Blood biomarkers for Alzheimer’s disease with the Lumipulse automated platform: Age-effect and clinical value interpretation

IF 3.2 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2024-10-22 DOI:10.1016/j.cca.2024.120014

Giulia Musso , Carlo Gabelli , Marco Puthenparampil , Chiara Cosma , Annachiara Cagnin , Paolo Gallo , Gianni Sorarù , Elena Pegoraro , Martina Zaninotto , Angelo Antonini , Stefania Moz , Carlo Federico Zambon , Mario Plebani , Maurizio Corbetta , Daniela Basso

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引用次数: 0

Abstract

Background

Advances in analytical methods have recently paved the way to Alzheimer’s disease (AD) biomarkers testing in blood along with the more established CSF testing. To ensure a forthcoming application of this low-invasive diagnostic that might allow to recognize early onset of dementia, appropriate pathological cut-points need to be defined.

Methods

In this cross-sectional study we measured blood and CSF neurofilament light chain (NFL), phosphorylated tau (pTau 181), Amyloid-β1-42 (AB 1–42) and Amyloid-β1-40 (AB 1–40) on a fully automated chemiluminescent platform (Lumipulse, Fujirebio) in 80 cognitively impaired patients and 55 cognitively unimpaired subjects. Clinical cut points were calculated with receiver-operator characteristic (ROC) curve analysis and a head-to-head comparison of blood and CSF testing was performed.

Results

Blood NFL best discriminant thresholds to distinguish neurodegenerative diseases from controls varied age-dependently, being 19 and 33 pg/mL in subjects 50–65 years and > 65 years respectively. AD was best framed by AB 1–42/1–40 ratio < 0.079 and ptau181 > 1 pg/mL. Though a strong correlation for all biomarkers, only blood AB ratio was equal to CSF testing for AD diagnosis.

Conclusions

The specific context of use might be considered to define the cut-offs of blood biomarkers of neurodegenerative diseases. Future efforts towards reference materials for each AD blood biomarker will improve clinical cut-offs.

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使用 Lumipulse 自动平台检测阿尔茨海默病的血液生物标志物：年龄效应与临床价值解读。

背景：最近，分析方法的进步为血液中的阿尔茨海默病（AD）生物标志物检测以及更为成熟的脑脊液检测铺平了道路。为了确保这种低侵入性诊断方法能够早日应用于痴呆症的早期诊断，需要确定适当的病理学切点：在这项横断面研究中，我们使用全自动化学发光平台（Lumipulse，富士比奥公司）测量了80名认知障碍患者和55名认知功能未受损者的血液和脑脊液神经丝轻链（NFL）、磷酸化tau（pTau 181）、淀粉样蛋白-β1-42（AB 1-42）和淀粉样蛋白-β1-40（AB 1-40）。通过接收器-操作者特征（ROC）曲线分析计算了临床切点，并对血液和脑脊液检测进行了头对头比较：区分神经退行性疾病和对照组的血液 NFL 最佳判别阈值随年龄而变化，50-65 岁和 65 岁以上受试者的最佳判别阈值分别为 19 和 33 pg/mL。AB 1-42/1-40 比率为 1 pg/mL，是诊断 AD 的最佳阈值。虽然所有生物标志物都有很强的相关性，但在诊断AD方面，只有血液AB比值与脑脊液检测结果相当：结论：在确定神经退行性疾病血液生物标志物的临界值时，应考虑具体的使用环境。未来，针对每种AD血液生物标志物的参考材料的开发工作将改善临床临界值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinica Chimica Acta 医学-医学实验技术

CiteScore

10.10

自引率

2.00%

发文量

1268

审稿时长

23 days

期刊介绍： The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.