MRI 导出的皮质变薄和血浆 P-Tau217 阿尔茨海默痴呆症特征,用于预测社区老年人中的阿尔茨海默痴呆症。

IF 2.3 Q3 CLINICAL NEUROLOGY
Neurology. Clinical practice Pub Date : 2024-06-01 Epub Date: 2024-04-15 DOI:10.1212/CPJ.0000000000200291
Lei Yu, Tianhao Wang, Oskar Hansson, Shorena Janelidze, Melissa Lamar, Konstantinos Arfanakis, David A Bennett, Julie A Schneider, Patricia A Boyle
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引用次数: 0

摘要

背景和目的:脑结构磁共振成像(MRI)和基于血液的磷酸化 tau(p-tau)测量是迄今为止侵入性最小、成本最低的阿尔茨海默病(AD)生物标志物之一。然而,人们对这些生物标志物在预测未来阿尔茨海默氏症痴呆诊断方面的优越性还知之甚少。本研究调查了2种特定的老年痴呆症生物标志物,即老年痴呆症皮质厚度特征(AD-CT)和血浆p-tau217,用于预测老年痴呆症:方法:数据来自宗教团体研究(Religious Orders Study)或拉什记忆与衰老项目(Rush Memory and Aging Project)的社区老年参与者。AD-CT是使用磁化预处理快速采集梯度回波序列从3T核磁共振扫描中获得的,并对先前确定的与AD有关联的皮质区域进行了厚度平均。血浆中的p-tau217使用礼来研究实验室在MSD平台上开发的免疫测定法进行量化。核磁共振成像扫描和血液标本都是在相同的就诊时间采集的,阿尔茨海默痴呆症的后续诊断是通过每年一次的详细临床评估确定的。Cox比例危险模型检验了这两种生物标记物与阿尔茨海默痴呆症的关联,并使用c统计量评估了预测的准确性:共纳入了 198 名平均年龄为 84 岁的老年人。在平均 4 年的随访期间,有 60 人(30%)患上了阿尔茨海默痴呆症。AD-CT(危险比:1.71,95% CI 1.26-2.31)和血浆 p-tau217(危险比:2.57,95% CI 1.83-3.61)分别与阿尔茨海默痴呆症的发生有关。在不同的时间范围内,血浆 p-tau217 预测准确性的 c 统计量(0.74-0.81)始终高于 AD-CT(0.70-0.75)。此外,将这两种生物标志物纳入同一模型后,AD-CT对c统计量的改善不大:讨论:血浆p-tau217在预测未来阿尔茨海默氏症痴呆诊断方面优于基于成像的AD皮层厚度特征。此外,除了血浆p-tau217之外,AD皮层厚度特征对预测准确性的影响很小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults.

Background and objectives: Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia.

Methods: Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics.

Results: A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT.

Discussion: Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

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来源期刊
Neurology. Clinical practice
Neurology. Clinical practice CLINICAL NEUROLOGY-
CiteScore
4.00
自引率
0.00%
发文量
77
期刊介绍: Neurology® Genetics is an online open access journal publishing peer-reviewed reports in the field of neurogenetics. The journal publishes original articles in all areas of neurogenetics including rare and common genetic variations, genotype-phenotype correlations, outlier phenotypes as a result of mutations in known disease genes, and genetic variations with a putative link to diseases. Articles include studies reporting on genetic disease risk, pharmacogenomics, and results of gene-based clinical trials (viral, ASO, etc.). Genetically engineered model systems are not a primary focus of Neurology® Genetics, but studies using model systems for treatment trials, including well-powered studies reporting negative results, are welcome.
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