Issue 26, 2026, Issue in Progress

Graphene field-effect transistor based multiplexed sensing platform for simultaneous detection of multiple Alzheimer's disease biomarkers

Abstract

Simultaneous detection of multiple biomarkers for one disease using a single drop of body fluid is challenging yet critical to confirm symptoms in the early stage. This study presents the development of a graphene field-effect transistor (GFET)-based multiplexed sensing platform designed for overcoming this obstacle. The platform utilizes a hexamethyldisilazane (HMDS) blocking layer as a hydrophobic treatment to enable recognition element (probe/aptamer) modifications within a small chip area (3 × 3 mm2), and this further enables simultaneous detection of multiple targets (multi-targets) in complex biological samples. The optimized aptamer/probe functionalization also enhances the specificity, sensitivity, and accuracy of the sensor. The technology was demonstrated with Alzheimer's disease (AD) biomarkers as a case study. Two distinctive biomarkers, hsa-miR-125b and Aβ42, are detected simultaneously with distinguishable signatures, and the lowest tested concentration is 1 fM. The cross-check experiments also show the effectiveness of the multi-target detection capability. This concise platform paves the way for accurate detection of early-stage diseases when the simultaneous identification of multiple biomarkers is required.

Graphical abstract: Graphene field-effect transistor based multiplexed sensing platform for simultaneous detection of multiple Alzheimer's disease biomarkers

Supplementary files

Article information

Article type
Paper
Submitted
29 Sep 2025
Accepted
26 Feb 2026
First published
07 May 2026
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2026,16, 23937-23944

Graphene field-effect transistor based multiplexed sensing platform for simultaneous detection of multiple Alzheimer's disease biomarkers

B. Guo, J. Wang, F. Lou, B. Yuan, Z. Chen, C. Tang, W. Chen, F. Yi, J. Jiang, G. Hu, C. Cong and Y. Lu, RSC Adv., 2026, 16, 23937 DOI: 10.1039/D5RA07384G

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