ArticleJournal of Zhejiang University. Science. B
Discovery of potential biomarkers for human atherosclerotic abdominal aortic aneurysm through untargeted metabolomics and transcriptomics.
Article in Journal of Zhejiang University. Science. B. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A narrative review of recent literature of circulating biomarkers of abdominal aortic aneurysm.JVS-vascular science · 2026Review
- Integrated multi-omics analysis reveals gut microbiota and metabolic characteristics in coronary heart disease.Frontiers in microbiology · 2026Article
- Article
- Sortilin-induced lipid accumulation and atherogenesis are suppressed by HNF1b SUMOylation promoted by flavone ofJournal of Zhejiang University. Science. B · 2023Article
- Multi-omics analysis identifies potential mechanisms by which high glucose accelerates macrophage foaming.Molecular and cellular biochemistry · 2023Article
- Targeting metabolism in aortic aneurysm and dissection: from basic research to clinical applications.International journal of biological sciences · 2023Review
- Effect of the Interaction between Viral PB2 and Host SphK1 on H9N2 AIV Replication in Mammals.Viruses · 2022Article
- Article
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Authors and funding
10 authors.
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Abstract
Abdominal aortic aneurysm (AAA) and atherosclerosis (AS) have considerable similarities in clinical risk factors and molecular pathogenesis. The aim of our study was to investigate the differences between AAA and AS from the perspective of metabolomics, and to explore the potential mechanisms of differential metabolites via integration analysis with transcriptomics. Plasma samples from 32 AAA and 32 AS patients were applied to characterize the metabolite profiles using untargeted liquid chromatography-mass spectrometry (LC-MS). A total of 18 remarkably different metabolites were identified, and a combination of seven metabolites could potentially serve as a biomarker to distinguish AAA and AS, with an area under the curve (AUC) of 0.93. Subsequently, we analyzed both the metabolomics and transcriptomics data and found that seven metabolites, especially 2'-deoxy-D-ribose (2dDR), were significantly correlated with differentially expressed genes. In conclusion, our study presents a comprehensive landscape of plasma metabolites in AAA and AS patients, and provides a research direction for pathogenetic mechanisms in atherosclerotic AAA.
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