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通路和网络的大规模研究，是一个新兴且迅速发展的研究领域。通过使用霰弹枪脂质组学（PI最近开发的一种技术）对脑脂质进行分析，我们已经表明，在阿尔茨海默病（即非常轻微的AD）的早期临床可识别阶段，个体中存在大量的硫脂质（一类特殊的髓鞘脂质）的质量损失和神经酰胺（一类与细胞死亡相关的鞘脂代谢产物）的质量显著增加。硫脂质丢失和神经酰胺升高代表了阿尔茨海默病发病的早期事件，并可能导致神经退行性变、突触丢失和阿尔茨海默病的病理发展。然而，导致这些变化的原因仍然未知。此外，目前尚不清楚其他鞘脂类质量水平的改变是否也发生在非常轻度的阿尔茨海默病中，哪些途径发生改变导致这些改变，以及这些脂质改变是否是阿尔茨海默病早期诊断的潜在生物标志物。为了确定阿尔茨海默病中硫脂质损失和神经酰胺增加的原因，并解决上述问题，我们将进一步发展散弹枪脂质组学来分析所有感兴趣的脂质类别，特别是许多次要的鞘脂类。将开发一种生物信息学方法，对复杂的脂质组学数据进行自动化、高通量处理，识别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。所开发的平台结构应适合于识别任何疾病状态引起的脂质代谢改变途径。然而，我们将把我们的研究重点放在识别非常轻度AD中存在的鞘脂组网络通路改变的生化机制上，并通过使用开发的平台测定非常轻度AD患者脑组织和脑脊液的脂质谱改变，发现潜在的脂质生物标志物，用于AD的早期诊断。总的来说，在这个应用程序中，我们将进一步开发散弹枪脂质组学和集成的生物信息学程序，并将这个开发的平台应用于AD研究。这些研究结果将揭示阿尔茨海默病中硫脂质损失的生化机制，为阿尔茨海默病的早期诊断确定新的脂质生物标志物，并为阿尔茨海默病的发病机制提供新的见解。

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.