Serum proteome analysis of Alzheimer´s disease in a population-based longitudinal cohort study - the AGES Reykjavik study

蛋白质是所有生命过程中的关键角色，无论是健康还是疾病，以及绝大多数药物 目标是蛋白质。复杂组织中蛋白质组的高通量检测与定量 例如血液，历史上一直受到可用方法的限制。最新进展 允许在大量人群中测量蛋白质组学。一个基于适体的蛋白质组学平台 最近开发的方法可以检测5457名表型个体血清中的4137种蛋白质 和遗传特征良好的基于人口年龄的雷克雅未克研究，其中3289人参与 在一项为期五年的跟踪研究中。 我们已经证明了 血清蛋白质聚集成共同调节网络 与常见疾病相一致，并作为基因变异驱动之间的中介 疾病和疾病在整个人口中的出现。在拟议的研究中，w E将 利用遗传学、蛋白质组学和基于网络的数据跨越多个大脑相关结果，使用 横断面和纵向研究设计，以描述全球血清的关系 蛋白质相互作用、遗传和迟发性阿尔茨海默病(LOAD)。随着年龄的增长 在人群中，负荷的流行率正在上升，使有效的负荷治疗成为 全球医疗体系中增长最快的未得到满足的医疗需求。我们提出了三个不同的目标。在……里面 目的1，我们将研究4137个血清蛋白以及淀粉样蛋白-β多肽和 蛋白质网络，在基线和五年后，到流行和偶发负荷。在目标2中，我们将 确定4137个血清蛋白与脑MRI结构标志物的相关性 神经退行性变与负荷和脑萎缩进展率的进一步联系。在《目标3》中，我们将 通过双向孟德尔随机化分析解决蛋白质和负载之间的因果关系， 使用调节血清蛋白质的变种作为遗传工具。据我们所知，这是最大的 到目前为止，蛋白质组学数据集包括测量的蛋白质数量和筛选的样本数量。这个 提出的项目之所以意义重大，原因有很多，例如：一、大规模蛋白质组学 与基因组和深层表现组数据相结合的数据促进了系统方法 装填。二、纵向数据在评估蛋白质生物标志物个体内变化中的应用 随着时间的推移，长期负荷相关结果的水平为稳健的生物标志物提供了独特的机会 大量的发现。三、全球血清蛋白的全基因组分析将提供科学的 具有新的遗传仪器来源的社区，用于检验因果关系并揭示因果关系 加载风险的潜在机制(S)。总而言之，拟议项目的结果将提供一个 负荷产生新生物标志物病因学的整体模型，并指出可操作的靶点 治疗这种疾病。

Proteins are the key players in all life processes, in health and disease, and the vast majority of drug targets are proteins. High throughput detection and quantification of the proteome in complex tissues such as blood has historically been hampered by the limitations of available methods. Recent progress allows proteomics to be measured in large populations. An aptamer-based proteomics platform was recently developed to measure 4137 proteins in the serum of 5457 individuals from the phenotypically and genetically well-characterized population-based AGES Reykjavik study, of which 3289 participated in a five-year follow-up study. We have shown that serum proteins cluster into co-regulatory networks that were aligned with common diseases and as intermediaries between genetic variation driving disease and with the appearance of disease across the population. In the proposed study, w e will leverage genetics, proteomics and network-based data across multiple brain related outcomes, using both cross-sectional and longitudinal study design, to describe the relationships of global serum proteins to each other, to genetics and to late-onset Alzheimer's disease (LOAD). With increasing aging of the population the prevalence of LOAD is on the rise, making effective LOAD treatment one of the fastest growing unmet medical needs in global healthcare systems. We propose three different aims. In Aim 1, we will examine the association of 4137 serum proteins as well as amyloid-β peptides and protein networks, at baseline and five years later, to prevalent and incident LOAD. In Aim 2, we will determine association of the 4137 serum proteins to structural brain MRI biomarkers of neurodegeneration for further links to LOAD and brain atrophy progression rates. In Aim 3, we will address causality between proteins and LOAD through bi-directional Mendelian randomization analysis, using variants that regulate serum proteins as genetic instruments. To our knowledge this is the largest proteomics data set to date as regards number of proteins measured and samples screened. The proposed project is significant for many reasons including for instance: i. the large-scale proteomics data integrated with variation in the genome and deep phenome data facilitates systems approaches to LOAD. ii. The application of longitudinal data to assess intra-individual changes in protein biomarker levels over time on long-term LOAD related outcomes offers unique opportunities for robust biomarker discoveries in LOAD. iii. Whole genome analysis of global serum proteins will provide the scientific community with a novel source of genetic instruments for tests of causality and to reveal the causal mechanism(s) underlying the risk of LOAD. In summary, the results of the proposed project will offer a holistic model of the etiology of LOAD yielding novel biomarkers and point to actionable targets for treating the disease.