The aim of the present study was to screen for biomarkers of Parkinson's disease (PD) using proteomics and bioinformatics approaches. PD patients were divided into three groups: Those without surgery (PD1 group); those who had undergone deep brain stimulation (DBS) surgery without electrode stimulation (PD2 group); and those who had undergone DBS surgery with 1 month of electrode stimulation (PD3 group). The non-Parkinson control group (CK group) was also involved. Quantitative proteomic analysis of human sera was performed through the use of tandem mass tag markers and liquid chromatography-mass spectrometry (LC-MS)-based techniques. For the proteins with quantitative information, a systematic bioinformatics analysis was then performed, including protein annotation, functional classification, functional enrichment and cluster analysis based on functional enrichment. Of the 739 proteins identified, quantitative information was available for 644. With regard to differential expression, 18 upregulated and 21 downregulated proteins were screened in the PD1/CK comparison group; 12 upregulated and 12 downregulated proteins in the PD2/PD1 comparison group; and 16 upregulated and 19 downregulated proteins in the PD3/PD2 comparison group. Coiled-coil domain-containing protein 154 (CCDC154) and tripartite motif-containing protein 3 (TRIM3) were key proteins involved in the molecular mechanisms of PD, participating in intracellular vesicle, ubiquitin protein ligase and transition metal ion-binding activities. After DBS surgery, desert hedgehog protein (DHH) was downregulated, whereas neuropilin-2 (NRP2) was upregulated; these participated in the ensheathment of neurons and the semaphorin receptor complex, respectively. The expression level of chloride intracellular channel protein 1 (CLIC1) was increased after 1 month of electrode stimulation following DBS. By combining proteomic approaches and LC-MS methods, significant proteins including CCDC154, TRIM3, DHH, NRP2 and CLIC1 were detected with high specificity and sensitivity. These may be used as novel biomarkers for early diagnosis of PD and the future development of treatments.

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Background Gait impairments including shuffling gait and hesitation are common in people with Parkinson’s disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD. Objective This study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS). Methods A total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated. Results The results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F1,48=69.75, P<.001, partial eta-square=0.59), initial step angle (F1,48=15.56, P<.001, partial eta-square=0.25), and last step angle (F1,48=61.99, P<.001, partial eta-square=0.56). Within the PD cohort, both the ALCT and DBS induced greater mean step angles (ACLT: F1,38=5.77, P=.02, partial eta-square=0.13; DBS: F1,52=8.53, P=.005, partial eta-square=0.14) and last step angles (ACLT: F1,38=10, P=.003, partial eta-square=0.21; DBS: F1,52=4.96, P=.003, partial eta-square=0.09), but no significant changes were observed in step time and number after the treatments. Additionally, these step angles were correlated with the Unified Parkinson's Disease Rating Scale, Part III score: mean step angle (single task: r=–0.60, P<.001; dual task: r=–0.52, P<.001), initial step angle (single task: r=–0.35, P=.006; dual task: r=–0.35, P=.01), and last step angle (single task: r=–0.43, P=.001; dual task: r=–0.41, P=.002). Conclusions This pilot study demonstrated that the gait angular characteristics, as quantified by the step angles, were sensitive to the disease severity of PD and, more importantly, can capture the effects of treatments on the gait, while the traditional metrics cannot. This indicates that these metrics may serve as novel markers to help the assessment of gait in those with PD as well as the rehabilitation of this vulnerable cohort.