Shotgun Lipidomics and Alterations in Sphingolipidomes in Alzheimer's Diseases

描述（由申请人提供）：脂质组学是对细胞脂质途径和网络的大规模研究，是一个新兴且迅速扩展的研究领域。通过使用鸟枪脂质组学（一种PI最近开发的技术）分析脑脂质，我们已经表明，在阿尔茨海默病的最早临床可识别阶段（即，非常轻微的AD）。硫脂丢失和神经酰胺升高代表AD发病机制的早期事件，并可能导致神经变性、突触丢失和AD病理学的发展。然而，导致这些变化的原因仍然未知。此外，目前还不清楚其他鞘脂类的质量水平是否也发生在非常轻度的AD中，哪些途径发生变化导致这些变化，以及这些脂质变化是否是AD早期诊断的潜在生物标志物。为了确定AD中硫苷脂损失和神经酰胺增加的原因并解决上述问题，我们将进一步开发鸟枪脂质组学，以分析所有感兴趣的脂质类别，特别是许多次要的鞘脂类别。将开发一种生物信息学方法，以产生复杂的脂质组学数据的自动化，高通量处理，以确定由疾病状态引起的脂质分子种类的改变，并构建脂质代谢网络图。所开发平台的结构应该适合识别任何疾病状态引起的脂质代谢途径的改变。然而，我们将把我们提出的研究重点放在识别非常轻度AD中存在的鞘脂体网络改变途径的生化机制上，并通过使用开发的平台确定非常轻度AD受试者脑组织和脑脊液的脂质谱改变来发现用于早期诊断AD的潜在脂质生物标志物。总的来说，在本申请中，我们将进一步开发鸟枪脂质组学和综合生物信息学程序，并将此开发的平台应用于AD研究。所得结果将揭示AD中硫苷脂丢失的生化机制，鉴定用于AD早期诊断的新型脂质生物标志物，并提供对AD发病机制的深入了解。

DESCRIPTION (provided by applicant): Lipidomics, the large-scale study of the pathways and networks of cellular lipids, is an emerging and rapidly expanding research field. Through the analyses of brain lipids using shotgun lipidomics, a technology recently developed by the PI, we have shown that a substantial mass loss of sulfatide (a class of specialized myelin sphingolipids) and a significant mass increase in ceramide (a class of sphingolipid metabolites associated with cell death) are present in individuals at the earliest clinically-recognizable stage of Alzheimer's disease (i.e., very mild AD). Sulfatide loss and ceramide elevation represent early events in AD pathogenesis and may contribute to neurodegeneration, synapse loss, and the development of AD pathology. However, the cause(s) leading to these changes still remain unknown. Moreover, it is unclear whether alterations in the mass levels of other sphingolipid classes also occur in very mild AD, which pathways are changed leading to these alterations, and whether these lipid alterations are potential biomarkers for the early diagnosis of AD. To identify the cause(s) of sulfatide loss and ceramide increase in AD and to address the above questions, we will further develop shotgun lipidomics to analyze all lipid classes of interest, specifically many minor sphingolipid classes. A bioinformatics approach will be developed to yield automated, high-throughput processing of complex lipidomics data, to identify the altered lipid molecular species induced by a disease state, and to construct a lipid metabolic network map. The structure of the developed platform should be suitable to identify altered pathways of lipid metabolism induced by any disease state. However, we will focus our proposed studies on the identification of the biochemical mechanism(s) underlying the altered pathways of the sphingolipidome networks present in very mild AD and the discovery of potential lipid biomarkers for the early diagnosis of AD through determination of the altered lipid profiles of brain tissue and cerebrospinal fluid from subjects with very mild AD using the developed platform. Collectively, in this application, we will further develop shotgun lipidomics and an integrated bioinformatics program and will apply this developed platform for AD studies. The obtained results will reveal the biochemical mechanisms underlying sulfatide loss in AD, identify novel lipid biomarkers for the early diagnosis of AD, and provide insight into AD pathogenesis.