Shao Yaping, Ouyang Yang, Li Tianbai, Liu Xinyao, Xu Xiaojiao, Li Song, Xu Guowang, Le Weidong
1Center for Clinical Research on Neurological Diseases, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
2Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Aging Dis. 2020 Dec 1;11(6):1459-1470. doi: 10.14336/AD.2020.0217. eCollection 2020 Dec.
The expending of elderly population worldwide has resulted in a dramatic rise in the incidence of chronic diseases such as Alzheimer's disease (AD). Inadequate understanding of the mechanisms underlying AD has hampered the development of efficient tools for definitive diagnosis and curative interventions. Previous studies have attempted to discover reliable biomarkers of AD, but these biomarkers can only be measured through invasive (neuropathological markers in cerebrospinal fluid) or expensive (positron emission tomography scanning or magnetic resonance imaging) techniques. Metabolomics is a high-throughput technology that can detect and catalog large numbers of small metabolites and may be a useful tool for characterization of AD and identification of biomarkers. In this study, we used ultra-performance liquid chromatography-mass spectrometry based untargeted metabolomics to measure the concentrations of plasma metabolites in a cohort of subjects with AD (n=44) and cognitively normal controls (Ctrl, n=94). The AD group showed marked reductions in levels of polyunsaturated fatty acids, acyl-carnitines, degradation products of tryptophan, and elevated levels of bile acids compared to the Ctrl group. We then validated the results using an independent cohort that included subjects with AD (n=30), mild cognitive impairment (MCI, n=13), healthy controls (n=43), and non-AD neurological disease controls (NDC, n=31). We identified five metabolites comprising cholic acid, chenodeoxycholic acid, allocholic acid, indolelactic acid, and tryptophan that were able to distinguish patients with AD from both Ctrl and NDC with satisfactory sensitivity and specificity. The concentrations of these metabolites were significantly correlated with disease severity. Our results also suggested that altered bile acid profiles in AD and MCI might indicate early risk for the development of AD. These findings may allow for development of new approaches for diagnosis of AD and may provide novel insights into AD pathogenesis.
全球老年人口的增加导致了诸如阿尔茨海默病（AD）等慢性疾病的发病率急剧上升。对AD潜在机制的认识不足阻碍了有效诊断工具和治疗干预措施的开发。先前的研究试图发现AD的可靠生物标志物，但这些生物标志物只能通过侵入性（脑脊液中的神经病理标志物）或昂贵（正电子发射断层扫描或磁共振成像）技术进行测量。代谢组学是一种高通量技术，可以检测和分类大量小分子代谢物，可能是用于AD特征描述和生物标志物鉴定的有用工具。在本研究中，我们使用基于超高效液相色谱 - 质谱的非靶向代谢组学方法测量了一组AD患者（n = 44）和认知正常对照（Ctrl，n = 94）的血浆代谢物浓度。与Ctrl组相比，AD组的多不饱和脂肪酸、酰基肉碱、色氨酸降解产物水平显著降低，胆汁酸水平升高。然后，我们使用一个独立队列验证了结果，该队列包括AD患者（n = 30）、轻度认知障碍（MCI，n = 13）、健康对照（n = 43）和非AD神经疾病对照（NDC，n = 31）。我们鉴定出五种代谢物，包括胆酸、鹅去氧胆酸、别胆酸、吲哚乳酸和色氨酸，它们能够以令人满意的灵敏度和特异性将AD患者与Ctrl和NDC区分开来。这些代谢物的浓度与疾病严重程度显著相关。我们的结果还表明，AD和MCI中胆汁酸谱的改变可能表明AD发生的早期风险。这些发现可能有助于开发AD诊断的新方法，并可能为AD发病机制提供新的见解。
