Content area
Abstract
Objective
Isolated REM sleep behavior disorder (iRBD) is considered as the strongest predictor of Parkinson's disease (PD). Reliable and accurate biomarkers for iRBD detection and the prediction of phenoconversion are in urgent need. This study aimed to investigate whether α‐Synuclein (α‐Syn) species in plasma neuron‐derived extracellular vesicles (NDEVs) could differentiate between iRBD patients and healthy controls (HCs).
Methods
Nanoscale flow cytometry was used to detect α‐Syn‐containing NDEVs in plasma.
Results
A total of 54 iRBD patients and 53 HCs were recruited. The concentrations of total α‐Syn, α‐Syn aggregates, and phosphorylated α‐Syn at Ser129 (pS129)‐containing NDEVs in plasma of iRBD individuals were significantly higher than those in HCs (
Interpretation
The current study demonstrated that the levels of total α‐Syn, α‐Syn aggregates, and pS129‐containing NDEVs in the plasma of individuals with iRBD were significantly higher compared to HCs. The levels of α‐Syn species‐containing NDEVs in plasma may serve as biomarkers for iRBD.
Full text
Introduction
Parkinson's disease (PD) is a common synucleinopathy characterized by the degeneration of dopaminergic neurons in the midbrain and the pathological aggregation of α-synuclein (α-Syn).1 Early diagnosis of PD remains challenging.2 Studies indicated that degeneration of up to 60–70% of dopaminergic neurons in the substantia nigra can precede the onset of typical motor symptoms.3 PD has a prodromal phase that can last for several years to several decades, during which various nonmotor symptoms, including REM Sleep Behavior Disorder (RBD), olfactory impairment, and constipation, may emerge. Among these symptoms, isolated RBD (iRBD) is considered the most robust predictor of PD,4 with up to 80% of individuals with iRBD developing PD or other α-synucleinopathies within 12 years.5 Accurate identification of individuals at high risk of PD, particularly through the analysis of accessible materials such as plasma, is critically important. Extracellular vesicles (EVs) are small vesicular structures that cells release into the surrounding environment, which are produced by a wide variety of cell types.6 EVs existed in various body fluids, including cerebrospinal fluid (CSF), blood, saliva, and urine.7–10 Central nervous system (CNS) derived EVs can at least partially transfer across the blood–brain barrier (BBB), which facilitates the assessment of EVs in peripheral blood as a means to reflect the CNS pathological features.11,12 Identifying EVs carrying specific markers enables the differentiation of EVs originating from distinct cell types such as neurons or glial cells.11,13 The neuronal markers such as L1CAM and the recently discovered anti-N-methyl-D-aspartate (NMDA) receptor subunit 2A (NMDAR2A) have been verified repeatedly.13–23
Multiple studies have explored the differences in plasma or serum levels of α-Syn in NDEVs between individuals with PD and healthy controls (HCs).24 A meta-analysis demonstrated a significant increase level of total α-Syn in the plasma NDEVs of PD individuals compared to HCs.24 Several studies have also examined levels of α-Syn in NDEVs in the plasma or serum of individuals with iRBD. Jiang C et al. investigated neuron-derived EVs in serum and observed significantly higher α-Syn concentrations in NDEVs in both iRBD and PD.25 Yan YQ et al. similarly investigated neuron-derived EVs and discovered significantly elevated concentrations of α-Syn in neuron-derived exosomes in the plasma of patients with probable iRBD (screened by RBD Questionnaire Hong Kong) and PD compared to HCs.26 Yan S et al. reported concentrations of α-Syn in NDEVs in serum were significantly higher in patients with iRBD compared to HCs. Those with positive CSF seed amplification assay (SAA) had higher α-Syn concentrations in NDEVs in serum compared with those who were CSF SAA negative.27 However, one study reported contradicting results. Niu M et al. found no significant difference in concentrations of α-Syn in NDEVs between the iRBD and HC groups.28 To date, existing studies mainly focused on total α-Syn in iRBD, research concentrated on other pathological α-Syn species, such as α-Syn aggregates and phosphorylated α-Syn at Ser129 (pS129), is needed.
Recently, a nanoscale flow cytometry-based technology has emerged that enables direct identification and quantification of EVs carrying specific proteins in blood. This innovative approach also facilitates the classification of EVs from different cell types, such as neurons,29 astrocytes,30,31 and platelets.32 In this study, we utilized nanoscale flow cytometry to detect α-Syn species positive NDEVs in plasma, with a specific focus on α-Syn aggregates and pS129. Our objective was to investigate whether α-Syn species in plasma NDEVs could differentiate between iRBD patients and HCs. Additionally, we aimed to investigate the differences in α-Syn species-containing NDEVs levels between iRBD patients who meet the criteria for prodromal PD and those who do not. Furthermore, we sought to explore the correlations between α-Syn species-containing NDEVs levels and the clinical features of iRBD.
Methods
Participants and clinical assessments
Subjects with iRBD patients and HCs were polysomnography (PSG)-confirmed and recruited from Beijing Tiantan Hospital. The inclusion criteria for iRBD patients were as follows: (1) confirmation of RBD based on the criteria outlined in the International Classification of Sleep Disorders, third edition (ICSD-3), without parkinsonism; (2) no history of neurological diseases, such as stroke, moderate-to-severe traumatic brain injury, hydrocephalus, or brain tumors; (3) no history of psychiatric diseases. The inclusion criteria for HCs were as follows: (1) no family history of movement disorders and (2) no history of neurological or psychiatric diseases.
