Oligodendroglial somatic SNCA copy number gains are associated with inclusions and disease onset in multiple system atrophy

Oligodendroglial somatic SNCA copy number gains are associated with inclusions and disease onset in multiple system atrophy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Oligodendroglial somatic SNCA copy number gains are associated with inclusions and disease onset in multiple system atrophy Caoimhe Morley, Ester Kalef-Ezra, Diego Perez-Rodriguez, Zane Jaunmuktane, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8701777/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Multiple system atrophy (MSA) is a rapidly progressive synucleinopathy of unknown aetiology with neuronal and oligodendroglial α-synuclein inclusions. We previously reported somatic copy number variants (CNVs), specifically gains, of SNCA (encoding α-synuclein) in MSA brains. Here, we expand on this work by combining fluorescent in situ hybridisation for SNCA on isolated nuclei with α-synuclein and SOX10 immunofluorescence, to assess oligodendrocyte-specific SNCA gains and losses, and their relationship with inclusions across differentially affected regions in two MSA subtypes: striatonigral degeneration (SND) and olivopontocerebellar atrophy (OPCA). Analysis of 13 SND, 12 OPCA, and 15 control brains demonstrated significantly higher somatic SNCA CNVs, both gains and losses, in MSA oligodendrocytes compared with controls (gains: 6.3% vs 2.0%; losses: 12.5% vs 7.4%, p < 0.0001 for both). Oligodendrocyte SNCA gains were high in the preferentially affected regions (putamen in SND, cerebellum in OPCA), where they were associated with a two-fold increased relative risk of α-synuclein inclusions in the same cell (p < 0.0001). Higher gain burden correlated with earlier disease onset (rho = -0.45, p = 0.03). Oligodendrocyte SNCA losses, conversely, showed less regional predilection, limited association with inclusions, and no correlation with onset age. As double strand DNA breaks have been reported in Lewy body diseases, and may cause deletions, we used immunofluorescence for γH2AX to explore their prevalence in MSA in a subset of experiments. The proportion of γH2AX-positive cells was significantly higher in MSA than controls, both overall (6.0% vs 2.2%, p = 0.049) and in oligodendrocytes (14.4% vs 5.5%, p = 0.02), and also in inclusion-bearing cells (22.2% vs 14.9%, p = 0.02). These findings define the oligodendrocyte-specific patterns of somatic SNCA CNVs in MSA, support a role for gains in MSA pathogenesis, and demonstrate the presence of SNCA losses and DNA double strand breaks which require further investigation. Multiple system atrophy alpha-synuclein somatic mutation CNV mosaicism SNCA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Multiple system atrophy (MSA) is a rare synucleinopathy characterised by varying combinations of autonomic failure, parkinsonism, and cerebellar ataxia, and a rapidly progressive disease course [9]. Although neuronal α-synuclein aggregation is a shared hallmark across all synucleinopathies, MSA is uniquely defined by the additional presence of glial cytoplasmic inclusions (GCIs) within oligodendrocytes [13, 59]. Neuronal inclusions, including neuronal cytoplasmic and neuronal nuclear inclusions, are distinct from the Lewy bodies (LBs) and Lewy neurites that characterise Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB), which are comparatively rare in MSA [22, 28, 55]. MSA diverges into distinct pathological subtypes, including striatonigral degeneration (SND), olivopontocerebellar atrophy (OPCA), and a mixed subtype. Despite these well-defined pathological patterns, the mechanisms that render oligodendrocytes and specific brain regions selectively vulnerable remain unclear and represent a critical gap to bridge in our understanding of MSA pathogenesis and phenotypic heterogeneity. In contrast to PD and DLB, where genetic studies have identified multiple Mendelian and risk loci implicating diverse biological pathways, the aetiology of MSA is unknown [27]. MSA shows no clear familial aggregation and very low heritability (< 7%) [10] and to date no major reproducible inherited genetic risk factors have been established [7, 57]. Nevertheless, chronic elevation of α-synuclein is sufficient to drive its aggregation, as demonstrated in PD cases with germline SNCA multiplications [53]. These cases highlight the strong dosage sensitivity of α-synuclein: SNCA duplications typically lead to later-onset parkinsonism with reduced penetrance, whereas triplications cause early-onset, rapidly progressive disease [18]. Some individuals with SNCA multiplications also exhibit mixed neuronal and glial pathology, suggesting that excess α-synuclein expression can also be detrimental to oligodendrocytes [53, 65]. Experimental models further support this, as oligodendrocyte-specific overexpression of human α-synuclein in mice generates GCI-like pathology, demyelination and neuroinflammation, with higher expression producing earlier and more severe neurodegeneration [52, 63]. Together, these observations suggest that cell- or region-restricted increases in SNCA dosage could contribute to the pathogenesis of MSA. Somatic mutations, arising post-zygotically and resulting in genetic mosaicism within the brain, have emerged as potential contributors to neurodegenerative disease [30, 36, 43, 61]. These alterations encompass a wide range, from single nucleotide variants to large-scale copy number variants (CNVs, gains or losses) and other structural variants. Somatic mutations may result from mitotic errors or diverse types of DNA damage, including highly mutagenic double stranded DNA breaks (DSBs) [46]. DSB repair in post-mitotic cells is primarily by non-homologous end joining (NHEJ) [33] which can lead to deletions [46]. DSBs have been reported in Lewy body diseases [28, 57], but not investigated in MSA to our knowledge. We previously demonstrated through fluorescence in situ hybridisation (FISH) studies somatic CNVs, specifically gains, of SNCA (encoding α-synuclein) in substantia nigra dopaminergic neurons in PD, with the highest levels reported in two MSA cases [38]. Subsequent work detected higher levels of SNCA gains in neurons of the cingulate cortex in both PD and MSA compared to controls, and in non-neurons in MSA only [40]. More recently, we demonstrated increased levels of somatic SNCA gains in differentially affected regions in MSA subtypes, the putamen in SND and cerebellum in OPCA, with an increased relative risk for a-synuclein inclusions at the single-cell level [14]. Importantly, these studies did not establish whether SNCA gains occur in oligodendrocytes, although their level was higher in oligodendrocytes in the substantia nigra of three SND cases analysed. Moreover, none included region-matched controls from the putamen, cerebellum, and substantia nigra, precluding assessment of whether somatic SNCA gains in these regions are truly enriched in MSA. Finally, the potential role of somatic SNCA losses has been unexplored and may have distinct functional consequences. Loss of α-synuclein function is not a known driver of any neurodegenerative disease, and experimental models have produced conflicting results regarding its impact [1, 6, 23, 45]. However, aggregated α-synuclein may sequester the protein and diminish its normal physiological functions [51, 62], raising the possibility that dosage reductions could contribute to cellular vulnerability under certain conditions. Together, these observations highlight the need for a systematic, cell-type-resolved and region-matched assessment of somatic SNCA CNVs in MSA. Here, we aim to address these gaps by applying an optimised protocol combining FISH and immunofluorescence on isolated nuclear suspensions, to eliminate sectioning artefacts and reliably call copy number losses in addition to gains. We find that, in MSA, somatic SNCA gains are enriched in SOX10 + oligodendrocytes relative to controls, in subtype-specific vulnerable regions, and associate with α-synuclein inclusions at both single-cell and regional levels, consistent with a role in pathogenesis. A higher burden of oligodendrocyte SNCA gains correlates with earlier disease onset, supporting a model in which pre-existing somatic SNCA mosaicism may predispose individuals to α-synuclein aggregation. We now show, for the first time, somatic SNCA losses, which are also higher in MSA, though more broadly distributed, with less clear regional associations with inclusions and no association with age of onset. Our results provide further insights into somatic SNCA CNVs in MSA, with oligodendrocyte gains potential drivers of pathogenesis. Furthermore, we perform immunofluorescence staining of tissue sections for phosphorylated H2AX at serine 139 (γH2AX), an established DSB marker [32], which reveals increased DSBs in MSA compared to controls, notably in oligodendrocytes and in cells with α-synuclein inclusions. Materials and Methods Human fresh-frozen post-mortem brain tissue Fresh-frozen post-mortem brain samples were obtained from the Queen Square Brain Bank for Neurological Disorders in London, United Kingdom. All subjects or their next of kin had given informed consent for brain donation and use in research. Ethics approval was provided by the National Research Ethics Service (07/MRE09/72). Tissue chips and 10 µm tissue sections were obtained from three brain regions including cerebellar white matter, putamen at the level of the anterior commissure, and the substantia nigra at the level of the red nucleus or decussation of the superior cerebellar peduncle. For clarity, these are hereafter referred to as the putamen, cerebellum , and substantia nigra , respectively. This study included a total of 42 subjects: 27 with pathologically confirmed MSA (15 SND, 12 OPCA) and 15 controls (14 neurologically healthy, 1 with dystonia but normal neuropathology). A summary of experiments performed across each group and brain region are shown in Supplementary Table 1. Nuclei isolation from fresh-frozen post-mortem brain tissue Nuclear fractions were isolated from fresh-frozen tissue as previously described [21, 40, 41]. All procedures were performed at 4°C to maintain nuclei integrity. Briefly, 20–50 mg of tissue was added to 500 µL of Nuclear Isolation Medium (NIM: 25 mM KCl, 5 mM MgCl 2 , 10 mM Tris/HCL pH 8.8, 250 mM