Metabolic Signatures for Alzheimer's Disease

描述（由申请人提供）：阿尔茨海默病（AD）是一种神经退行性疾病，是老年痴呆症的最常见原因。随着人口老龄化的快速增长，迫切需要开发更有效的治疗方法来预防和治疗AD。虽然AD传统上通过临床标准（例如认知测试、分期仪器）进行诊断和监测，但需要经验证的生物标志物，其可以补充临床测量并且可以提供对疾病机制的进一步了解。已经进行了大量研究来验证生物标志物，例如脑萎缩测量、海马体积、葡萄糖代谢摄取和β-淀粉样蛋白或tau蛋白水平。然而，到目前为止，还没有一种生物标志物被完全接受为足够敏感和特异的诊断或跟踪对治疗的反应。代谢组学是一个强大的新技术平台，提供了一个快照的生化途径在特定的时间点。它是对代谢组的综合研究，代谢组是存在于细胞、组织和体液中的生物化学物质（或小分子）的库。它已被指定为NIH路线图倡议下开发的一个重要领域。我们已经在代谢组学中建立了复杂的生物化学和信息学平台，使我们能够定义几种CNS疾病的初始特征，包括AD的初始脑脊液（CSF）衍生特征。我们计划使用这些互补代谢组学技术来捕获与病理和临床状态相关的AD各个阶段的全面生化变化和生化特征。具体而言，我们将在病理确诊的AD患者样本和匹配的对照样本中进行CSF代谢组学研究，以询问特定途径并确认我们的初步研究产生的假设。此外，我们将前瞻性地从活体AD患者和对照组中收集血浆样本和CSF样本，以测试与血浆代谢组学的效用有关的次要假设，及其与CSF代谢组学的相关性以及同一组个体随时间的认知变化。最后，我们计划研究AD患者和对照组的空腹血浆脂组学模式，与其他代谢组学参数的关系。这些研究可能有助于突出疾病中新的受损途径，并确定药物开发的潜在靶点。

DESCRIPTION (provided by applicant): Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia in the elderly. With the rapid growth of the aging population, there is an urgent need to develop more effective therapies to prevent and treat AD. Although AD is traditionally diagnosed and monitored by clinical criteria (e.g. cognitive tests, staging instruments), there is a need for validated biomarkers that can compliment clinical measures and that can provide further insights into disease mechanisms. Large studies have been undertaken to validate biomarkers such as brain atrophy measures, hippocampal volumes, glucose metabolic uptake and beta-amyloid ortau protein levels. However, to date, no single biomarker has yet been fully accepted as being sufficiently sensitive and specific for diagnosis or tracking response to therapy. Metabolomics is a powerful new technology platform that provides a snap shot of biochemical pathways at a particular point in time. It is the comprehensive study of the metabolome, the repertoire of bio-chemicals (or small molecules) present in cells, tissue and body fluid. It has been earmarked as an important area to develop under the NIH roadmap initiative. We have already established sophisticated biochemical and informatics platforms in metabolomics that have enabled us to define initial signatures for several CNS disorders including an initial cerebrospinal fluid (CSF) derived signature for AD. We plan to use these complementary metabolomics technologies to capture comprehensive biochemical changes and biochemical signatures at various stages of AD in relation to pathologic and clinical status. Specifically, we will perform CSF metabolomics in a sample of AD patients with pathologically confirmed diagnoses and matched control samples to interrogate specific pathways and confirm hypotheses generated by our pilot studies. In addition, we will prospectively collect plasma samples and CSF samples from living AD patients and controls to test secondary hypotheses pertaining to utility of plasma metabolomics, and its correlation with CSF metabolomics as well as cognitive changes over time in the same set of individuals. Finally, we plan to examine fasting plasma lipomic patterns in AD patients and controls, in relation to other metabolomic parameters. These studies may serve to highlight new impaired pathways in the disease and identify potential targets for drug developments.