Lumipulse 血浆 Aβ42/40 和 pTau181 免疫测定在检测淀粉样病理学方面的性能。

IF 4 Q1 CLINICAL NEUROLOGY Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2024-01-31 eCollection Date: 2024-01-01 DOI:10.1002/dad2.12545
Daniel J Figdore, Heather J Wiste, Joshua A Bornhorst, Randall J Bateman, Yan Li, Jonathan Graff-Radford, David S Knopman, Prashanthi Vemuri, Val J Lowe, Clifford R Jack Jr, Ronald C Petersen, Alicia Algeciras-Schimnich
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引用次数: 0

摘要

简介本研究评估了Lumipulse血浆β-淀粉样蛋白(Aβ)42/40和pTau181与其他检测方法相比在检测淀粉样蛋白正电子发射断层扫描(PET)异常方面的性能:对认知功能未受损者(179人)和MCI/AD痴呆症患者(36人)的血浆样本进行回顾性评估。使用 Lumipulse 和 Simoa 免疫测定法测定血浆 Aβ42/40 和 pTau181。此外,还对血浆 Aβ42/40 的免疫沉淀质谱 (IP-MS) 分析进行了评估。结果:结果:Lumipulse 和 IP-MS Aβ42/40 检测异常淀粉样蛋白-PET 的诊断准确率最高(曲线下面积 [AUC] 分别为 0.81 和 0.84)。Lumipulse 和 Simoa pTau181 检测方法的性能较低(AUC 分别为 0.74 和 0.72)。Simoa Aβ42/40测定的诊断准确性最低(AUC为0.57)。与单独使用Aβ42/40相比,Lumipulse结合使用Aβ42/40(AUC 0.83)或Simoa结合使用pTau181(AUC 0.71)并没有显著提高性能:讨论:在检测异常淀粉样蛋白-PET方面,Lumipulse Aβ42/40检测法与IP-MS Aβ42/40检测法的性能相似;两种检测法的性能均优于两种p-tau181免疫检测法。Simoa Aβ42/Aβ40测定预测淀粉样蛋白-PET异常状态的准确性最低:Lumipulse血浆Aβ42/Aβ40检测异常淀粉样蛋白-PET的AUC为0.81,与之前报道的IP-MS相当,高于Simoa。
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Performance of the Lumipulse plasma Aβ42/40 and pTau181 immunoassays in the detection of amyloid pathology.

Introduction: This study evaluated the performance of the Lumipulse plasma beta-amyloid (Aβ) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid-positron emission tomography (PET).

Methods: Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP-MS) assay for plasma Aβ42/40 was also evaluated. Amyloid-PET status was the outcome measure.

Results: Lumipulse and IP-MS Aβ42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid-PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71).

Discussion: The Lumipulse Aβ42/40 assay showed similar performance to the IP-MS Aβ42/40 assay for detection of an abnormal amyloid-PET; and both assays performed better than the two p-tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid-PET status.

Highlights: Lumipulse plasma Aβ42/Aβ40 AUC for abnormal amyloid-PET detection was 0.81.This performance was comparable to previously reported IP-MS and higher than Simoa.Performance of Alzheimer's disease blood biomarkers varies between assays.

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来源期刊
CiteScore
7.80
自引率
7.50%
发文量
101
审稿时长
8 weeks
期刊介绍: Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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