Alpha-Synuclein Autoimmune Decline in Prodromal Multiple System Atrophy and Parkinson’s Disease

Multiple-system trophy (MSA) and Parkinson’s Disease (PD) are both progressive, neurodegenerative diseases characterized by neuropathological deposition of aggregated alpha-synuclein (αSyn). The causes behind this aggregation are still unknown. We have reported aberrancies in MSA and PD patients in naturally occurring autoantibodies (nAbs) against αSyn (anti-αSyn-nAbs), which are important partakers in anti-aggregatory processes, immune-mediated clearance, and anti-inflammatory functions. To elaborate further on the timeline of autoimmune aberrancies towards αSyn, we investigated here the Immunoglobulin (Ig) affinity profile and subclass composition (IgG-total, IgG1-4 and IgM) of anti-αSyn-nAbs in serum samples from prodromal (p) phases of MSA and PD. Using an electrochemiluminescence competition immunoassay, we confirmed that the repertoire of high-affinity anti-αSyn-nAbs is significantly reduced in pMSA and pPD. Further, we demonstrated that pPD had increased anti-αSyn IgG-total levels compared to pMSA and controls, concordant with increased anti-αSyn IgG1 levels in pPD. Anti-αSyn IgG2 and IgG4 levels were reduced in pMSA and pPD compared with controls, whereas anti-αSyn IgG3 levels were reduced in pMSA compared to pPD and controls. The results indicate that the impaired reactivity towards αSyn occurs prior to disease onset. The apparent lack of high-affinity anti-αSyn nAbs may result in reduced clearance of αSyn, leading to aggregation of the protein. Thus, this study provides novel insights into possible causes behind the pathogenesis in synucleinopathies such as MSA and PD.


Introduction
The multiple-system atrophy (MSA) and Parkinson's disease (PD) are both progressive, neurodegenerative disorders characterized by abnormal misfolding and depositions of alpha-synuclein (αSyn) into neurons in PD, and into oligodendrocytes in MSA [1,2]. For this reason, they are defined as synucleinopathies, a group of diseases characterized by pathological αSyn aggregates in brain and peripheral neuronal cells, which also include dementia with Lewy bodies (DLB) and the rarer pure autonomic failure (PAF) [3]. There is accumulating evidence indicating that αSyn deposition not only occurs in the brain but to a high degree also in peripheral organs. This is shown by increased phosphorylation of αSyn at Serine-129 αSyn in skin samples [4,5], αSyn accumulation in the gut [6][7][8], as well as a generalized whole-body αSyn-seeding capability in MSA and PD [9][10][11]. Remarkably, αSyn can also be detected in different body fluids such as blood, cerebrospinal fluid, saliva, and as shown most recently in tears [12][13][14], which are body compartments accessible to the immune system. Synucleinopathies can thereby be considered multisystem disorders, substantiating the hypothesis that the αSyn pathology spreading from peripheral organs to the brain may be a critical feature at the prodromal phases before the classical, motor systems get manifested.
