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

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)11-18
Number of pages8
JournalBone Reports
Volume9
DOIs
Publication statusPublished - 12-2018

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Orthopedics and Sports Medicine

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