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Sci Rep. 2016 Dec 15;6:39227. doi: 10.1038/srep39227.

Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis.

Kind T1, Cho E2, Park TD3, Deng N4, Liu Z4, Lee T5, Fiehn O1,6, Kim J2,4,7,8.

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West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA.
University of California Los Angeles, CA, USA.
University of California, Berkerly, CA, USA.
Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Department of Urology, Inha University College of Medicine, Incheon, South Korea.
King Abdulaziz University, Jeddah, Saudi Arabia.
Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA.


This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms.

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