Naturally occurring autoantibodies (nAbs), mainly immunoglobulin (Ig) G and IgM isotypes, comprise an important part of the Ig repertoire from the innate immune system. nAbs have protective roles in maintaining protein homeostasis via a T-cell-independent manner [15,16]. As shown in pre-clinical models, anti-αSyn nAbs isolated from intravenous Ig (IVIg) confer protective properties [17], presenting highly diverse binding profiles to monomeric, oligomeric, and fibrillary structures of αSyn [17]. Furthermore, specific nAbs produced from single αSyn clonotypes from healthy individuals also display protective effects [18]. In humans, we and others have evaluated the IgG repertoire of αSyn reactive nAbs in PD and MSA [19][20][21][22], showing specifically in PD a tendency to increased total IgG anti-αSyn nAbs levels, particular in early disease as also reviewed by Scott et al. 2018 [22]. The complexity in αSyn autoimmunity further expands, since the total IgG anti-αSyn nAbs compartment consists of four subclasses, IgG1-4, each of which have different biological functions [23]. We have previously found several aberrancies in the four IgG subclasses and IgM, both in plasma and CSF, which is suggestive of highly and perhaps changing immuno-αSyn interactions and responses. Most importantly, when looking at the nAbs affinity, we found a decline in the high-affinity repertoire of anti-αSyn nAbs in PD and MSA patients, as shown both for plasma [24] and CSF [21]. The progressive nature of synucleinopathies and previous reports of phenoconversion from prodromal syndromes such as idiopathic REM-sleep behavior disorder (iRBD) [25] to synucleinopathic disorders serve as evidence that pathological events occur years prior to symptoms onset. It is our belief that this αSyn-specific immune decline may have a pathological effect on αSyn homeostasis and impair the clearance of αSyn toxic species and for that reason, we hypothesize that the reduction of high-affinity anti-αSyn-nAbs occurs years prior to disease onset. The aim of this study was therefore to evaluate high-affinity anti-αSyn nAbs in serum samples taken from PD and MSA patients up to 12 years before diagnosis. A reduction of high-affinity anti-αSyn-nAbs in the prodromal phases advocates for immunization strategies already administrated according to prodromal symptoms/phases.

Affinity Measurement of Anti-αSyn nAbs in pMSA and pPD
To measure the relative affinity of anti-αSyn IgG nAbs in serum, we adapted our previously established competitive ELISA assay [21,24] to the ultrasensitive Meso Scale Discovery (MSD) platform. The anti-αSyn binding profiles were firstly assessed using randomly chosen serum pooled samples of 10 pMSA and 10 pPD patients, and 10 controls. We observed noticeable differences in the binding profiles between control, and pMSA and pPD patients ( Figure 1A). The double sigmoid profile divides the anti-αSyn nAbs into two distinct subsets; the low-affinity anti-αSyn nAbs are revealed in the presence of high concentrations of αSyn monomers (25-200 nM), and the high-affinity nAbs are revealed in the presence of low concentrations of αSyn monomers (1-25 nM). Based on the competition curve profile, we selected four different concentrations of αSyn to measure the relative affinity of anti-αSyn nAbs (high-affinity profile: 2 nM and 12.5 nM αSyn; low-affinity profile: 50 nM and 200 nM αSyn) in the individual serum samples from 59 pMSA and 82 pPD patients, and 67 controls. The repertoires of high-affinity nAbs were significantly different at 12.5 nM ( Figure 1B,E) and 2 nM ( Figure 1B,F) between controls and pMSA (12.5 nM: p = 0.004, 2 nM: p = 0.011) and pPD (12.5 nM: p = 0.020; 2 nM: p < 0.001), respectively. Comparing the groups separated based on time prior to diagnosis (0-4 years and >4 years prior to diagnosis), we observed a significant reduction in anti-αSyn nAbs in pMSA at 12 nM (p = 0.043) and 2 nM (p = 0.027) 0-4 years prior to diagnosis compared to controls. In pPD we observed a reduction at 12 nM 0-4 years prior to diagnosis (p = 0.017) and a reduction at 2 nM in pPD at >4 years prior (p = 0.004) and 0-4 years prior (p = 0.004) (G-J) shows the data from (C-F) for individual serum samples from pMSA and pPD divided into two prodromal age stages (0-4 years and > 4 years prior to diagnosis), Pearson's correlation of prodromal age, and the high-affinity nAbs at 2 nM in pMSA patients (K). All data are presented as "% of max binding" of anti-αSyn nAbs calculated as described in Section 4.5. Differences between groups were tested using multiple linear regression modeling including age and sex as confounding variables. Graphs (C-J) are presented as truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Anti-αSyn IgG Subclasses and IgM nAbs in pMSA and pPD
