Unveiling therapeutic targets and preventive components for kidney insufficiency and blood stasis-type BPH: bridging metabolomics, network pharmacology and reverse screening

揭示肾功能不全和血瘀型良性前列腺增生的治疗靶点和预防成分:代谢组学、网络药理学和反向筛选的桥梁

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Abstract

Benign prostatic hyperplasia (BPH) is a common disease affecting male urinary system function and quality of life, with its incidence increasing due to population ageing and unhealthy lifestyles. Modern medicine mainly adopts symptomatic treatments such as 5-alpha reductase inhibitors and alpha1 adrenergic receptor blockers. However, due to the complex pathogenesis of BPH, these drugs can only partially alleviate symptoms and have shortcomings such as high treatment costs and significant side effects. BPH is similar to the descriptions of "Jīng Lóng" and "Lóng Bì" in traditional Chinese medicine (TCM), and its onset is closely related to liver and kidney dysfunction. Kidney insufficiency and blood stasis are common clinical syndromes of BPH. Compared with modern medicine, treatment based on syndrome differentiation of TCM can achieve good results in treating this subtype of BPH. Therefore, guided by the holistic view of TCM, adopting a holistic and systematic research approach to explore therapeutic targets and potential therapeutic components for BPH with a specific syndrome can provide new ideas for the clinical treatment of BPH. This study integrated clinical metabolomics and network pharmacology to identify therapeutic targets for kidney insufficiency and blood stasis-type BPH. Serum analysis of BPH patients and healthy controls for testosterone, estradiol, SRD5α2, NF-κB p65, and TGF-β levels, alongside metabolomics and network pharmacology, revealed hormonal imbalance, increased inflammatory/fibrotic markers, and 58 differential metabolites in BPH. Pathway enrichment analysis identified 6 key metabolic pathways, while network pharmacology constructed four compound-reaction-enzyme-gene networks and pinpointed 178 potential targets, including 23 core targets. Reverse screening against the Yaozh Database-Natural Product AI Engine Platform matched 11 druggable targets with 49 interacting components, and target-component fitting analysis confirmed the reliability of 8 core targets. This combined approach validated the findings of hormonal imbalance and significant metabolic pathway changes and provided valuable insights for BPH treatment and drug development.

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