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

作　　者：陈朴[1] 于燕波[1] 黄贱英[1] 李红毅[1] 董海胜[1] 陈斌[1] 

机构地区：[1]中国航天员科研训练中心,航天医学基础与应用国家重点实验室,航天营养与食品工程重点实验室,北京100094

出　　处：《波谱学杂志》2016年第3期395-405,共11页Chinese Journal of Magnetic Resonance

基　　金：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)

摘　　要：不同职业的人群健康状态不同,需要不同的健康管理方法,根据各类人群的体质特征建立健康状态的评估方法有助于开展个性化的健康指导.招募运动员(Athlete,n=31)和体力劳动者(Labour,n=42)共73人,分别收集两组志愿者的晨尿.运用一维核磁共振(1D NMR)技术检测尿液中的代谢产物.建立主成分(PCA)及正交偏最小二乘判别分析(OPLS-DA)模型筛选2类人群间的差异代谢标志物.通过可接收操作特征曲线(ROC)评价代谢标志物的假阳性特征,t-test检验代谢标志物的显著性.利用代谢标志物建立两类人群的偏最小二乘判别分析(PLS-DA)预测模型.模型的有效性通过内部交叉、置换检验和外部预测检验确认.结果显示2类人群之间差异的代谢物有24个,通过其中20个代谢标志物建立的预测模型最优(曲线下面积AUC=0.998).内部交叉验证的误判率(FDR)分别为3.2%和0.内部置换检验的p=3.34×10^(–5).外部预测检验误判率为0.这为不同职业人群健康预测模型的建立提供了思路.Under the concept of personal-based health care, different health managementstrategies are needed for different populations. To achieve this goal, the first step is tocharacterize the health-related differences among different populations. To this end, werecruited a total of 31 athletes and 42 labor workers to exam population-level differences intheir 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 datacollected were then used to build supervised and unsupervised pattern recognition models（PCA model and OPLS-DA model） to differentiate the two populations. Metabolitescontributing significantly to the population difference in urinary metabonome wereidentified by VIP plot, among which false positives were discovered by receiver operatingcharacteristic curve （ROC） and t-test. Predictive PLS-DA model was built, and validated byinternal cross-validation, permutation tests and external prediction. The results showed thata 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 samplesfrom the external prediction set were classified correctly, suggesting that the PLS-DAmodel 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 

分 类 号：O482.53[理学—固体物理] O657.2[理学—物理]