Identification of exosomal biomarkers and its optimal isolation and detection method for the diagnosis of Parkinson's disease: A systematic review and meta-analysis.

Ageing Res Rev

Institute of Digital Anti-aging Healthcare, Inje University, Gimhae 50834, Republic of Korea; Biohealth Products Research Center (BPRC), Inje University, Gimhae 50834, Republic of Korea; Research Center for Aged-life Redesign (RCAR), Inje University, Gimhae 50834, Republic of Korea; Department of Physical Therapy, College of Healthcare Medical Science & Engineering, Inje University, Gimhae 50834, Republic of Korea; Department of Physical Therapy, Graduate School of Inje University, Gimhae 50834, Republic of Korea; Department of Rehabilitation Science, Graduate School of Inje University, Gimhae 50834, Republic of Korea. Electronic address:

Published: December 2022

Recently, there has been growing interest in exosomal biomarkers for their active targeting and specificity for delivering their cargos (proteins, lipids, nucleic acids) from the parent cell to the recipient cell. Currently, the clinical diagnosis of Parkinson's disease (PD) is mainly based on a clinician's neuropsychological examination and motor symptoms (e.g., bradykinesia, rigidity, postural instability, and resting tremor). However, this diagnosis method is not accurate due to overlapping criteria of other neurodegenerative diseases. Exosomes are differentially expressed in PD and a combination of types and contents of exosomes might be used as a biomarker in PD. Here, we systematically reviewed and meta-analyzed exosomal contents, types and sources of exosomes, method of isolation, and protein quantification tools to determine the optimum exosome-related attributes for PD diagnosis. Pubmed, Embase, and ISI Web of Science were searched for relevant studies. 25 studies were included in the meta-analysis. The Ratio of Mean (RoM) with 95% confidence intervals (CI) was calculated to estimate the effect size. Biomarker performances were rated by random-effects meta-analysis with the Restricted Maximum Likelihood (REML) method. The study protocol is available at PROSPERO (CRD42022331885). Exosomal α-synuclein (α-Syn) was significantly altered in PD patients from healthy controls [RoM = 1.67, 95% CI (0.99 to 2.35); p = 0.00] followed by tau [RoM = 1.33, 95% CI (0.79 to 1.87); p = 0.00], PS-129 [RoM = 0.97, 95% CI (0.54 to 1.40); p = 0.00], and DJ-1/PARK7 [RoM = 0.93, 95% CI (0.64 to 1.21); p = 0.00]. Central nervous system derived L1CAM exosome [RoM = 1.24, 95% CI (1.04 to 1.45); p = 0.00] from either plasma [RoM = 1.35, 95% CI (1.09 to 1.61); p = 0.00]; or serum [RoM = 1.47, 95% CI (1.05 to 1.90); p = 0.00] has been found the optimum type of exosome. The exosome isolation by ExoQuick [RoM = 1.16, 95% CI (0.89 to 1.43); p = 0.00] and protein quantification method by ELISA [RoM = 1.28, 95% CI (1.15 to 1.41); p = 0.00] has been found the optimum isolation and quantification method, respectively for PD diagnosis. This meta-analysis suggests that α-Syn in L1CAM exosome derived from blood, isolated by ExoQuick kit, and quantified by ELISA can be used for PD diagnosis.

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http://dx.doi.org/10.1016/j.arr.2022.101764DOI Listing

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