Micro- and nanoscale biosensing technologies for early diagnosis of Parkinson's disease

Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, remains challenging to diagnose at its earliest stages due to the absence of definitive biomarkers and overlapping clinical features with other synucleinopathies, thereby delaying therapeutic intervention and effective disease management. This review provides an integrative evaluation of established and emerging approaches for detecting PD-specific biomarkers in biofluids and tissues with high sensitivity and specificity. Conventional assays such as seed amplification techniques, proximity ligation and extension methods, bead-based microarrays, and immunoassays including ELISA, electrochemiluminescence, and SIMOA are examined alongside their performance metrics and inherent limitations. We then highlight next-generation micro- and nanoscale biosensing platforms, including nanopore-based resistive pulse sensing, surface plasmon resonance (SPR), surface-enhanced Raman spectroscopy (SERS), field-effect transistors (FETs), electrochemical sensors, and lateral flow assays (LFAs), which are capable of ultrasensitive detection at nano- to attomolar concentrations. Particular emphasis is given to nucleic acid-based technologies such as aptasensors, genosensors, and CRISPR/Cas systems for their exceptional molecular recognition, programmable signal outputs, and portability. The potential of artificial intelligence and machine learning tools (e.g., SVM, RF, DNN) to improve biomarker interpretation, enable multiplexed analysis, and facilitate real-time monitoring is also discussed. Finally, we outline key translational challenges, including assay standardization, clinical validation, scalability, integration into wearable and point-of-care devices, and regulatory hurdles towards the development of robust, clinically deployable diagnostic platforms for early PD detection and monitoring.