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A blood marker for Parkinson’s Disease: Neuronal exosome-derived α-synuclein

TL;DR: This study demonstrates that the detection of pathological α-synuclein conformers from neuron-derived exosomes from plasma samples has the potential of a promising blood-biomarker of PD.
Abstract: To date, no reliable clinically applicable biomarker has been established for Parkinson’s disease (PD). Our results indicate that a long hoped blood test for Parkinson’s disease may be realized. We here assess the potential of pathological α-synuclein originating from neuron-derived exosomes from blood plasma as a possible biomarker. Following the isolation of neuron-derived exosomes from plasma of PD patients and non-PD individuals immunoblot analyses were performed to detect exosomal α-synuclein. Under native conditions significantly increased signals of disease-associated α-synuclein forms in neuron-derived exosomes were measured in all individuals with PD and clearly distinguished PD samples from controls. By performing a protein misfolding cyclic amplification assay these aggregates could be amplified and seeding could be demonstrated. Moreover, the aggregates exhibited β-sheet-rich structures and showed a fibrillary appearance. Our study demonstrates that the detection of pathological α-synuclein conformers from neuron-derived exosomes from plasma samples has the potential of a promising blood-biomarker of PD.

Summary (2 min read)

Introduction

  • Therefore, the correct diagnosis and appropriate therapy is still highly dependent on the professional experience of the examiner, and many epidemiological or post-mortem studies found high rates of misdiagnoses in PD [3] [4] [5] [6] .
  • An earlier detection of the disease, ideally in the prodromal phase before motor symptoms occur, is of utmost importance for the development and application of disease-modifying therapies.
  • Finally, the assessment of clinical symptoms by scales is still used as primary outcome parameter in most clinical trials.
  • Many studies have focused on the identification of α-syn in accessible peripheral tissues for instance biopsies of the gastrointestinal tract, skin or salivary glands [9] [10] [11] [12] .
  • Which are released extracellularly and can be isolate from plasma samples.

Demographics

  • There was no age distribution difference among the groups (p = 0.49).
  • Mean disease duration of PD patients was 3 (1-13) years and mean clinical motor symptom score (Movement Disorder Society Unified Parkinson's Disease Rating Scale Part 3, MDS-UPDRS-III) was 26.7.

Isolation and detection of EVs from peripheral blood

  • After gradual centrifugation and exosome precipitation (Fig. 1a ), the successful isolation of EVs was confirmed through immunoblotting, dynamic light scattering (DLS) and transmission electron microscopy (TEM).
  • The isolation of EVs was confirmed through dot blot analyses using native plasma samples and comparing them to isolated EVs (PD#1-#2, Ctrl#1-#2) (Fig. 1b , Extended Data Fig. 1a ).
  • The exosomal marker CD63 was significantly enriched in samples of EVs after normalization to total protein (Fig. 1c ).
  • Further characterization of the diameter and morphology of EVs was gained by negative stain TEM and showed a homogenous preparation of EVs (Fig. 1f ).
  • Analyzed samples of PD patients and controls showed no differences in mean radius distribution according to the TEM-based size distribution.

Identification of NEs from peripheral blood

  • The purification of NEs (Fig. 2a ) led to a significantly increased signal of L1 cell adhesion molecule (NCAM-L1) when compared to native plasma samples and plasma-derived exosomes (PD#4-#5, Ctrl#4-#5) (Fig. 2b-c ; Extended Data Fig. 2b ).
  • Unspecific binding to the used beads and/or the anti-NCAM-L1 antibody were excluded using an immunoblot approach (Extended Data Fig. 2a ).
  • In addition, TEM and DLS studies of NEs revealed no significant differences between both groups.
  • NEs from PD patients showed significantly increased signal intensity in dot blot analyses utilizing the structure-specific α-syn antibody (MJFR) in comparison to control NEs (PD#5-#6, Ctrl#5-#6) (Fig. 3d, e ; Extended Data Fig. 3n ).

