Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome.

Journal: World journal of urology
PMID:

Abstract

PURPOSE: To identify biomarkers for diagnosis and classification of interstitial cystitis/bladder pain syndrome (IC/BPS) by urinary lipidomics coupled with machine learning.

Authors

  • Takuya Iwaki
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Makoto Kurano
    Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Masahiko Sumitani
    Department of Pain and Palliative Medicine, The University of Tokyo Hospital, Tokyo, Japan.
  • Aya Niimi
    Department of Urology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Akira Nomiya
    Department of Urology, Japan Organization of Occupational Health and Safety, Kanto Rosai Hospital, Kanagawa, Japan.
  • Jun Kamei
    Department of Urology, Jichi Medical University, Tochigi, Japan.
  • Satoru Taguchi
    Department of Urology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan.
  • Yuta Yamada
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Hongo7-3-1, Bunkyo-ku, Tokyo, Japan.
  • Yusuke Sato
    Graduate School of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Masaki Nakamura
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Daisuke Yamada
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Tomonori Minagawa
    Department of Urology, Shinshu University School of Medicine, Nagano, Japan.
  • Hiroshi Fukuhara
    Department of Urology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan.
  • Haruki Kume
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Hongo7-3-1, Bunkyo-ku, Tokyo, Japan.
  • Yukio Homma
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Hongo7-3-1, Bunkyo-ku, Tokyo, Japan.
  • Yoshiyuki Akiyama
    Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.