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Backgrounds: Numerous lines of evidence support the intricate interplay between Parkinson's disease (PD) and the PINK1-dependent mitophagy process. This study aimed to evaluate differences in plasma PINK1 levels among idiopathic PD, PD syndromes (PDs), and healthy controls., Methods: A total of 354 participants were included, consisting of 197 PD patients, 50 PDs patients, and 107 healthy controls were divided into two cohorts, namely the modeling cohort (cohort 1) and the validated cohort (cohort 2). An enzyme-linked immunosorbent assay (ELISA)-based analysis was performed on PINK1 and α-synuclein oligomer (Asy-no). The utilization of the area under the curve (AUC) within the receiver-operating characteristic (ROC) curves served as a robust and comprehensive approach to evaluate and quantify the predictive efficacy of plasma biomarkers alone, as well as combined models, in distinguishing PD patients from controls., Results: PINK1 and Asy-no were elevated in the plasma of PD and PDs patients compared to healthy controls. The AUCs of PINK1 (0.771) and Asy-no (0.787) were supposed to be potentially eligible plasma biomarkers differentiating PD from controls but could not differentiate PD from PDs. Notably, the PINK + Asy-no + Clinical RBD model showed the highest performance in the modeling cohort and was comparable with the PINK1 + Clinical RBD in the validation cohort. Moreover, there is no significant correlation between PINK1 and UPDRS, MMSE, HAMD, HAMA, RBDQ-HK, and ADL scores., Conclusion: These findings suggest that elevated PINK1 in plasma holds the potential to serve as a non-invasive tool for distinguishing PD patients from controls. Moreover, the outcomes of our investigation lend support to the plausibility of implementing a feasible blood test in future clinical translation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hong, Zheng, Hou, Jiang, Lu, Wang, Zhou, Ye, Xie and Li.)