Causal effects of genetically determined metabolites and metabolite ratios on esophageal diseases: a two-sample Mendelian randomization study

Background Esophageal diseases (ED) are a kind of common diseases of upper digestive tract. Previous studies have proved that metabolic disorders are closely related to the occurrence and development of ED. However, there is a lack of evidence for causal relationships between metabolites and ED, as well as between metabolite ratios representing enzyme activities and ED. Herein, we explored the causality of genetically determined metabolites (GDMs) on ED through Mendelian Randomization (MR) study. Methods Two-sample Mendelian randomization analysis was used to assess the causal effects of genetically determined metabolites and metabolite ratios on ED. A genome-wide association analysis (GWAS) encompassing 850 individual metabolites along with 309 metabolite ratios served as the exposures. Meanwhile, the outcomes were defined by 10 types of ED phenotypes, including Congenital Malformations of Esophagus (CME), Esophageal Varices (EV), Esophageal Obstructions (EO), Esophageal Ulcers (EU), Esophageal Perforations (EP), Gastroesophageal Reflux Disease (GERD), Esophagitis, Barrett's Esophagus (BE), Benign Esophageal Tumors (BETs), and Malignant Esophageal Neoplasms (MENs). The standard inverse variance weighted (IVW) method was applied to estimate the causal relationship between exposure and outcome. Sensitivity analyses were carried out using multiple methods, including MR-Egger, Weighted Median, MR-PRESSO, Cochran's Q test, and leave-one-out analysis. P < 0.05 was conventionally considered statistically significant. After applying the Bonferroni correction for multiple testing, a threshold of P < 4.3E-05 (0.05/1159) was regarded as indicative of a statistically significant causal relationship. Furthermore, metabolic pathway analysis was performed using the web-based MetaboAnalyst 6.0 software. Results The findings revealed that initially, a total of 869 candidate causal association pairs (P-ivw< 0.05) were identified, involving 442 metabolites, 145 metabolite ratios and 10 types of ED. However, upon applying the Bonferroni correction for multiple testing, only 36 pairs remained significant, involving 28 metabolites (predominantly lipids and amino acids), 5 metabolite ratios and 6 types of ED. Sensitivity analyses and reverse MR were performed for these 36 causal association pairs, where the results showed that the pair of EV and 1-(1-enyl-palmitoyl)-2-linoleoyl-GPE (p-16:0/18:2) did not withstand the sensitivity tests, and Hexadecenedioate (C16:1-DC) was found to have a reverse causality with GERD. The final 34 robust causal pairs included 26 metabolites, 5 metabolite ratios and 5 types of ED. The involved 26 metabolites predominantly consisted of methylated nucleotides, glycine derivatives, sex hormones, phospholipids, bile acids, fatty acid dicarboxylic acid derivatives, and N-acetylated amino acids. Furthermore, through metabolic pathway analysis, we uncovered 8 significant pathways that played pivotal roles in five types of ED conditions. Conclusions This study integrated genomics with metabolomics to assess causal relationships between ED and both metabolites and metabolite ratios, uncovering several key metabolic features in ED pathogenesis. These findings have potential as novel biomarkers for ED and provide insights into the disease's etiology and progression. However, further clinical and experimental validations are necessary