The role of phosphatidylinositol (18:1_18:1) in benign prostatic hyperplasia: an integrated study of Mendelian randomization and network pharmacology.

BACKGROUND

Benign Prostatic Hyperplasia (BPH), marked by prostate enlargement, can greatly reduce quality of life. While studies hint at a connection between lipids and BPH, the roles of different lipid types are not well understood. The exact impact and treatment potential of these lipids in BPH are unclear, necessitating more research. Mendelian randomization (MR) provides a rigorous framework for elucidating causal relationships between modifiable exposures and outcomes, by leveraging the random assortment of genetic variants during gametogenesis. The aim of the current study was to systematically explore the underlying causal role of plasma lipids in the risk of BPH via two-sample MR analysis to find novel target for the treatment of BPH.

METHODS

Using two-sample MR analyses with data from the FinnGene and UK Biobank cohorts, we comprehensively investigated the causal effects of 179 circulating lipids on benign prostatic hyperplasia (BPH) risk. Integrated network pharmacology explored lipids-BPH interactions. lipids target predicted via multi-database screening (SuperPred/TargetNet/PharmMapper/SwissTargetPrediction) with UniProt validation. BPH targets sourced from DisGeNET/GeneCards/TTD/OMIM. Molecular docking performed in Discovery Studio. Shared targets analyzed through PPI networks. Hub genes identified by CytoHubba using four topological algorithms. GO/KEGG enrichment were considered significant with P ≤ 0.05.

FINDINGS

Genetically proxied circulating Phosphatidylinositol (18:1_18:1) (Pl(18:1_18:1)) and Phosphatidylcholine (16:0_18:2) (PC(16:0_18:2)) demonstrated significant inverse associations with BPH risk. In FinnGen Biobank, Pl(18:1_18:1) yielded OR = 0.95 (95%CI 0.90-0.99, P = 2.98 × 10⁻³) by IVW, OR = 0.91 (0.86-0.98, P = 7.24 × 10⁻³) by WM, and OR = 0.93 (0.82-1.05, P = 0.25) by MR-Egger; PC(16:0_18:2) showed OR = 0.95 (0.91-0.99, P = 2.43 × 10⁻²), OR = 0.95 (0.90-1.00, P = 4.09 × 10⁻²), OR = 0.93 (0.84-1.02, P = 0.13). In UK Biobank, Pl(18:1_18:1) exhibited OR = 0.88 (0.81-0.95, P = 1.25 × 10⁻²), OR = 0.88 (0.78-0.98, P = 2.26 × 10⁻²), OR = 0.80 (0.67-0.95, P = 2.29 × 10⁻²); PC(16:0_18:2) demonstrated OR = 0.92 (0.86-0.98, P = 9.90 × 10⁻⁴), OR = 0.93 (0.85-1.02, P = 0.10), OR = 0.89 (0.70-1.01, P = 7.98 × 10⁻²). Sensitivity analyses across both the FinnGen and UK Biobank cohorts confirmed robust causal estimates for the identified lipid-BPH relationships. No evidence of disproportionate SNP influence was detected(FinnGene: PC(16:0_18:2) P = 0.024, Pl(18:1_18:1) P = 0.021; UK Biobank: PC(16:0_18:2) P = 0.032, Pl(18:1_18:1) P = 0.041). Advanced MR analyses, supplemented by network pharmacology approaches, suggest that Pl(18:1_18:1) may reduce the risk of BPH by modulating the activity of the epidermal growth factor receptor (EGFR) rather than by altering its expression levels(OR = 1.02 95%CI, 0.93-1.12, P = 0.65 by IVW; OR = 1.07, 95%CI 0.95-1.21, P = 0.28 by WM; OR = 0.95, 95%CI 0.76-1.18, P = 0.65 by MR-Egger).

INTERPRETATION

Our findings collectively emphasize the causal significance of Pl(18:1_18:1) in the pathogenesis of BPH, as evidenced by a comprehensive MR framework. Additionally, our insights from network pharmacology indicate that Pl(18:1_18:1) may act as a therapeutic modulator of BPH by influencing the EGFR pathway. These results not only identify Pl(18:1_18:1) as a promising therapeutic target for BPH management but also establish a robust theoretical foundation for its clinical application in BPH treatment strategies.