A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease

Sensitive detection of low-abundance biomarkers in blood is essential for the early diagnosis of Alzheimer's disease (AD). Although the single molecule array (Simoa) platform offers femtomolar-level sensitivity and surpasses conventional assays such as enzyme-linked immunosorbent assay, its broader clinical utility is constrained by issues like nonspecific binding and a limited dynamic range. In this study, we present a surface-engineered microfluidic platform incorporating engineered beads to reduce nonspecific binding, electrostatic bead-microwell pairing for improved capture efficiency, and an algorithmic calibration model to extend the dynamic range. These innovations collectively improve the analytical sensitivity and quantification accuracy for plasma Aβ1-42 and pTau181. Statistical analyses assessed correlation between our microfluidic platform and Quanterix Simoa, and evaluated our diagnostic ability using the Quanterix Simoa measurements as the reference standard in individuals with AD (<i>N</i> = 107) and cognitively normal controls (<i>N</i> = 100). We further validated diagnostic cutoff values in an independent cohort. The microfluidic platform demonstrates a superior diagnostic performance and enables reliable longitudinal monitoring of plasma biomarkers. Our results highlight the potential of the surface-engineered microfluidic platform for clinical translation in neurodegenerative disease diagnostics.

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Publication Details

Journal
ACS Sensors
Published
2025-11-24
DOI
https://doi.org/10.1021/acssensors.5c03653
Citations
2
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
1.35
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article

A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease

Zheqi Hu, Zhixin Zhou, Cheng Peng, Zhihong Ke et al.
2 citations
ACS Sensors
3D Printing in Biomedical Research
1.35
article

A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease

Zheqi Hu, Zhixin Zhou, Cheng Peng, Zhihong Ke, Yue Cheng, Dan Yang, Yun Xu, Chenglu Mao, Hao Chen, Tan Yi, Limoran Tang, Shujuan Xu, Han Shen, Hongpan Xu, Wenqian Gao
article en
2 citations

Abstract

Sensitive detection of low-abundance biomarkers in blood is essential for the early diagnosis of Alzheimer's disease (AD). Although the single molecule array (Simoa) platform offers femtomolar-level sensitivity and surpasses conventional assays such as enzyme-linked immunosorbent assay, its broader clinical utility is constrained by issues like nonspecific binding and a limited dynamic range. In this study, we present a surface-engineered microfluidic platform incorporating engineered beads to reduce nonspecific binding, electrostatic bead-microwell pairing for improved capture efficiency, and an algorithmic calibration model to extend the dynamic range. These innovations collectively improve the analytical sensitivity and quantification accuracy for plasma Aβ1-42 and pTau181. Statistical analyses assessed correlation between our microfluidic platform and Quanterix Simoa, and evaluated our diagnostic ability using the Quanterix Simoa measurements as the reference standard in individuals with AD (<i>N</i> = 107) and cognitively normal controls (<i>N</i> = 100). We further validated diagnostic cutoff values in an independent cohort. The microfluidic platform demonstrates a superior diagnostic performance and enables reliable longitudinal monitoring of plasma biomarkers. Our results highlight the potential of the surface-engineered microfluidic platform for clinical translation in neurodegenerative disease diagnostics.

ACS SensorsVol. 11(1)
Nanjing University of Information Science and Technology (CN), Alltech (United States) (US), Nanjing Health and Health Commission (CN), Nanjing Brain Hospital (CN), Nanjing Drum Tower Hospital (CN), Center for Translational Molecular Medicine (NL), Kai Biotech (South Korea) (KR), Nanjing University (CN)
Openalex Percentile: Top 17%
3D Printing in Biomedical Research
1.35
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