A novel strategy for rapidly and accurately screening biomarkers based on ultraperformance liquid chromatography-mass spectrometry metabolomics data
A novel strategy for rapidly and accurately screening biomarkers based on ultraperformance liquid chromatography-mass spectrometry metabolomics data
复制标题
基于超高效液相色谱-质谱代谢组学数据快速准确筛选生物标志物的新策略
DOI：
10.1016/j.aca.2019.03.012
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发表时间：
2019-07-31
影响因子：
6.2
通讯作者：
Ling, Xiaomei
中科院分区：
文献类型：
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作者：
Li, Cong;Zhang, Jianmei;Ling, Xiaomei
我们报道了一种基于超高效液相色谱-质谱（UPLC-MS）代谢组学数据快速准确筛选生物标志物的新策略。首先，通过方法验证对原始变量进行筛选，得到初步变量。其次，从初步变量中选择变量，并通过检验不同的单因素阈值（变量投影重要性（VIP）、倍数变化（FC）、受试者工作特征曲线下面积（AUROC）和-ln（p值））形成变量集。然后进行偏最小二乘判别分析（PLS-DA）模型。通过对模型（RX）-X-2、（RY）-Y-2和Q（2）的比较，确定了各因子的最佳阈值和相应的变量集。第三，对第二步得到的变量集进行多因素筛选。通过（RX）-X-2、（RY）-Y-2和Q（2）的比较，找出了多因素的最佳组合和相应的变量集。因此获得了预期的生物标志物。该策略成功应用于阿尔茨海默病（AD）模型的尿液、血浆、海马和皮层样品中生物标志物的筛选，显著缩短了筛选和鉴定生物标志物的时间，改善了（RX）-X-2、（RY）-Y-2和Q（2），从而增强了PLS-DA模型的解释、分组和预测能力。这项工作可以为寻找潜在生物标志物的科学家提供有价值的线索。该方法可用于快速、高效、准确地筛选生物标志物。(C)2019 Elsevier B. V.版权所有。
We reported a novel strategy for rapidly and accurately screening biomarkers based on ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) metabolomics data. First, the preliminary variables were obtained by screening the original variables using method validation. Second, the variables were selected from the preliminary variables and formed the variable sets by testing different thresholds of single factor (variable importance in projection (VIP), fold change (FC), the area under the receiver operating characteristic curve (AUROC), and -ln(p-value)). Then the partial least squares-discriminant analysis (PLS-DA) models were performed. The best threshold of each factor, and the corresponding variable set were found by comparing the models' (RX)-X-2, (RY)-Y-2, and Q(2). Third, the second-step-obtained variable sets were further screened by multi-factors. The best combination of the multi-factors, and the corresponding variable set were found by comparing (RX)-X-2, (RY)-Y-2, and Q(2). The expected biomarkers were thus obtained. The proposed strategy was successfully applied to screen biomarkers in urine, plasma, hippocampus, and cortex samples of Alzheimer's disease (AD) model, and significantly decreased the time of screening and identifying biomarkers, improved the (RX)-X-2, (RY)-Y-2, and Q(2), therefore enhanced the interpreting, grouping, and predicting abilities of the PLS-DA model compared with generally-applied procedure. This work can provide a valuable clue to scientists who search for potential biomarkers. It is expected that the developed strategy can be written as a program and applied to screen biomarkers rapidly, efficiently and accurately. (C) 2019 Elsevier B.V. All rights reserved.