In iRBD group, the severity of motor symptoms was assessed using the MSD-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Cognitive function was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Orthostatic hypotension (OH) was defined as a blood pressure drop of ≥20/10 mmHg upon standing. Olfactory function was evaluated based on scores in odor identification using a 16-item odor stick test. Additional nonmotor scales used included the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Modified Apathy Evaluation Scale (MAES), Scale for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), Pittsburgh Sleep Quality Index (PSQI), and the Epworth Sleepiness Scale (ESS).
Based on the criteria for prodromal PD,4 the included iRBD group was divided into two subgroups: those who met the criteria for prodromal PD and those who did not. In iRBD group, the biomarkers evaluated included sex, pesticide exposure, nonsmoking status, presence of first-degree relative with PD, type 2 diabetes mellitus, physical inactivity, possible RBD, subthreshold parkinsonism, constipation, excessive daytime somnolence, symptomatic orthostatic hypotension, erectile dysfunction, urinary dysfunction, and global cognitive deficit. The calculation method was as follows: First, the pretest probability was determined based on the age of each patient. Then, the product of the likelihood ratios (LRs) of all risk markers and prodromal markers was calculated (total LRs). The posttest probability was calculated using the formula in the criteria for prodromal PD. Missing markers were assigned an LR of 1. If the total LRs was higher than the threshold for the patient's age group or the posttest probability ≥80%, it was considered to meet the criteria for prodromal PD.
Plasma sample preparation
Venous blood samples were collected from the participants in the morning under fasting conditions. Blood was collected using polypropylene collection and storage tubes containing EDTA. The blood samples were centrifuged at 4°C and 1500 × g for 15 min. After centrifugation, the plasma sample from the upper layer was further centrifuged at 4°C and 12,000 × g for 10 min. The supernatant was transferred to a new tube for further analysis. The reference plasma was pooled equally with centrifuged plasma from 9 HCs subjects, then diluted 1:1 with PBS, and ultracentrifuged at 4°C and 180,000 × g for 4 h. The top layer supernatant was collected as EV-depleted plasma. The pelleted EVs were resuspended in 200 μL PBS for immunoprecipitation or lysed using 100uL RIPA for western blot. The sample was stored at −80°C before use.
Immunoprecipitation
NMRAR2A-positive EVs were immunoprecipitated by anti-NMRAR2A (ab174636, abcam) and Dynabeads Antibody Coupling Kit (14311D, Thermo Fisher Scientifc) according to the manufacturer's instructions. Briefly, 10 μg of anti-NMRAR2A antibody was mixed with 1 mg of beads and incubated at 37°C with continuous rotation. Then, the bead mixture was added to the resuspended EV pellet and incubated overnight at 4°C with continuous rotation. To elute the EVs from the beads, 70 μL of glycine buffer (0.1 M, pH = 3) was used and subsequently balanced with 15 μL of Tris buffer (1 M, pH = 7). The NMRAR2A-positive EVs were preserved at −80°C.
Transmission electron microscopy (
Five μL of NMRAR2A-positive EVs was applied onto a copper grid with a carbon support membrane. Incubate for 60 seconds, carefully remove any excess sample using filter paper, and then stain with a 2% uranyl acetate solution for 60 seconds. Carefully remove any excess uranyl acetate solution using filter paper and allow the sample to air-dry. Capture electron microscope images using a Tecnai F20 TEM operating at 200 kilovolts.
Western blotting analysis
The total protein concentrations of EV-depleted plasma and EVs were determined using the Bicinchoninic Acid Assay (23225, Life Technologies, Eugene, United States). Subsequently, 15 μg of proteins extracted from plasma was separated using a 4–20% ExpressPlus™ PAGE Gel (M42010C, Genscript, Nanjing, China) and transferred onto nitrocellulose (NC) membranes. The NC membranes were subsequently blocked using 5% nonfat milk and incubated overnight at 4°C with the following antibodies: mouse NMDAR2A monoclonal antibody (ab174636, abcam), polyclonal anti-Alix (12422-1-AP, Proteintech, 1:5000), and CD9 (MA1-19002, Termo Fisher Scientifc, 1:500). Then, the membranes were incubated with horseradish peroxidase-conjugated secondary antibody for 1 h at room temperature. To visualize the immunoreactive bands, a chemiluminescence kit (WBKLS0500, EMD Millipore Corporation, Billerica, United States) and a Bio-Rad Chemidoc XRS+ Imager were utilized.
Zetaview
Plasma samples from 9 iRBD patients and 9 HCs were diluted 1:500 in PBS (pH 7.4). The diluted samples were subsequently analyzed using the ZetaView platform (Particle Metrix) following the manufacturer's instructions to assess the distribution and concentration of nanoparticles.
Nanoscale flow cytometry analysis
Fluorophore-conjugated antibodies were prepared using Zenon IgG labeling kits from Invitrogen/Life Technologies. The ZENON™ Alexa Fluor 647 Rabbit IgG labeling kit (Z25308, Life Technologies, Eugene, United States) was used to label recombinant anti-α-Syn MJFR-1 (ab138501, Abcam, Cambridge, MA, United States) antibody. The ZENON™ Alexa Fluor 488 Rabbit IgG labeling kit (Z25302, Life Technologies, Eugene, United States) was used to label recombinant anti-α Syn aggregate MJFR-14 (ab209538, Abcam, Cambridge, MA, United States) antibody. The ZENON™ Alexa Fluor Pacific Blue Mouse IgG2a labeling kit (Z25156, Life Technologies, Eugene, United States) was used to label pS129 (825701, BioLegend, San Diego, CA, United States) antibody. The ZENON™ Alexa Fluor 405 Mouse IgG2b labeling kit (Z25213, Life Technologies, Eugene, United States) and ZENON™ Alexa Fluor 647 Mouse IgG2b labeling kit (Z25208, Life Technologies, Eugene, United States) were used to label the mouse NMDAR2A monoclonal antibody (ab174636, abcam) antibody.