Amplification of pathological plasma exosomal α-syn

  • Seeding capacity of the detected soluble α-syn species was tested using a PMCA assay optimized for α-syn 28, 29 .
  • In addition, the authors analyzed the signal intensity after incubation with the MJFR antibody of the untreated plasma samples before and after PMCA by dot blot analysis (PD#8-#9, Ctrl#8-#9) (Fig. 4c ).
  • For both time points no significant signal differences between PD and control plasma samples were detected (Fig. 4c-e ).
  • Individual ThioT signal curves of all analyzed samples (native plasma, EVs, NEs) of PD patients (red, n=15) and controls (grey, n=15) subjected to the sixth PMCA round are depicted in Extended Data Fig. 3g-i .
  • To visualize formed α-syn structures, TEM imaging was applied on amplified α-syn conformers after six rounds of PMCA and fibrillary structures/aggregates were observed in NEs derived from PD plasma (PD#1) (Fig. 4r ).

Discussion

  • The results of their study clearly demonstrate that a pathological α-syn form can be extracted and amplified from NEs derived from blood plasma of PD patients.
  • Interestingly, some studies detected a higher level of α-syn in NEs in PD patients by ELISA and Luminex assays or mass spectrometry and multiplexed electrochemiluminescence compared to healthy controls, which was not seen in their experiments using common standard methods like immunoblotting 20, 47, 53 .
  • Taken together, their findings are based on a strict sequence and essential combination of experimental steps containing the isolation of NEs and subsequent analysis of the soluble fraction under native conditions with an antibody that detects pathological α-syn species.
  • The authors could show incipient differences in MJFR antibody signal intensities between controls and PD patients for EVs after six rounds of PMCA and a substantial increase of the difference after analyzing NEs.

Conclusion

  • In summary, the authors demonstrate for the first time that pathological α-syn detected in plasma-derived NEs can serve as a biomarker to differentiate PD patients from healthy controls.
  • Further confirmation of the presence of pathological α-syn was reached by amplification and visualizing of the aggregates.
  • Clinical parameters of analyzed cohorts Statistics were determined by unpaired two-tailed Student´s t-test and Fisher´s exact test, also known as Table 1.

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A blood marker for Parkinsons Disease: Neuronal
exosome-derived α-synuclein
Annika Kluge ( Annika.Kluge@uksh.de )
Department of Neurology, University Hospital Kiel
Josina Bunk
Institute of Biochemistry, Christian-Albrecht-University Kiel
Eva Schaeffer
University Hospital Kiel, Department of Neurology
Alice Drobny
Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University
Erlangen-Nürnberg
Wei Xiang
Friedrich-Alexander-University Erlangen-Nürnberg (FAU)
Henrike Knacke
Department of Neurology, University Hospital Kiel
Simon Bub
Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University
Erlangen-Nürnberg
Wiebke Lückstädt
Institute of Anatomy, Christian-Albrecht-University Kiel https://orcid.org/0000-0002-1698-6770
Philipp Arnold
Institute of Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-Nürnberg
Ralph Lucius
Institute of Anatomy, Christian-Albrecht-University Kiel
Daniela Berg
University Hospital Schleswig-Holstein Kiel https://orcid.org/0000-0001-5796-5442
Friederike Zunke
University Hospital Erlangen
Article
Keywords: Parkinson's Disease, biomarker, α-synuclein
Posted Date: August 12th, 2021

