Untargeted Metabolomic Analysis of Human Plasma Indicates Differentially Affected Polyamine and L-Arginine Metabolism in Mild Cognitive Impairment Subjects Converting to Alzheimer's Disease
Untargeted Metabolomic Analysis of Human Plasma Indicates Differentially Affected Polyamine and L-Arginine Metabolism in Mild Cognitive Impairment Subjects Converting to Alzheimer's Disease
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DOI：
10.1371/journal.pone.0119452
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发表时间：
2015-03-24
期刊：
影响因子：
3.7
通讯作者：
Green, Brian D.
中科院分区：
文献类型：
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作者：
Graham, Stewart F.;Chevallier, Olivier P.;Green, Brian D.
本研究结合高分辨率质谱（HRMS），先进的化学计量学和途径富集分析，分析参加记忆诊所的患者的血液代谢组：轻度认知障碍（MCI; n = 16），MCI的情况下，在后续的后续发展阿尔茨海默氏病（MCI_AD; n = 19），和健康的年龄匹配的控制（对照; n = 37）。用乙腈提取血浆，并使用先前优化的方法，将其上样至与Xevo G2 QT质谱仪偶联的Acquity UPLC HILIC（1.7 μ m x 2.1 x 100 mm）色谱柱。使用包括6751个光谱特征的数据来构建能够准确区分Ctrl、MCI和MCI_AD的OPLS-DA统计模型。该模型准确地区分了（R2 = 99.1%; Q2 = 97%）那些后来发展为AD的MCI患者。使用S图来筛选感兴趣的离子，这些离子负责解释患者组之间的最大变异量。代谢物数据库搜索和途径富集分析表明22个生化途径的干扰，令人兴奋的是，它发现两个相互关联的代谢领域（多胺代谢和L-精氨酸代谢）在这个明确定义的临床队列中被不同地破坏。本文所述的优化的非靶向HRMS方法不仅证明了可以区分人血液中的这些病理，而且还证明了可以比常规临床诊断早多达2年预测“处于AD风险中”的MCI患者。来自记忆诊所患者的血浆的基于血液的代谢物谱分析是改善MCI和AD诊断以及通过更好的患者分层来完善临床试验的新颖且可行的方法。
This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy agematched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7 mu m x 2.1 x 100 mm) column coupled to a Xevo G2 QT of mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.