全球代谢组学雷区:研究罕见疾病时分析前因素的混淆效应

IF 3 Q2 CHEMISTRY, ANALYTICAL Analytical science advances Pub Date : 2023-07-21 DOI:10.1002/ansa.202300010
Hanne Bendiksen Skogvold, Steven Ray Haakon Wilson, Per Ola Rønning, Linda Ferrante, Siri Hauge Opdal, Torleiv Ole Rognum, Helge Rootwelt, Katja Benedikte Prestø Elgstøen
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引用次数: 1

摘要

在研究罕见疾病或医疗条件时,一个常见的挑战是患者数量有限,通常导致较长的纳入期以及不平等的采样和存储条件。本研究的主要目的是展示在比较样品时受到不同的分析前条件的挑战。在使用化学处理过的滤卡制备新的干血点之前,我们对来自婴儿猝死综合征病例和对照组的血液样本进行了全球(通常称为“非靶向”)液相色谱-高分辨率质谱代谢组学分析,这些血液样本作为干血点在无化学处理的滤卡上保存15年,在室温下与作为全血在- 80°C下保存的相同血液样本进行了比较。主成分分析图根据过滤卡的类型和存储方式明显区分了样本,但没有区分婴儿猝死综合征与对照组。值得注意的是,分别在正电离和负电离模式下检测到的5161个和1587个代谢物特征中,有1263个和642个被发现在不同的分析前条件下有显著的2倍变化。研究表明,干血斑代谢组在很大程度上受分析前因素的影响。这强调了在研究设计和解释过程中彻底解决分析前因素的重要性,从而能够识别样本组之间真实的生物学差异,同时防止其他因素或随机变化被错误地解释为阳性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A global metabolomics minefield: Confounding effects of preanalytical factors when studying rare disorders

A common challenge when studying rare diseases or medical conditions is the limited number of patients, usually resulting in long inclusion periods as well as unequal sampling and storage conditions. The main purpose of this study was to demonstrate the challenges when comparing samples subject to different preanalytical conditions. We performed a global (commonly referred to as “untargeted”) liquid chromatography-high resolution mass spectrometry metabolomics analysis of blood samples from cases of sudden infant death syndrome and controls stored as dried blood spots on a chemical-free filter card for 15 years at room temperature compared with the same blood samples stored as whole blood at −80°C before preparing new dried blood spots using a chemically treated filter card. Principal component analysis plots distinctly separated the samples based on the type of filter card and storage, but not sudden infant death syndrome versus controls. Note that, 1263 out of 5161 and 642 out of 1587 metabolite features detected in positive and negative ionization mode, respectively, were found to have significant 2-fold changes in amounts corresponding to different preanalytical conditions. The study demonstrates that the dried blood spot metabolome is largely affected by preanalytical factors. This emphasizes the importance of thoroughly addressing preanalytical factors during study design and interpretation, enabling identification of real, biological differences between sample groups whilst preventing other factors or random variation to be falsely interpreted as positive results.

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