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Biomarker Screening by LCMS and Liquid Chip Technology in Acute Aortic Dissection
Yong Ren1, Yue Zhang1, Bin Li1
1Department of Cardiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China.
Insights
This study identifies four key metabolites—AFMK, Glycerophosphocholine, Inosine, and Sphingfungin B—as potential biomarkers for aortic dissection (AD). These findings offer new insights into the molecular mechanisms underlying AD, potentially improving diagnostic approaches.
Area of Science:
- Biochemistry
- Molecular Biology
- Cardiovascular Medicine
Background:
- Aortic dissection (AD) is a life-threatening cardiovascular condition.
- Peripheral blood biomarkers show promise for AD diagnosis, but underlying molecular mechanisms remain unclear.
Purpose of the Study:
- To investigate potential blood metabolites and cytokines as diagnostic biomarkers for AD.
- To explore the molecular mechanisms linking metabolic changes to AD pathogenesis.
Main Methods:
- Serum samples from healthy subjects, AD patients, and acute myocardial infarction (AMI) patients were analyzed using Liquid Chromatography-Mass Spectrometry for four metabolites (AFMK, Glycerophosphocholine, Inosine, SPH).
- Cell factor expression in the three groups was assessed using Liquid Chip Technology.
Main Results:
- Diagnostic models based on the four metabolites achieved a 97.8% effective diagnosis rate and an 89.8% accuracy in distinguishing between AMI and AD.
- Significant differences in the expression of 23 cytokines were observed across the groups.
- Correlation analysis revealed significant associations between cytokines (e.g., miP-1, IL-7, MIP-1β, EGF) and the four identified metabolites.
Conclusions:
- AFMK, Glycerophosphocholine, Inosine, and Sphingfungin B are identified as potential biomarkers for AD.
- The metabolic processes involved in AD may be influenced by cytokines such as miP-1, IL-7, MIP-1β, and EGF.
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.
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