Five μL of Component A from the labeling kit was incubated with 1 μg of antibody at room temperature under light-protected conditions for 30 min. Component B was diluted to a concentration of 1 μg/μL using phosphate-buffered saline (PBS). Then, adding 5 μL of Component B, followed by further incubation at room temperature under light-protected conditions for 15 min. For each participant, 5 μL of plasma was added to the flow cytometry tube. Subsequently, 0.1 μg of the fluorescent-conjugated NMDAR2A antibody system was added to each participant's plasma and incubated for 30 min at room temperature under light-protected conditions. After the completion of incubation, 0.2 μg of the fluorescent-conjugated α-Syn antibody system was added to each participant's plasma and incubated for 20 min at room temperature under light-protected conditions. Following incubation, the mixture was diluted 1:60 with PBS and vortexed. Then, centrifuge for 10 s using a hand-held centrifuge. Subsequently, quantitative detection was carried out using the Cytoflex S platform (Beckman Coulter, Milano, Italy) on the nanoscale flow cytometry. Violet Side Scatter Height (VSSC-H) mode was used to detect small vesicles below 500 nm. Fluorescent-labeled EVs were obtained from each sample at a medium flow rate of 30 μL/min. Gates were set based on immunoglobulin isotype controls and blank controls. The concentrations of total α-Syn, α-Syn aggregates, pS129 positive and NMDAR2A positive EVs were calculated by considering the flow rate during detection and the dilution ratio of PBS. Immunoglobulin isotype controls and EV-depleted plasma controls of the corresponding species were also labeled at the same final concentrations as the antibodies. All samples were tested within 4 h after labeling. Cytometry analysis for each α-Syn species was conducted in a single batch on the same day.
Statistical analysis
Statistical analysis was conducted using SPSS 26.0 and GraphPad Prism 8. The normality of all data was assessed using the K-S test. The two-sample independent t-test was used for normally distributed continuous variables, and the Mann–Whitney U test was used for non-normally distributed continuous variables. The chi-square test was used for categorical variables. Pearson correlation analysis was employed to assess the correlation between normally distributed continuous variables, while Spearman rank correlation analysis was used to evaluate the correlation between non-normally distributed continuous variables. Statistical significance was defined as a P-value less than 0.05. Binary logistic regression was used to create a multivariable logistic regression model suited for iRBD diagnosis. The receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC), and the Youden Index was used to determine the optimal cutoff value.
Results
Demographic and clinical features
Between March 2022 and March 2023, a total of 54 individuals with iRBD were recruited for this study, along with 53 age-matched HCs. The median age of iRBD patients was 65.5 (60, 70), with 34 males (63%) and 20 females (37%). Among them, 43 individuals (80%) met the criteria for prodromal PD, while 11 individuals (20%) did not. Fifteen individuals (28%) had OH, while 39 individuals (72%) did not. Among the individuals with iRBD, 20 (37%) were smokers, and 34 (63%) were nonsmokers. The HC group had a median age of 64 (60, 67.5), with 29 males (55%) and 24 females (45%). There was no significant difference in age or sex between the iRBD and HC groups. The demographic and clinical characteristics of all participants were presented in Table 1.
Table 1 Demographic and clinical features.
| Group | iRBD | HC | p |
| Females/males | 20/34 | 24/29 | 0.435a |
| Age, yearc | 65.5 (60.0, 70.0) | 64.0 (60.0, 67.5) | 0.241d |
| Disease duration, yearc | 5 (3, 10) | – | – |
| MDS-UPDRS Ic | 7.5 (6, 11) | – | – |
| MDS-UPDRS IIc | 1 (0, 2) | – | – |
| MDS-UPDRS IIIc | 4 (1.75, 7.25) | – | – |
| MDS-UPDRS totalc | 15 (9, 22) | – | – |
| MMSEc | 28 (27, 29) | – | – |
| MoCAc | 23 (21, 26) | – | – |
| RBDSQc | 7 (5, 9) | – | – |
| SCOPA-AUTb | 12.63 ± 6.72 | – | – |
| MAESc | 9 (3.75, 18.25) | – | – |
| PSQIb | 11.57 ± 5.58 | – | – |
| ESSc | 3 (1, 5) | – | – |
| Sniffin’ sticksb | 7.4 ± 2.56 | – | – |
| Total LRs for prodromal PDc | 1789 (336, 7818) | – | – |
| Posttest probability for prodromal PDc | 0.97 (0.84, 0.99) | – | – |
| Probability of prodromal PD ≥80%, n (%) | 43 (80%) | – | – |
| OH, (%) | 15 (28%) | – | – |
| Smoke, (%) | 20 (37%) | – | – |
| Total α-Syn (104)/mLc | 93.8 (63.7, 185.5) | 60.4 (47.4, 75.2) | <0.0001d |
| α-Syn aggregates (104)/mLc | 171.6 (124.7, 291.0) | 75.6 (57.4, 100.0) | <0.0001d |
| pS129 (104)/mLc | 243.0 (155.6, 314.7) | 96.0 (72.6, 118.0) | <0.0001d |
Characteristics of
Transmission electron microscopy analysis was conducted on the NDEVs obtained by NMDAR2A-IP from the EV pellet of ultracentrifuged reference plasma samples, aiming to analyze their morphology and size. NDEVs with a diameter of approximately 100 nm and a dish-like structure were detected (Fig. 1A). Western blot analysis was performed to examine EV-specific markers. The results showed enrichment of NMDAR2A, as well as the general EV markers including Alix and CD9, in the reference EV sample obtained from ultracentrifugation (Fig. 1B). NTA was utilized to determine the size and distribution of the EVs, revealing a broad peak with a maximum centered around 100 nm (Fig. 1C,D). The plasma concentration of EVs was determined in both the iRBD and HC groups using NTA. No significant difference in EV concentration was observed between the two groups (Fig. 1E).
