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The reliability of plasma biomarkers of Alzheimer's disease (AD) can be compromised by protease‐induced degradation. This can limit the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). In this study, we conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions. We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 h. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0 h or 24 h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA and P100 tubes, followed by storage at RT for 0 h or 24 h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation‐mass spectrometry (IP‐MS) assays. Both the IP‐MS and Simoa methods revealed that the use of P100 tubes significantly improves the stability of Aβ42 and Aβ40 across all approaches. However, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP‐MS assay in Approach 3. No significant differences were observed in the levels of plasma p‐tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches. Supplementation of blood collection tubes with protease inhibitors could reduce the protease‐induced degradation of plasma Aβ42 and Aβ40, and the Aβ42/40 ratio for the IP‐MS assay. These findings have crucial implications for preanalytical procedures, particularly in resource‐limited settings. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]