Bone Reports (Dec 2018)

Metabolomics-based profiles predictive of low bone mass in menopausal women

  • Takeshi Miyamoto,
  • Akiyoshi Hirayama,
  • Yuiko Sato,
  • Tami Koboyashi,
  • Eri Katsuyama,
  • Hiroya Kanagawa,
  • Atsuhiro Fujie,
  • Mayu Morita,
  • Ryuichi Watanabe,
  • Toshimi Tando,
  • Kana Miyamoto,
  • Takashi Tsuji,
  • Atsushi Funayama,
  • Tomoyoshi Soga,
  • Masaru Tomita,
  • Masaya Nakamura,
  • Morio Matsumoto

Journal volume & issue
Vol. 9
pp. 11 – 18

Abstract

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Osteoporosis is a skeletal disorder characterized by compromised bone strength and increased risk of fracture. Low bone mass and/or pre-existing bone fragility fractures serve as diagnostic criteria in deciding when to start medication for osteoporosis. Although osteoporosis is a metabolic disorder, metabolic markers to predict reduced bone mass are unknown. Here, we show serum metabolomics profiles of women grouped as pre-menopausal with normal bone mineral density (BMD) (normal estrogen and normal BMD; NN), post-menopausal with normal BMD (low estrogen and normal BMD; LN) or post-menopausal with low BMD (low estrogen and low BMD; LL) using comprehensive metabolomics analysis. To do so, we enrolled healthy volunteer and osteoporosis patient female subjects, surveyed them with a questionnaire, measured their BMD, and then undertook a comprehensive metabolomics analysis of sera of the three groups named above. We identified 24 metabolites whose levels differed significantly between NN/LN and NN/LL groups, as well as 18 or 10 metabolites whose levels differed significantly between NN/LN and LN/LL, or LN/LL and NN/LN groups, respectively. Our data shows metabolomics changes represent useful markers to predict estrogen deficiency and/or bone loss. Keywords: Metabolomics, Metabolite, Women, Estradiol, Estrogen, Menopause, Bone mineral density