Integrating the summary data-based mendelian randomization and transcriptomic analysis identifies candidate genes and repositioning targets for asthma

Notwithstanding considerable progress in comprehending the molecular mechanisms and therapeutic approaches for asthma, it continues to be a widespread public health issue worldwide, resulting in considerable economic strains. The objective of this research was to uncover genes linked to the development of asthma. This research performed a Summary Data-based Mendelian Randomization (SMR) analysis to identify genes associated with asthma, using information gathered from genome-wide association studies (GWAS), expression quantitative trait loci (eQTLs), and transcriptomic datasets. Furthermore, drug enrichment analysis and molecular docking simulations were utilized to investigate possible therapeutic targets. The SMR analysis identified 190 candidate genes, of which 45 were validated using Gene Expression Omnibus (GEO) datasets. These genes were predominantly enriched in the "Renin Secretion" pathway. Mendelian randomization analysis indicated a significant causal relationship between renin levels and asthma susceptibility: Inverse Variance Weighted (IVW) method: Odds Ratio (OR) = 1.073, 95% Confidence Interval (CI) = 1.032–1.116, p < 0.001; MR-Egger: OR = 1.099, 95% CI = 1.013–1.192, p = 0.031; Weighted Median: OR = 1.076, 95% CI = 1.017–1.137, p = 0.011. Furthermore, ivermectin and gefitinib emerged as potential pharmacological agents for asthma management. This study delineates multiple genes potentially implicated in asthma pathogenesis, highlighting several associated with the renin secretion pathway. The Mendelian randomization analysis underscores a causal link between elevated renin levels and increased asthma risk. These findings warrant further investigation to elucidate the precise mechanisms underlying these associations and to validate the therapeutic efficacy of the identified agents.