Exploring the association between gastroesophageal reflux disease and hyperlipidemia through bioinformatics and Mendelian randomization.

Observational research has found a relationship between gastroesophageal reflux disease (GERD) and hyperlipidemia (HLP). This study explored the relationship between GERD and HLP using bioinformatics and Mendelian randomization (MR) methods. We first conducted bioinformatics analyses to identify differentially expressed genes (DEGs) from disease datasets and then performed a two-sample MR analysis with aggregated genome-wide association study (GWAS) data to investigate the relationship. 11 DEGs were shared between GERD and HLP. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, cholesterol metabolism, renin secretion, and glycerolipid metabolism may represent common underlying mechanisms between the 2 diseases. The Inverse Variance Weighted (IVW) method identified P values of < .001 and .003 between GERD and HLP in the primary and replication MR analysis, respectively. The results were robust, as confirmed with the heterogeneity and pleiotropy tests. This study revealed the causal relationship between GERD and HLP through comprehensive approaches. The implicated shared genes and pathways offer valuable insights into potential therapeutic avenues and highlight the importance of addressing this link in clinical practice.