Given that different antibody IgG isotypes (IgG-total, IgG1-4) and IgM carry out different functions in the immune system, we further aimed to explore the autoimmune reactivity towards αSyn in the prodromal phases of MSA and PD. We observed a significant increase of total IgG reactivity towards αSyn in pPD compared to pMSA (p = 0.001) and controls (p = 0.002) (Figure 2A). This increase was traced down to increased anti-αSyn IgG1 nAbs in pPD compared to both pMSA (p = 0.018) and controls (p = 0.017) ( Figure 2B). Interestingly, we observed similar patterns with reduced nAb levels in pMSA and pPD (G-J) shows the data from (C-F) for individual serum samples from pMSA and pPD divided into two prodromal age stages (0-4 years and > 4 years prior to diagnosis), Pearson's correlation of prodromal age, and the high-affinity nAbs at 2 nM in pMSA patients (K). All data are presented as "% of max binding" of anti-αSyn nAbs calculated as described in Section 4.5. Differences between groups were tested using multiple linear regression modeling including age and sex as confounding variables. Graphs (C-J) are presented as truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Anti-αSyn IgG Subclasses and IgM nAbs in pMSA and pPD
Given that different antibody IgG isotypes (IgG-total, IgG1-4) and IgM carry out different functions in the immune system, we further aimed to explore the autoimmune reactivity towards αSyn in the prodromal phases of MSA and PD. We observed a significant increase of total IgG reactivity towards αSyn in pPD compared to pMSA (p = 0.001) and controls (p = 0.002) (Figure 2A). This increase was traced down to increased anti-αSyn IgG1 nAbs in pPD compared to both pMSA (p = 0.018) and controls (p = 0.017) ( Figure 2B). Interestingly, we observed similar patterns with reduced nAb levels in pMSA and pPD compared to controls in the anti-αSyn IgG2 (pMSA: p < 0.001, pPD: p < 0.001), the anti-αSyn IgG3 (pMSA: p < 0.001, pPD: p < 0.001) and the anti-αSyn IgG4 (pMSA: p < 0.001, pPD: p < 0.001) immune compartment ( Figure 2C-E). The reductions in relative levels of anti-αSyn IgG2, IgG3, and IgG4 were found regardless of prodromal age stage (0-4 years and <4 years) (Table S3 and Figure S1). We did observe a significant difference in anti-αSyn IgM nAbs, however, the multiple comparison test did not identify differences between groups ( Figure 2F). compared to controls in the anti-αSyn IgG2 (pMSA: p < 0.001, pPD: p < 0.001), the anti-αSyn IgG3 (pMSA: p < 0.001, pPD: p < 0.001) and the anti-αSyn IgG4 (pMSA: p < 0.001, pPD: p < 0.001) immune compartment ( Figure 2C-E). The reductions in relative levels of anti-αSyn IgG2, IgG3, and IgG4 were found regardless of prodromal age stage (0-4 years and <4 years) (Table S3 and Figure S1). We did observe a significant difference in anti-αSyn IgM nAbs, however, the multiple comparison test did not identify differences between groups ( Figure 2F).

Figure 2.
Serum anti-αSyn IgG-total, IgG subclasses, and IgM nAbs. The graphs represent relative levels of anti-αSyn (A); IgG-total and IgG1-4 (B-E); and IgM (F) nAbs in individual pMSA (n = 59), pPD (n = 82) and control (n = 67) serum samples. Data are presented as relative optical densities normalized to standard curve using anti-αSyn monoclonal antibody. Differences between groups were tested using multiple linear regression modeling including age and sex as confounding variables. Graphs are presented as truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Total αSyn Levels in pMSA and pPD
Total amounts of serum αSyn were measured by MSD commercial assay. Interestingly, we observed an increased amount of total αSyn in pPD compared to pMSA (p = Figure 2. Serum anti-αSyn IgG-total, IgG subclasses, and IgM nAbs. The graphs represent relative levels of anti-αSyn (A); IgG-total and IgG1-4 (B-E); and IgM (F) nAbs in individual pMSA (n = 59), pPD (n = 82) and control (n = 67) serum samples. Data are presented as relative optical densities normalized to standard curve using anti-αSyn monoclonal antibody. Differences between groups were tested using multiple linear regression modeling including age and sex as confounding variables. Graphs are presented as truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Total αSyn Levels in pMSA and pPD
Total amounts of serum αSyn were measured by MSD commercial assay. Interestingly, we observed an increased amount of total αSyn in pPD compared to pMSA (p = 0.004) and controls (p < 0.001) ( Figure 3A). The significant increase was secluded to >4 years prior to diagnosis compared to both pMSA (p = 0.004) and controls (p < 0.001).
