Profiling identifies a biomarker panel that quantifies Aβ pathology in a Chinese cohort, suggesting effective screening tools.
INTRODUCTION While current blood‐based biomarkers for Alzheimer's disease (AD) are effective for determining amyloid beta (Aβ) pathology positivity/negativity, they are insufficient for quantifying Aβ plaque deposition. METHODS We profiled 325 plasma proteins in a Hong Kong Chinese cohort using the Nucleic Acid Linked Immuno‑Sandwich Assay (NULISAseq) platform. We analyzed the dysregulation trajectories of the blood proteome along Aβ pathology progression and used machine learning to develop a biomarker panel to quantify Aβ pathology. RESULTS We identified 43 blood proteins correlated with Aβ plaque accumulation and selected 8 proteins to construct a model. This model was strongly correlated with amyloid positron emission tomography Centiloid values ( r = 0.89), enabling quantification of Aβ deposition and classification of early‐stage pathology (area under the curve = 0.93). DISCUSSION This study provides a systematic profile of dynamic protein alterations during Aβ pathology progression. Moreover, we developed a biomarker assay that accurately quantifies Aβ pathology, offering a potential tool to facilitate early screening and monitoring of amyloid pathology.
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Zheng et al. (2026) studied this question.
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