DOI: https://doi.org/10.21203/rs.3.rs-783910/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License. 
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1
A blood marker for Parkinson’s Disease: Neuronal exosome-derived α-synuclein 1
2
Annika Kluge
1*
, Josina Bunk
2
, Eva Schaeffer
1
, Alice Drobny
3
, Wei Xiang
3
, Henrike Knacke
1
, 3
Simon Bub
3
, Wiebke Lückstädt
4
, Philipp Arnold
5
, Ralph Lucius
4
, Daniela Berg
1#
, Friederike 4
Zunke
3#*
5
6
1
Department of Neurology, University Hospital Kiel, Kiel, Germany 7
2
Institute of Biochemistry, Christian-Albrecht-University Kiel, Kiel, Germany 8
3
Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander 9
University Erlangen-Nürnberg, Erlangen, Germany 10
4
Institute of Anatomy, Christian-Albrecht-University Kiel, Kiel, Germany 11
5
Institute of Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-12
Nürnberg, Erlangen, Germany 13
#
contributed equally 14
*correspondence: Annika.Kluge@uksh.de; Friederike.Zunke@fau.de 15
16
Abstract 17
To date, no reliable clinically applicable biomarker has been established for Parkinson’s 18
disease (PD). Our results indicate that a long hoped blood test for Parkinson’s disease may 19
be realized. We here assess the potential of pathological α-synuclein originating from 20
neuron-derived exosomes from blood plasma as a possible biomarker. Following the 21
isolation of neuron-derived exosomes from plasma of PD patients and non-PD individuals 22
immunoblot analyses were performed to detect exosomal α-synuclein. Under native 23
conditions significantly increased signals of disease-associated α-synuclein forms in neuron-24
derived exosomes were measured in all individuals with PD and clearly distinguished PD 25
samples from controls. By performing a protein misfolding cyclic amplification assay these 26
aggregates could be amplified and seeding could be demonstrated. Moreover, the 27
aggregates exhibited β-sheet-rich structures and showed a fibrillary appearance. Our study 28
demonstrates that the detection of pathological α-synuclein conformers from neuron-derived 29
exosomes from plasma samples has the potential of a promising blood-biomarker of PD. 30
31
Keywords: α-synuclein, Parkinson´s disease, biomarker, plasma, extracellular vesicles, 32
neuron-derived exosomes, protein misfolding cyclic amplification. 33
34
Introduction 35
To date the gold-standard to confirm Parkinson’s Disease (PD) is the post-mortem detection 36
of misfolded α-synuclein -syn) as structural component of Lewy bodies in dopaminergic 37
neurons in the substantia nigra (SN)
1
. However, in the clinical routine the diagnosis of PD is 38
still based on the detection of motor symptoms, supported by imaging techniques and the 39
assessment of concurrent non-motor symptoms and risk factors for PD
2
. Therefore, the 40
correct diagnosis and appropriate therapy is still highly dependent on the professional 41
experience of the examiner, and many epidemiological or post-mortem studies found high 42

