Evaluating the causal relationship between human blood metabolites and gastroesophageal reflux disease

Abstract

Background: Gastroesophageal reflux disease (GERD) affects approximately 13% of the global population. However, the pathogenesis of GERD has not been fully elucidated. The development of metabolomics as a branch of systems biology in recent years has opened up new avenues for the investigation of disease processes. As a powerful statistical tool, Mendelian randomization (MR) is widely used to explore the causal relationship between exposure and outcome.

Aim: To analyze of the relationship between 486 blood metabolites and GERD.

Methods: Two-sample MR analysis was used to assess the causal relationship between blood metabolites and GERD. A genome-wide association study (GWAS) of 486 metabolites was the exposure, and two different GWAS datasets of GERD were used as endpoints for the base analysis and replication and meta-analysis. Bonferroni correction is used to determine causal correlation features (P < 1.03 × 10^-4). The results were subjected to sensitivity analysis to assess heterogeneity and pleiotropy. Using the MR Steiger filtration method to detect whether there is a reverse causal relationship between metabolites and GERD. In addition, metabolic pathway analysis was conducted using the online database based MetaboAnalyst 5.0 software.

Results: In MR analysis, four blood metabolites are negatively correlated with GERD: Levulinate (4-oxovalerate), stearate (18:0), adrenate (22:4n6) and p-acetamidophenylglucuronide. However, we also found a positive correlation between four blood metabolites and GERD: Kynurenine, 1-linoleoylglycerophosphoethanolamine, butyrylcarnitine and guanosine. And bonferroni correction showed that butyrylcarnitine (odd ratio 1.10, 95% confidence interval: 1.05-1.16, P = 7.71 × 10^-5) was the most reliable causal metabolite. In addition, one significant pathways, the "glycerophospholipid metabolism" pathway, can be involved in the pathogenesis of GERD.

Conclusion: Our study found through the integration of genomics and metabolomics that butyrylcarnitine may be a potential biomarker for GERD, which will help further elucidate the pathogenesis of GERD and better guide its treatment. At the same time, this also contributes to early screening and prevention of GERD. However, the results of this study require further confirmation from both basic and clinical real-world studies.

Keywords: Biomarkers; Blood metabolites; Causality; Gastroesophageal reflux disease; Mendelian randomization; Metabolic pathway; Pathogenesis.

Figure 1

Overview of this Mendelian randomization analysis. Assumption 1, genetic instruments are strongly associated with the exposures of interest; Assumption 2, genetic instruments are independent of confounding factors; Assumption 3, genetic instruments are not associated with outcome and affect outcome only via exposures. IVW: Inverse variance weighted; LD: Linkage disequilibrium; LOO analysis: Leave-one-out analysis; MR-PRESSO: MR-Pleiotropy RESidual sum and outlier; SNPs: Single nucleotide polymorphisms; WM: Weighted median; BMI: Body mass index; T2DM: Type 2 diabetes mellitus.

Figure 2

Forest plot for the causality of blood metabolites on gastroesophageal reflux disease derived from inverse variance weighted analysis. CI: Confidence interval; OR: Odd ratio.

Figure 3

Scatterplot of significantly associated (inverse variance weighted derived P < 0.05) and directionally consistent estimates. SNP: Single nucleotide polymorphisms.

Figure 4

Meta-analysis of significantly associated (inverse variance weighted derived P < 0.05) between metabolites and gastroesophageal reflux disease. CI: Confidence interval; OR: Odd ratio.