Urinary metabolites identified using metabolomic analysis as potential biomarkers of nocturia in elderly men
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ORIGINAL ARTICLE
Urinary metabolites identified using metabolomic analysis as potential biomarkers of nocturia in elderly men Satoru Kira1 · Takahiko Mitsui1 · Tatsuya Miyamoto1 · Tatsuya Ihara1 · Hiroshi Nakagomi1 · Yuka Hashimoto2 · Hajime Takamatsu2 · Masayuki Tanahashi2 · Masahiro Takeda2 · Sachiko Tsuchiya1 · Norifumi Sawada1 · Masayuki Takeda1 Received: 19 July 2019 / Accepted: 25 November 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Purpose To investigate the association between nocturia and urinary metabolites in elderly men using metabolomic analysis. Methods We recruited 66 men aged 65–80 years. The 3-day frequency volume chart (FCV), International Prostate Symptom Score (IPSS), and quality of life score were used to assess micturition behavior. Participants with the total IPSS > 0 and ≥ 1.5 micturition on an average for three nights were included in the nocturia group. Participants with the total IPSS 0.33 [12].
Metabolomics by capillary electrophoresis time‑of‑flight mass spectrometry Urine sampling and processing were performed as follows: 50 µL of urine was added to 450 µL of methanol containing internal standards and mixed. Then, 500 µL of chloroform and 200 µL of MilliQ water were added and mixed again. After centrifugation with 15,000 × g for 30 min, the aqueous layer was sampled and passed through a 5 kDa membrane filter and dried under reduced pressure. The residue was reconstituted with 50 µL of MilliQ-water containing internal standards for capillary electrophoresis time-of-flight mass spectrometry. CE-TOFMS was carried out using an Agilent CE Capillary Electrophoresis System equipped with an Agilent 6224 Time-of-Flight Mass Spectrometer, Agilent 1310B Isocratic HPLC Pump, Agilent G1603A CE-MS Adapter Kit, and Agilent G1607A CE-ESI-MS Sprayer Kit (all from Agilent Technologies, Waldbronn, Germany). The systems were controlled using Agilent G1601BA ChemStation software, ver. B.04.03, for CE (Agilent Technologies). The metabolites were analyzed on a fused-silica capillary (internal diameter, 50 μm; total length, 80 cm; Human Metabolome Technologies, Inc., Tsuruoka, Japan) with commercial running and rinse buffers for electrophoresis (solution ID: H3301-1001 for cation analysis, and H3302-1021 and H3302-1022 for anion analysis; Human Metabolome Technologies) as the electrolyte. The sample was injected at a pressure of 50 mbar for 10 s (approximately 10 nL) for cation analysis and for 25 s (approximately 25 nL) for anion analysis. The sample was scanned using a spectrometer over an m/z range of 50–1000. Peaks were extracted using the automatic integration software MasterHands (ver. 2.13.0.8; Keio University,
World Journal of Urology
Tsuruoka, Japan) to obtain peak information including m/z, CE migration time, and peak area. Signal peaks corresponding to isotopomers, adduct ions, and other product ions of known metabolites were excluded, and the remaining peaks corresponding to putative metabolites were annotated based on the corresponding reference migratio
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