression in serum of the 3 groups showed that there were significant differences in the expression of 23 cytokines. By correlation analysis, it was found that miP-1, IL-7, MIP-1β, EGF and other cytokines were significantly correlated with the 4 metabolic molecules.
CONCLUSIONS: AFMK, Glycerophosphocholine, Inosine, Sphingfungin B (SPH) metabolites are potential biomarkers for AD, and the influence of related metabolic process may be related to the expression of miP-1, IL-7, MIP-1β, EGF, and other cytokines.