sucrose, 1X cOmplete™ EDTA-free Protease Inhibitor Cocktail (Roche, 04693132001) and 1 mM dithiothreitol. Tissue was initially homogenised using a plastic pestle (20 strokes) and supplemented with 0.1% Triton-X 100. Complete homogenisation was performed using Dounce tissue grinders with a loose and tight pestle (5–10 strokes each, Sigma-Aldrich D8938). The homogenate was centrifuged at 1000 g for 8 min at 4°C, after which the supernatant was removed. The resulting pellet was resuspended in 700 µL of 25% Iodixanol prepared using 417 µL of Optiprep™ Density Gradient Medium (60% w/v Iodixanol, Sigma-Aldrich D1556) in 500 µL of NIM and 83 µL of Optiprep Diluent for Nuclei (ODN: 150 mM KCl, 30 mM MgCl 2 , 60 mM Tris/HCl pH 8.8 and 250 mM sucrose, 1X cOmplete™ EDTA-free Protease Inhibitor Cocktail). Subsequently, the 25% Iodixanol/homogenate mixture was gently layered using a syringe onto 1 mL of 29% Iodixanol (483 µL Optiprep™ Density Gradient Medium and 517 µL ODN) to form a gradient. The tube was ultracentrifuged at 10,300 g for 20 min at 4°C. The debris layer and supernatant were discarded, leaving 50 µL of buffer above the pellet. The pellet was resuspended according to the downstream analysis (see subheading Combined Immuno-Fluorescence in situ hybridisation (Immuno-FISH)). Combined immuno-fluorescence in situ hybridisation (immuno-FISH) on isolated nuclei We used the previously published FISH protocol on tissue sections [15] with minor modifications for compatibility with isolated nuclei. The same custom-designed red 50kb SNCA probe SureFISH (Agilent G110997R-8) was used, and in a subset of experiments a green 767kb Chr 7 chromosome enumeration probe (CEP) probe (G110899G-8) was included for reference. To account for potential variability between experiments, each batch was prepared containing a mixture of MSA subtypes and Controls. Isolated nuclei were fixed with ice-cold Carnoy’s Fixative (3:1 Methanol: Acetic Acid) and incubated on a rotator disk for 1 h at 4°C. The nuclei were dropped onto an Epredia™ SuperFrost Ultra Plus Gold Adhesion slides (Epredia, 11976299) and allowed to fully evaporate. Nuclei were permeabilised using a solution of 0.005% pepsin (Roche, 10108057001) in 10 mM HCl at 37°C for 5 min. Following digestion, slides were transferred to PBS supplemented with 1 mM MgCl₂ for 5 min, then washed twice in PBS. Slides were dehydrated through an ethanol series consisting of 70%, 90%, and 100% molecular-biology grade ethanol, each for 2 min, and then air-dried for 10 min. Next, slides were treated with 70% UltraPure™ formamide (Invitrogen, 15518746) in 2X saline sodium citrate (SSC) buffer at 72°C for 2 min. A second dehydration step was performed using ice-cold ethanol solutions (70%, 90%, and 100%). FISH probe reactions were prepared according to the manufacturer’s guidelines. The FISH probe mixture was denatured at 72°C for 5 min, and 10 µL of the mixture was applied per slide. A 22 × 22 mm coverslip was mounted and sealed using Fixogum rubber cement. Hybridisation was carried out in a humidified chamber at 37°C for 48–72 h. After hybridisation, slides were immersed in 2× SSC buffer at room temperature (RT) for 10 min to allow coverslip removal. They were then washed in preheated Wash Buffer 1 (Agilent, G9401A) at 72°C for 2 min, followed by a 1 min wash in Wash Buffer 2 (Agilent, G9402A) at RT. Finally, slides were washed three times in PBS for 10 min each. For immunostaining, blocking solution was prepared with 10% goat serum in PBS with 0.2% Triton-X 100 and incubated for 1 h at RT. Primary antibody solutions were prepared in 2% goat serum and 0.2% Triton-X 100 according to the concentrations listed (see subheading Antibodies used ). All primary antibodies were incubated overnight at 4°C. Following washes, species-specific secondary antibodies were applied and incubated for 1 h at RT. Nuclei were counterstained with 1 µg/mL DAPI (4',6-diamidino-2-phenylindole) solution for 20 min. Slides were cover-slipped with Agilent Mounting Buffer (G9403A). Slides were imaged using a Leica DM6B epifluorescence microscope coupled to an ORCAII Digital CCD camera (Hamamatsu, Shizuoka, Japan) and controlled by Leica Application Suite X (Leica, Wetzlar, Germany). Z-stacks of 10 images separated by 0.5 µm stacks (5 µm depth total) using appropriate fluorescence filters were obtained with a 40X lens objective. All images were analysed blinded to the donor group and region. FISH signals were visualised using the ImageJ software v1.53t and analysed through manual counting first without the protein markers to obtain unbiased counts and then reviewed with the other colour channels. Exclusion criteria for a cell included (1) autofluorescence, as identified by overlapping signals on more than one channel, obscuring the nucleus, (2) faint, unclear or completely absent FISH signals, and (3) indistinguishable copy number status of overlapping nuclei. Immunofluorescence on fresh-frozen tissue sections Fresh-frozen tissue sections were cryosectioned at 10 µm thickness and mounted onto Superfrost Plus slides. Tissue sections were thawed for 20 min at RT and then fixed with 10% neutral-buffered formalin for 20 min at RT followed by permeabilization with 0.3% Triton-X in PBS for 60 min. A blocking solution containing 10% goat serum in 0.2% Triton-X 100 in PBS was applied for 1 hour at RT. Primary antibodies were prepared in 2% goat serum and 0.2% Triton-X 100 according to the concentrations listed (see subheading Antibodies used ) and incubated overnight at 4°C. Secondary antibodies were prepared in 2% goat serum and 0.2% Triton-X 100 and incubated for 1 h at RT. A 1X solution of TrueBlack® Lipofuscin Autofluorescence Quencher (Biotium, 23007) was prepared in 70% ethanol and was applied to each slide for 1 min. DAPI (4′,6-diamidino-2-phenylindole) was applied at a final concentration of 1 µg/mL to each slide for 20 min. Slides were mounted with ProLong™ Gold Antifade (Thermo Fisher Scientific, P36930). For immunofluorescence markers, image analysis was performed through manual counting using ImageJ software v1.53t. Individual optical Z-stacks (10 stacks at 0.5 µm intervals, corresponding to a total optical depth of 5 µm) were examined to confirm true cellular co-localisation and exclude artefacts arising from overlapping fluorescence in adjacent focal planes. Cell counts and inclusion co-localisation were performed manually within defined regions of interest using merged and single-channel images. Identical exposure and threshold settings were applied across all samples within each staining batch. Antibodies used To label oligodendrocytes, a rabbit monoclonal anti-SOX10 antibody (1:50; 0.5 µg/mL; clone SP267, Abcam, ab227680) was used. Alpha-synuclein inclusions were detected using either a mouse monoclonal antibody (1:100; 2 µg/mL; clone 211, Santa Cruz, sc-12767) or a rabbit monoclonal antibody (1:1000; 1 µg/mL; clone MJFR1, Abcam, ab13850), depending on the compatibility with co-stained markers. A mouse monoclonal anti-phospho-Histone H2AX (Ser139) antibody (1:200; 5 µg/mL; clone JBW301) was used to detect DNA DSB repair. Secondary antibodies (anti-mouse/anti-rabbit) were used conjugated to 488 and 647 fluorophores (Thermo Fisher Scientific) at 2 µg/mL (1:500). Statistics All statistical analyses were performed in RStudio v2024.12.1 unless otherwise stated. Variables were assessed for normality using the Shapiro-Wilk test, and equality of variance was assessed with Levene’s test for homogeneity of variance. Pairwise comparisons of normally distributed data were performed using the Student t-test (with Welch correction for unequal variance) or the nonparametric Mann-Whitney U test accordingly. For comparisons involving more than two groups, a one-way ANOVA for normally distributed data was used with Tukey’s HSD post-hoc correction, and the nonparametric Kruskal-Wallis was used with Dunn’s post-hoc correction. Where applicable, Bonferroni correction was applied to adjust for multiple comparisons. For normally distributed data, results are presented as the mean ± standard deviation (SD); for non-normal data or non-parametric comparisons, the median and interquartile range (IQR) are reported. Boxplots display the median and IQR, with whiskers extending to 1.5× IQR. Contingency tables were analysed using the Chi-square or Fisher’s exact test based on sample size. For correlation assessments, Spearman’s rank correlation was performed. Relative risk scores were calculated using MedCalc ( https://www.medcalc.org/en/calc/relative_risk.php ). P-values are two-tailed and, unless otherwise stated, are nominal. Results Somatic SNCA CNVs are more frequent in MSA than controls and gains are enriched in MSA oligodendrocytes To explore whether somatic SNCA CNVs are associated with inclusion-bearing cells in MSA, we performed FISH using a custom-designed SureFISH 50kb SNCA probe we previously used [14, 40] combined with immunofluorescence for SOX10, a well-established oligodendrocyte marker [42, 54], which is expressed across oligodendrocyte maturation stages [17] and α-synuclein to visualise inclusions. To characterise somatic losses of SNCA , which cannot be reliably done on tissue sections due to sectioning artefacts, all experiments were done on isolated nuclei from fresh-frozen post-mortem brain tissue (workflow depicted in Fig. 1 a). FISH on isolated nuclei allowed us to also significantly reduce the exposure time to pepsin, a protease which is known to variably digest inclusions in MSA [64], therefore allowing for better epitope preservation. We found that, in MSA, α-synuclein inclusions are well-retained in nuclear preparations due to their perinuclear and/or nuclear localisation, with no significant difference observed between levels of inclusions on sections versus nuclei as detected by immunofluorescence for the same case and region ( p = 0.31, n = 8, Supplementary Fig. 1). The final dataset included at least one brain region from 13 SND cases, 12 OPCA cases, and 15 controls. All three brain regions (putamen, cerebellum, substantia nigra) were analysed in 10 controls, 6 SND, and 7 OPCA cases. There were no statistically significant differences in mean age at death across groups (Table 1 ) (Controls: 71.3 years; SND: 67.9 years; OPCA: 64.2 years, p = 0.14) or in median post-mortem interval (PMI) (Controls: 46.6 hours; SND: 43.8 hours; OPCA: 67.5 hours, p = 0.12). Sex distribution was comparable between groups ( p = 0.83). Among MSA subtypes, there were no significant differences in mean age at disease onset (SND: 61.8 years; OPCA: 57.1 years, p = 0.14) or in disease duration (SND: 6.2 years; OPCA: 8.0 years, p = 0.11). The overall median total cell count per region from each brain was 88, and the median SOX10⁺ cell count was 46. No significant differences were observed across total cell counts (Kruskal-Wallis p = 0.46) or SOX10⁺ cell counts (Kruskal-Wallis p = 0.15) analysed across groups within brain regions (Supplementary Fig. 2). All results divided by disease status, brain region and cell type are shown in Supplementary Table 2. Indicative images of oligodendrocytes with and without CNVs and inclusions are shown in Fig. 1 b. We first quantified the percentage of SOX10⁺ cells with SNCA gains in both MSA subtypes and controls by taking the average across the regions analysed. This revealed a significant difference in the percentage of SOX10⁺ gains in MSA, where they were enriched over threefold compared to controls (6.3% vs 2.0%, p < 0.0001). SNCA gains in SOX10⁻ cells were also higher (5.7 vs 3.4%) however this was non-significant ( p = 0.07) (Fig. 1 c). We next assessed somatic SNCA losses, which were even higher than gains, and significantly increased in MSA compared to controls in both SOX10 + cells (12.5% vs 7.4%, p < 0.0001), and SOX10⁻ cells (11.1 vs 8.2%, p < 0.01). These results indicate that somatic SNCA gains and losses are both enriched in MSA, preferentially in oligodendrocytes, with less striking enrichment across SOX10⁻ cells. Table 1 Summary of donor characteristics for the immuno-FISH cohort Group n Age at death (years) PMI (hrs) Age at disease onset (years) Disease duration (years) Sex (M/F) Mean ± SD Median [IQR] Mean ± SD Median [IQR] Mean ± SD Median [IQR] Mean ± SD Median [IQR] Control 15 71.3 ± 11.2 71 [63–75] 64.1 ± 43.4 46.6 [38.6–96.5] N/A N/A N/A N/A 8 (53.3%) / 7 (46.75) SND 13 67.9 ± 8.3 67 [63–72] 49.8 ± 22.1 43.8 [36.8–53] 61.8 ± 8.0 63 [57–67] 6.2 ± 1.3 6 [5–7] 6 (46.2%) / 7 (53.8%) OPCA 12 64.2 ± 6.8 66.5 [57.8–69.2] 69.3 ± 21.1 67.5 [58.4–86] 57.1 ± 6.5 57 [52-61.5] 8.0 ± 3.3 7 [6–10] 5 (41.7%) / 7 (58.3%) p-value ANOVA p = 0.14 Kruskal-Wallis p = 0.12 Student t-test p = 0.14 Student t-test p = 0.11 Chi-square p = 0.83 Demographic and sample characteristics of control and MSA subgroups. Data are presented as mean ± SD (standard deviation) and median [interquartile range]. PMI, post-mortem interval. SND, striatonigral degeneration. OPCA, olivopontocerebellar atrophy. N/A = not applicable. Reference probe locus exhibits relative genomic stability in MSA compared to controls and also compared to SNCA To assess whether the observed SNCA CNVs reflect a locus-specific instability rather than a global genomic phenomenon, we omitted the α-synuclein staining and used a reference probe targeting chromosome 7 for most control experiments (n = 29), and a subset of MSA (n = 6) (representative images in Fig. 2 a). SOX10⁺ reference gains were rare and comparable between MSA and controls (median 0% for controls, 0.5% for MSA, adjusted p = 1), (Fig. 2 b) as were SOX10⁻ gains (median 0% for both, adjusted p = 1) (Fig. 2 c). Reference losses were higher but also showed no significant differences between MSA and controls for SOX10⁺ cells (median 3.4% vs. 3.0%, adjusted p = 1) (Fig. 2 d) or SOX10⁻ cells (median 4.7% vs. 3.3%, adjusted p = 1) (Fig. 2 e). Within SOX10⁺ cells, gains of both probes were found in only one cell in the MSA case and none in the control group. Among SOX10⁻ cells, gains of both probes were identified in a small number of control cells and were not detected in MSA. The median proportions of cells carrying both-probe losses were higher than for gains but were comparable between MSA and controls (SOX10⁺ = 1.2% vs 1.7%, SOX10⁻ = 1.3% vs 1.7%). Next, to directly compare SNCA with the reference locus, we performed paired analyses within the same case and region. In controls, SNCA gains were significantly more frequent than reference gains in both SOX10 + (1.9% vs 0%, adjusted p = 0.03) (Fig. 2 b) and SOX10⁻ populations (2.9% vs 0%, adjusted p < 0.001) (Fig. 2 c). In MSA, the same trend was observed in SOX10 + gains, though the difference did not reach significance after correction (6.7% vs 0.5%, adjusted p = 0.13) (Fig. 2 b). There was no difference between SOX10⁻ SNCA and reference gains (1.7 vs 0%, adjusted p = 1) (Fig. 2 c). A similar pattern was observed for losses. In controls, SNCA losses were significantly more frequent than reference losses in both SOX10⁺ (median = 6.3% vs. 3.0%; adjusted p < 0.01) (Fig. 2 d) and SOX10⁻ populations (median = 7.5% vs. 3.3%; adjusted p < 0.01) (Fig. 2 e). In MSA, SNCA losses were likewise higher relative to reference losses in SOX10⁺ cells (median = 12.0% vs. 3.4%) though this did not reach significance (adjusted p = 0.13) (Fig. 2 d). Similarly, in SOX10⁻ cells there was an increase in SNCA losses compared to the reference though this was non-significant (median = 13.1% vs. 4.7%; adjusted p = 0.13) (Fig. 2 e). Overall, these results support the relative genomic stability of the reference probe locus, consistent with our previous findings [14, 38, 40] and indicate that CNVs are preferentially enriched at the SNCA locus, including both gains and losses in controls. Somatic SNCA Gains in Oligodendrocytes Are Most Enriched in Severely Affected MSA Regions and Correlate with α-Synuclein Inclusions Given the distinct regional patterns of pathology in MSA subtypes, with predominant involvement of the putamen in SND, the cerebellum in OPCA, and the substantia nigra in both, we next assessed whether the frequency of somatic SNCA gains in oligodendrocytes varies across these regions, as we had found in similar work without cell type characterisation [14] (Fig. 3 a). In the OPCA subtype, significantly higher proportions of SOX10⁺ SNCA gains were observed compared to controls in all three regions examined: cerebellum (median 8.7% vs. 3.0%, adjusted p = 0.001), putamen (9.5% vs. 2.0%, adjusted p = 0.02), and substantia nigra (8.4% vs. 2.4%, adjusted p = 0.001), In the SND subtype compared to controls, significant increases were observed in the putamen (7.3% vs. 2.0%, adjusted p = 0.01) and substantia nigra (6.4% vs. 2.4%, adjusted p = 0.03), but not in the cerebellum (adjusted p = 0.27). When comparing SNCA oligodendrocyte gain frequencies in a given region between MSA subtypes, we noted a 2.2-fold higher difference in OPCA cerebellum compared to SND cerebellum (8.7% vs 3.9%), however this was non-significant after correction (adjusted p = 0.09). We noted no difference between SND and OPCA putamen (7.3% vs 9.5%; adjusted p = 1). We next compared differentially affected regions within each MSA type. Within the SND group, we compared the putamen and cerebellum which revealed a 1.9-fold increase in SOX10⁺ gains in the putamen (7.3 vs 3.9%, adjusted p = 0.09). Within the OPCA group, there was no difference between the cerebellum and putamen (8.7% vs 9.5%, adjusted p = 0.40). The relative enrichment of gains in the putamen compared to the cerebellum in SND, but lack of regional differences in SOX10⁺ SNCA gains in OPCA, could suggest that our OPCA cohort had a less pronounced cerebellar predominance, with the putamen affected almost to the same extent. To assess this, we compared the proportion of SOX10⁺ α-synuclein⁺ cells in preferentially affected regions (OPCA: cerebellum; SND: putamen) versus lesser affected regions (OPCA: putamen; SND: cerebellum) (Supplementary Fig. 3). In OPCA cases, the median percentage of SOX10⁺ inclusions was 26.1% in the cerebellum and 17.7% in the putamen, reflecting a 1.5-fold difference ( p = 0.12). In contrast, SND cases exhibited a more pronounced 3.1-fold regional difference, with median values of 35.9% in the putamen and 11.5% in the cerebellum ( p = 0.07). These findings demonstrate that our OPCA cohort has more regionally extensive pathology than SND, and therefore regional patterns of CNVs, if related to disease, would be expected primarily in SND. Next, we performed the same analysis for SOX10⁻ cells (Fig. 3 b). Significant differences in median percentages of gains were observed in the cerebellum and putamen of the OPCA group compared to controls (cerebellum: 7.9% vs. 3.2%, adjusted p = 0.03; putamen: 8.3% vs. 2.3%, p = 0.02). In the SND group, the difference between the putamen was not significant (5.7% vs. 2.3%, adjusted p = 0.09). A significant difference was observed in the cerebellum between OPCA and SND cases (7.9% vs 0%, adjusted p = 0.01), whereas no significant difference was found in the putamen. Interestingly, although the substantia nigra showed significant increases in SOX10 + cells, there were no group differences for SOX10⁻ gains. Within each MSA subtype, we noted no differences across any of the regions (OPCA: ANOVA p = 0.48; SND: Kruskal-Wallis p = 0.21). These results reflect a similar but less pronounced regional trend for SNCA gains in SOX10⁻ cells as there are for SNCA gains in oligodendrocytes. Next, to determine whether SNCA gains in oligodendrocytes are associated with an increased risk of α-synuclein pathology at the single-cell level, we compared the proportion of SOX10 + oligodendrocytes containing inclusions between cells with a SNCA gain and those with copy number 2, stratified by brain region and MSA subtype (Table 2 ). This revealed a significant relative risk (RR) for presence of an α-synuclein inclusion with an oligodendrocyte SNCA gain in the preferentially affected region of each subtype (OPCA cerebellum, RR: 2.4, p < 0.0001, SND putamen. RR: 2.1, p < 0.0001) and the substantia nigra (OPCA RR: 2, p = 0.001; SND RR 1.8, p = 0.046), but not the less affected region in each MSA subtype (OPCA putamen, RR = 1.2, p = 0.63; SND cerebellum: RR = 0.3, p = 0.07). These findings support the hypothesis that SNCA gains increase the susceptibility of individual oligodendrocytes to inclusion formation in predominantly affected regions. Consistent with this, the regional frequency of oligodendrocyte SNCA gains was significantly correlated with the overall burden of GCIs in the most affected regions of each MSA subtype (rho = 0.49, p = 0.02), supporting a role for SNCA gains in determining the regional distribution of pathology. Recently, evidence suggested that neuronal