Int. J. Mol. Sci. 2022, 23, x FOR PEER REVIEW 6 o 0.004) and controls (p < 0.001) ( Figure 3A). The significant increase was secluded to years prior to diagnosis compared to both pMSA (p = 0.004) and controls (p < 0.001). . Differences between groups were tested using multiple li regression modeling including age and sex as confounding variables. Graphs are represente truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Discussion
This is the first study to report aberrancies in the anti-αSyn nAb compartment in p dromal stages of MSA and PD. We previously reported similar aberrancies in anti-α nAbs in these two synucleinopathies as part of the disease progression in diagnosed tients [21,24]. Firstly, here we report both low-affinity and high-affinity repertoires of a αSyn nAbs in the serum of controls as well as prodromal MSA and PD cases, and as s for diagnosed patients [21,24], the high-affinity anti-αSyn nAb repertoire was significa reduced in pMSA and pPD ( Figure 1). In pMSA, the reduction was found predomina close to disease onset (0-4 years), whereas in pPD this decline was observed at ear prodromal stages (>4 years). Secondly, we observed that pPD had increased relative le of anti-αSyn IgG-total nAbs, very likely due to the increase in anti-αSyn IgG1 frac (Figure 2), and there was a relative reduction of anti-αSyn IgG2, IgG3, and IgG4 level both pMSA and pPD compared to healthy controls. This is surprising, as it is opposit that observed in already diagnosed MSA and PD patients [20,21].
Anti-αSyn nAbs have extensively been evaluated in blood plasma and to some ex also in cerebrospinal fluid in PD, MSA, and PD with dementia (PDD). A thorough systemic meta-analysis by Scott et al. 2018 [22] found evidence for an increase in α nAbs in PD patients particularly at early stages (<5.9 years) [19,[26][27][28][29], which is in with our results showing increases in anti-αSyn total IgG levels nAbs already in the p dromal phase of PD. Notably, the IgG reactivity is driven by the IgG1 subclass respon IgG1 is the most abundant IgG subclass as it is considered to be a classical mediator, b ing to every human Fc gamma receptor (FcγRs) on immune cells, leading to pro-infl matory cytokine production, antibody-mediated phagocytosis, and C1q complement tivation [30,31]. We speculate that the increase in anti-αSyn nAb responses is triggered a higher load of peripheral αSyn in these patients, however, as the high-affinity antib pool is reduced, this increased IgG1 production may be characterized by a lower affi . Differences between groups were tested using multiple linear regression modeling including age and sex as confounding variables. Graphs are represented as truncated violin plots with median (bold lines) and 25% quantiles (thin lines).

Discussion
This is the first study to report aberrancies in the anti-αSyn nAb compartment in prodromal stages of MSA and PD. We previously reported similar aberrancies in anti-αSyn nAbs in these two synucleinopathies as part of the disease progression in diagnosed patients [21,24]. Firstly, here we report both low-affinity and high-affinity repertoires of anti-αSyn nAbs in the serum of controls as well as prodromal MSA and PD cases, and as seen for diagnosed patients [21,24], the high-affinity anti-αSyn nAb repertoire was significantly reduced in pMSA and pPD ( Figure 1). In pMSA, the reduction was found predominantly close to disease onset (0-4 years), whereas in pPD this decline was observed at earlier prodromal stages (>4 years). Secondly, we observed that pPD had increased relative levels of anti-αSyn IgG-total nAbs, very likely due to the increase in anti-αSyn IgG1 fraction (Figure 2), and there was a relative reduction of anti-αSyn IgG2, IgG3, and IgG4 levels in both pMSA and pPD compared to healthy controls. This is surprising, as it is opposite to that observed in already diagnosed MSA and PD patients [20,21].
