Metabolomic profiles associated with bone mineral density in US Caucasian women

Qi Zhao, Hui Shen, Kuan Jui Su, Ji Gang Zhang, Qing Tian, Lan Juan Zhao, Chuan Qiu, Qiang Zhang, Timothy J. Garrett, Jiawang Liu, Hong Wen Deng

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. Methods: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. Results: The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (P permutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95% CI: 0.83-0.94) and 0.97 (95% CI: 0.94-0.99), respectively (P for the difference = 0.0004). Conclusion: Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.

Original languageEnglish (US)
Article number57
JournalNutrition and Metabolism
Volume15
Issue number1
DOIs
StatePublished - Aug 10 2018

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Metabolomics
Bone Density
Discriminant Analysis
Least-Squares Analysis
Bile Acids and Salts
Amino Acids
Logistic Models
Pelvic Bones
Osteoporotic Fractures
Bone Fractures
Serum
ROC Curve
Liquid Chromatography
Osteoporosis
Mass Spectrometry
Lipids
Bone and Bones
Acids
Health

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics

Cite this

Metabolomic profiles associated with bone mineral density in US Caucasian women. / Zhao, Qi; Shen, Hui; Su, Kuan Jui; Zhang, Ji Gang; Tian, Qing; Zhao, Lan Juan; Qiu, Chuan; Zhang, Qiang; Garrett, Timothy J.; Liu, Jiawang; Deng, Hong Wen.

In: Nutrition and Metabolism, Vol. 15, No. 1, 57, 10.08.2018.

Research output: Contribution to journalArticle

Zhao, Q, Shen, H, Su, KJ, Zhang, JG, Tian, Q, Zhao, LJ, Qiu, C, Zhang, Q, Garrett, TJ, Liu, J & Deng, HW 2018, 'Metabolomic profiles associated with bone mineral density in US Caucasian women', Nutrition and Metabolism, vol. 15, no. 1, 57. https://doi.org/10.1186/s12986-018-0296-5
Zhao, Qi ; Shen, Hui ; Su, Kuan Jui ; Zhang, Ji Gang ; Tian, Qing ; Zhao, Lan Juan ; Qiu, Chuan ; Zhang, Qiang ; Garrett, Timothy J. ; Liu, Jiawang ; Deng, Hong Wen. / Metabolomic profiles associated with bone mineral density in US Caucasian women. In: Nutrition and Metabolism. 2018 ; Vol. 15, No. 1.
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abstract = "Background: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. Methods: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. Results: The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (P permutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95{\%} CI: 0.83-0.94) and 0.97 (95{\%} CI: 0.94-0.99), respectively (P for the difference = 0.0004). Conclusion: Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.",
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AU - Su, Kuan Jui

AU - Zhang, Ji Gang

AU - Tian, Qing

AU - Zhao, Lan Juan

AU - Qiu, Chuan

AU - Zhang, Qiang

AU - Garrett, Timothy J.

AU - Liu, Jiawang

AU - Deng, Hong Wen

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N2 - Background: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. Methods: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. Results: The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (P permutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95% CI: 0.83-0.94) and 0.97 (95% CI: 0.94-0.99), respectively (P for the difference = 0.0004). Conclusion: Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.

AB - Background: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. Methods: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. Results: The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (P permutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95% CI: 0.83-0.94) and 0.97 (95% CI: 0.94-0.99), respectively (P for the difference = 0.0004). Conclusion: Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.

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