Pulmonary Research Group, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Department of Clinical, Social and Administrative Sciences, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.
PLoS One. 2014 Jan 21;9(1):e85732. doi: 10.1371/journal.pone.0085732. eCollection 2014.
We discovered that serious issues could arise that may complicate interpretation of metabolomic data when identical samples are analyzed at more than one NMR facility, or using slightly different NMR parameters on the same instrument. This is important because cross-center validation metabolomics studies are essential for the reliable application of metabolomics to clinical biomarker discovery. To test the reproducibility of quantified metabolite data at multiple sites, technical replicates of urine samples were assayed by 1D-(1)H-NMR at the University of Alberta and the University of Michigan. Urine samples were obtained from healthy controls under a standard operating procedure for collection and processing. Subsequent analysis using standard statistical techniques revealed that quantitative data across sites can be achieved, but also that previously unrecognized NMR parameter differences can dramatically and widely perturb results. We present here a confirmed validation of NMR analysis at two sites, and report the range and magnitude that common NMR parameters involved in solvent suppression can have on quantitated metabolomics data. Specifically, saturation power levels greatly influenced peak height intensities in a frequency-dependent manner for a number of metabolites, which markedly impacted the quantification of metabolites. We also investigated other NMR parameters to determine their effects on further quantitative accuracy and precision. Collectively, these findings highlight the importance of and need for consistent use of NMR parameter settings within and across centers in order to generate reliable, reproducible quantified NMR metabolomics data.
我们发现，当相同的样本在多个 NMR 设备上进行分析，或在同一台仪器上使用略有不同的 NMR 参数时，可能会出现严重的问题，从而使代谢组学数据的解释变得复杂。这一点很重要，因为跨中心验证代谢组学研究对于代谢组学在临床生物标志物发现中的可靠应用是必不可少的。为了测试多个地点定量代谢物数据的重现性，我们在阿尔伯塔大学和密歇根大学使用 1D-（1）H-NMR 对尿液样本的技术重复进行了检测。尿液样本是按照采集和处理的标准操作规程从健康对照者中获得的。随后使用标准统计技术进行的分析表明，可以实现跨站点的定量数据，但也表明以前未被识别的 NMR 参数差异会极大地扰乱结果。我们在这里对两个站点的 NMR 分析进行了确认验证，并报告了溶剂抑制中常见的 NMR 参数对定量代谢组学数据的影响范围和幅度。具体来说，对于许多代谢物，饱和功率水平以频率相关的方式极大地影响了峰高强度，这显著影响了代谢物的定量。我们还研究了其他 NMR 参数，以确定它们对进一步定量准确性和精密度的影响。总的来说，这些发现强调了在中心内和中心之间一致使用 NMR 参数设置以生成可靠、可重现的定量 NMR 代谢组学数据的重要性和必要性。