[IMAGE OMITTED. SEE PDF]
The levels of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs were compared between the samples of reference plasma and the EV-depleted plasma, with the IgG isotype served as a technical control for these comparisons (Fig. 2A–F). The accuracy of EV measurement was evaluated using a linearity dilution strategy. Briefly, the reference plasma labeled with α-Syn and NMDAR2A antibodies was diluted at ratios of 1:120, 1:240, and 1:480 in PBS and processed using the Cytoflex S platform (Fig. 2G–I).
[IMAGE OMITTED. SEE PDF]
The concentrations of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs in plasma were shown in Table 1 for both the iRBD and HC groups. The total α-Syn, α-Syn aggregates, and pS129-containing NDEV concentrations in plasma of iRBD individuals were significantly higher than those in HCs (ptotal α-Syn <0.0001; pα-Syn aggregates <0.0001; ppS129 <0.0001, Figure 3A–C).
[IMAGE OMITTED. SEE PDF]
ROC analyses revealed that the levels of total α-Syn-containing NDEVs in plasma demonstrated a sensitivity of 98.11% and a specificity of 50% in distinguishing iRBD from HCs, with an AUC of 0.764 (95% CI 0.674–0.854). α-Syn aggregate-containing NDEVs exhibited a sensitivity of 90.57% and a specificity of 77.78% in differentiating iRBD from HCs, with an AUC of 0.909 (95% CI 0.854–0.965). PS129-containing NDEVs showed a sensitivity of 90.57% and a specificity of 85.19% in discriminating iRBD from HCs, with an AUC of 0.925 (95% CI 0.875–0.975) (Fig. 3D). A binary logistic regression with forward stepwise selection was utilized to develop a multivariable logistic regression model. This model included concentrations of various α-Syn species-containing NDEVs. The integrated model attained an AUC of 0.965, with a sensitivity of 94.3% and specificity of 88.9% (Fig. 3E).
Correlations of α-Syn-containing
To explore the clinical significance of α-Syn-containing NDEV concentrations in iRBD patients, we analyzed their correlations with demographic and clinical characteristics, such as age, disease duration, MMSE, MoCA, RBDSQ, PSQI, ESS, MAES, SCOPA-AUT, Sniffin’ Sticks olfactory scores, and MDS-UPDRS-III score (Fig. 4A). In iRBD group, a negative correlation was observed between the levels of α-Syn aggregate-containing NDEVs in plasma and Sniffin’ Sticks olfactory scores (r = −0.351, p = 0.039) (Fig. 4B). However, no significant correlations were found between the levels of α-Syn aggregate-containing NDEVs and age, disease duration, severity assessed by the MDS-UPDRS III score, cognitive scores, or other indicators. Additionally, there were no significant correlations observed between the levels of total α-Syn and pS129-containing NDEVs in plasma and clinical characteristics.
[IMAGE OMITTED. SEE PDF]
The partial correlation analysis, adjusted for age and sex, revealed a persistent negative correlation between the levels of α-Syn aggregate-containing NDEVs in plasma and Sniffin’ Sticks olfactory scores in the iRBD group (r = −0.440, p = 0.010). After adjusting for age and sex, no significant correlations were found between the levels of α-Syn aggregate-containing NDEVs and disease duration, MDS-UPDRS III scores, cognitive scores, or other indicators. Additionally, no significant correlations were observed between the levels of total α-Syn and pS129-containing NDEVs in plasma and clinical characteristics.
In iRBD group, smokers exhibited significantly lower levels of α-Syn aggregates and pS129-containing NDEVs in plasma compared to nonsmokers (pα-Syn aggregates = 0.014, ppS129 = 0.003; Fig. 4C–E). No significant differences were observed in the plasma levels of total α-Syn-containing NDEVs between the groups. Subgrouping based on prodromal PD criteria, gender, and the presence of OH also revealed no significant differences in the levels of α-Syn species-containing NDEVs in plasma between the two groups.
Discussion
This study revealed significant increase of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs levels in the plasma of individuals with iRBD compared to HCs through nanoscale flow cytometry analysis. Additionally, α-Syn aggregate-containing NDEV levels were significantly correlated with the olfactory functions in iRBD individuals, which is one of the most important prodromal clinical dysfunctions of PD. We also observed a decreased levels of α-Syn aggregates and pS129-containing NDEVs in plasma in iRBD smokers, supporting the hypothesis that smoking may have a protect effect against PD.
Previous studies reported increased α-Syn concentrations in the CSF of patients with iRBD compared to HCs,33–35 along with a higher rate of positive α-Syn SAA in CSF.36–39 The dopamine transporter (DAT) PET scan facilitates the functional evaluation of the nigrostriatal dopaminergic system.40,41 Several independent cohorts, using different tracers, demonstrated decreased dopaminergic innervation in iRBD.42,43 The impairment of the substantia nigra in patients with iRBD was also confirmed using structural neuroimaging techniques.44,45 Recently, Yan S et al. reported a significant increase in α-Syn concentrations in NDEVs in iRBD serum compared to the HCs and found that α-Syn concentrations in NDEVs were increased in at-risk participants with a positive CSF SAA.27 The current study found elevated concentrations of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs in the plasma of individuals with iRBD compared to HCs. These suggested that NDEVs may reflect pathological changes in CNS and that patients with iRBD may experience these pathological changes in the CNS prior to phenoconversion. α-Syn can readily transfer from the CNS to peripheral blood through NDEVs.11 α-Syn species-containing NDEVs in plasma might serve as potential biomarkers for iRBD and could predict phenoconversion, but further longitudinal validation is still needed.
Previous studies on CNS-derived EVs have predominantly focused on total α-Syn. α-Syn can undergo different post-translational modifications, such as phosphorylation, nitration, and ubiquitination.46–48 pS129 is the primary disease-associated modification accounting for over 90% of α-Syn found in Lewy bodies.49 Since the initial study in 2000, the aggregated form of α-Syn has been suggested as the main cause of neuronal dysfunction.50 α-Syn aggregates can induce neurotoxicity through various mechanisms and possess the ability to self-replicate and propagate from one cell to another.51,52 There is growing evidence supporting the role of α-Syn aggregates in the pathogenesis of PD.53,54 So far, only one study detected the concentrations of pS129 in plasma NDEVs within the iRBD population. However, a significant number of these samples were below the detection range,25 primarily due to the technical limitations. To date, there has been no studies investigating the concentrations of α-Syn aggregates in plasma NDEVs within the iRBD population. In current study, we investigated various α-Syn species in plasma NDEVs, with a specific focus on α-Syn aggregates and pS129. The findings revealed that α-Syn aggregates and pS129 in plasma NDEVs exhibited better diagnostic efficacy compared to total α-Syn-containing NDEVs. This is in line with the hypothesis that α-Syn aggregates and pS129 in plasma NDEVs may better reflect CNS pathological changes in iRBD than total α-Syn. The area under the ROC curve for an integrative model incorporating the levels of α-Syn, pS129, and α-Syn aggregate-containing NDEVs in plasma was 0.965. This demonstrated improved diagnostic efficacy compared to previous studies focusing solely on total α-Syn in plasma or serum NDEVs.25–28 However, further verifications, especially longitudinal studies, are still critical for testing the prediction efficacy of these biomarkers for the phenoconversion of iRBD patients.
In this study, EVs were directly detected using a nanoscale flow cytometry analysis. Previous studies typically involve immunocapture assays followed by Electrochemiluminescence (ECL) analysis25,27,28 or Ella system analysis.26 Traditional methods typically required 250–1000 μL of plasma or serum.25–28 One major advantage of the nanoscale flow cytometry method is that it enables one-step detection, with high sensitivity and a requirement of only 5 μL of plasma, facilitating its widespread application.
In the current study, the MJFR-14 antibody was utilized to detect α-Syn aggregates positive NDEVs. We have previously conducted validation studies for the MJFR-14 antibody that demonstrated its capacity to specifically detect α-Syn aggregates with minimal cross-reactivity toward the monomeric form, using an electrochemiluminescence-based assay with recombinant α-Syn standards.55 However, it has been reported by Kumar et al. that while the MJFR-14 antibody showed a preference for binding α-Syn oligomers, it also exhibited binding to monomers.56 This suggests that while our validation efforts confirm the utility of MJFR-14 for identifying α-Syn aggregates, the possibility of cross-reactivity cannot be entirely excluded. The inconsistencies underscore the need for further research to refine the specificity of antibodies used in detecting various forms of α-Syn.
This study demonstrated a negative correlation between the olfactory scores and the α-Syn aggregate-containing NDEVs levels in the plasma of the iRBD group. In PD, olfactory dysfunction may result from pathological changes including Lewy bodies and neuronal loss in the olfactory bulb, tract, and piriform cortex. According to Braak staging, the olfactory bulb is the initial site of α-Syn aggregation in PD progression.57,58 Olfactory dysfunction serves as a marker for identifying high-risk patients likely to progress to α-synucleinopathies in the short term.59 Plasma α-Syn aggregate-containing NDEVs might reflect pathological changes in the olfactory conduction pathways and predict short-term phenotypic conversion in iRBD patients. Future follow-up studies should concentrate on examining the variations in the timeline for conversion to α-synucleinopathy among iRBD patients, focusing on those with different levels of α-synuclein aggregate-containing NDEVs and varying degrees of olfactory dysfunction.
Additionally, our study observed that individuals with iRBD who smoke exhibited lower levels of α-Syn aggregates and pS129-containing NDEVs in plasma compared to nonsmokers. This finding aligns with previous epidemiological studies indicating a negative correlation between smoking and PD.60,61 However, the mechanisms underlying this association are not definitively established. Although nicotine is often cited for its potential neuroprotective effects, the pathways through which it may exert these effects are varied.62 Nicotine was demonstrated to stimulate dopamine release in smokers and enhance the degradation of sirtuin 6, a pro-inflammatory protein.63 Additionally, cholinergic deficits are also observed in PD, which might be mitigated by nicotine, acting as an agonist for nicotinic acetylcholine receptors.64 Despite multiple proposed mechanisms suggesting smoking might reduce the risk of PD, the effect of nicotine intake on PD is still debated, as shown in clinical trials.65–70 It is important to acknowledge that the differences observed in our study, while statistically significant, are relatively modest and there is a substantial overlap in the levels of α-Syn aggregates and pS129-containing NDEVs between smokers and nonsmokers. While we found a correlation between smoking and α-Syn aggregates as well as pS129-containing NDEVs, the precise role of nicotine in influencing α-Syn pathology remains elusive. Further detailed studies are essential, especially those examining the relationship between α-Syn aggregates, pS129-containing NDEVs in plasma, and established neurodegenerative markers such as neurofilament light (NfL), to better understand the underlying mechanisms.
Among the 54 patients with iRBD included in the study, 43 (80%) fulfilled the criteria for prodromal PD, highlighting the elevated risk of subsequent synucleinopathy in this cohort. Notably, no statistically significant correlation was observed between the concentration of α-Syn-species-containing NDEVs and either the total LRs or the posttest probabilities for PD. Furthermore, no significant differences were found in the plasma concentrations of α-Syn-containing NDEVs between iRBD patients who met the criteria for prodromal PD and those who did not. This lack of differentiation could be attributed to our method of quantifying positive gated events rather than absolute concentrations of α-Syn-species-containing NDEVs, potentially impacting the sensitivity needed to detect subtle correlations with prodromal risk in PD. Additionally, the predominance of our cohort already classified as prodromal PD, with disproportionate numbers between the two iRBD subgroups, may further hinder our ability to discern statistically significant differences. In our upcoming longitudinal study of this group, we plan to monitor the evolution of prodromal probability scores and the levels of α-Syn-species in NDEVs over time. This could reveal if α-Syn-species-containing NDEVs might predict the iRBD phenoconversion. Currently, any conclusions drawn from our results, particularly the absence of significant statistical correlations, should be considered with caution.
Conclusion
The current study demonstrated that the levels of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs in the plasma of individuals with iRBD were significantly higher compared to HCs. The levels of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs in plasma can potentially serve as biomarkers for iRBD.
Author Contributions
XW, XL, FX, and ZY designed the study. XW, YZ, WK, HC, CY, SL, BZ, and JW were responsible for recruitment of patients and collection of (clinical) patient data. XW, YZ, WK, and HC performed the experiments. XW, YZ, HC, WK, and ZY interpreted the data. XW performed the literature review and wrote the manuscript draft. All authors critically revised and contributed to the manuscript draft, and read and approved the final manuscript.
Acknowledgments
We deeply appreciate the participants for their generous donation of samples.
Funding Information
This research was funded by the Beijing Municipal Natural Science Foundation (Grant Numbers 7244331, 7232013 and 7212031), the National Natural Science Foundation of China (Grant Numbers 82271459, 82020108012, and 82071422), and the National Key Research and Development Program of China (Grant Number 2018YFC1312001).
Conflict of Interest
The authors have no relevant financial or nonfinancial interests to disclose.
Informed Consent Statement
All participants provided written informed consent.
Data Availability Statement
Anonymized data presented in this article will be shared by request from any qualified investigator.
Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson's disease. Mov Disord. 2015;30(12):1591‐1601.
Armstrong MJ, Okun MS. Diagnosis and treatment of Parkinson disease: a review. JAMA. 2020;323(6):548‐560.
Lang AE, Lozano AM. Parkinson's disease. First of two parts. N Engl J Med. 1998;339(15):1044‐1053.
Heinzel S, Berg D, Gasser T, Chen H, Yao C, Postuma RB. Update of the MDS research criteria for prodromal Parkinson's disease. Mov Disord. 2019;34(10):1464‐1470.
Schenck CH, Boeve BF, Mahowald MW. Delayed emergence of a parkinsonian disorder or dementia in 81% of older men initially diagnosed with idiopathic rapid eye movement sleep behavior disorder: a 16‐year update on a previously reported series. Sleep Med. 2013;14(8):744‐748.
Théry C, Witwer KW, Aikawa E, et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines. J Extracell Vesicles. 2018;7(1): [eLocator: 1535750].
Bobrie A, Colombo M, Raposo G, Thery C. Exosome secretion: molecular mechanisms and roles in immune responses. Traffic. 2011;12(12):1659‐1668.
Ogawa Y, Kanai‐Azuma M, Akimoto Y, Kawakami H, Yanoshita R. Exosome‐like vesicles with dipeptidyl peptidase IV in human saliva. Biol Pharm Bull. 2008;31(6):1059‐1062.
Barreiro K, Lay AC, Leparc G, et al. An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles. J Extracell Vesicles. 2023;12(2): [eLocator: e12304].
Caby MP, Lankar D, Vincendeau‐Scherrer C, Raposo G, Bonnerot C. Exosomal‐like vesicles are present in human blood plasma. Int Immunol. 2005;17(7):879‐887.
Shi M, Liu C, Cook TJ, et al. Plasma exosomal alpha‐synuclein is likely CNS‐derived and increased in Parkinson's disease. Acta Neuropathol. 2014;128(5):639‐650.
Ha D, Yang N, Nadithe V. Exosomes as therapeutic drug carriers and delivery vehicles across biological membranes: current perspectives and future challenges. Acta Pharm Sin B. 2016;6(4):287‐296.
Tian C, Stewart T, Hong Z, et al. Blood extracellular vesicles carrying synaptic function‐ and brain‐related proteins as potential biomarkers for Alzheimer's disease. Alzheimers Dement. 2023;19(3):909‐923.
Sytnyk V, Leshchyns'ka I, Schachner M. Neural cell adhesion molecules of the immunoglobulin superfamily regulate synapse formation, maintenance, and function. Trends Neurosci. 2017;40(5):295‐308.
Badhwar A, Hirschberg Y, Tamayo NV, et al. Assessment of brain‐derived extracellular vesicle enrichment for blood biomarker analysis in age‐related neurodegenerative diseases: an international overview. bioRxiv. 2023.
Dutta S, Hornung S, Kruayatidee A, et al. α‐Synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson's disease from multiple system atrophy. Acta Neuropathol. 2021;142(3):495‐511.
Fiandaca MS, Kapogiannis D, Mapstone M, et al. Identification of preclinical Alzheimer's disease by a profile of pathogenic proteins in neurally derived blood exosomes: a case‐control study. Alzheimers Dement. 2015;11(6):600‐607.e1.
Gu D, Liu F, Meng M, et al. Elevated matrix metalloproteinase‐9 levels in neuronal extracellular vesicles in Alzheimer's disease. Ann Clin Transl Neurol. 2020;7(9):1681‐1691.
Jiang C, Hopfner F, Berg D, et al. Validation of α‐synuclein in L1CAM‐Immunocaptured exosomes as a biomarker for the stratification of parkinsonian syndromes. Mov Disord. 2021;36(11):2663‐2669.
Nogueras‐Ortiz CJ, Mahairaki V, Delgado‐Peraza F, et al. Astrocyte‐ and neuron‐derived extracellular vesicles from Alzheimer's disease patients effect complement‐mediated neurotoxicity. Cells. 2020;9(7):1618.
Ohmichi T, Mitsuhashi M, Tatebe H, Kasai T, Ali El‐Agnaf OM, Tokuda T. Quantification of brain‐derived extracellular vesicles in plasma as a biomarker to diagnose Parkinson's and related diseases. Parkinsonism Relat Disord. 2019;61:82‐87.
Pulliam L, Liston M, Sun B, Narvid J. Using neuronal extracellular vesicles and machine learning to predict cognitive deficits in HIV. J Neurovirol. 2020;26(6):880‐887.
Suire CN, Eitan E, Shaffer NC, et al. Walking speed decline in older adults is associated with elevated pro‐BDNF in plasma extracellular vesicles. Exp Gerontol. 2017;98:209‐216.
Xylaki M, Chopra A, Weber S, Bartl M, Outeiro TF, Mollenhauer B. Extracellular vesicles for the diagnosis of Parkinson's disease: systematic review and meta‐analysis. Mov Disord. 2023;38(9):1585‐1597.
Jiang C, Hopfner F, Katsikoudi A, et al. Serum neuronal exosomes predict and differentiate Parkinson's disease from atypical parkinsonism. J Neurol Neurosurg Psychiatry. 2020;91(7):720‐729.
Yan YQ, Pu JL, Zheng R, et al. Different patterns of exosomal alpha‐synuclein between Parkinson's disease and probable rapid eye movement sleep behavior disorder. Eur J Neurol. 2022;29(12):3590‐3599.
Yan S, Jiang C, Janzen A, et al. Neuronally derived extracellular vesicle α‐synuclein as a serum biomarker for individuals at risk of developing Parkinson disease. JAMA Neurol. 2024;81(1):59‐68.
Niu M, Li Y, Li G, et al. A longitudinal study on alpha‐synuclein in plasma neuronal exosomes as a biomarker for Parkinson's disease development and progression. Eur J Neurol. 2020;27(6):967‐974.
Guo Z, Tian C, Shi Y, et al. Blood‐based CNS regionally and neuronally enriched extracellular vesicles carrying pTau217 for Alzheimer's disease diagnosis and differential diagnosis. Acta Neuropathol Commun. 2024;12(1):38.
Jiang S, Li X, Li Y, et al. APOE from patient‐derived astrocytic extracellular vesicles alleviates neuromyelitis optica spectrum disorder in a mouse model. Sci Transl Med. 2024;16(736): [eLocator: eadg5116].
Wang P, Lan G, Xu B, et al. Alpha‐synuclein‐carrying astrocytic extracellular vesicles in Parkinson pathogenesis and diagnosis. Transl Neurodegener. 2023;12(1):40.
Wang Z, Zheng Y, Cai H, et al. Abeta1‐42‐containing platelet‐derived extracellular vesicle is associated with cognitive decline in Parkinson's disease. Front Aging Neurosci. 2023;15: [eLocator: 1170663].
Wang XT, Yu H, Liu FT, et al. Associations of sleep disorders with cerebrospinal fluid α‐synuclein in prodromal and early Parkinson's disease. J Neurol. 2022;269(5):2469‐2478.
Ye G, Li Y, Zhou L, et al. Predictors of conversion to α‐synucleinopathy diseases in idiopathic rapid eye movement sleep behavior disorder. J Parkinsons Dis. 2020;10(4):1443‐1455.
Mollenhauer B, Caspell‐Garcia CJ, Coffey CS, et al. Longitudinal analyses of cerebrospinal fluid α‐synuclein in prodromal and early Parkinson's disease. Mov Disord. 2019;34(9):1354‐1364.
Concha‐Marambio L, Weber S, Farris CM, et al. Accurate detection of α‐synuclein seeds in cerebrospinal fluid from isolated rapid eye movement sleep behavior disorder and patients with Parkinson's disease in the DeNovo Parkinson (DeNoPa) cohort. Mov Disord. 2023;38:567‐578.
Poggiolini I, Gupta V, Lawton M, et al. Diagnostic value of cerebrospinal fluid alpha‐synuclein seed quantification in synucleinopathies. Brain. 2022;145(2):584‐595.
Iranzo A, Fairfoul G, Ayudhaya ACN, et al. Detection of alpha‐synuclein in CSF by RT‐QuIC in patients with isolated rapid‐eye‐movement sleep behaviour disorder: a longitudinal observational study. Lancet Neurol. 2021;20(3):203‐212.
Rossi M, Candelise N, Baiardi S, et al. Ultrasensitive RT‐QuIC assay with high sensitivity and specificity for Lewy body‐associated synucleinopathies. Acta Neuropathol. 2020;140(1):49‐62.
Bergareche A, Rodriguez‐Oroz MC, Estanga A, et al. DAT imaging and clinical biomarkers in relatives at genetic risk for LRRK2 R1441G Parkinson's disease. Mov Disord. 2016;31(3):335‐343.
Miyamoto M, Miyamoto T. Neuroimaging of rapid eye movement sleep behavior disorder: transcranial ultrasound, single‐photon emission computed tomography, and positron emission tomography scan data. Sleep Med. 2013;14(8):739‐743.
Albin RL, Koeppe RA, Chervin RD, et al. Decreased striatal dopaminergic innervation in REM sleep behavior disorder. Neurology. 2000;55(9):1410‐1412.
