In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms.

ABSTRACT: Lower urinary tract symptoms (LUTS) are a range of irritative or obstructive symptoms that commonly afflict aging population. The diagnosis is mostly based on patient-reported symptoms, and current medication often fails to completely eliminate these symptoms. There is a pressing need for objective non-invasive approaches to measure symptoms and understand disease mechanisms. We developed an in-depth workflow combining urine metabolomics analysis and machine learning bioinformatics to characterize metabolic alterations and support objective diagnosis of LUTS. Machine learning feature selection and statistical tests were combined to identify candidate biomarkers, which were statistically validated with leave-one-patient-out cross-validation and absolutely quantified by selected reaction mon

SUBMITTER: Hao L 

PROVIDER: S-EPMC4977550 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature