INTRODUCTION When analyzing the human plasma metabolome with Nuclear Magnetic Resonance (NMR) spectroscopy, the Carr-Purcell-Meiboom-Gill (CPMG) experiment is commonly employed for large studies. However, this process can lead to compromised statistical analyses due to residual macromolecule signals. In addition, the utilization of Trimethylsilylpropanoic acid (TSP) as an internal standard often leads to quantification issues, and binning, as a spectral summarization step, can result in features not clearly assignable to metabolites. OBJECTIVES Our aim was to establish a new complete protocol for large plasma cohorts collected with the purpose of describing the comparative metabolic profile of groups of samples. METHODS We compared the conventional CPMG approach to a novel procedure that involves diffusion NMR, using the Longitudinal Eddy-Current Delay (LED) experiment, maleic acid (MA) as the quantification reference and peak picking for spectral reduction. This comparison was carried out using the ultrafiltration method as a gold standard in a simple sample classification experiment, with Partial Least Squares-Discriminant Analysis (PLS-DA) and the resulting metabolic signatures for multivariate data analysis. In addition, the quantification capabilities of the method were evaluated. RESULTS We found that the LED method applied was able to detect more metabolites than CPMG and suppress macromolecule signals more efficiently. The complete protocol was able to yield PLS-DA models with enhanced classification accuracy as well as a more reliable set of important features than the conventional CPMG approach. Assessment of the quantitative capabilities of the method resulted in good linearity, recovery and agreement with an established amino acid assay for the majority of the metabolites tested. Regarding repeatability, ~ 85% of all peaks had an adequately low coefficient of variation (< 30%) in replicate samples. CONCLUSION Overall, our comparison yielded a high-throughput untargeted plasma NMR protocol for optimized data acquisition and processing that is expected to be a valuable contribution in the field of metabolic biomarker discovery.

中文翻译：

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用于比较非靶向代谢组学的高通量血浆 NMR 方案的比较。


简介 在使用核磁共振 (NMR) 波谱分析人血浆代谢组时，大型研究通常采用 Carr-Purcell-Meiboom-Gill (CPMG) 实验。然而，由于残留的大分子信号，该过程可能会导致统计分析受到影响。此外，使用三甲基甲硅烷基丙酸 (TSP) 作为内标通常会导致量化问题，而分箱作为光谱汇总步骤可能会导致无法明确分配给代谢物的特征。目标我们的目标是为收集的大量血浆建立一个新的完整方案，目的是描述样本组的比较代谢特征。方法 我们将传统的 CPMG 方法与涉及扩散 NMR 的新颖程序进行了比较，使用纵向涡流延迟 (LED) 实验、马来酸 (MA) 作为定量参考和光谱缩减的峰值选取。这种比较是在简单的样品分类实验中使用超滤方法作为金标准进行的，并使用偏最小二乘判别分析 (PLS-DA) 和由此产生的代谢特征进行多变量数据分析。此外，还评估了该方法的定量能力。结果我们发现所应用的 LED 方法能够比 CPMG 检测更多的代谢物，并更有效地抑制大分子信号。完整的协议能够生成具有更高分类精度的 PLS-DA 模型，以及比传统 CPMG 方法更可靠的一组重要特征。 该方法的定量能力评估显示出良好的线性、回收率，并且与大多数测试代谢物的既定氨基酸测定一致。关于重复性，在重复样品中，约 85% 的所有峰具有足够低的变异系数 (< 30%)。结论 总的来说，我们的比较产生了一种高通量非靶向血浆 NMR 方案，用于优化数据采集和处理，预计将在代谢生物标志物发现领域做出有价值的贡献。