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NIA-AA 研究框架的应用:在 AIBL 研究中使用脑脊液生物标志物来定义阿尔茨海默病的生物学定义。

Application of the NIA-AA Research Framework: Towards a Biological Definition of Alzheimer's Disease Using Cerebrospinal Fluid Biomarkers in the AIBL Study.

机构信息

Samantha C. Burnham, CSIRO, 343 Royal Parade, Parkville, VIC 3052, Australia, Email:

出版信息

J Prev Alzheimers Dis. 2019;6(4):248-255. doi: 10.14283/jpad.2019.25.

DOI:10.14283/jpad.2019.25
PMID:31686097
Abstract

BACKGROUND

The National Institute on Aging and Alzheimer's Association (NIA-AA) have proposed a new Research Framework: Towards a biological definition of Alzheimer's disease, which uses a three-biomarker construct: Aß-amyloid, tau and neurodegeneration AT(N), to generate a biomarker based definition of Alzheimer's disease.

OBJECTIVES

To stratify AIBL participants using the new NIA-AA Research Framework using cerebrospinal fluid (CSF) biomarkers. To evaluate the clinical and cognitive profiles of the different groups resultant from the AT(N) stratification. To compare the findings to those that result from stratification using two-biomarker construct criteria (AT and/or A(N)).

DESIGN

Individuals were classified as being positive or negative for each of the A, T, and (N) categories and then assigned to the appropriate AT(N) combinatorial group: A-T-(N)-; A+T-(N)-; A+T+(N)-; A+T-(N)+; A+T+(N)+; A-T+(N)-; A-T-(N)+; A-T+(N)+. In line with the NIA-AA research framework, these eight AT(N) groups were then collapsed into four main groups of interest (normal AD biomarkers, AD pathologic change, AD and non-AD pathologic change) and the respective clinical and cognitive trajectories over 4.5 years for each group were assessed. In two sensitivity analyses the methods were replicated after assigning individuals to four groups based on being positive or negative for AT biomarkers as well as A(N) biomarkers.

SETTING

Two study centers in Melbourne (Victoria) and Perth (Western Australia), Australia recruited MCI individuals and individuals with AD from primary care physicians or tertiary memory disorder clinics. Cognitively healthy, elderly NCs were recruited through advertisement or via spouses of participants in the study.

PARTICIPANTS

One-hundred and forty NC, 33 MCI participants, and 27 participants with AD from the AIBL study who had undergone CSF evaluation using Elecsys® assays. INTERVENTION (if any): Not applicable.

MEASUREMENTS

Three CSF biomarkers, namely amyloid β1-42, phosphorylated tau181, and total tau, were measured to provide the AT(N) classifications. Clinical and cognitive trajectories were evaluated using the AIBL Preclinical Alzheimer Cognitive Composite (AIBL-PACC), a verbal episodic memory composite, an executive function composite, California Verbal Learning Test - Second Edition; Long-Delay Free Recall, Mini-Mental State Examination, and Clinical Dementia Rating Sum of Boxes scores.

RESULTS

Thirty-eight percent of the elderly NCs had no evidence of abnormal AD biomarkers, whereas 33% had biomarker levels consistent with AD or AD pathologic change, and 29% had evidence of non-AD biomarker change. Among NC participants, those with biomarker evidence of AD pathology tended to perform worse on cognitive outcome assessments than other biomarker groups. Approximately three in four participants with MCI or AD had biomarker levels consistent with the research framework's definition of AD or AD pathologic change. For MCI participants, a decrease in AIBL-PACC scores was observed with increasing abnormal biomarkers; and increased abnormal biomarkers were also associated with increased rates of decline across some cognitive measures.

CONCLUSIONS

Increasing biomarker abnormality appears to be associated with worse cognitive trajectories. The implementation of biomarker classifications could help better characterize prognosis in clinical practice and identify those at-risk individuals more likely to clinically progress, for their inclusion in future therapeutic trials.

摘要

背景

美国国家老龄化研究所和阿尔茨海默病协会(NIA-AA)提出了一个新的研究框架:迈向阿尔茨海默病的生物学定义,该框架使用三生物标志物构建:Aβ-淀粉样蛋白、tau 和神经退行性变 AT(N),以生成基于生物标志物的阿尔茨海默病定义。

目的

使用新的 NIA-AA 研究框架使用脑脊液(CSF)生物标志物对 AIBL 参与者进行分层。评估不同 AT(N)分层组的临床和认知特征。将这些发现与使用双生物标志物构建标准(AT 和/或 A(N))进行分层的结果进行比较。

设计

个体被归类为 A、T 和(N)类别中的每一个为阳性或阴性,然后被分配到适当的 AT(N)组合组:A-T-(N)-;A+T-(N)-;A+T+(N)-;A+T-(N)+;A+T+(N)+;A-T+(N)-;A-T-(N)+;A-T+(N)+。根据 NIA-AA 研究框架,将这 8 个 AT(N)组进一步分为四个主要感兴趣的组(正常 AD 生物标志物、AD 病理变化、AD 和非 AD 病理变化),并评估每个组在 4.5 年内的相应临床和认知轨迹。在两项敏感性分析中,在根据 AT 生物标志物和 A(N)生物标志物的阳性或阴性将个体分配到四个组后,复制了该方法。

地点

澳大利亚墨尔本(维多利亚)和珀斯(西澳大利亚)的两个研究中心,从初级保健医生或三级记忆障碍诊所招募 MCI 个体和 AD 个体。认知健康的老年人 NC 通过广告或通过研究参与者的配偶招募。

参与者

来自 AIBL 研究的 140 名 NC、33 名 MCI 参与者和 27 名 AD 参与者,他们使用 Elecsys® 测定法进行了 CSF 评估。

干预措施(如果有):无。

测量

使用三种 CSF 生物标志物,即淀粉样蛋白β 1-42、磷酸化 tau181 和总 tau,进行分类,以提供 AT(N)分类。使用 AIBL 临床前阿尔茨海默病认知综合评分(AIBL-PACC)、口头情景记忆综合评分、执行功能综合评分、加利福尼亚语言学习测试-第二版;长时间延迟自由回忆、简易精神状态检查和临床痴呆评定量表总分评估临床和认知轨迹。

结果

38%的老年 NC 没有异常 AD 生物标志物的证据,而 33%的 NC 有 AD 或 AD 病理变化的生物标志物水平,29%的 NC 有非 AD 生物标志物变化的证据。在 NC 参与者中,那些有 AD 病理生物标志物证据的人在认知结果评估中表现不如其他生物标志物组。大约四分之三的 MCI 或 AD 参与者的生物标志物水平与研究框架对 AD 或 AD 病理变化的定义一致。对于 MCI 参与者,随着异常生物标志物的增加,AIBL-PACC 评分下降;异常生物标志物的增加也与一些认知测量的下降率增加有关。

结论

生物标志物异常的增加似乎与认知轨迹的恶化有关。生物标志物分类的实施有助于更好地描述临床实践中的预后,并确定那些更有可能临床进展的风险个体,以便将其纳入未来的治疗试验。

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