Mendelian Randomization Analysis Reveals Causal Effects of Circulating Metabolites on Hyperaldosteronism

Abstract

Observational studies have demonstrated that metabolites may have effect on the development of hyperaldosteronism. However, whether these associations are causal remain uncertain. This study aimed to evaluate the causal relationships between circulating metabolites and hyperaldosteronism. We performed a two-sample mendelian randomization (MR) analysis to investigate the causal relationships. Summary data for circulating metabolites were sourced from a large published genome-wide association study (GWAS). Data for hyperaldosteronism were obtained from FinnGen R12, comprising 931 cases and 479,069 controls of European ancestry. The inverse-variance weighted (IVW) method was used to estimate the causal effects. MR-Egger regression, weighted median, and weighted mode approaches were applied as complementary analyses to assess robustness. Sensitivity analyses and reverse MR analyses were performed to evaluate the reliability of the observed associations. Additionally, pathway enrichment analysis was conducted using MetaboAnalyst 5.0. We finally identified 59 metabolites/metabolic ratios nominally associated with hyperaldosteronism (P_IVW < 0.05). Among them, 37 showed a positive and suggestive causal relationship, while 29 exhibited a negative and suggestive causal effect. Pathway analysis highlighted two significantly enriched metabolic pathways: glycerophospholipid metabolism (p = 4.63 × 10⁻⁵) and glycerolipid metabolism (p = 0.041). This study provides suggestive evidence for a potential influence of blood metabolites on the development of hyperaldosteronism, offering novel insights into its early detection and therapeutic strategies.