Characterizing the AD Metabolome in Brain Tissue Samples of Individuals from Diverse Populations

我们之前的工作和AD研究总体上的一个关键限制是主要依赖来自 高加索血统的参与者。而高加索人群中AD的代谢组学研究为我们提供了 拥有大量与药物发现和开发相关的发现和线索，目前还没有大规模的- 不同人群的脑组织规模代谢组学研究。这大大阻碍了我们的能力 评估这些人群的研究结果的概括性，或确定 共享的以及可能特定于人群的那些。然而，这是最重要的，作为贡献 阿尔茨海默病的遗传和环境风险因素的类型以及与阿尔茨海默病的共病类型可能在不同的 人口。例如，心血管风险的增加被认为在 与白人相比，非裔美国人(AA)AD的患病率。考虑到强大的新陈代谢基础 心血管和心脏代谢健康，可能有机会发现新的疾病途径和 基因x环境(GxE)在这个群体中的相互作用：社会经济环境可能在 与白人相比，人群多样化，从而提高了发现新代谢变化的可能性 受不同环境的影响。为确保早期诊断的成功，临床试验的患者分层 (以及最终的治疗)，患者-靶点匹配，基于生物标记物概况的临床预测 精准医学范式，我们需要对代谢、临床和生物标记物有完整的知识 不同人群的概况，以及高加索人。本附录旨在克服这些数据--以及 使用AA和拉丁美洲的大脑样本生成大规模代谢组学数据的知识差距 (La)个人，利用多个群体的力量，将不同种族的参与者收集为 AMP-AD计划。这有望将AD代谢障碍的生化知识扩展到 包括那些与这些少数群体相关的人。通过与AMP-AD合作伙伴合作，我们将系统地 解决种族差异对整个AD连续体的大脑健康代谢方面的贡献 在这些AD风险升高的人群中发现与AD发病相关的途径和分子。穿过 将这些数据与我们的高加索人AD代谢组学特征大型数据库进行比较和对比，我们 旨在提供关于常见和特殊疾病的机制和亚类的生化见解 到特定的人群。最后，通过将研究结果整合到我们的AD地图集中，我们进一步致力于注释AMP- 广告候选人的目标是与人口相关性相关。通过本附录生成的所有数据都将 通过AD知识门户中的存储与研究社区实时共享。成功 这个项目的完成将产生一份与以下方面相关的途径和潜在治疗靶点的清单 群体，与那些与单一群体更相关的群体形成对比。

A key limitation of our previous work and AD research in general is the predominant reliance of samples from participants of Caucasian ancestry. While metabolomics studies of AD in Caucasian cohorts have provided us with a large body of findings and leads relevant to drug discovery and development, there are currently no large- scale metabolomics studies of brain tissue available in diverse populations. This significantly hampers our ability to assess generalizability of findings across these populations or to identify pathways and molecules that are shared as well as those that may be population-specific. This is, however, of greatest importance, as contribution and types of genetic and environmental risk factors for and co-morbidities with AD may be distinct in diverse populations. For example, increased cardiovascular risk is thought to play an important role in the increased prevalence of AD in African Americans (AA) compared to whites. Given the strong metabolic underpinnings of cardiovascular and cardiometabolic health, there may be opportunities to uncover novel disease pathways and gene x environment (GxE) interactions in this population: the socioeconomic milieu is likely to be different in diverse populations compared to whites, thereby raising the possibility to discover novel metabolic changes influenced by distinct environments. To ensure success in early diagnosis, patient-stratification for clinical trials (and ultimately therapies), patient-target matching, clinical predictions based on biomarker profiling in a precision-medicine paradigm, we need to have complete knowledge on the metabolic, clinical and biomarker profiles of diverse populations, as well as Caucasians. This supplement aims to overcome this data- and knowledge-gap by generating large-scale metabolomics data using brain samples from AA and Latin American (LA) individuals, harnessing the power of multiple cohorts with ethnically diverse participants collected as part of the AMP-AD initiative. This is expected to expand the biochemical knowledge on metabolic failures in AD to include those relevant to these minority populations. By working with our AMP-AD partners, we will systematically address contributions of racial differences on metabolic aspects of brain health across the AD continuum to discover pathways and molecules linked to AD pathogenesis in these populations with elevated AD risk. Through comparing and contrasting this data to our large database of metabolomic signatures of AD in Caucasians, we aim to provide biochemical insights about mechanisms and sub-classes of disease that are common and specific to certain populations. Finally, via integrating study outcomes into our AD Atlas, we further aim to annotate AMP- AD candidate targets with respect to population relevance. All data generated through this supplement will be shared in real time with the research community through deposition in the AD Knowledge Portal. Successful completion of this project will generate a list of pathways and potential therapeutic targets that are relevant across populations, contrasted by those that are more relevant to single populations.