A New Perspective on Gas Chromatography-Mass Spectrometry Urinary Metabolomic Analysis and Efficient Risk Assessment of Urolithiasis: Morning Urine Organic Acid Profiles.

ABSTRACT:

Introduction

Urolithiasis is characterized by a high morbidity and recurrence rate, primarily attributed to metabolic disorders. The identification of more metabolic biomarkers would provide valuable insights into the etiology of stone formation and the assessment of disease risk. The present study aimed to seek potential organic acid (OA) biomarkers from morning urine samples and explore new methods based on machine learning (ML) for metabolic risk prediction of urolithiasis.

Methods

Morning urine samples were collected from 117 healthy controls and 156 urolithiasis patients. Gas chromatography-mass spectrometry was used to obtain metabolic profiles. Principal component analysis and ML were carried out to screen robust markers and establish a prediction evaluation model.

SUBMITTER: Yang J 

PROVIDER: S-EPMC11844692 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature