Multiplexed impedimetric zinc oxide nanorods-modified aptasensor on carbon ink-inscribed paper electrodes for the specific and sensitive co-detection of Alzheimer's and Parkinson's disease.

Neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD), represent a growing health burden, while early diagnosis remains challenging because established diagnostic approaches, including cerebrospinal fluid analysis and neuroimaging, are invasive, expensive, and unsuitable for decentralized point-of-care testing. Recent progress in electrochemical and paper-based biosensors has enabled low-cost, portable, and multiplexed biomarker analysis. However, their clinical translation remains limited by low biomarker concentrations, matrix interference, nonspecific adsorption, sensor-to-sensor variability, storage stability, and the need for validation using clinical samples. Herein, a paper-based multiplex electrochemical aptasensor was developed for simultaneous impedimetric detection of amyloid beta-42 (Aβ-42) and alpha synuclein-60 (αS-60), biomarkers associated with AD and PD, respectively. The device comprised screen-printed carbon and silver electrodes on a cellulose substrate, two independently functionalized working electrodes, zinc oxide nanorods (ZnO-NRs) as electroactive signal-amplification layers, and target-specific DNA aptamers as biorecognition elements. Electrochemical impedance spectroscopy was used for label-free measurement of target-induced changes in charge-transfer resistance. The sensor exhibited a linear response from 0.1 ng/mL to 10 µg/mL for both biomarkers, with limits of detection of 4.41 ng/mL for Aβ-42 and 2.62 ng/mL for αS-60. The platform further detected both analytes in artificial cerebrospinal fluid and artificial saliva, demonstrating that the paper-based sensing interface remains responsive in physiologically mimicked matrices. Overall, this study provides a low-cost, disposable, label-free, and multiplexed proof-of-concept platform for simultaneous AD- and PD-associated biomarker detection. Although the system demonstrates promising performance in artificial matrices, further optimization of sensitivity, surface immobilization, antifouling behaviour, long-term storage, and validation using real clinical saliva and CSF samples will be required before practical diagnostic deployment.