Kivisäkk Pia, Magdamo Colin, Trombetta Bianca A, Noori Ayush, Kuo Yi Kai E, Chibnik Lori B, Carlyle Becky C, Serrano-Pozo Alberto, Scherzer Clemens R, Hyman Bradley T, Das Sudeshna, Arnold Steven E
Alzheimer's Clinical & Translational Research Unit and Massachusetts Alzheimer's Disease Research Center, Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA.
Center for Advanced Parkinson Research and Precision Neurology Program, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA.
Brain Commun. 2022 Jun 14;4(4):fcac155. doi: 10.1093/braincomms/fcac155. eCollection 2022.
Plasma-based biomarkers present a promising approach in the research and clinical practice of Alzheimer's disease as they are inexpensive, accessible and minimally invasive. In particular, prognostic biomarkers of cognitive decline may aid in planning and management of clinical care. Although recent studies have demonstrated the prognostic utility of plasma biomarkers of Alzheimer pathology or neurodegeneration, such as pTau-181 and NF-L, whether other plasma biomarkers can further improve prediction of cognitive decline is undetermined. We conducted an observational cohort study to determine the prognostic utility of plasma biomarkers in predicting progression to dementia for individuals presenting with mild cognitive impairment due to probable Alzheimer's disease. We used the Olink™ Proximity Extension Assay technology to measure the level of 460 circulating proteins in banked plasma samples of all participants. We used a discovery data set comprised 60 individuals with mild cognitive impairment (30 progressors and 30 stable) and a validation data set consisting of 21 stable and 21 progressors. We developed a machine learning model to distinguish progressors from stable and used 44 proteins with significantly different plasma levels in progressors versus stable along with age, sex, education and baseline cognition as candidate features. A model with age, education, APOE genotype, baseline cognition, plasma pTau-181 and 12 plasma Olink protein biomarker levels was able to distinguish progressors from stable with 86.7% accuracy (mean area under the curve = 0.88). In the validation data set, the model accuracy was 78.6%. The Olink proteins selected by the model included those associated with vascular injury and neuroinflammation (e.g. IL-8, IL-17A, TIMP-4, MMP7). In addition, to compare these prognostic biomarkers to those that are altered in Alzheimer's disease or other types of dementia relative to controls, we analyzed samples from 20 individuals with Alzheimer, 30 with non-Alzheimer dementias and 34 with normal cognition. The proteins NF-L and PTP-1B were significantly higher in both Alzheimer and non-Alzheimer dementias compared with cognitively normal individuals. Interestingly, the prognostic markers of decline at the mild cognitive impairment stage did not overlap with those that differed between dementia and control cases. In summary, our findings suggest that plasma biomarkers of inflammation and vascular injury are associated with cognitive decline. Developing a plasma biomarker profile could aid in prognostic deliberations and identify individuals at higher risk of dementia in clinical practice.
基于血浆的生物标志物在阿尔茨海默病的研究和临床实践中是一种很有前景的方法,因为它们价格低廉、易于获取且微创。特别是,认知衰退的预后生物标志物可能有助于临床护理的规划和管理。尽管最近的研究已经证明了阿尔茨海默病病理或神经退行性变的血浆生物标志物(如pTau-181和NF-L)的预后效用,但其他血浆生物标志物是否能进一步改善对认知衰退的预测仍未确定。我们进行了一项观察性队列研究,以确定血浆生物标志物在预测因可能的阿尔茨海默病导致轻度认知障碍的个体进展为痴呆症方面的预后效用。我们使用Olink™ 邻近延伸分析技术来测量所有参与者储存血浆样本中460种循环蛋白的水平。我们使用了一个发现数据集,其中包括60名轻度认知障碍个体(30名进展者和30名稳定者),以及一个验证数据集,由21名稳定者和21名进展者组成。我们开发了一个机器学习模型来区分进展者和稳定者,并使用进展者与稳定者血浆水平有显著差异的44种蛋白质以及年龄、性别、教育程度和基线认知作为候选特征。一个包含年龄、教育程度、APOE基因型、基线认知、血浆pTau-181和12种血浆Olink蛋白生物标志物水平的模型能够以86.7%的准确率区分进展者和稳定者(曲线下平均面积 = 0.88)。在验证数据集中,模型准确率为78.6%。该模型选择的Olink蛋白包括那些与血管损伤和神经炎症相关的蛋白(如IL-8、IL-17A、TIMP-4、MMP7)。此外,为了将这些预后生物标志物与相对于对照组在阿尔茨海默病或其他类型痴呆症中发生改变的生物标志物进行比较,我们分析了20名阿尔茨海默病患者、30名非阿尔茨海默病痴呆患者和34名认知正常个体的样本。与认知正常个体相比,NF-L和PTP-1B蛋白在阿尔茨海默病和非阿尔茨海默病痴呆患者中均显著升高。有趣的是,轻度认知障碍阶段衰退的预后标志物与痴呆症和对照病例之间不同的标志物没有重叠。总之,我们的研究结果表明,炎症和血管损伤的血浆生物标志物与认知衰退有关。开发血浆生物标志物谱可能有助于预后评估,并在临床实践中识别出患痴呆症风险较高的个体。