2
rates of misdiagnoses in PD
3-6
. Another major shortcoming of the clinical approach to 43
diagnose PD is the substantially delayed diagnosis in the course of the disease, as the 44
diagnosis-defining motor symptoms occur only late in the neurodegenerative process, i.e. 45
when more than 50 % of dopaminergic neurons in the SN have already been lost
7
. An earlier 46
detection of the disease, ideally in the prodromal phase before motor symptoms occur, is of 47
utmost importance for the development and application of disease-modifying therapies. 48
Finally, the assessment of clinical symptoms by scales is still used as primary outcome 49
parameter in most clinical trials. This semi-quantitative approach is an imprecise reflection of 50
actual disease progression, depending on a variety of potential confounders such as 51
medication intake, examiner’s experience and physical as well as psychological form of the 52
patient on the day of examination. 53
Taken together, there is an urgent need for an objective and reliable biomarker, to improve 54
the diagnostic accuracy of PD, detect the disease in early stages (preferably in the prodromal 55
state) and monitor disease progression. In this respect, the detection of pathological α-syn as 56
neuropathological hallmark of PD has been in the centre of attention in a wide range of 57
studies
8
. Many studies have focused on the identification of α-syn in accessible peripheral 58
tissues for instance biopsies of the gastrointestinal tract, skin or salivary glands
9-12
. 59
Moreover, there are first promising findings regarding the identification and characterization 60
of pathological α-syn forms in biofluids, such as the cerebrospinal fluid (CSF)
13
. However, 61
apart from still highly varying outcomes regarding sensitivity and specificity, all these 62
techniques are limited due to their invasiveness. Compared to those options an easy and 63
low-risk obtainable medium is blood plasma or serum
14
. With regard to contaminations and 64
inconsistent α-syn levels in the blood
14-18
, recent studies focused on extracellular vesicles 65
(EVs) like exosomes (30-100 nm membrane vesicles of endocytic origin) and microvesicles 66
(100 nm-1 µm)
19-21
. EVs released by cells of the central nervous system (CNS) (neuron-67
derived exosomes, NEs) have the capacity to pass the blood brain barrier (BBB) and 68
transport nucleic acids and proteins including α-syn
20,22
. In this manuscript the terms 69
‘exosomes’ and ‘extracellular vesicles’ will be used interchangeably to denote vesicles, which 70
are released extracellularly and can be isolate from plasma samples. For a more detailed 71
description of exosome nomenclature please see the article of the International Society for 72
Extracellular Vesicles
23
. 73
74
In this study we combined a specific preparation of NEs and the use of structure-specific 75
antibodies to detect pathological α-syn conformers isolated from the blood of PD patients and 76
compared them to non-PD individuals. Using a protein misfolding cyclic amplification assay 77
(PMCA)
13
, we analyzed the detected protein form in its capacity to seed α-syn aggregation 78
and built filamentous structures. In this study we demonstrate for the first time that the 79
detection of pathological α-syn conformers extracted from NEs is possible and can be 80
applied as suitable, easy to assess biomarker for PD that reliably discriminates patients from 81
controls. 82
83
Results 84
Demographics 85
Plasma samples were collected from 15 patients with PD (mean age 67 years, range 86
46-84 years) and 15 controls (mean age 75 years, range 50-85 years). There was no age 87
distribution difference among the groups (p = 0.49). Mean disease duration of PD patients 88

3
was 3 (1-13) years and mean clinical motor symptom score (Movement Disorder Society 89
Unified Parkinson's Disease Rating Scale Part 3, MDS-UPDRS-III) was 26.7. Summarized 90
data of both groups are listed in Table 1; available clinical data for each patient/control is 91
listed in the Extended Data Table 1. 92
93
Isolation and detection of EVs from peripheral blood 94
After gradual centrifugation and exosome precipitation (Fig. 1a), the successful isolation of 95
EVs was confirmed through immunoblotting, dynamic light scattering (DLS) and transmission 96
electron microscopy (TEM). The isolation of EVs was confirmed through dot blot analyses 97
using native plasma samples and comparing them to isolated EVs (PD#1-#2, Ctrl#1-#2) 98
(Fig. 1b, Extended Data Fig. 1a). The exosomal marker CD63 was significantly enriched in 99
samples of EVs after normalization to total protein (Fig. 1c). Increased CD63 levels within the 100
samples of EVs indicated a sufficient protocol for enrichment of EVs. Following the exosomal 101
isolation western blot analyses depicted an increased anti-CD63 antibody signal in both 102
groups (PD#1-#5, Ctrl#1-#5) (Fig. 1d). In comparison with untreated plasma samples, 103
increased signal intensities were detected after isolation of EVs (Extended Data Fig. 1b). 104
Comparing control and PD samples, no significant differences in CD63 levels could be found 105
after normalization to Coomassie Brilliant Blue (CBB) staining (Fig. 1e). Further 106
characterization of the diameter and morphology of EVs was gained by negative stain TEM 107
and showed a homogenous preparation of EVs (Fig. 1f). All images can be found in 108
Extended Data Fig. 1c. Particle size measurement from TEM images showed no differences 109
in EVs between PD and control samples (Extended Data Fig. 1d). Furthermore, DLS 110
measurements confirmed the presence of uniform particles with the size as EVs (Fig. 1g)
19
. 111
Analyzed samples of PD patients and controls showed no differences in mean radius 112
distribution according to the TEM-based size distribution. In summary, we demonstrate the 113
sufficient isolation of EVs from blood plasma samples, exhibiting no differences in size or 114
morphology between PD patients and controls. 115
116
Identification of NEs from peripheral blood 117
The purification of NEs (Fig. 2a) led to a significantly increased signal of L1 cell adhesion 118
molecule (NCAM-L1) when compared to native plasma samples and plasma-derived 119
exosomes (PD#4-#5, Ctrl#4-#5) (Fig. 2b-c; Extended Data Fig. 2b). Unspecific binding to the 120
used beads and/or the anti-NCAM-L1 antibody were excluded using an immunoblot 121
approach (Extended Data Fig. 2a). Comparing NCAM-L1 levels of NEs of PD patients and 122
controls showed no significant differences (Fig. 2c). Next, different isoforms of NCAM-L1 123
were detected through western blot analyses in samples containing NEs (Ctrl#1-#2, PD#3) 124
(Fig. 2d, Extended Data Fig. 2d). Unspecific binding to the anti-NCAM-L1 antibody and/or the 125
anti-NCAM-L1 antibody with beads were also excluded through western blot analysis 126
(Extended Data Fig. 2c). For both approaches the protocol of NEs-isolation was performed 127
as usual. A significant increase in NCAM-L1 levels was detected for NEs samples (Fig. 2e) 128
and the purification of NEs resulted in a significant increase of other established neuronal 129
markers as synaptophysin
24
, the pan-neuronal marker protein gene product 9.5 (PGP9.5, 130
also known as ubiquitin C-terminal hydrolase L1 (UCHL-1)) and neuron-specific enolase 131
(NSE)
25,26
, which confirm the homogenous and neuronal origin (Fig. 2f; Extended Data 132

Citations
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TL;DR: In this article, the International Parkinson Disease and Movement Disorders society (MDS) diagnostic criteria against a gold-standard expert clinical diagnosis and to compare concordance/accuracy of the MDS criteria to 1988 United Kingdom brain bank criteria were calculated.
Abstract: Objective: To validate the International Parkinson Disease and Movement Disorders society (MDS) diagnostic criteria against a gold-standard expert clinical diagnosis and to compare concordance/accuracy of the MDS criteria to 1988 United Kingdom brain bank criteria. Background: In 2015, the MDS published the new clinical diagnostic criteria for Parkinson’s disease (PD). These criteria aimed to codify/reproduce the expert clinical diagnostic process, to help standardize diagnosis in research and clinical settings. Their accuracy compared to expert clinical diagnosis has not been tested. Design/Methods: From 8 centers, we recruited 626 patients with parkinsonism (434 with PD and 192 with other causes, diagnosed by an expert treating physician). A second, less experienced neurologist evaluated the presence/absence of each individual item from the diagnostic criteria. The overall accuracy/concordance rate, sensitivity, and specificity of diagnostic criteria were calculated. Results: Of 434 patients diagnosed with PD, 94.5% met MDS criteria for probable PD (i.e. a 5.5% false-negative rate). Of 192 non-PD patients, 88.5% were identified as non-PD by the criteria (i.e. a 11.5% false-positive rate). The overall accuracy for probable PD was 92.6%. For the clinically-established PD category, 59.3% of PD patients and only 1.6% of non-PD patients met MDS criteria. Compared to MDS probable PD criteria, the UK brain bank criteria had significantly lower sensitivity (89.2%, p=0.008), specificity (79.2%, p=0.018), and overall accuracy (86.4%, p Conclusions: The MDS criteria demonstrated high sensitivity and specificity compared to gold-standard expert diagnosis. To meet the unmet gap of specific diagnostic criteria for early PD, we suggest additional ‘Clinically-Established Early PD’ criteria to be used for clinical trials of early PD. Study Supported by: Michael J. Fox Foundation Disclosure: Dr. Postuma has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biotie, Roche/Prothena, Teva Neurosciences, Jazz Pharmaceuticals, Novartis Canada, Theranexus, GE HealthCare, . Dr. Poewe has nothing to disclose. Dr. Litvan has received personal compensation for serving onthe scientific steering committee of the Biotie/Parkinson Study Group clinical trial Dr. Lewis has nothing to disclose. Dr. Lang has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Abbvie, Acorda, Avanir Pharmaceuticals, Biogen, Bristol Myers Squibb, Sun Pharma, Cipla, Intekrin, Merck, Medichem, Medtronic, Teva, UCB, and Sunovion, . Dr. Halliday has nothing to disclose. Dr. Goetz has nothing to disclose. Dr. Chan has nothing to disclose. Dr. Slow has nothing to disclose. Dr. Seppi has nothing to disclose. Dr. Schaeffer has nothing to disclose. Dr. Berg has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with UCB Pharma GmbH, Lundbeck, Prexton Therapeutics, GE-Healthcare. Dr. Rios Romenets has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with NIA, Genentech/Roche. Dr. Rios Romenets has received research support from NIA, Genentech/Roche. Dr. Mi has nothing to disclose. Dr. Maetzler has nothing to disclose. Dr. Li has nothing to disclose. Dr. Heim has nothing to disclose. Dr. Bledsoe has nothing to disclose.