Anti-αSyn nAbs have extensively been evaluated in blood plasma and to some extent also in cerebrospinal fluid in PD, MSA, and PD with dementia (PDD). A thorough and systemic meta-analysis by Scott et al. 2018 [22] found evidence for an increase in αSyn nAbs in PD patients particularly at early stages (<5.9 years) [19,[26][27][28][29], which is in line with our results showing increases in anti-αSyn total IgG levels nAbs already in the prodromal phase of PD. Notably, the IgG reactivity is driven by the IgG1 subclass responses. IgG1 is the most abundant IgG subclass as it is considered to be a classical mediator, binding to every human Fc gamma receptor (FcγRs) on immune cells, leading to pro-inflammatory cytokine production, antibody-mediated phagocytosis, and C1q complement activation [30,31]. We speculate that the increase in anti-αSyn nAb responses is triggered by a higher load of peripheral αSyn in these patients, however, as the high-affinity antibody pool is reduced, this increased IgG1 production may be characterized by a lower affinity profile, resulting in diminished capacity for immune clearance leading to αSyn aggregation. In support of this, it was recently shown that anti-αSyn nAbs present in healthy individuals not only recognize different αSyn structures [32], but also inhibit the aggregation of αSyn by altering fibril formation in cell culture [33]. Further, anti-αSyn nAbs isolated from IVIg has shown rescuing effects in both low-and high-dose paradigms in the A53T transgenic PD mice model [17].
When looking at the IgGs subclasses, we observed decreases in anti-αSyn IgG2, IgG3, and IgG4 nAbs levels in PD and MSA compared to control individuals. These subclassspecific aberrancies prior to disease may suggest a compartmentalization discrepancy in the antibody-producing B cells. Supporting this, several studies have investigated B cells [34][35][36], most recently, in a single-cell study in PD patients, where they discovered a significant decrease in the naive B cell population, an increase in the memory B cells, and a higher frequency in immunoglobulin class switching in PD patients [37]. They furthermore showed upregulated MHC class II gene and AP-1 transcription factor expression, indicating an increased antigen-presentation in PD patients [37]. Furthermore, αSyn-specific T-cell reactivity in PD patients prior to diagnosis and around motor symptom initiation that decreases during disease progression, supports the idea that there are αSyn-specific antigen responses in early PD [38]. There is evidence that both the humoral and cell-mediated (adaptive) immunity compartments are implicated in prodromal and early PD stages [39] and likely also for MSA [40,41]. To what extent B-cells populations are also dysregulated in MSA must be investigated. An additional interesting tactic would be using the results from this study and others, not only for biomarker potential, but also in the debate regarding passive immunization candidates for synucleinopathies. Most candidates are of the IgG1 subclass [42]. The present results and previous reports show that especially MSA have increased IgG1 anti-αSyn nAbs in plasma and IgG1 and IgG3 in CSF [20,21]. The increments of these specific possibly pro-inflammatory nAbs could contribute to the ongoing inflammation, proposed to be initiated by the interplay between the immune system and aSyn [43]. The rationale behind choosing IgG4 for the ABBV-0805 candidate relies on the hypothesis to reduce inflammation by stabilizing the IgG4 molecule, which lacks the complement-binding functions and has a weaker Fcγ receptor interaction, resulting in less pro-inflammatory responses, which is beneficial for long-term immunization [44].
The pathological hallmarks of MSA and PD are the abnormal accumulation of the protein αSyn [1,2], but, on the other hand, αSyn is also a crucial protein involved in vesicle transport [45] and a key component of the immune system, playing a critical role in the development of both B cells and T cells, regulating immune function, as well as influencing microglia [46][47][48][49]. Hence, deregulation of αSyn levels may not only have a pathological effect reflected in the inclusions in neurons and oligodendrocytes, but also directly affect immune system regulation, which may influence the production of anti-αSyn nAbs.
