Benign prostatic hyperplasia (BPH) as a common geriatric disease in urology, the incidence and prevalence are rapidly increasing with the aging society, prompting an urgent need for effective prevention and treatment of BPH. However, limited therapeutic efficacy and higher risk of complications result in the treatment of BPH remaining challenging. The unclear pathogenic mechanism also hampers further exploration of therapeutic approaches for BPH. In this study, we used multi-omics methods to integrate genomics, transcriptomics, immunomics, and metabolomics data and identify biomolecules associated with BPH. We performed transcriptomic imputation, summary data-based Mendelian randomization (SMR), joint/conditional analysis, colocalization analysis, and FOCUS to explore high-confidence genes associated with BPH in blood and prostate tissue. Subsequently, three-step SMR was used to identify the DNA methylation sites regulating high-confidence genes to improve the pathogenic pathways of BPH. We also used cis-instruments of druggable genes to conduct SMR analysis to find potential drug targets for BPH. Finally, we used MR analysis to explore the immune pathways and metabolomics related to BPH. Multiple analytical methods identified BTN3A2 (Blood: TWAS Z score = 5.02912, TWAS P = 4.93 × 10-7; Prostate: TWAS Z score = 4.89, TWAS P = 1.01 × 10-6) and C4A (Blood: TWAS Z score = 4.90754, TWAS P = 9.22 × 10-7; Prostate: TWAS Z score = 5.084, TWAS P = 3.70 × 10-7) as high-confidence genes for BPH and identified the cg14345882-BTN3A2-BPH pathogenic pathway. We also used druggable gene data to identify 30 promising therapeutic target genes, including BTN3A2 and C4A. For MR analysis of immune pathways, we identified immune cell surface molecules as well as the inflammatory factor IL-17 (OR = 1.25, 95% CI = 1.09-1.43, PFDR = 0.12, Maximum likelihood) as risk factors for BPH. In addition, we found that disulfide levels of cysteinylglycine (OR = 1.11, 95% CI = 1.05-1.18, P = 5.18 × 10-4, Weighted median), oxidation levels of cysteinylglycine (OR = 1.09, 95% CI = 1.04-1.14, P = 3.87 × 10-4, Weighted median), and sebacate levels (OR = 1.05, 95% CI = 1.02-1.08, P = 3.0 × 10-4, Maximum likelihood) increase the risk of BPH. This multi-omics study explored biomolecules associated with BPH, improved the pathogenic pathways of BPH, and identified promising therapeutic targets. Our results provide evidence for future studies aimed at developing appropriate therapeutic interventions.