Bauckneht M, Chincarini A, De Carli F, et al. Presynaptic dopaminergic neuroimaging in REM sleep behavior disorder: a systematic review and meta‐analysis. Sleep Med Rev. 2018;41:266‐274.
De Marzi R, Seppi K, Hogl B, et al. Loss of dorsolateral nigral hyperintensity on 3.0 tesla susceptibility‐weighted imaging in idiopathic rapid eye movement sleep behavior disorder. Ann Neurol. 2016;79(6):1026‐1030.
Frosini D, Cosottini M, Donatelli G, et al. Seven tesla MRI of the substantia nigra in patients with rapid eye movement sleep behavior disorder. Parkinsonism Relat Disord. 2017;43:105‐109.
Oueslati A. Implication of alpha‐synuclein phosphorylation at S129 in synucleinopathies: what have we learned in the last decade? J Parkinsons Dis. 2016;6(1):39‐51.
Arawaka S, Sato H, Sasaki A, Koyama S, Kato T. Mechanisms underlying extensive Ser129‐phosphorylation in α‐synuclein aggregates. Acta Neuropathol Commun. 2017;5(1):48.
Zhang J, Li X, Li JD. The roles of post‐translational modifications on α‐synuclein in the pathogenesis of Parkinson's diseases. Front Neurosci. 2019;13:381.
Fujiwara H, Hasegawa M, Dohmae N, et al. Alpha‐synuclein is phosphorylated in synucleinopathy lesions. Nat Cell Biol. 2002;4(2):160‐164.
Lucking CB, Brice A. Alpha‐synuclein and Parkinson's disease. Cell Mol Life Sci. 2000;57(13–14):1894‐1908.
Wong YC, Krainc D. α‐Synuclein toxicity in neurodegeneration: mechanism and therapeutic strategies. Nat Med. 2017;23(2):1‐13.
Du XY, Xie XX, Liu RT. The role of α‐synuclein oligomers in Parkinson's disease. Int J Mol Sci. 2020;21(22):8645.
Winner B, Jappelli R, Maji SK, et al. In vivo demonstration that alpha‐synuclein oligomers are toxic. Proc Natl Acad Sci USA. 2011;108(10):4194‐4199.
Cremades N, Cohen SI, Deas E, et al. Direct observation of the interconversion of normal and toxic forms of α‐synuclein. Cell. 2012;149(5):1048‐1059.
Zheng Y, Cai H, Wang X, et al. Erythrocytic alpha‐synuclein species as biomarkers for isolated rapid eye movement sleep behavior disorder. Mov Disord. 2023;38(12):2315‐2317.
Kumar ST, Jagannath S, Francois C, Vanderstichele H, Stoops E, Lashuel HA. How specific are the conformation‐specific α‐synuclein antibodies? Characterization and validation of 16 α‐synuclein conformation‐specific antibodies using well‐characterized preparations of α‐synuclein monomers, fibrils and oligomers with distinct structures and morphology. Neurobiol Dis. 2020;146: [eLocator: 105086].
Braak H, Del Tredici K, Rub U, de Vos RA, Jansen Steur EN, Braak E. Staging of brain pathology related to sporadic Parkinson's disease. Neurobiol Aging. 2003;24(2):197‐211.
Rey NL, Wesson DW, Brundin P. The olfactory bulb as the entry site for prion‐like propagation in neurodegenerative diseases. Neurobiol Dis. 2018;109(Pt B):226‐248.
Mahlknecht P, Iranzo A, Högl B, et al. Olfactory dysfunction predicts early transition to a Lewy body disease in idiopathic RBD. Neurology. 2015;84(7):654‐658.
Checkoway H, Powers K, Smith‐Weller T, Franklin GM, Longstreth WT Jr, Swanson PD. Parkinson's disease risks associated with cigarette smoking, alcohol consumption, and caffeine intake. Am J Epidemiol. 2002;155(8):732‐738.
Gorell JM, Rybicki BA, Johnson CC, Peterson EL. Smoking and Parkinson's disease: a dose‐response relationship. Neurology. 1999;52(1):115‐119.
Quik M, Perez XA, Bordia T. Nicotine as a potential neuroprotective agent for Parkinson's disease. Mov Disord. 2012;27(8):947‐957.
Olsen AL, Clemens SG, Feany MB. Nicotine‐mediated rescue of α‐synuclein toxicity requires synaptic vesicle glycoprotein 2 in drosophila. Mov Disord. 2023;38(2):244‐255.
Bohnen NI, Yarnall AJ, Weil RS, et al. Cholinergic system changes in Parkinson's disease: emerging therapeutic approaches. Lancet Neurol. 2022;21(4):381‐392.
Hanagasi HA, Lees A, Johnson JO, Singleton A, Emre M. Smoking‐responsive juvenile‐onset Parkinsonism. Mov Disord. 2007;22(1):115‐119.
Mitsuoka T, Kaseda Y, Yamashita H, et al. Effects of nicotine chewing gum on UPDRS score and P300 in early‐onset parkinsonism. Hiroshima J Med Sci. 2002;51(1):33‐39.
Ebersbach G, Stock M, Muller J, Wenning G, Wissel J, Poewe W. Worsening of motor performance in patients with Parkinson's disease following transdermal nicotine administration. Mov Disord. 1999;14(6):1011‐1013.
Clemens P, Baron JA, Coffey D, Reeves A. The short‐term effect of nicotine chewing gum in patients with Parkinson's disease. Psychopharmacology. 1995;117(2):253‐256.
Fagerstrom KO, Pomerleau O, Giordani B, Stelson F. Nicotine may relieve symptoms of Parkinson's disease. Psychopharmacology. 1994;116(1):117‐119.
Brenner SR. Smoking duration, intensity, and risk of Parkinson disease. Neurology. 2010;75(6):574‐575. author reply.
© 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.