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应用 ID-LC-MS/MS 定量蛋白质的测量不确定度评估。

Estimation of measurement uncertainty for the quantification of protein by ID-LC-MS/MS.

机构信息

Material Measurement Laboratory (Biomolecular Measurement Division), National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899-8390, USA.

Information Technology Laboratory (Statistical Engineering Division), National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899-8390, USA.

出版信息

Anal Bioanal Chem. 2023 Jul;415(16):3265-3274. doi: 10.1007/s00216-023-04705-8. Epub 2023 May 26.

Abstract

The emergence of mass spectrometry (MS)-based methods to quantify proteins for clinical applications has led to the need for accurate and consistent measurements. To meet the clinical needs of MS-based protein results, it is important that the results are traceable to higher-order standards and methods and have defined uncertainty values. Therefore, we outline a comprehensive approach for the estimation of measurement uncertainty of a MS-based procedure for the quantification of a protein biomarker. Using a bottom-up approach, which is the model outlined in the "Guide to the Expression of Uncertainty of Measurement" (GUM), we evaluated the uncertainty components of a MS-based measurement procedure for a protein biomarker in a complex matrix. The cause-and-effect diagram of the procedure is used to identify each uncertainty component, and statistical equations are derived to determine the overall combined uncertainty. Evaluation of the uncertainty components not only enables the calculation of the measurement uncertainty but can also be used to determine if the procedure needs improvement. To demonstrate the use of the bottom-up approach, the overall combined uncertainty is estimated for the National Institute of Standards and Technology (NIST) candidate reference measurement procedure for albumin in human urine. The results of the uncertainty approach are applied to the determination of uncertainty for the certified value for albumin in candidate NIST Standard Reference Material® (SRM) 3666. This study provides a framework for measurement uncertainty estimation of a MS-based protein procedure by identifying the uncertainty components of the procedure to derive the overall combined uncertainty.

摘要

基于质谱(MS)的方法在临床应用中定量蛋白质的出现,导致了对准确和一致的测量的需求。为了满足基于 MS 的蛋白质结果的临床需求,重要的是将结果追溯到更高级别的标准和方法,并具有定义的不确定度值。因此,我们概述了一种全面的方法,用于估算基于 MS 的蛋白质生物标志物定量程序的测量不确定度。使用自下而上的方法,即“测量不确定度表达指南”(GUM)中概述的模型,我们评估了复杂基质中基于 MS 的蛋白质生物标志物测量程序的不确定度分量。程序的因果图用于识别每个不确定度分量,并推导出统计方程来确定整体组合不确定度。评估不确定度分量不仅可以计算测量不确定度,还可以确定程序是否需要改进。为了演示自下而上方法的使用,我们估计了美国国家标准与技术研究院(NIST)候选参考测量程序在人尿中白蛋白的整体组合不确定度。不确定性方法的结果应用于确定候选 NIST 标准参考物质(SRM)3666 中白蛋白的认证值的不确定度。本研究通过确定程序的不确定度分量来推导出整体组合不确定度,为基于 MS 的蛋白质程序的测量不确定度估算提供了框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b494/10287794/0e10cb60c0b3/216_2023_4705_Fig1_HTML.jpg

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