inclusions may also be a key driver of early MSA pathogenesis [64]. We therefore additionally quantified the RR of SNCA gains in inclusions within SOX10⁻ cells (Table 2 ), with the limitation that SOX10⁻ cells comprise a heterogeneous mix of cell types, likely neuronal in inclusion-bearing cells, but more diverse among non-inclusion-bearing cells. This analysis revealed a significant RR of 3.6 (p = 0.002) for inclusions in SOX10⁻ cells with SNCA gains in the cerebellum of OPCA cases. No other regions in OPCA or any regions in SND showed significant RR. However the low number of inclusion-bearing SOX10⁻ cells may have contributed to the lack of significance elsewhere. Table 2 Relative risk for α-synuclein inclusions in cells with and without somatic SNCA gains. Region MSA subtype Gains CN2 RR 95% CI p-value Total aSyn+ % Total aSyn+ % SOX10 + cells Cerebellum OPCA 42 26 61.9 276 71 25.7 2.4 1.7–3.3 < 0.0001* SND 32 2 6.3 517 114 22.1 0.3 0.07–1.1 0.07 Putamen OPCA 30 7 23.3 355 70 19.7 1.2 0.6–2.3 0.60 SND 48 32 66.7 438 136 31.1 2.1 1.7–2.7 < 0.0001* SN OPCA 37 16 43.2 371 80 21.6 2.0 1.3–3 0.001* SND 30 9 30.0 360 59 16.4 1.8 1–3.3 0.046* SOX10⁻ cells Cerebellum OPCA 47 7 14.9 439 18 4.1 3.6 1.6–8.2 0.002* SND 6 0 0 287 15 5.2 1.3 0.1–21 0.84 Putamen OPCA 41 1 2.4 338 11 3.3 0.7 0.1–5.7 0.78 SND 24 2 8.3 274 24 8.8 1.0 0.2–3.8 0.94 SN OPCA 30 2 6.7 375 10 2.7 2.5 0.6–10.9 0.22 SND 16 0 0 208 7 3.4 0.8 0.05–13.7 0.89 SOX10 + and SOX10⁻ cells shown separately. The RR estimates with 95% confidence intervals (CI) and corresponding p-values are indicated. Statistically significant RR p-values (< 0.05) are highlighted with an asterisk (*). Somatic SNCA losses show widespread regional distributions and relative risk of α-synuclein inclusions Having established overall SNCA losses in MSA SOX10⁺ oligodendrocytes and SOX10⁻ cells, we next compared their levels across the cerebellum, putamen, and substantia nigra among OPCA, SND, and control groups (Fig. 4 ). In SOX10⁺ cells, SNCA losses were significantly more frequent in the cerebellum of OPCA cases (median 15.4%) and SND cases (13.0%) compared with controls (6.7%; adjusted p < 0.0001 and p = 0.03, respectively). In the putamen, both OPCA (15.0%) and SND (13.7%) showed increased SNCA losses versus controls (6.4%; adjusted p = 0.02 and p = 0.01, respectively). In the substantia nigra, we observed a significant difference between SND and control (11.9% vs 6.5%, adjusted p = 0.02) but not OPCA (8.0%, p = 0.72). Comparisons between SND and OPCA cases revealed no significant differences across any of the regions. Moreover, region-wise comparisons within each MSA subtype showed no significant differences (Kruskal-Wallis: OPCA p = 0.06; SND p = 0.77). For SOX10⁻ cells, SNCA losses were significantly elevated in the cerebellum of SND (14.7%) compared to controls (4.3%, adjusted p = 0.01), whereas the excess of OPCA losses was not significant (10.9%; adjusted p = 0.1). In the putamen, SNCA loss frequencies did not differ significantly between controls and either MSA subtype (controls: 8.8%; OPCA: 11.1%; SND: 15.6%). Similarly, the substantia nigra showed no significant group differences (SND: 10.5%; OPCA: 14.1%; controls: 9.1%). SNCA loss frequencies were also comparable across regions within each MSA subtype (Kruskal-Wallis: OPCA p = 0.36; SND p = 0.81). These results indicate that SNCA losses in MSA do not show a clear regional predilection based on differential regional involvement in each subtype. As we had shown a relationship of SNCA gains with α-synuclein inclusions at the single cell level, we next assessed this for SNCA losses. At the single-cell level, a significantly increased RR of SNCA loss in oligodendrocytes with inclusions was observed in the substantia nigra of both MSA subtypes (RR 1.9, p = 0.003 SND, RR 2 OPCA p = 0.0008) and SND putamen (RR 1.4, p = 0.03), however this was not observed in the OPCA cerebellum (RR 1.1, p = 0.6) (Table 3 ). As for non-oligodendrocytes, there was significant RR of SNCA loss in cells with inclusions only in OPCA substantia nigra (RR 3.7, p = 0.01), although there was a possible increased risk in all regions (Table 3 ). Combining all regions together leads to an overall RR for both SOX10 + oligodendrocytes (OPCA RR: 1.5, p = 0.004; SND RR 1.4, p = 0.0007) and SOX10⁻ cells (OPCA RR: 2.7, p = 0.0006; SND RR 1.7, p = 0.07). These results suggest that, like SNCA gains, losses are also associated with inclusions, but in a more widespread manner, without the clear cell-type and regional predilection seen for SNCA gains. Table 3 Relative risk for α-synuclein inclusions in cells with and without somatic SNCA losses Region MSA subtype Losses CN2 RR 95% CI p-value Total aSyn+ % Total aSyn+ % SOX10 + cells Cerebellum OPCA 62 18 29.0 276 71 25.7 1.1 0.7–1.7 0.60 SND 77 21 27.3 517 114 22.1 1.3 0.9–1.9 0.20 Putamen OPCA 58 14 24.1 355 70 19.7 1.2 0.7–2 0.40 SND 72 31 43.1 438 136 31.1 1.4 1–1.87 0.03* SN OPCA 45 19 42.2 371 80 21.5 2.0 1.3–2.9 0.0008* SND 60 19 31.7 360 59 16.4 1.9 1.2–3 0.003* SOX10⁻ cells Cerebellum OPCA 55 5 9.1 439 18 4.1 2.2 0.9–5.7 0.10 SND 42 5 11.9 287 15 5.2 2.3 0.9–5.9 0.09 Putamen OPCA 46 4 8.7 338 11 3.3 2.7 0.9–8 0.08 SND 49 5 10.2 274 24 8.8 1.2 0.5–2.9 0.74 SN OPCA 61 6 9.8 375 10 2.7 3.7 1.4–9.8 0.009* SND 35 3 8.6 208 7 3.4 2.5 0.7–9.4 0.16 The RR estimates with 95% confidence intervals (CI) and corresponding p-values are indicated. Statistically significant RR p-values (< 0.05) are highlighted with an asterisk (*). SNCA gains reflect an intrinsic case-level propensity for gains in other cell types and other brain regions associated with younger age of disease onset As we had seen apparent inter-individual variability in our CNV analysis, we explored whether this variability reflects a case-level propensity rather than being restricted to region-specific pathology. We first examined within-individual patterns of oligodendrocyte SNCA gains across brain regions by performing pairwise Spearman’s rank correlation analyses between the most and lesser affected brain regions within each case, revealing a significant positive correlation (rho = 0.56, p = 0.02; Fig. 5 a). To determine whether cases with higher mosaicism in oligodendrocytes also had higher mosaicism in other cell types, we compared the frequency of SNCA gains in SOX10⁺ and SOX10⁻ cells across all regions, which also showed a significant positive correlation in MSA (rho = 0.5, p = < 0.0001) (Fig. 5 b) but not in controls (rho = 0.2, p = 0.2). Taken together, this supports the idea that SNCA gains may represent an intrinsic, case-level tendency in MSA, across regions and cell types. We performed the same analysis for SNCA losses. No significant correlations were observed between SOX10⁺ and SOX10⁻ cells (rho = -0.002, p = 1). Losses did, however, show a strong correlation between the most and lesser affected regions (rho = 0.7, p = 0.002). Given the previous observation in PD of a negative correlation between age of onset and SNCA gains in the key affected region, the substantia nigra, and cell type (dopaminergic neurons) [38] we wondered whether such a relationship might exist for MSA. We investigated whether SOX10 + oligodendrocyte SNCA gains were associated with age of onset by taking the average percentage per case across the regions analysed. This revealed a significant negative correlation (rho = -0.45, p = 0.03) for age of disease onset (Fig. 5 c), which was not observed for SOX10⁻ SNCA gains (rho = -0.12, p = 0.58) (Fig. 5 d). There was no significant correlation with age of death (rho = -0.35, p = 0.09), disease duration (rho = 0.10, p = 0.63), or PMI (rho = 0.27, p = 0.19). We did not detect any significant associations between SNCA losses in SOX10 + and SOX10⁻ cells and these clinical parameters (Supplementary Table 3). These results suggests that oligodendrocyte SNCA gains, but not SNCA gains or losses in SOX10⁻ cells, may have a role in determining onset age. DNA double-stranded breaks are enriched in MSA oligodendrocytes and are associated with α-synuclein pathology To investigate whether DSBs are associated with MSA pathology, we performed immunofluorescence staining for γH2AX phosphorylated at Ser139, an established marker of DSBs [32], in at least one region from three controls, three SND cases, and five OPCA cases (demographics summarised in Supplementary Table 4). Subsets of experiments included γH2AX with either α-synuclein or SOX10 (Supplementary Table 5), as simultaneous detection of all three markers was not possible due to species overlap and secondary antibody compatibility. We observed two γH2AX staining patterns, diffuse pan-nuclear staining and bright foci (Fig. 6 a). Pan-nuclear γH2AX signalling has been attributed to clustered DNA damage associated with several pathogenic cellular responses such as apoptosis and replication stress [12, 35, 37], as well as more non-specific physiological responses such as increased cellular activity [50]. Accordingly, we focused on analysing the discrete γH2AX foci, irrespective of pan-nuclear staining, as these are more reliable indicators of an active downstream DNA damage response. First, to determine if the DSB response is altered in MSA compared to controls, we classified cells with one or more foci as γH2AX + . Across all brain regions analysed, the median percentage of γH2AX + cells was significantly higher in MSA than in controls (6.0% vs 2.2%, p = 0.049) (Fig. 6 b), indicating an increase in DNA damage response activity. To identify the affected cell populations, we performed an immunofluorescence experiment with SOX10 on two controls (cerebellum and SN from one, putamen from the other), two OPCA (cerebellum or SN from each) and two SND (cerebellum and SN from both). This revealed a significant enrichment of DSBs in oligodendrocytes in MSA versus controls (14.4% vs 5.5%, p = 0.02) (Fig. 6 c) indicating that DSBs are present in cell types known to be vulnerable in MSA. We also noted a slightly higher level of γH2AX + in SOX10⁻ cells than in controls (3.1% vs 1.6%) (Fig. 6 d), however this difference was non-significant ( p = 0.30). This pattern suggests that the DSB response is enriched within oligodendroglial populations. We next assessed whether DSB accumulation was linked to α-synuclein pathology. Paired comparisons revealed significantly more γH2AX foci in α-synuclein+ nuclei than α-synuclein– nuclei (22.2% vs 14.9%, p = 0.02) (Fig. 6 e), suggesting a strong association between α-synuclein aggregation and DSB burden at the single-cell level. This finding is consistent with previous reports in DLB, where γH2AX accumulation and p53 activation occur in neurons with nuclear α-synuclein [26]. Finally, we examined whether DSB burden varied across brain regions with differential involvement in MSA. Due to the small number of paired samples, statistical comparisons were performed at the group level rather than within-case pairs. Overall, γH2AX levels were 3.7-fold higher in the more affected regions compared with less affected regions (18.8% vs 5.1%) although this did not reach statistical significance (p = 0.11). Discussion In this study, we build upon growing evidence implicating somatic SNCA copy number gains in MSA by defining their cellular distribution, regional patterns, and relationship to α-synuclein inclusions. We show that SNCA gains are increased in MSA relative to controls, particularly in SOX10 + oligodendrocytes, the glial cell type predominantly affected by α-synuclein pathology. Within each subtype, oligodendrocyte SNCA gains tend to be high in regions that are selectively vulnerable, namely the cerebellum in OPCA and putamen in SND, and the substantia nigra in both. At the single-cell level, oligodendrocyte gains are associated with a 2-fold increased relative risk for α-synuclein inclusions in affected regions, an association that was reflected at the regional level, where the frequency of gains correlated with the overall burden of α-synuclein pathology. These results, taken together with the association between higher oligodendrocyte SNCA gain burden and earlier age of disease onset, are supportive of a role in MSA pathogenesis, possibly by locally raising the intracellular α-synuclein to pathogenic thresholds. The regional distribution of oligodendrocyte SNCA gains differ between MSA subtypes. In SND, gains are enriched in the putamen relative to the cerebellum, consistent with the established regional predilection of pathology in this subtype. In contrast, in OPCA, oligodendrocyte SNCA gains are present at comparable levels in the cerebellum and putamen. In line with this, we found that the burden of GCIs in our cohort is 3-fold higher in SND in the putamen compared to the cerebellum, but only 1.5-fold higher in OPCA in the cerebellum compared to putamen. This may reflect the broader regional pathology seen in OPCA, where severe cerebellar and putaminal involvement often coexist [20], although, we cannot exclude sampling bias or small sample size effects contributing to the pattern observed in our samples. We also detect excess gains in SOX10⁻ cells consistent with our prior reports of neuronal SNCA mosaicism in MSA cingulate cortex and substantia nigra [38, 40] which may also contribute to disease pathogenesis. Neuronal inclusions are becoming more widely recognised as early events in MSA pathogenesis [64]. However, as we did not include neuronal markers in the present study, we cannot definitively assign SOX10⁻ cells with inclusions to a neuronal lineage. Further experiments using neuronal markers with α-synuclein would be necessary to assess this. Case-level analyses reveal that the level of SNCA gains in MSA is positively correlated across other brain regions and between SOX10 + oligodendrocytes and SOX10⁻ cells within the same individual, suggesting that these somatic gains reflect an intrinsic, case-specific propensity that is not observed in controls. These relationships may be consistent with an early clonal origin that produces descendant cells across multiple regions or cell types, supporting a model in which a subset of MSA patients may have pre-existing somatic SNCA mosaicism for gains that increases the likelihood of developing α-synuclein aggregation in later life. However, we cannot rule out the other possibility of a general increased susceptibility to SNCA copy number variation within MSA, in which case individual cells may carry unique rather than shared CNVs, with different size and distinct breakpoints. While the former could be characterised fully by deep long read whole genome sequencing (WGS), the latter would require single cell WGS. This is presently limited generally to megabase-scale CNVs [21] and could thus miss smaller events, although we did detect one in our pilot MSA single cell WGS study [40]. Long read single cell WGS could detect events of all sizes, and was recently reported in the brain in a small study including MSA [19]. While these findings strengthen the case for a pathogenic role of somatic SNCA gains in MSA, our protocol on isolated nuclei also allowed the characterisation of somatic SNCA losses. Losses are higher in MSA, and exhibit a more widespread distribution across cell-types and regions, with a variable but overall positive association with α-synuclein pathology, but no correlation with onset age or disease duration. Collectively, these observations raise important questions regarding the timing and origin of these CNVs, which cannot be resolved with the current data. Gains and losses can arise through distinct mechanisms. Large-scale gains are most likely to reflect mitotic errors such as chromosome mis-segregation or DNA replication defects, and are typically clonal [5, 16]. This raises the likelihood that such gains occur prior to MSA pathogenesis, as the cells known to form α-synuclein inclusions are mostly post-mitotic, although we cannot exclude their emergence during low-level clonal expansion of glial progenitors in disease progression. We also cannot rule out that gains arise secondarily in post-mitotic cells, potentially through rare mechanisms such as cell-cycle re-entry and localised DNA synthesis, which has been reported in other neurodegenerative diseases [39, 48]. Importantly, gains and losses may sometimes occur concomitantly during non-allelic homologous recombination (NAHR), resulting in one daughter cell with a duplication and another with a reciprocal deletion [49], a process that could contribute to the mixed patterns of CNVs we observe. A somatic SNCA loss on the other hand could occur post-mitotically secondary to DNA damage in the form of DSBs, rather than a primary event. DSBs can lead to widespread genomic deletions, which is particularly relevant in the brain as the main pathway for DSB repair in post-mitotic cells, NHEJ, is known to be error-prone [34, 44]. To explore this possibility, and to contextualise the SNCA CNV landscape within a broader framework of possible genomic instability, we explored DNA DSBs using γH2AX. We found widespread DNA DSB accumulation in MSA, with γH2AX foci enriched in SOX10 oligodendrocytes, and in cells with α-synuclein inclusions. This finding suggests an association between α-synuclein aggregation and activation of DNA DSB repair within the oligodendroglial population in MSA. This may also occur in neurons, as shown in Lewy body diseases [26, 56], although we cannot determine this in MSA, as we did not separate neurons from other SOX10⁻ cells. We therefore hypothesise that somatic SNCA losses are secondary to disease progression, and may result from mis-repaired DSBs. To conclusively determine, however, whether SNCA losses results from DSBs, would require combining FISH with γH2AX immunofluorescence. This leads to the question of whether the propensity of the SNCA gene to acquire CNVs in MSA reflects specific instability of that gene, which has been suggested to be within a fragile site [47], or whether genome-wide somatic CNVs, known to occur in healthy brain cells [33], are enriched in MSA. The overall higher frequency of SNCA CNVs in controls relative to the reference probe suggests that the SNCA locus itself may be inherently prone to structural instability, independent of disease status, consistent with previous work showing minimal gains of other reference probes [14, 38]. The reference probe in our study was equally affected by CNVs (predominantly losses) in MSA and controls, arguing against an overall tendency for CNVs in MSA. Our pilot single cell WGS of large CNVs genome-wide did detect them in ~30% of MSA cells, including a putaminal neuron with extensive nuclear inclusions and large-scale genomic losses encompassing SNCA , likely to have arisen by NHEJ [40]. Larger scWGS will be required, however, to determine if genome-wide CNVs are enriched in MSA. Another limitation is that, while we propose sustained overexpression of SNCA mRNA as the mechanism by which gains contribute to pathogenesis, we have not demonstrated this. An increase in SNCA mRNA in MSA oligodendrocytes has been reported previously through quantitative reverse transcription PCR, though these results were non-significant [2]. More recently, a higher level of SNCA transcripts was found in oligodendrocytes with inclusions using RNAScope, though the numbers of cases analysed were limited [25]. It thus remains unclear whether SNCA mRNA is increased in MSA, especially across individual cell types. Ideally, methods assessing DNA and RNA in the same cell would clarify these relationships. While in situ approaches are limited by DNA-RNA cross-reactivity, sequencing of the DNA and RNA of the same nucleus [60], although challenging, is becoming possible, including in the human brain [8]. Nonetheless, RNA measurements still only represent a snapshot at the point of death of cells surviving in a disease environment, rather than reflect long-term expression patterns, and are influenced by both pre-mortem and post-mortem changes [11, 58]. While our findings strongly implicate somatic SNCA gains as contributors to MSA pathology, it is important to acknowledge that these gains may represent only one facet of a multifactorial disease. Somatic mosaicism may serve as a “first hit” or modifier that increases vulnerability to α-synuclein aggregation. Supporting this, we did not find an association of SNCA gains with α-synuclein inclusions in the OPCA putamen, despite high levels of SNCA gains. Furthermore, both somatic SNCA gains and losses have been identified in neurologically healthy individuals from the UK Biobank data, though some of these had reported blood-based cancers, therefore it is unclear if they would be found also in the brain, and others were younger than the typical age of onset for MSA or PD [4]. Similarly, individuals with germline SNCA