Department of Psychiatry, University of Rostock, Rostock, Germany.
J Alzheimers Dis. 2013;33 Suppl 1:S329-47. doi: 10.3233/JAD-2012-129030.
The diagnosis of Alzheimer's disease (AD) is presently going through a paradigm shift from disease categories to dimensions and toward the implementation of biomarkers to support identification of predementia and even preclinical asymptomatic stages of the disease. We outline the methodological basis of presently available biomarkers and technological methodologies in AD, including exploratory and hypothesis-based plasma and blood candidates, cerebrospinal fluid markers of amyloid load and axonal destruction, and imaging markers of amyloid deposition, synaptic dysfunction, cortical functional and structural disconnection, and regional atrophy. We integrate biomarker findings into a comprehensive model of AD pathogenesis from healthy aging to cognitive decline, the resilience to cerebral amyloid load (RECAL) matrix. The RECAL framework integrates factors of risk and resilience to cerebral amyloid load for individual risk prediction. We show the clinical consequences when the RECAL matrix is operationalized into a diagnostic algorithm both for individual counseling of subjects and for the identification of at risk samples for primary and secondary preventive trials. We discuss the implication of biomarkers for the identification of prodromal AD for the primary care system that seems presently not even prepared to cope with the increasing number of subjects afflicted with late stage AD dementia, let alone future cohorts of subjects searching counseling or treatment of predementia and asymptomatic stages of AD. The paradigm shift in AD diagnosis and its operationalization into a diagnostic framework will have major implications for our understanding of disease pathogenesis. Now, for the first time, we have access to in vivo markers of key events in AD pathogenesis integrated into a heuristic framework that makes strong predictions on pattern of multimodal biomarkers in different stages of AD. Critical testing of these predictions will help us to modify or even falsify the currently hold assumptions on the pathogenesis of AD based on in vivo evidence in humans.
目前，阿尔茨海默病（AD）的诊断正经历从疾病类别向维度的转变，并朝着实施生物标志物的方向发展，以支持对痴呆前和甚至疾病无症状临床前阶段的识别。我们概述了目前 AD 中可用的生物标志物和技术方法的方法学基础，包括探索性和基于假设的血浆和血液候选物、淀粉样蛋白负荷和轴突破坏的脑脊液标志物，以及淀粉样蛋白沉积、突触功能障碍、皮质功能和结构连接中断以及区域萎缩的成像标志物。我们将生物标志物的发现整合到从健康衰老到认知能力下降的 AD 发病机制的综合模型中，即大脑淀粉样蛋白负荷（RECAL）矩阵中。RECAL 框架整合了个体大脑淀粉样蛋白负荷风险和弹性的因素，用于个体风险预测。我们展示了当 RECAL 矩阵被操作化为诊断算法时的临床后果，无论是用于个体咨询，还是用于识别原发性和二级预防试验的高危样本。我们讨论了生物标志物对前驱 AD 识别的影响，对于目前甚至没有准备好应对患有晚期 AD 痴呆的患者人数不断增加的初级保健系统，更不用说未来寻求痴呆前和 AD 无症状阶段咨询或治疗的患者群体而言，这种影响将是巨大的。AD 诊断的范式转变及其操作化为诊断框架将对我们对疾病发病机制的理解产生重大影响。现在，我们首次获得了 AD 发病机制关键事件的体内标志物，这些标志物被整合到一个启发式框架中，对 AD 不同阶段的多种模式生物标志物模式做出了强有力的预测。对这些预测的严格测试将帮助我们根据人类体内证据修改甚至否定目前关于 AD 发病机制的假设。