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TL;DR: Zhang et al. as discussed by the authors explored PD immune infiltration patterns and identified novel immune-related diagnostic biomarkers by using weighted gene co-expression network analysis (WGCNA) to explore the key module most significantly associated with PD; the intersection of DEGs and the key modules in WGCNA were considered common genes (CGs).
Abstract: Background Parkinson’s disease (PD) is Pengfei Zhang Liwen Zhao Pengfei Zhang Liwen Zhao a common neurological disorder involving a complex relationship with immune infiltration. Therefore, we aimed to explore PD immune infiltration patterns and identify novel immune-related diagnostic biomarkers. Materials and methods Three substantia nigra expression microarray datasets were integrated with elimination of batch effects. Differentially expressed genes (DEGs) were screened using the “limma” package, and functional enrichment was analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to explore the key module most significantly associated with PD; the intersection of DEGs and the key module in WGCNA were considered common genes (CGs). The CG protein–protein interaction (PPI) network was constructed to identify candidate hub genes by cytoscape. Candidate hub genes were verified by another two datasets. Receiver operating characteristic curve analysis was used to evaluate the hub gene diagnostic ability, with further gene set enrichment analysis (GSEA). The immune infiltration level was evaluated by ssGSEA and CIBERSORT methods. Spearman correlation analysis was used to evaluate the hub genes association with immune cells. Finally, a nomogram model and microRNA-TF-mRNA network were constructed based on immune-related biomarkers. Results A total of 263 CGs were identified by the intersection of 319 DEGs and 1539 genes in the key turquoise module. Eleven candidate hub genes were screened by the R package “UpSet.” We verified the candidate hub genes based on two validation sets and identified six (SYT1, NEFM, NEFL, SNAP25, GAP43, and GRIA1) that distinguish the PD group from healthy controls. Both CIBERSORT and ssGSEA revealed a significantly increased proportion of neutrophils in the PD group. Correlation between immune cells and hub genes showed SYT1, NEFM, GAP43, and GRIA1 to be significantly related to immune cells. Moreover, the microRNA-TFs-mRNA network revealed that the microRNA-92a family targets all four immune-related genes in PD pathogenesis. Finally, a nomogram exhibited a reliable capability of predicting PD based on the four immune-related genes (AUC = 0.905). Conclusion By affecting immune infiltration, SYT1, NEFM, GAP43, and GRIA1, which are regulated by the microRNA-92a family, were identified as diagnostic biomarkers of PD. The correlation of these four genes with neutrophils and the microRNA-92a family in PD needs further investigation.
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