波谱学杂志2016，Vol.33Issue(3)：395-405,11.DOI:10.11938/cjmr20160304
运动员与体力劳动者代谢组学判别模型的建立
Urinary Metabonome Differentiates Athletes and Labor Workers
摘要
Abstract
Under the concept of personal-based health care, different health management strategies are needed for different populations. To achieve this goal, the first step is to characterize the health-related differences among different populations. To this end, we recruited a total of 31 athletes and 42 labor workers to exam population-level differences in their urinary metabonome. First morning urine was collected and stored at-80℃ until use. 1H NMR spectra of the urine samples were collected on a 600 MHz spectrometer. The data collected were then used to build supervised and unsupervised pattern recognition models (PCA model and OPLS-DA model) to differentiate the two populations. Metabolites contributing significantly to the population difference in urinary metabonome were identified byVIP plot, among which false positives were discovered by receiver operating characteristic curve (ROC) andt-test. Predictive PLS-DA model was built, and validated by internal cross-validation, permutation tests and external prediction. The results showed that a PLS-DA model built upon 20 discriminating metabolites had the best predictive accuracy (AUC = 0.998), and the most significant level (p= 3.34×10–5). In addition, all samples from the external prediction set were classified correctly, suggesting that the PLS-DA model built upon 20 discriminating metabolites had high sensitivity and specificity.关键词
核磁共振(NMR)/代谢组学/模式识别/模型检验Key words
nuclear magnetic resonance (NMR)/metabonomics/pattern recognition/model verification分类
数理科学引用本文复制引用
陈朴,于燕波,黄贱英,李红毅,董海胜,陈斌..运动员与体力劳动者代谢组学判别模型的建立[J].波谱学杂志,2016,33(3):395-405,11.基金项目
航天医学基础与应用国家重点实验室基金资助项目(SMFA11A03)，国家自然科学基金资助项目(31101251、81202612) （SMFA11A03）
