EC Neurology

The promise of nanosensors for the early detection of Parkinson's disease biomarkers lies in their unparalleled sensitivity and miniaturization, which allow for the identification of pathological signs at ultralow concentrations. These advanced tools show immense potential in analyzing key biofluids, including blood and cerebrospinal fluid for direct biomarkers, as well as non-invasive sources like saliva and tears, which offer a convenient window into neurological health. Furthermore, the development of specialized nanoprobes enables the in vivo imaging of pathological protein aggregates within the brain, providing a real-time view of disease progression. The power of these technologies is greatly amplified by integration with artificial intelligence, which can decipher complex biomarker patterns to predict disease onset and stratify patients. However, the path to clinical adoption faces significant challenges, including ensuring biocompatibility, achieving manufacturing scalability, navigating regulatory pathways, and conclusively demonstrating clinical utility. Future progress depends on interdisciplinary efforts to create multiplexed, point-of-care, and even theranostic platforms that combine diagnosis with treatment. Ultimately, by overcoming these translational hurdles, nanosensor technology holds the potential to revolutionize Parkinson's disease management by enabling pre-symptomatic detection and personalized intervention.

 Keywords: Nanosensors; Parkinson’s Disease; Early Detection; Biomarkers; Neurodegenerative Diseases; Diagnostics; Alpha-Synuclein; Liquid Biopsy

