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

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,...

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Autores principales: Miyamoto, Takeshi, Hirayama, Akiyoshi, Sato, Yuiko, Koboyashi, Tami, Katsuyama, Eri, Kanagawa, Hiroya, Fujie, Atsuhiro, Morita, Mayu, Watanabe, Ryuichi, Tando, Toshimi, Miyamoto, Kana, Tsuji, Takashi, Funayama, Atsushi, Soga, Tomoyoshi, Tomita, Masaru, Nakamura, Masaya, Matsumoto, Morio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019687/
https://www.ncbi.nlm.nih.gov/pubmed/29955645
http://dx.doi.org/10.1016/j.bonr.2018.06.004
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author Miyamoto, Takeshi
Hirayama, Akiyoshi
Sato, Yuiko
Koboyashi, Tami
Katsuyama, Eri
Kanagawa, Hiroya
Fujie, Atsuhiro
Morita, Mayu
Watanabe, Ryuichi
Tando, Toshimi
Miyamoto, Kana
Tsuji, Takashi
Funayama, Atsushi
Soga, Tomoyoshi
Tomita, Masaru
Nakamura, Masaya
Matsumoto, Morio
author_facet Miyamoto, Takeshi
Hirayama, Akiyoshi
Sato, Yuiko
Koboyashi, Tami
Katsuyama, Eri
Kanagawa, Hiroya
Fujie, Atsuhiro
Morita, Mayu
Watanabe, Ryuichi
Tando, Toshimi
Miyamoto, Kana
Tsuji, Takashi
Funayama, Atsushi
Soga, Tomoyoshi
Tomita, Masaru
Nakamura, Masaya
Matsumoto, Morio
author_sort Miyamoto, Takeshi
collection PubMed
description 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.
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spelling pubmed-60196872018-06-28 Metabolomics-based profiles predictive of low bone mass in menopausal women Miyamoto, Takeshi Hirayama, Akiyoshi Sato, Yuiko Koboyashi, Tami Katsuyama, Eri Kanagawa, Hiroya Fujie, Atsuhiro Morita, Mayu Watanabe, Ryuichi Tando, Toshimi Miyamoto, Kana Tsuji, Takashi Funayama, Atsushi Soga, Tomoyoshi Tomita, Masaru Nakamura, Masaya Matsumoto, Morio Bone Rep Article 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. Elsevier 2018-06-18 /pmc/articles/PMC6019687/ /pubmed/29955645 http://dx.doi.org/10.1016/j.bonr.2018.06.004 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Miyamoto, Takeshi
Hirayama, Akiyoshi
Sato, Yuiko
Koboyashi, Tami
Katsuyama, Eri
Kanagawa, Hiroya
Fujie, Atsuhiro
Morita, Mayu
Watanabe, Ryuichi
Tando, Toshimi
Miyamoto, Kana
Tsuji, Takashi
Funayama, Atsushi
Soga, Tomoyoshi
Tomita, Masaru
Nakamura, Masaya
Matsumoto, Morio
Metabolomics-based profiles predictive of low bone mass in menopausal women
title Metabolomics-based profiles predictive of low bone mass in menopausal women
title_full Metabolomics-based profiles predictive of low bone mass in menopausal women
title_fullStr Metabolomics-based profiles predictive of low bone mass in menopausal women
title_full_unstemmed Metabolomics-based profiles predictive of low bone mass in menopausal women
title_short Metabolomics-based profiles predictive of low bone mass in menopausal women
title_sort metabolomics-based profiles predictive of low bone mass in menopausal women
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019687/
https://www.ncbi.nlm.nih.gov/pubmed/29955645
http://dx.doi.org/10.1016/j.bonr.2018.06.004
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