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 (Ppermutation = 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.
Keywords: Bone mineral density; Liquid chromatography-mass spectrometry; Metabolites; Metabolomic; Osteoporosis.