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

Publication ,  Journal Article
Hao, L; Greer, T; Page, D; Shi, Y; Vezina, CM; Macoska, JA; Marker, PC; Bjorling, DE; Bushman, W; Ricke, WA; Li, L
Published in: Sci Rep
August 9, 2016

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 monitoring assay. Receiver operating characteristic analysis showed highly-accurate prediction power of candidate biomarkers to stratify patients into disease or non-diseased categories. The key metabolites and pathways may be possibly correlated with smooth muscle tone changes, increased collagen content, and inflammation, which have been identified as potential contributors to urinary dysfunction in humans and rodents. Periurethral tissue staining revealed a significant increase in collagen content and tissue stiffness in men with LUTS. Together, our study provides the first characterization and validation of LUTS urinary metabolites and pathways to support the future development of a urine-based diagnostic test for LUTS.

Duke Scholars

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Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

August 9, 2016

Volume

6

Start / End Page

30869

Location

England

Related Subject Headings

  • Spectrometry, Mass, Electrospray Ionization
  • ROC Curve
  • Quality Control
  • Prostate
  • Metabolomics
  • Metabolome
  • Male
  • Machine Learning
  • Lower Urinary Tract Symptoms
  • Humans
 

Citation

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Hao, L., Greer, T., Page, D., Shi, Y., Vezina, C. M., Macoska, J. A., … Li, L. (2016). In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms. Sci Rep, 6, 30869. https://doi.org/10.1038/srep30869
Hao, Ling, Tyler Greer, David Page, Yatao Shi, Chad M. Vezina, Jill A. Macoska, Paul C. Marker, et al. “In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms.Sci Rep 6 (August 9, 2016): 30869. https://doi.org/10.1038/srep30869.
Hao L, Greer T, Page D, Shi Y, Vezina CM, Macoska JA, et al. In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms. Sci Rep. 2016 Aug 9;6:30869.
Hao, Ling, et al. “In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms.Sci Rep, vol. 6, Aug. 2016, p. 30869. Pubmed, doi:10.1038/srep30869.
Hao L, Greer T, Page D, Shi Y, Vezina CM, Macoska JA, Marker PC, Bjorling DE, Bushman W, Ricke WA, Li L. In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms. Sci Rep. 2016 Aug 9;6:30869.

Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

August 9, 2016

Volume

6

Start / End Page

30869

Location

England

Related Subject Headings

  • Spectrometry, Mass, Electrospray Ionization
  • ROC Curve
  • Quality Control
  • Prostate
  • Metabolomics
  • Metabolome
  • Male
  • Machine Learning
  • Lower Urinary Tract Symptoms
  • Humans