Assessing the relationships of 1,400 blood metabolites with abdominal aortic aneurysm: a Mendelian randomization study

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.