Fluorescence tagged salivary exosomes as a nano tool in early diagnosis of Parkinson’s disease

Abstract Parkinson’s disease is generally asymptomatic at earlier stages. The pressing need is for the susceptibility risk biomarkers, that can aid in better diagnosis and therapeutics as well can objectively serve to measure the endpoint of disease progression. The role of exosomes in progression of neurodegenerative diseases is already reported and its cargo could be potent in playing a revolutionary role in biomarker discovery. In our study, the salivary exosomes were efficiently isolated by chemical precipitation from subjects (PD = 70, healthy controls = 26 and probable PD = 08) followed by antibody-based validation through CD63, CD9, GAPDH, flotillin 1, L1CAM, and calnexin. Morphological characterization of the isolated exosomes through transmission elcetrom microscopy (TEM). The exosome quantification via fluorescence and antibody-based nanoparticle tracking analysis (NTA). The total alpha-synuclein (α-syntotal) in salivary exosomal cargo was quantified by ELISA. The disease severity staging confirmation was done by 99mTc-TRODAT-SPECT. We observed a significant increase in total exosome concentration in PD patients than the healthy control (HC) where fluorescence-tagged exosomes were observed to be higher in PD (p < 0.0001) than the HC using NTA with a sensitivity of 94.34%. This results was validated through exosomes tagged with antibody CD63 (p = 0.006) with a similar sensitivity of 94.12%. We further validated our findings with the ELISA-based α-syntotal concentration in exosomes where it was observed to be higher in PD with a sensitivity of 88.24%. The striatal binding ratios in 99mTc-TRODAT-SPECT shown positive correlation with fluorescent exosomes concentration r = 0.3000, α-syntotal concentration r = 0.8000. In this study for the first time we have found that the fluorescence tagged exosomes has potential to screen the progression of disease with clinically acceptable sensitivity and can be a potent early detection method for PD.