1. Munhoz RP., et al. "The clinical diagnosis of Parkinson's disease". Arquivos de Neuro-Psiquiatria 6 (2024): 1-10.
2. Tanaka M. "Parkinson's disease: Bridging gaps, building biomarkers, and reimagining clinical translation". Cells 15 (2025): 1161.
3. Armstrong MJ and Okun MS. "Diagnosis and treatment of Parkinson disease: a review". Journal of the American Medical Association6 (2020): 548-560.
4. Gupta A., et al. "Quality of life and psychological problems in patients undergoing neurological rehabilitation". Annals of Indian Academy of Neurology 4 (2008): 225-230.
5. Willmen L., et al. "The economic burden of diagnostic uncertainty on rare disease patients". BMC Health Services Research 1 (2024): 1388.
6. Stefanis L. "α-synuclein in Parkinson's disease". Cold Spring Harbor Perspectives in Medicine 2 (2012): a009399.
7. Xie W., et al. "New insights into the role of mitochondrial dysfunction and protein aggregation in Parkinson's disease". Biochimica et Biophysica Acta 11 (2010): 935-941.
8. Lind-Holm Mogensen F., et al. "Microglial dynamics and neuroinflammation in prodromal and early Parkinson's disease". Journal of Neuroinflammation 1 (2025): 136.
9. Arena G., et al. "Neurodegeneration and neuroinflammation in Parkinson's disease: a self-sustained loop". Current Neurology and Neuroscience Reports 8 (2022): 427-440.
10. Wardhan Y., et al. "Exploring the complex interplay between Parkinson's disease and BAG proteins". Behavioural Brain Research 469 (2024): 115054.
11. Sharma P and Dhamija RK. "The quest for Parkinson's disease biomarkers: traditional and emerging multi-omics approaches". Molecular Biology Reports 1 (2025): 831.
12. Akdemir ÜÖ., et al. "Dopamine transporter SPECT imaging in Parkinson’s disease and parkinsonian disorders". Turkish Journal of Medical Sciences 2 (2021): 400-410.
13. Gujral J., et al. "PET, SPECT, and MRI imaging for evaluation of Parkinson's disease". American Journal of Nuclear Medicine and Molecular Imaging 6 (2024): 371-390.
14. Gualerzi A., et al. "Extracellular vesicles as biomarkers for Parkinson's disease: How far from clinical translation?". International Journal of Molecular Sciences 2 (2024): 1136.
15. Chen H., et al. "Metabolomic profiling uncovers diagnostic biomarkers and dysregulated pathways in Parkinson's disease". Frontiers in Neurology 16 (2025): 1608031.
16. Jiang P., et al. "Biosensors for early detection of Parkinson's disease: principles, applications, and future prospects". Biosensors (Basel)5 (2025): 280.
17. Malekzad H., et al. "Noble metal nanoparticles in biosensors: recent studies and applications". Nanotechnology Reviews 3 (2017): 301-329.
18. Gao L., et al. "Nanotechnology for neurodegenerative diseases: recent progress in brain-targeted delivery, stimuli-responsive platforms, and organelle-specific therapeutics". International Journal of Nanomedicine 20 (2025): 11015-11044.
19. Yadav VK., et al. "Recent advances in nanotechnology for Parkinson's disease: diagnosis, treatment, and future perspectives". Frontiers in Medicine (Lausanne) 12 (2025): 1535682.
20. Shoukat CA., et al. "Plasmonic ELISA for biomarker detection: a review of mechanisms, functionalization strategies, and emerging modalities". ACS Applied Bio Materials 7 (2025): 5512-5531.
21. de la Rica R and Stevens MM. "Plasmonic ELISA for the ultrasensitive detection of disease biomarkers with the naked eye". Nature Nanotechnology 12 (2012): 821-824.
22. Silva IJSD., et al. "Alpha-synuclein aggregation in Parkinson's disease". Advances in Protein Chemistry and Structural Biology 146 (2025): 35-75.
23. Khatami SH., et al. "Electrochemical biosensors in early detection of Parkinson disease". Clinica Chimica Acta 565 (2025): 120001.
24. Mandala SHS., et al. "Enhanced plasmonic biosensor utilizing paired antibody and label-free Fe₃O₄ nanoparticles for highly sensitive and selective detection of Parkinson's α-synuclein in serum". Biosensors (Basel) 10 (2021): 402.
25. Hatano T., et al. "α-synuclein: A promising biomarker for Parkinson's disease and related disorders". Journal of Movement Disorders 2 (2024): 127-137.
26. Usha Kiran P., et al. "Mitochondrial dysfunction and oxidative stress in Parkinson's disease: mechanisms, biomarkers, and therapeutic strategies". Tissue Barriers (2025): 2537991.
27. Lunati A., et al. "The genetic landscape of Parkinson's disease". Revue Neurologique (Paris) 9 (2018): 628-643.
28. Billingsley KJ., et al. "Genetic risk factors in Parkinson's disease". Cell and Tissue Research 1 (2018): 9-20.
29. Dasari M and Medapati RV. "Cerebrospinal Fluid Biomarkers for Diagnosis of Parkinson's disease: A Systematic Review". Cureus2 (2025): e79386.
30. Heineman A., et al. "Challenges and opportunities of early Parkinson's disease biomarkers: α-synuclein, leucine-rich repeat kinase 2 (LRRK2), DJ-1, and microRNA’s”. Cureus9 (2025): e91510.
31. Yadav S., et al. "Nanobiosensors in neurodegenerative disease diagnosis: A promising pathway for early detection". Digital Health 11 (2025): 20552076251342457.
32. Jang YO., et al. "Transferrin-conjugated magnetic nanoparticles for the isolation of brain-derived blood exosomal MicroRNAs: A novel approach for Parkinson's disease diagnosis". Analytica Chimica Acta 1306 (2024): 342623.
33. Madhusudhan K., et al. "Early detection of Parkinson's disease via aptamer-CRISPR platform". Neuroscience 586 (2025): 163-195.
34. Liu N., et al. "Current trends in blood biomarkers detection and neuroimaging for Parkinson's disease". Ageing Research Reviews 104 (2025): 102658.
35. Adam H., et al. "Electro-sensing analysis for Parkinson's disease biomarker on dual-electrode surface: complemented by molecular docking”. Biotechnology and Applied Biochemistry (2025).
36. Zetterberg H and Compta Y. "A tear fluid proteome of Parkinson's disease". Parkinsonism and Related Disorders 63 (2019): 1-2.
37. Gao F., et al. "SERS-based optical nanobiosensors for the detection of Alzheimer's disease". Biosensors (Basel)9 (2023): 880.
38. Elsheikh S., et al. "Advancing brain research through surface-enhanced Raman spectroscopy (SERS): Current applications and future prospects". Biosensors (Basel) 1 (2024): 33.
39. Ali I., et al. "Nanotechnology in Parkinson's disease: overcoming drug delivery challenges and enhancing therapeutic outcomes". Drug Delivery and Translational Research (2025).
40. Belloli S., et al. "Translation imaging in Parkinson's disease: Focus on neuroinflammation". Frontiers in Aging Neuroscience 12 (2020): 152.
41. Tian GL., et al. "The development of a PET radiotracer for imaging alpha synuclein aggregates in Parkinson's disease". RSC Medicinal Chemistry (2025).
42. Gong T., et al. "Implication of bimodal magnetic resonance and fluorescence imaging probes in advanced healthcare: enhancing disease diagnosis and targeted therapy”. International Journal of Nanomedicine 20 (2025): 9473-9503.
43. Li Q., et al. "Fluorescent probes for α-synuclein biomarkers: Innovations in early diagnosis and therapeutic monitoring of Parkinson's disease". Clinica Chimica Acta 579 (2025): 120612.
44. Grancharova T., et al. "Gold nanoparticles in Parkinson's disease therapy: a focus on plant-based green synthesis". Cureus2 (2024): e54671.
45. Wüllner U., et al. "The heterogeneity of Parkinson's disease”. Journal of Neural Transmission (Vienna)6 (2023): 827-838.
46. Dennis AP and Strafella AP. "The role of AI and machine learning in the diagnosis of Parkinson's disease and atypical parkinsonisms". Parkinsonism and Related Disorders 126 (2024): 106986.
47. Hassan YM., et al. "Integrating artificial intelligence with nanodiagnostics for early detection and precision management of neurodegenerative diseases". Journal of Nanobiotechnology 1 (2025): 668.
48. Dipankar P., et al. "Artificial intelligence based advancements in nanomedicine for brain disorder management: an updated narrative review". Frontiers in Medicine (Lausanne) 12 (2025): 1599340.
49. Tabashum T., et al. "Machine learning models for Parkinson disease: systematic review". JMIR Medical Informatics 12 (2024): e50117.
50. Alves B., et al. "Stakeholder perspectives on trustworthy AI for Parkinson disease management using a cocreation approach: qualitative exploratory study". Journal of Medical Internet Research 27 (2025): e73710.
51. Lafi Z., et al. "Carbon-based nanotechnology for Parkinson's disease: diagnostic and therapeutic innovations". Nanomedicine (London)16 (2025): 2023-2041.
52. Berman SE and Siderowf AD. "Current status of α-synuclein biomarkers and the need for α-synuclein PET tracers". Cells 16 (2025): 1272.
53. Yadav VK., et al. "Recent advances in nanotechnology for Parkinson's disease: diagnosis, treatment, and future perspectives”. Frontiers in Medicine (Lausanne) 12 (2025): 1535682.
54. Jiang P., et al. "Biosensors for early detection of Parkinson's disease: principles, applications, and future prospects". Biosensors (Basel) 5 (2025): 280.
55. Tolosa E., et al. "Challenges in the diagnosis of Parkinson's disease". Lancet Neurology5 (2021): 385-397.