Department of Chemistry, University of Alberta, Edmonton, Canada.
Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.
J Alzheimers Dis. 2018;65(4):1401-1416. doi: 10.3233/JAD-180711.
Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.
我们使用非侵入性生物体液(唾液),应用强大的代谢组学工作流程,在阿尔茨海默病(AD)中进行无偏生物标志物的发现。我们对认知正常(CN)、轻度认知障碍(MCI)和 AD 组进行了分析和区分。该工作流程涉及使用 Dansylation 衍生化进行差异化化学同位素标记液相色谱质谱分析,以深入分析胺/酚亚代谢组。总共(N = 109)个样本分为发现阶段(DP)(n = 82;35 个 CN、25 个 MCI、22 个 AD)和暂定验证阶段(VP)(n = 27;10 个 CN、10 个 MCI、7 个 AD)。在 DP 中,我们检测到了 6230 种代谢物。两两分析证实了 AD 与 CN(63)、AD 与 MCI(47)和 MCI 与 CN(2)的生物标志物。然后,我们确定了最佳的区分生物标志物和诊断面板。一个 3 种代谢物的面板可区分 AD 与 CN 和 MCI(DP 和 VP:曲线下面积 [AUC] = 1.000)。MCI 和 CN 组的最佳区分面板是 2 种代谢物(DP:AUC = 0.779;VP:AUC = 0.889)。此外,使用经过正向验证的代谢物,我们能够区分 AD 与 CN 和 MCI,且具有良好的诊断性能(AUC>0.8)。唾液是一种有前途的生物体液,可用于进行无偏和靶向 AD 生物标志物的发现和机制检测。鉴于其广泛的可用性和方便的可及性,唾液是一种可促进全球 AD 生物标志物研究多样化的生物体液。