multiplications typically develop a clinical picture resembling PD rather than MSA, and do not always contain GCIs [24]. These observations suggest that SNCA copy number variation alone is unlikely to be sufficient to cause MSA, but may act as a contributory or permissive factor whose pathogenicity depends on additional influences, such as cell-type–specific stress, environmental risk factors, coexisting inherited as yet unidentified genetic variants, or indeed other somatic mutations. Such mutations could arise within the brain or originate in the periphery, including in the context of clonal haematopoiesis of indeterminate potential, an age-related process recently reported to be associated with MSA [29]. Nonetheless, our findings reinforce the rationale for therapeutic approaches that lower α-synuclein levels, including antibody-based and antisense strategies already in development [3]. The enrichment of somatic SNCA gains in affected cells also supports the value of using SNCA overexpression approaches, either alone or alongside other perturbations, to explore how increased α-synuclein dosage interacts with additional cellular processes. More broadly, our results point to somatic variation as a contributor to non-heritable genetic risk in MSA and helps advance our understanding of its aetiology. Declarations Competing Interests Zane Jaunmuktane is a member of the Acta editorial board, but was not involved in the assessment or decision-making process for this manuscript. The other authors report no conflicts of interest. Author Contribution C.M. Sample preparation, data collection, statistical analysis, manuscript writing. E.K.E. Experimental supervision and manuscript revision. D.P.R. Experimental supervision and manuscript revision. Z.J. Providing human brain samples and neuropathological characterisation, manuscript revision and supervision of the project. C.P. Conception and design, manuscript revision, and overall supervision of the project. Acknowledgement This work was funded by the Multiple System Atrophy Trust. We thank the patients and their relatives for their invaluable contribution through brain donation. We thank UCL Queen Square Brain Bank administrative and technical staff for their assistance. Data Availability All code used to generate the statistical analyses and figures in this study is available on GitHub at https://github.com/caoimhemorley/somatic-SNCA-CNV-FISH-analysis. All raw cell counts and summarised datasets supporting the findings of this study are provided in the Supplementary Materials. Representative images are included in the figures, and additional raw image data are available from the corresponding author upon reasonable request. 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The other authors report no conflicts of interest. Supplementary Files SupplementaryFile1FINAL.docx SupplementaryFile2Final.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 22 Feb, 2026 Reviews received at journal 20 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 28 Jan, 2026 Submission checks completed at journal 28 Jan, 2026 First submitted to journal 26 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8701777","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":582274161,"identity":"0c50f675-9271-4bd5-a382-adc993b52242","order_by":0,"name":"Caoimhe Morley","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Caoimhe","middleName":"","lastName":"Morley","suffix":""},{"id":582274162,"identity":"17b37600-a7c1-4bd1-804b-4cfb56cf3e0e","order_by":1,"name":"Ester Kalef-Ezra","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Ester","middleName":"","lastName":"Kalef-Ezra","suffix":""},{"id":582274163,"identity":"e666f0b1-68f2-4920-8ff3-a58e7eb73c9b","order_by":2,"name":"Diego Perez-Rodriguez","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Diego","middleName":"","lastName":"Perez-Rodriguez","suffix":""},{"id":582274164,"identity":"88296f00-934a-4cce-a0fb-399c281fef66","order_by":3,"name":"Zane Jaunmuktane","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Zane","middleName":"","lastName":"Jaunmuktane","suffix":""},{"id":582274165,"identity":"6e8eb75b-7700-472e-bbf0-cfaa14593294","order_by":4,"name":"Christos Proukakis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYPCCBAYJZgbGBwwMFmAuYwORWpgNGBgkSNHCwMAmQZQW/gbeYx8+tqXJS7azP6vmqZFg4G8/wCY5A48WiQN8yTNntuUYzmbmMbvNc0yCQeJMApvkBjxaDBh4jJl52yoY5zHzsN3mbQA67AYDm+QDIrTYz2Nmf1YM0iJPpJacxNnMDGbMIC0GIC34HCZxmC+Zcca5tOSZzTzGknOOSfAYnklstsTnff723sMMH8qSbWecP/7ww5saGzm544cP3uzBo4WBmQeVz0NERPIQkB8Fo2AUjIJRAAATYj41SX/gBgAAAABJRU5ErkJggg==","orcid":"","institution":"University College London","correspondingAuthor":true,"prefix":"","firstName":"Christos","middleName":"","lastName":"Proukakis","suffix":""}],"badges":[],"createdAt":"2026-01-26 15:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8701777/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8701777/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101524280,"identity":"96f764c8-47ac-4f0b-a595-8117aa0cdd3e","added_by":"auto","created_at":"2026-01-30 17:55:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":189353,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Experimental overview of the immuno-FISH workflow. Fresh-frozen post-mortem tissue from control donors and individuals with SND and OPCA was processed to generate isolated nuclear suspensions. Tissue was dissociated by Dounce homogenisation and nuclei were separated through an iodixanol gradient before mounting on slides. The combined immuno-FISH assay used an \u003cem\u003eSNCA\u003c/em\u003e oligonucleotide FISH probe together with immunofluorescent detection of SOX10 to mark oligodendrocyte lineage nuclei and α-synuclein to detect inclusions. Created in BioRender. M, C. (2026) https://BioRender.com/xtqohau (b) Representative immuno-FISH images showing \u003cem\u003eSNCA\u003c/em\u003e FISH signal together with α-synuclein and SOX10 staining. Examples of nuclei with different \u003cem\u003eSNCA\u003c/em\u003e copy number (CN) states are shown for SOX10\u003csup\u003e+\u003c/sup\u003e α-synuclein\u003csup\u003e+\u003c/sup\u003e and SOX10\u003csup\u003e+\u003c/sup\u003e α-synuclein⁻ nuclei. White arrows indicate \u003cem\u003eSNCA\u003c/em\u003e FISH signals. Scale bar = 5 μm. (c) Quantification of somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs in SOX10\u003csup\u003e+\u003c/sup\u003e and SOX10⁻ nuclei across MSA (n = 25) and control (n = 15) groups. Box plots display the proportion of nuclei with \u003cem\u003eSNCA\u003c/em\u003e gain or loss within each group. Group comparisons were performed with the Mann-Whitney U test\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/7cd28446c85dd1bca6b5457d.png"},{"id":101524270,"identity":"8c590579-4e43-4e93-9751-564826c31f4d","added_by":"auto","created_at":"2026-01-30 17:55:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":184919,"visible":true,"origin":"","legend":"\u003cp\u003eTwo-probe FISH analysis across SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes and SOX10⁻ cells (a) representative immuno-FISH images showing examples of \u003cem\u003eSNCA\u003c/em\u003e and reference probe with SOX10 staining and different copy number states. Scale bar = 5 μm. (b) Reference probe and \u003cem\u003eSNCA\u003c/em\u003e gain quantification in SOX10\u003csup\u003e+\u003c/sup\u003e cells, (c) Reference probe and \u003cem\u003eSNCA\u003c/em\u003e gain quantification in SOX10⁻ cells (d) Reference probe and \u003cem\u003eSNCA\u003c/em\u003e loss quantification in SOX10\u003csup\u003e+\u003c/sup\u003e cells (e) Reference probe and \u003cem\u003eSNCA\u003c/em\u003e loss quantification in SOX10⁻ cells. Statistical significance was determined using Mann-Whitney U test and paired Wilcoxon signed-rank tests, with Bonferroni correction for multiple comparisons (n = 4)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/0fb52be7161760279f78e06c.png"},{"id":101524278,"identity":"c6859fb8-ce88-4692-8843-3a1a7f47d5c8","added_by":"auto","created_at":"2026-01-30 17:55:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":127840,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of percentage \u003cem\u003eSNCA\u003c/em\u003e gains in (a) SOX10\u003csup\u003e+\u003c/sup\u003e cells and (b) SOX10⁻ cells across the cerebellum, putamen, and substantia nigra (SN). Regional panels compare three groups: OPCA, SND, and control. Statistical significance was assessed using the Kruskal-Wallis test followed by Dunn’s post-hoc tests with Bonferroni correction for multiple comparisons (n = 3). P-values less than 0.05 are indicated by an asterisk (*)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/009ce19ef648bba42df0a325.png"},{"id":101524271,"identity":"546efc33-dfe7-4d44-8e53-67d20bc884c4","added_by":"auto","created_at":"2026-01-30 17:55:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":128038,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of percentage \u003cem\u003eSNCA\u003c/em\u003e losses in (a) SOX10\u003csup\u003e+\u003c/sup\u003e cells and (b) SOX10⁻ cells across the cerebellum, putamen, and substantia nigra (SN). Regional panels compare three groups: OPCA, SND, and control. Statistical significance was assessed using the Kruskal-Wallis test followed by Dunn’s post-hoc tests with Bonferroni correction for multiple comparisons (n = 3). P-values less than 0.05 are indicated by an asterisk (*)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/3b9e2f97111ecb4a0b891303.png"},{"id":101751993,"identity":"9260ab34-6ec5-4e52-a10f-68c8e4fae03d","added_by":"auto","created_at":"2026-02-03 10:24:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":164029,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation analyses examining relationships between (a) Percentage of SOX10\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eSNCA\u003c/em\u003e gains in the region most affected in each subtype (OPCA cerebellum; SND putamen) compared with the region lesser affected (OPCA putamen; SND cerebellum). (b) Percentage of SOX10\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eSNCA\u003c/em\u003e gains plotted against SOX10⁻ \u003cem\u003eSNCA\u003c/em\u003e gains across all regions analysed. (c) Average percentage of SOX10\u003csup\u003e+\u003c/sup\u003e \u003cem\u003eSNCA\u003c/em\u003e gains plotted against age at disease onset. (d) Average percentage of SOX10⁻ \u003cem\u003eSNCA\u003c/em\u003e gains plotted against age at disease onset. Each panel includes a linear model illustrating the overall trend (black) together with separate trend lines for OPCA and SND\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/51856b958c686dedd19f7a14.png"},{"id":101524277,"identity":"cba1d214-e90f-4380-870e-5351625ba8cc","added_by":"auto","created_at":"2026-01-30 17:55:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":250434,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Immunofluorescence images showing representative γH2AX staining. The upper panel of images shows γH2AX staining together with α-synuclein in MSA tissue. The middle set shows γH2AX together with SOX10 in MSA tissue. The lower set shows γH2AX together with SOX10 in control tissue. For each set the individual markers are shown separately followed by a merged image that includes an inset with representative nuclei containing γH2AX staining. Orange arrows indicate examples of pan-nuclear γH2AX signal. Scale bar = 20 μm. (b) Quantification of cells that contain ≥ 1 γH2AX foci in MSA compared with control. (c) Proportion of SOX10\u003csup\u003e+\u003c/sup\u003e cells that contain ≥ 1 γH2AX labelling foci in MSA compared with control. (d) Proportion of SOX10⁻ cells with ≥ 1 γH2AX positivity in MSA compared with control. (e) Paired comparison of α-synuclein (aSyn)+ versus aSyn- cells with ≥ 1 γH2AX foci. (f) Percentage of γH2AX positive cells in the region most affected for each subtype (OPCA cerebellum; SND putamen) compared with the region lesser affected (OPCA putamen; SND cerebellum). Unpaired comparisons were performed using the Mann-Whitney U test and paired comparisons used the Wilcoxon paired test. Significant values \u0026lt;0.05 are indicated with an asterisk (*)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/198e527faab318cca2131977.png"},{"id":101756147,"identity":"4df5cdfd-54da-4236-87b3-729763c5cfb6","added_by":"auto","created_at":"2026-02-03 10:56:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2374227,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/a54d110f-9727-4f94-99b6-3c1fdd7ae728.pdf"},{"id":101524279,"identity":"a267d1ad-7ad8-4601-a323-e5d5d6e76c84","added_by":"auto","created_at":"2026-01-30 17:55:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1751097,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1FINAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/3b23fbcf13a5cb48619a3dc2.docx"},{"id":101754673,"identity":"d0beaf86-9d99-4475-ac04-d8da0e3bcd58","added_by":"auto","created_at":"2026-02-03 10:44:36","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":129209,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile2Final.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8701777/v1/8e646febf74534a315c6c4fb.xlsx"}],"financialInterests":"Competing interest reported. Zane Jaunmuktane is a member of the Acta editorial board, but was not involved in the assessment or decision-making process for this manuscript. The other authors report no conflicts of interest.","formattedTitle":"Oligodendroglial somatic SNCA copy number gains are associated with inclusions and disease onset in multiple system atrophy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultiple system atrophy (MSA) is a rare synucleinopathy characterised by varying combinations of autonomic failure, parkinsonism, and cerebellar ataxia, and a rapidly progressive disease course [9]. Although neuronal α-synuclein aggregation is a shared hallmark across all synucleinopathies, MSA is uniquely defined by the additional presence of glial cytoplasmic inclusions (GCIs) within oligodendrocytes [13, 59]. Neuronal inclusions, including neuronal cytoplasmic and neuronal nuclear inclusions, are distinct from the Lewy bodies (LBs) and Lewy neurites that characterise Parkinson\u0026rsquo;s disease (PD) and Dementia with Lewy bodies (DLB), which are comparatively rare in MSA [22, 28, 55]. MSA diverges into distinct pathological subtypes, including striatonigral degeneration (SND), olivopontocerebellar atrophy (OPCA), and a mixed subtype. Despite these well-defined pathological patterns, the mechanisms that render oligodendrocytes and specific brain regions selectively vulnerable remain unclear and represent a critical gap to bridge in our understanding of MSA pathogenesis and phenotypic heterogeneity.\u003c/p\u003e \u003cp\u003eIn contrast to PD and DLB, where genetic studies have identified multiple Mendelian and risk loci implicating diverse biological pathways, the aetiology of MSA is unknown [27]. MSA shows no clear familial aggregation and very low heritability (\u0026lt;\u0026thinsp;7%) [10] and to date no major reproducible inherited genetic risk factors have been established [7, 57]. Nevertheless, chronic elevation of α-synuclein is sufficient to drive its aggregation, as demonstrated in PD cases with germline \u003cem\u003eSNCA\u003c/em\u003e multiplications [53]. These cases highlight the strong dosage sensitivity of α-synuclein: \u003cem\u003eSNCA\u003c/em\u003e duplications typically lead to later-onset parkinsonism with reduced penetrance, whereas triplications cause early-onset, rapidly progressive disease [18]. Some individuals with \u003cem\u003eSNCA\u003c/em\u003e multiplications also exhibit mixed neuronal and glial pathology, suggesting that excess α-synuclein expression can also be detrimental to oligodendrocytes [53, 65]. Experimental models further support this, as oligodendrocyte-specific overexpression of human α-synuclein in mice generates GCI-like pathology, demyelination and neuroinflammation, with higher expression producing earlier and more severe neurodegeneration [52, 63]. Together, these observations suggest that cell- or region-restricted increases in \u003cem\u003eSNCA\u003c/em\u003e dosage could contribute to the pathogenesis of MSA.\u003c/p\u003e \u003cp\u003eSomatic mutations, arising post-zygotically and resulting in genetic mosaicism within the brain, have emerged as potential contributors to neurodegenerative disease [30, 36, 43, 61]. These alterations encompass a wide range, from single nucleotide variants to large-scale copy number variants (CNVs, gains or losses) and other structural variants. Somatic mutations may result from mitotic errors or diverse types of DNA damage, including highly mutagenic double stranded DNA breaks (DSBs) [46]. DSB repair in post-mitotic cells is primarily by non-homologous end joining (NHEJ) [33] which can lead to deletions [46]. DSBs have been reported in Lewy body diseases [28, 57], but not investigated in MSA to our knowledge. We previously demonstrated through fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridisation (FISH) studies somatic CNVs, specifically gains, of \u003cem\u003eSNCA\u003c/em\u003e (encoding α-synuclein) in substantia nigra dopaminergic neurons in PD, with the highest levels reported in two MSA cases [38]. Subsequent work detected higher levels of \u003cem\u003eSNCA\u003c/em\u003e gains in neurons of the cingulate cortex in both PD and MSA compared to controls, and in non-neurons in MSA only [40]. More recently, we demonstrated increased levels of somatic \u003cem\u003eSNCA\u003c/em\u003e gains in differentially affected regions in MSA subtypes, the putamen in SND and cerebellum in OPCA, with an increased relative risk for a-synuclein inclusions at the single-cell level [14].\u003c/p\u003e \u003cp\u003eImportantly, these studies did not establish whether \u003cem\u003eSNCA\u003c/em\u003e gains occur in oligodendrocytes, although their level was higher in oligodendrocytes in the substantia nigra of three SND cases analysed. Moreover, none included region-matched controls from the putamen, cerebellum, and substantia nigra, precluding assessment of whether somatic \u003cem\u003eSNCA\u003c/em\u003e gains in these regions are truly enriched in MSA. Finally, the potential role of somatic \u003cem\u003eSNCA\u003c/em\u003e losses has been unexplored and may have distinct functional consequences. Loss of α-synuclein function is not a known driver of any neurodegenerative disease, and experimental models have produced conflicting results regarding its impact [1, 6, 23, 45]. However, aggregated α-synuclein may sequester the protein and diminish its normal physiological functions [51, 62], raising the possibility that dosage reductions could contribute to cellular vulnerability under certain conditions. Together, these observations highlight the need for a systematic, cell-type-resolved and region-matched assessment of somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs in MSA.\u003c/p\u003e \u003cp\u003eHere, we aim to address these gaps by applying an optimised protocol combining FISH and immunofluorescence on isolated nuclear suspensions, to eliminate sectioning artefacts and reliably call copy number losses in addition to gains. We find that, in MSA, somatic \u003cem\u003eSNCA\u003c/em\u003e gains are enriched in SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes relative to controls, in subtype-specific vulnerable regions, and associate with α-synuclein inclusions at both single-cell and regional levels, consistent with a role in pathogenesis. A higher burden of oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains correlates with earlier disease onset, supporting a model in which pre-existing somatic \u003cem\u003eSNCA\u003c/em\u003e mosaicism may predispose individuals to α-synuclein aggregation. We now show, for the first time, somatic \u003cem\u003eSNCA\u003c/em\u003e losses, which are also higher in MSA, though more broadly distributed, with less clear regional associations with inclusions and no association with age of onset. Our results provide further insights into somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs in MSA, with oligodendrocyte gains potential drivers of pathogenesis. Furthermore, we perform immunofluorescence staining of tissue sections for phosphorylated H2AX at serine 139 (γH2AX), an established DSB marker [32], which reveals increased DSBs in MSA compared to controls, notably in oligodendrocytes and in cells with α-synuclein inclusions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHuman fresh-frozen post-mortem brain tissue\u003c/h2\u003e \u003cp\u003eFresh-frozen post-mortem brain samples were obtained from the Queen Square Brain Bank for Neurological Disorders in London, United Kingdom. All