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通过与骨密度的关联对骨质疏松症进行代谢组学研究。

Metabolomics Insights into Osteoporosis Through Association With Bone Mineral Density.

机构信息

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.

出版信息

J Bone Miner Res. 2021 Apr;36(4):729-738. doi: 10.1002/jbmr.4240. Epub 2021 Feb 2.

Abstract

Osteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by liquid chromatography with tandem mass spectrometry (LC-MS/MS) in 1552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2 to 10 years later using dual-energy X-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified 27 metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (area under the curve [AUC] = 0.74 for the model with identified metabolites and risk factors versus AUC = 0.70 with risk factors alone, p = .001; net reclassification index = 0.07, p = .03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (false discovery rate [FDR] p value = .028). Furthermore, three causally related metabolites (glycine, phosphatidylcholine [PC], and triacylglycerol [TAG]) were negatively associated with FN-BMD, whereas PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).

摘要

骨质疏松症是一种以骨矿物质密度(BMD)降低为特征的疾病,会增加骨折的风险。仅使用传统危险因素并不能完全解释测量的 BMD 或骨质疏松性骨折风险。代谢组学可能提供更多信息。我们的目的是确定与 BMD 相关的代谢标志物,这些标志物可预测骨折风险。我们通过液相色谱-串联质谱法(LC-MS/MS)评估了 1552 名弗雷明汉后代研究参与者的 209 种血浆代谢物,并在 2 至 10 年后使用双能 X 线吸收法测量股骨颈(FN)和腰椎(LS)BMD。在代谢组学分析后长达 27 年的随访期间,我们评估了骨质疏松性骨折。通过内部验证的 LASSO 回归,我们确定了 27 种与 FN-BMD 或 LS-BMD 相关的代谢物。纳入选定的代谢物可显著提高预测和分类骨质疏松性骨折风险的能力,超越传统危险因素(纳入鉴定代谢物和危险因素的模型的曲线下面积 [AUC]为 0.74,而仅纳入危险因素的 AUC 为 0.70,p =.001;净重新分类指数 = 0.07,p =.03)。在来自香港骨质疏松症研究(HKOS)的 634 名参与者中,我们复制了通过纳入选定代谢物来改善骨折预测的显著效果。甘氨酸、丝氨酸和苏氨酸代谢途径(包括鉴定出的四种代谢物:肌酸、二甲基甘氨酸、甘氨酸和丝氨酸)显著富集(错误发现率 [FDR]p 值 =.028)。此外,通过 Mendelian 随机分析发现,三种因果相关的代谢物(甘氨酸、磷脂酰胆碱 [PC]和三酰甘油 [TAG])与 FN-BMD 呈负相关,而 PC 和 TAG 与 LS-BMD 呈负相关。总之,与 BMD 相关的代谢物有助于预测骨质疏松性骨折风险。通过进一步的实验验证,解释这三种代谢物对 BMD 影响的潜在因果机制是值得的。我们的研究结果可能为骨质疏松症的发病机制提供新的见解。

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