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Urinary Metabolic Phenotyping of Women with Lower Urinary Tract Symptoms
Author(s) -
Rhian Bray,
Stefano Cacciatore,
Beatriz Jiménez,
Rufus Cartwright,
Alex Digesu,
Ruwan Fernando,
Elaine Holmes,
Jeremy K. Nicholson,
Phillip R. Bennett,
David A. MacIntyre,
Vik Khullar
Publication year - 2017
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.7b00568
Subject(s) - medicine , lower urinary tract symptoms , urinary system , urine , nocturia , overactive bladder , urology , urinary incontinence , metabolome , urinary urgency , body mass index , gynecology , pathology , metabolite , prostate , alternative medicine , cancer
Lower urinary tract symptoms (LUTS), including urinary incontinence, urgency and nocturia, affect approximately half of women worldwide. Current diagnostic methods for LUTS are invasive and costly, while available treatments are limited by side effects leading to poor patient compliance. In this study, we aimed to identify urine metabolic signatures associated with LUTS using proton nuclear magnetic resonance (1H NMR) spectroscopy. A total of 214 urine samples were collected from women attending tertiary urogynecology clinics (cases; n = 176) and healthy control women attending general gynecology clinics (n = 36). Despite high variation in the urine metabolome across the cohort, associations between urine metabolic profiles and BMI, parity, overactive bladder syndrome, frequency, straining, and bladder storage were identified using KODAMA (knowledge discovery by accuracy maximization). Four distinct urinary metabotypes were identified, one of which was associated with increased urinary frequency and low BMI. Urine from these patients was characterized by increased levels of isoleucine and decreased levels of hippurate. Our study suggests that metabolic profiling of urine samples from LUTS patients offers the potential to identify differences in underlying etiology, which may permit stratification of patient populations and the design of more personalized treatment strategies

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