Based on our results, we hypothesize that the immune clearance mechanism in MSA and PD is under pressure, probably already many years before disease onset, rendering subclinical pathological immune changes before symptomatic manifestations (Figure 4). We previously found the same observation in CSF samples of MSA and PD patients [21], which is suggestive that the autoimmune decline is not restricted only to the lymphatic system but also apparent in the CSF and possibly also in the brain. Hence, we believe that the autoimmune aberrancies are a whole-body disease phenomenon. That being said, whether the decline in CSF is present in the prodromal phases and whether the decline is apparent in the brain following disease progression and in the prodromal phases needs to be further elucidated. The important question that remains is if the reduction of highaffinity anti-αSyn-nAbs is causative to the toxic accumulation of αSyn or if the increasing load of αSyn applies a pressure to the immune system, tipping the balance towards an exhaustion of the immune response? slower autoimmune decline, extended over a longer prodromal period ( Figure 1J). There are reports corroborating our findings and suggesting that the median time to phenoconversion from iRBD is 8.0 years for PD, with an overall phenoconversion rate of 6.25% per year and a suggested shorter period for MSA, with 16 patients eventually developing MSA after a mean follow-up time of 4.5 years [50]. Age at diagnosis of iRBD was 60 ± 8 years, and age at conversion to MSA 64 ± 9 years, with a time from iRBD diagnosis to conversion of 4 ± 3 years. Prodromal MSA and PD evidence, however, is still limited. There are some limitations to discuss in this study. Although the sample size fulfills the recommended criteria for these types of studies [22], we must consider the biological variations, which manifested in relatively large distribution variations in our samples. Another limitation is the time-gap there may be between the clinical onset vs. definite diagnosis of particularly MSA patients, but also in some PD individuals, as these diseases may be masqueraded by other diseases at early stages [51]. So, we cannot rule out that some patient samples were taken when the patient already had shown the first clinical signs even though the final diagnosis was not given.
The strength of this study relies in the unique cohort from the Danish National Biobank, which provides us with access to samples obtained from all individuals in contact to the primary health care service, which are stored in a biobank for future research. This is linked to the Danish National Patient Register, where all diagnoses are registered. These results are explorative, and the next step will be to validate levels of anti-αSyn antibodies in a longitudinal study. Our study also brings up an important aspect of the length of the prodromal phases in both MSA and PD. Given the linear association ( Figure 1K), it seems that the course of anti-αSyn specific autoimmune decline in the prodromal phase of MSA is shorter, about 4 years ( Figure 1J), yet more progressive in comparison to pPD, which seems to have a slower autoimmune decline, extended over a longer prodromal period ( Figure 1J). There are reports corroborating our findings and suggesting that the median time to phenoconversion from iRBD is 8.0 years for PD, with an overall phenoconversion rate of 6.25% per year and a suggested shorter period for MSA, with 16 patients eventually developing MSA after a mean follow-up time of 4.5 years [50]. Age at diagnosis of iRBD was 60 ± 8 years, and age at conversion to MSA 64 ± 9 years, with a time from iRBD diagnosis to conversion of 4 ± 3 years. Prodromal MSA and PD evidence, however, is still limited.
There are some limitations to discuss in this study. Although the sample size fulfills the recommended criteria for these types of studies [22], we must consider the biological variations, which manifested in relatively large distribution variations in our samples. Another limitation is the time-gap there may be between the clinical onset vs. definite diagnosis of particularly MSA patients, but also in some PD individuals, as these diseases may be masqueraded by other diseases at early stages [51]. So, we cannot rule out that some patient samples were taken when the patient already had shown the first clinical signs even though the final diagnosis was not given.
The strength of this study relies in the unique cohort from the Danish National Biobank, which provides us with access to samples obtained from all individuals in contact to the primary health care service, which are stored in a biobank for future research. This is linked to the Danish National Patient Register, where all diagnoses are registered. These results are explorative, and the next step will be to validate levels of anti-αSyn antibodies in a longitudinal study.

