Plasma proteomic signatures predict incident benign prostatic hyperplasia: a prospective cohort study of 20 996 men
Journal of Global Health, 2026
Li H., Zhang Y., Chen L., Yuan J., Qin F., Wang X., Xiong Y.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Rology | Pathophysiology & Patient Stratification | Plasma | Olink Explore 3072/384 |
Abstract
Background
Benign prostatic hyperplasia (BPH) is a prevalent disease in elderly men. However, the plasma proteomic signatures for incident BPH are absent, hindering early prediction and risk stratification. We aimed to identify plasma proteins associated with incident BPH and the implicated biological pathways.
Methods
This prospective cohort was constructed based on the UK Biobank, enrolling 20 996 BPH-free males at baseline. We used the Olink Explore platform to determine the abundances of 2920 plasma proteins. We used Cox regression models to evaluate associations and the Extreme Gradient Boosting model to perform feature selection and predictive modelling. We performed pathway enrichment and Mendelian randomisation analyses to elucidate the molecular pathways involved and assess causality.
Results
During the median follow-up period of 13.38 years, 2405 incident BPH cases were recorded. Cox regression identified 92 plasma proteins significantly associated with BPH risk (false discovery rate <0.05). Extreme Gradient Boosting model prioritised a three-protein signature: TSPAN1 (hazard ratio (HR) = 1.24) and KLK3 (HR = 1.34) as risk factors, and EDA2R (HR = 0.83) as a protective factor. This three-protein panel achieved an AUC of 0.71 (95% confidence interval = 0.69–0.73) for predicting BPH onset. Enrichment analysis revealed the associated proteins were mainly involved in immune-inflammatory pathways and stromal remodelling. As revealed by Mendelian randomisation, TSPAN1 and KLK3 were causally associated with incident BPH.ConclusionsWe identified a three-protein panel (TSPAN1, KLK3, EDA2R) which can predict incident BPH. The findings highlight potential targets for non-invasive risk assessment and therapy.