ArticleFrontiers in pharmacology2024
Assessing the relationships of 1,400 blood metabolites with abdominal aortic aneurysm: a Mendelian randomization study.
Article in Frontiers in pharmacology, 2024. 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.
- Article
- Single-cell analysis of TIGD genes in hepatocellular carcinoma: Prognostic value and functional characterization.Translational oncology · 2026Article
- Pathogenetic Gut Microbiota in Aortic Diseases: Evidence and Mechanisms Across Aneurysm, Dissection, and Inflammatory Aortopathies.Nutrients · 2026Review
- Integrative Mendelian randomization and spatial transcriptomics analysis reveals causal links between plasma lipidome and non-small cell lung cancer.Discover oncology · 2025Article
- Causal effects of circulating inflammatory proteins on colorectal cancer: a Mendelian randomization and Spatial transcriptomic study.Discover oncology · 2025Article
- Expression and prognostic value of SEC13 across multiple tumour types and its association with the regulation by Pulsatilla chinensis: a multi-omics and Mendelian Randomization Study.Discover oncology · 2025Article
- Cost-effectiveness of open versus laparoscopic pancreaticoduodenectomy: a retrospective Markov model analysis from China.Frontiers in oncology · 2025Article
- Diabetic cardiomyopathy from a gut microbiota perspective: research progress and prospects.Frontiers in medicine · 2025Review
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Authors and funding
11 authors.
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Abstract
Background: Abdominal aortic aneurysm (AAA) is one of the most dangerous types of vascular diseases worldwide. Metabolic disturbance affects disease risk and provide underlying therapeutic targets. Previous studies have reported an association between metabolic disorders and AAA. However, evidence of a causal relationship between blood metabolites and AAA is still lacking at present. Methods: Using Mendelian randomization (MR), we assessed the causal association between 1,400 serum metabolites and AAA. The inverse variance weighted method (IVW), weighted median, MR-Egger regression, simple mode, as well as weighted mode methods were used for evaluating the causality between blood metabolites and AAA. Pleiotropy and heterogeneity tests were further conducted. Results: Through strict screening, 17 known metabolites, 7 unknown metabolites and 5 metabolite ratios related to AAA were identified. Among all the metabolites, 24 were found to have negative associations, while 5 exhibited positive associations. The top five metabolites associated with an increased risk of AAA were Oleoyl-linoleoyl-glycerol (18:1/18:2) [2], Glycosyl-N-(2-hydroxynervonoyl)-sphingosine (d18:1/24:1(2OH)), Glycochenodeoxycholate 3-sulfate, X-21441 and X-24328. In contrast, the top five metabolites that were linked to a reduced risk of AAA included Uridine to pseudouridine ratio, Octadecanedioate, Phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] ratio, 1-(1-enyl-palmitoyl)-GPE (p-16:0), and 1-stearoyl-GPG (18:0). Conclusion: Among the 1,400 blood metabolites, we identified 17 known metabolites, 7 unknown metabolites, and 5 metabolite ratios associated with AAA. This MR study may provide a novel significant insight for the screening and prevention of AAA.
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