Autor: |
Yun Gong, Tangzhiming Li, Qiyun Liu, Xiaoyu Wang, Zixian Deng, Lixin Cheng, Biao Yu, Huadong Liu |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-10 (2024) |
Druh dokumentu: |
article |
ISSN: |
1471-2261 |
DOI: |
10.1186/s12872-024-03798-y |
Popis: |
Abstract Background Pathogenesis and diagnostic biomarkers of aortic dissection (AD) can be categorized through the analysis of differential metabolites in serum. Analysis of differential metabolites in serum provides new methods for exploring the early diagnosis and treatment of aortic dissection. Objectives This study examined affected metabolic pathways to assess the diagnostic value of metabolomics biomarkers in clients with AD. Method The serum from 30 patients with AD and 30 healthy people was collected. The most diagnostic metabolite markers were determined using metabolomic analysis and related metabolic pathways were explored. Results In total, 71 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism and four different metabolites considered of most diagnostic value including N2-gamma-glutamylglutamine, PC(phocholines) (20:4(5Z,8Z,11Z,14Z)/15:0), propionyl carnitine, and taurine. These four predictive metabolic biomarkers accurately classified AD patient and healthy control (HC) samples with an area under the curve (AUC) of 0.9875. Based on the value of the four different metabolites, a formula was created to calculate the risk of aortic dissection. Risk score = (N2-gamma-glutamylglutamine × -0.684) + (PC (20:4(5Z,8Z,11Z,14Z)/15:0) × 0.427) + (propionyl carnitine × 0.523) + (taurine × -1.242). An additional metabolic pathways model related to aortic dissection was explored. Conclusion Metabolomics can assist in investigating the metabolic disorders associated with AD and facilitate a more in-depth search for potential metabolic biomarkers. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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