Lista Simone, Zetterberg Henrik, O'Bryant Sid E, Blennow Kaj, Hampel Harald
AXA Research Fund & UPMC Chair, Paris, France.
Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du cerveau et dela moelle (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), HôpitalPitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France.
Methods Mol Biol. 2017;1598:101-115. doi: 10.1007/978-1-4939-6952-4_5.
Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.
在过去几十年里，人们对阿尔茨海默病（AD）生物学的理解取得了重大进展。然而，AD及其他与年龄相关的神经退行性疾病的早期检测和诊断仍然是一个具有挑战性的科学前沿领域。因此，有必要全面发现（涉及所有个体的、趋同或不同的生化疾病机制）、开发、验证和鉴定具有诊断和预后功能的标准化生物标志物，这些生物标志物在特异性、敏感性以及阳性和阴性预测值方面具有精确的性能特征。
探索性高通量技术领域的方法创新，如测序、微阵列以及基于质谱的蛋白质/肽分析，已从多种生物系统（如生物体液、细胞、组织和器官）生成了大量的全球分子数据集。这种方法上的进展已将注意力转向执行独立于假设的全面探索性分析（与经典的假设驱动候选方法相对），目的是全面了解生理和疾病中的生物系统。系统生物学范式将实验生物学与精确且严谨的计算建模相结合，以描述和预测生物系统的动态特征。蛋白质组学领域中动态发展的技术平台（包括质谱）的使用，加快了生物标志物发现和验证的进程，从而显著改进AD的诊断。目前，作为系统生物学范式一部分的蛋白质组学被指定为有效探索性发现预期在AD的早期检测、诊断、预后和治疗开发中发挥有效作用的前瞻性生物标志物候选物所需的主导成熟科学之一。