Patient Samples
A total of 208 serum samples were retrieved from the Danish National Biobank, Statens Serum Institute (SSI), Copenhagen, DK, which contains more than 25 million samples collected by the Danish public health sector and connected to the Danish National Patient Register. pMSA diagnosis was identified as: ICD-9 code 333 up to 1998 and with ICD-10 codes: G23 and G90.3 from 1999 to present. pPD was identified as: ICD-9 code 332 code up to 1998 and ICD-10 code G20 code from 1999 to present. The control samples were randomly chosen based on general background population cohort on negative diagnosis criteria in the following: Infectious and parasitic diseases: ICD-10: A00-B99; ICD-8: 000-136; diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism: ICD10: D50-D89; ICD8: 280-289; diabetes: IDC10: E10-E11; ICD8: 249-250; diseases of the nervous system: ICD10: G00-G99; ICD8 320-358; diseases of the respiratory system: ICD10 J00-J99; ICD8 460-519; diseases of the skin and subcutaneous tissue: ICD10 L00-L99; ICD8 680-709; and diseases of the musculoskeletal system and connective tissue: ICD10 M00-M99; ICD8 710-738. We analyzed 59 pMSA, 82 pPD, and 67 healthy controls ( Table 1). The project was approved by the Regional ethical committee (j.no.: H-15016232) and the Danish data protection agency (j.no.: P-2020-937). All demographic data were blinded to the experimental worker and first disclosed at analysis point.

αSyn Affinity Measurement Using Electrochemiluminescence Assay
The evaluation of binding affinity was carried out as previously reported [24]

αSyn Measurement Using MSD Platform
Total αSyn in serum samples was measured using the commercially available U-PLEX ® Human αSyn kit (MSD ® Multi-Array Assay System, Meso Scale Diagnostics, LLC, Rockville, MD, USA, cat#K151WKK) following the manufacturer's instructions. Prior to measurements, we optimized the assay to determine serum concentrations. Serum samples were diluted to 1:50 in Diluent 49 provided by MSD. The plates were measured at the MSD Sector Imager S600 (Meso Scale Diagnostics, LLC, Rockville, MD, USA).

Statistics
The data were analyzed using R v. 3.5.2 [52] and GraphPad Prism v. 9.3.1 (Graph-Pad Software Inc., San Diego, CA, USA). Differences in demographics were tested using Fischer's exact test for sex, Kruskall-Wallis test with Dunn's multiple comparison test for age at sample withdrawal, and Mann-Whitney U test for Age at diagnosis and prodromal age (years prior to diagnosis). Outliers were excluded using the ROUT test with false discovery rate, Q, set at 1%. The percentage of maximum binding was calculated as following: % of max binding = 100 − (OD read out − OD 2000nM competition )/(OD 0nM competition − OD 2000nM competition ) × 100. For group comparison, we used multiple linear regression including age and sex as possible confounding variables using Anova from the car package [53]. For multiple comparisons using Tukey's range test including confounding variables, the glht and mcp functions from the multcomp package [54] were applied. To determine associations with prodromal age and measured outcomes, Pearson's correlation was used. Differences were considered significant at p < 0.05.

Conclusions
In conclusion, this study revealed that the decline in repertoire of high-affinity anti-αSyn nAbs in MSA and PD patients appears to be present already in the prodromal phases of MSA and PD. Furthermore, our study supports the supposition that the anti-αSyn IgG nAb responses in PD are dominant at early disease stages. This can be a classical IgG1 response to the increased serum concentration of circulating αSyn protein. These results further frame how immunopathogenesis may be a contributing factor to the etiology of synucleinopathies and thereby advocates for effective, passive immunizations already in prodromal or/and early stages of synucleinopathies.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijms23126554/s1. Author Contributions: J.F. and T.B.: Designed and conceptualized the study and played major roles in the acquisition of data, analysis of data, and drafted the manuscript for intellectual content. E.B.: Major role in acquisition of data, analysis of data, and revised the manuscript for intellectual content. T.B, B.P., and S.A. interpreted the data and drafted a significant portion of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement: This study was approved by the regional ethical committee of the Capital Region of Denmark (H-15016232) and the Data Protection Agency for RegionH (P-2020-937).

Informed Consent Statement: Not applicable.
Data Availability Statement: Data can be accessed upon reasonable request.