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Decoding Benign Prostatic Hyperplasia: Insights from Multi-Fluid Metabolomic Analysis.

Xiaoyu Xu1,2, Haisong Tan1, Wei Zhang1,3

  • 1Department of Urology, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, P. R. China.

Small Methods
|February 3, 2025
PubMed
Summary
This summary is machine-generated.

Accurate diagnosis of benign prostatic hyperplasia (BPH) is crucial. This study identifies novel urinary and serum metabolic patterns and biomarkers using MALDI MS, improving early BPH detection and personalized treatment strategies.

Keywords:
benign prostatic hyperplasiabiomarkersclassificationlower urinary tract symptomsmetabolic patten

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Area of Science:

  • Biochemistry
  • Medical Diagnostics
  • Analytical Chemistry

Background:

  • Rising incidence of benign prostatic hyperplasia (BPH) with aging populations necessitates improved diagnostic methods.
  • Current BPH diagnosis faces challenges due to a lack of specific biomarkers for differentiating it from other causes of lower urinary tract symptoms (LUTS).

Purpose of the Study:

  • To develop and validate a metabolomic detection platform for identifying novel biomarkers for early and accurate BPH diagnosis.
  • To differentiate BPH from other LUTS and healthy individuals using urinary and serum metabolic patterns.

Main Methods:

  • Utilized a nanoparticle-assisted matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) metabolomic platform for urine and serum analysis.
  • Employed a two-step screening approach: automated identification of urinary metabolic patterns (UMPs) to distinguish healthy from LUTS groups, followed by serum metabolic patterns (SMPs) to identify BPH within the LUTS cohort.
  • Identified eight BPH-sensitive metabolic markers.

Main Results:

  • The MALDI MS platform demonstrated rapid analysis, minimal sample consumption, and high reproducibility.
  • Achieved an AUC of 0.830 for accurately identifying BPH cases within the LUTS cohort using SMPs.
  • Identified eight BPH-sensitive metabolic markers with uniform distribution across age groups.

Conclusions:

  • This metabolomic approach provides valuable insights for the early diagnosis of BPH.
  • The identified biomarkers and metabolic patterns can enhance clinical practice and personalized treatment strategies for BPH.
  • The study contributes to improving patient care for aging populations affected by BPH.