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Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories

机译:共享的参考材料在基于MS的检测平台和实验室之间协调脂质组学

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摘要

Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: ) different sample introduction methods (separation vs. DI methods); ) different MS instruments; and ) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., “shared references”) can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma.
机译:人血浆脂质的定量质谱分析是一种有前途的技术,可转化为临床应用。当前基于MS的脂质组学方法依赖于直接输注(DI)或色谱脂质分离方法(包括反相和亲水相互作用LC)。但是,由于缺乏参考值,脂质标记物在实验室医学中的使用受到了限制,这在很大程度上是因为全世界不同实验室所测量的浓度存在很大差异。即使使用相同的起始原料,也可以通过使用不同的样品制备方案,特定于方法的校准程序以及其他实验和数据报告参数来解释这些不一致之处。在这里,我们通过考虑以下因素,系统地研究了其中一些变量在健康成年人血浆样品脂质分析的多种方法中的作用:)不同的样品引入方法(分离与DI方法); )不同的MS仪器;和)可比分析平台中的实验室间差异。这些实验变量中的每一个都导致不同的定量结果,甚至包括针对各个脂质类别的同位素标记内标。我们证明,对常用参考样品(即“共享参考”)进行适当的归一化可以很大程度上纠正这些系统的方法特定的定量偏差。因此,为了协调脂质组学领域的数据,对于人类血浆,应在内部长期参考文献上添加通用的共享参考样本,例如NIST SRM 1950。

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