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，在健康和疾病中，以及绝大多数药物 目标是蛋白质。复杂组织蛋白质组的高通量检测与定量 例如血液，在历史上一直受到可用方法的限制的阻碍。最新进展 允许在大群体中测量蛋白质组学。基于适体的蛋白质组学平台， 最近开发了一种用于测量5457名个体血清中4137种蛋白质的表型 和遗传特征良好的人口为基础的AGES雷克雅未克研究，其中3289人参加 一项为期五年的跟踪研究。 我们已经证明 血清蛋白聚集成协同调节网络 与常见疾病相一致，并作为遗传变异驱动 疾病和疾病在人群中的出现。在研究中，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， 横断面和纵向研究设计，以描述全球血清 蛋白质相互作用，遗传学和迟发性阿尔茨海默病（LOAD）。随着老龄化的加剧 在人口中，LOAD的患病率正在上升，使有效的LOAD治疗成为 全球医疗保健系统中未满足的医疗需求增长最快。我们提出了三个不同的目标。在 目的1，我们将检测4137种血清蛋白以及淀粉样β肽与 蛋白质网络，在基线和五年后，流行和事件负载。在目标2中，我们 确定4137种血清蛋白质与脑MRI结构生物标志物的相关性， 神经变性与LOAD和脑萎缩进展率的进一步联系。在目标3中，我们 通过双向孟德尔随机化分析解决蛋白质和LOAD之间的因果关系， 使用调节血清蛋白的变异体作为遗传工具。据我们所知，这是最大的 蛋白质组学数据集迄今为止的蛋白质数量测量和筛选的样品。的 拟议的项目是重要的，原因有很多，包括例如：i。大规模蛋白质组学 与基因组和深层表型组数据中的变异相结合的数据促进了系统方法， 即可.二.应用纵向数据评估蛋白质生物标志物的个体内变化 长期LOAD相关结局随时间推移的水平为稳健的生物标志物提供了独特的机会 在负载中发现。三.全球血清蛋白的全基因组分析将提供科学的 社区与一个新的来源的遗传工具的因果关系的测试，并揭示因果关系 导致LOAD风险的潜在机制。总之，拟议项目的结果将提供一个 LOAD病因学的整体模型产生了新的生物标志物，并指出了可操作的靶点， 治疗疾病。

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.