Alzheimer’s disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

中文翻译：

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阿尔茨海默病血液生物标志物：研究设计、样本采集、处理、生物样本库、测量和结果报告的实用指南

尽管经过数十年的研究和临床调查，阿尔茨海默氏病 (AD) 是最常见的痴呆症，但理解和治疗仍然具有挑战性。这可能部分是由于缺乏广泛可用且具有成本效益的诊断和预后方式。近年来，在技术进步的推动下，基于血液的 AD 生物标志物领域取得了重大进展，主要是提高了检测和测量平台的分析灵敏度和精度。几种血液生物标志物已显示出准确检测 AD 病理生理学的巨大潜力。因此，人们对应用这些生物标志物进行诊断和预后产生了很大的兴趣，作为替代指标来研究各种协变量对 AD 病理生理学的影响，并加速 AD 治疗试验和监测治疗效果。然而，血液样本的采集、处理、存储、分析和报告方式缺乏标准化，可能会影响这些生物标志物测量的可重复性，从而可能阻碍其在临床和研究环境中广泛使用的进展。为了帮助解决这些问题，我们提供了根据最近关于样本处理对血液生物标志物测量影响的研究结果制定的基本指南。这些指南涵盖了重要的考虑因素，包括研究设计、血液采集、血液处理、生物样本库、生物标志物测量和结果报告。此外，拟议的指南包括用于遗传和核糖核酸分析的适当血液处理程序的最佳实践。虽然我们关注 AT(N) 标准的关键血液 AD 生物标志物（例如，淀粉样蛋白 -β [Aβ]40、Aβ42、Aβ42/40 比率、总 tau、磷酸化 tau、神经丝轻链、脑-衍生的 tau 蛋白和胶质纤维酸性蛋白），我们预计这些指南通常适用于其他类型的血液生物标志物。我们还预计这些指南将帮助研究人员规划和执行生物标志物研究，实现样品处理的协调，以提高研究之间的可比性。