subjects or their next of kin had given informed consent for brain donation and use in research. Ethics approval was provided by the National Research Ethics Service (07/MRE09/72). Tissue chips and 10 \u0026micro;m tissue sections were obtained from three brain regions including cerebellar white matter, putamen at the level of the anterior commissure, and the substantia nigra at the level of the red nucleus or decussation of the superior cerebellar peduncle. For clarity, these are hereafter referred to as the \u003cem\u003eputamen, cerebellum\u003c/em\u003e, and \u003cem\u003esubstantia nigra\u003c/em\u003e, respectively. This study included a total of 42 subjects: 27 with pathologically confirmed MSA (15 SND, 12 OPCA) and 15 controls (14 neurologically healthy, 1 with dystonia but normal neuropathology). A summary of experiments performed across each group and brain region are shown in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNuclei isolation from fresh-frozen post-mortem brain tissue\u003c/h3\u003e\n\u003cp\u003eNuclear fractions were isolated from fresh-frozen tissue as previously described [21, 40, 41]. All procedures were performed at 4\u0026deg;C to maintain nuclei integrity. Briefly, 20\u0026ndash;50 mg of tissue was added to 500 \u0026micro;L of Nuclear Isolation Medium (NIM: 25 mM KCl, 5 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 10 mM Tris/HCL pH 8.8, 250 mM sucrose, 1X cOmplete\u0026trade; EDTA-free Protease Inhibitor Cocktail (Roche, 04693132001) and 1 mM dithiothreitol. Tissue was initially homogenised using a plastic pestle (20 strokes) and supplemented with 0.1% Triton-X 100. Complete homogenisation was performed using Dounce tissue grinders with a loose and tight pestle (5\u0026ndash;10 strokes each, Sigma-Aldrich D8938). The homogenate was centrifuged at 1000\u003cem\u003eg\u003c/em\u003e for 8 min at 4\u0026deg;C, after which the supernatant was removed. The resulting pellet was resuspended in 700 \u0026micro;L of 25% Iodixanol prepared using 417 \u0026micro;L of Optiprep\u0026trade; Density Gradient Medium (60% w/v Iodixanol, Sigma-Aldrich D1556) in 500 \u0026micro;L of NIM and 83 \u0026micro;L of Optiprep Diluent for Nuclei (ODN: 150 mM KCl, 30 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 60 mM Tris/HCl pH 8.8 and 250 mM sucrose, 1X cOmplete\u0026trade; EDTA-free Protease Inhibitor Cocktail). Subsequently, the 25% Iodixanol/homogenate mixture was gently layered using a syringe onto 1 mL of 29% Iodixanol (483 \u0026micro;L Optiprep\u0026trade; Density Gradient Medium and 517 \u0026micro;L ODN) to form a gradient. The tube was ultracentrifuged at 10,300\u003cem\u003eg\u003c/em\u003e for 20 min at 4\u0026deg;C. The debris layer and supernatant were discarded, leaving 50 \u0026micro;L of buffer above the pellet. The pellet was resuspended according to the downstream analysis (see subheading Combined Immuno-Fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridisation (Immuno-FISH)).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCombined immuno-fluorescence\u003c/b\u003e \u003cb\u003ein situ\u003c/b\u003e \u003cb\u003ehybridisation (immuno-FISH) on isolated nuclei\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe used the previously published FISH protocol on tissue sections [15] with minor modifications for compatibility with isolated nuclei. The same custom-designed red 50kb \u003cem\u003eSNCA\u003c/em\u003e probe SureFISH (Agilent G110997R-8) was used, and in a subset of experiments a green 767kb Chr 7 chromosome enumeration probe (CEP) probe (G110899G-8) was included for reference. To account for potential variability between experiments, each batch was prepared containing a mixture of MSA subtypes and Controls.\u003c/p\u003e \u003cp\u003eIsolated nuclei were fixed with ice-cold Carnoy\u0026rsquo;s Fixative (3:1 Methanol: Acetic Acid) and incubated on a rotator disk for 1 h at 4\u0026deg;C. The nuclei were dropped onto an Epredia\u0026trade; SuperFrost Ultra Plus Gold Adhesion slides (Epredia, 11976299) and allowed to fully evaporate. Nuclei were permeabilised using a solution of 0.005% pepsin (Roche, 10108057001) in 10 mM HCl at 37\u0026deg;C for 5 min. Following digestion, slides were transferred to PBS supplemented with 1 mM MgCl₂ for 5 min, then washed twice in PBS. Slides were dehydrated through an ethanol series consisting of 70%, 90%, and 100% molecular-biology grade ethanol, each for 2 min, and then air-dried for 10 min. Next, slides were treated with 70% UltraPure\u0026trade; formamide (Invitrogen, 15518746) in 2X saline sodium citrate (SSC) buffer at 72\u0026deg;C for 2 min. A second dehydration step was performed using ice-cold ethanol solutions (70%, 90%, and 100%).\u003c/p\u003e \u003cp\u003e FISH probe reactions were prepared according to the manufacturer\u0026rsquo;s guidelines. The FISH probe mixture was denatured at 72\u0026deg;C for 5 min, and 10 \u0026micro;L of the mixture was applied per slide. A 22 \u0026times; 22 mm coverslip was mounted and sealed using Fixogum rubber cement. Hybridisation was carried out in a humidified chamber at 37\u0026deg;C for 48\u0026ndash;72 h. After hybridisation, slides were immersed in 2\u0026times; SSC buffer at room temperature (RT) for 10 min to allow coverslip removal. They were then washed in preheated Wash Buffer 1 (Agilent, G9401A) at 72\u0026deg;C for 2 min, followed by a 1 min wash in Wash Buffer 2 (Agilent, G9402A) at RT. Finally, slides were washed three times in PBS for 10 min each.\u003c/p\u003e \u003cp\u003eFor immunostaining, blocking solution was prepared with 10% goat serum in PBS with 0.2% Triton-X 100 and incubated for 1 h at RT. Primary antibody solutions were prepared in 2% goat serum and 0.2% Triton-X 100 according to the concentrations listed (see subheading \u003cem\u003eAntibodies used\u003c/em\u003e). All primary antibodies were incubated overnight at 4\u0026deg;C. Following washes, species-specific secondary antibodies were applied and incubated for 1 h at RT. Nuclei were counterstained with 1 \u0026micro;g/mL DAPI (4',6-diamidino-2-phenylindole) solution for 20 min. Slides were cover-slipped with Agilent Mounting Buffer (G9403A).\u003c/p\u003e \u003cp\u003eSlides were imaged using a Leica DM6B epifluorescence microscope coupled to an ORCAII Digital CCD camera (Hamamatsu, Shizuoka, Japan) and controlled by Leica Application Suite X (Leica, Wetzlar, Germany). Z-stacks of 10 images separated by 0.5 \u0026micro;m stacks (5 \u0026micro;m depth total) using appropriate fluorescence filters were obtained with a 40X lens objective. All images were analysed blinded to the donor group and region. FISH signals were visualised using the ImageJ software v1.53t and analysed through manual counting first without the protein markers to obtain unbiased counts and then reviewed with the other colour channels. Exclusion criteria for a cell included (1) autofluorescence, as identified by overlapping signals on more than one channel, obscuring the nucleus, (2) faint, unclear or completely absent FISH signals, and (3) indistinguishable copy number status of overlapping nuclei.\u003c/p\u003e\n\u003ch3\u003eImmunofluorescence on fresh-frozen tissue sections\u003c/h3\u003e\n\u003cp\u003eFresh-frozen tissue sections were cryosectioned at 10 \u0026micro;m thickness and mounted onto Superfrost Plus slides. Tissue sections were thawed for 20 min at RT and then fixed with 10% neutral-buffered formalin for 20 min at RT followed by permeabilization with 0.3% Triton-X in PBS for 60 min. A blocking solution containing 10% goat serum in 0.2% Triton-X 100 in PBS was applied for 1 hour at RT. Primary antibodies were prepared in 2% goat serum and 0.2% Triton-X 100 according to the concentrations listed (see subheading \u003cem\u003eAntibodies used\u003c/em\u003e) and incubated overnight at 4\u0026deg;C. Secondary antibodies were prepared in 2% goat serum and 0.2% Triton-X 100 and incubated for 1 h at RT. A 1X solution of TrueBlack\u0026reg; Lipofuscin Autofluorescence Quencher (Biotium, 23007) was prepared in 70% ethanol and was applied to each slide for 1 min. DAPI (4\u0026prime;,6-diamidino-2-phenylindole) was applied at a final concentration of 1 \u0026micro;g/mL to each slide for 20 min. Slides were mounted with ProLong\u0026trade; Gold Antifade (Thermo Fisher Scientific, P36930).\u003c/p\u003e \u003cp\u003eFor immunofluorescence markers, image analysis was performed through manual counting using ImageJ software v1.53t. Individual optical Z-stacks (10 stacks at 0.5 \u0026micro;m intervals, corresponding to a total optical depth of 5 \u0026micro;m) were examined to confirm true cellular co-localisation and exclude artefacts arising from overlapping fluorescence in adjacent focal planes. Cell counts and inclusion co-localisation were performed manually within defined regions of interest using merged and single-channel images. Identical exposure and threshold settings were applied across all samples within each staining batch.\u003c/p\u003e\n\u003ch3\u003eAntibodies used\u003c/h3\u003e\n\u003cp\u003eTo label oligodendrocytes, a rabbit monoclonal anti-SOX10 antibody (1:50; 0.5 \u0026micro;g/mL; clone SP267, Abcam, ab227680) was used. Alpha-synuclein inclusions were detected using either a mouse monoclonal antibody (1:100; 2 \u0026micro;g/mL; clone 211, Santa Cruz, sc-12767) or a rabbit monoclonal antibody (1:1000; 1 \u0026micro;g/mL; clone MJFR1, Abcam, ab13850), depending on the compatibility with co-stained markers. A mouse monoclonal anti-phospho-Histone H2AX (Ser139) antibody (1:200; 5 \u0026micro;g/mL; clone JBW301) was used to detect DNA DSB repair. Secondary antibodies (anti-mouse/anti-rabbit) were used conjugated to 488 and 647 fluorophores (Thermo Fisher Scientific) at 2 \u0026micro;g/mL (1:500).\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eAll statistical analyses were performed in RStudio v2024.12.1 unless otherwise stated. Variables were assessed for normality using the Shapiro-Wilk test, and equality of variance was assessed with Levene\u0026rsquo;s test for homogeneity of variance. Pairwise comparisons of normally distributed data were performed using the Student t-test (with Welch correction for unequal variance) or the nonparametric Mann-Whitney U test accordingly. For comparisons involving more than two groups, a one-way ANOVA for normally distributed data was used with Tukey\u0026rsquo;s HSD post-hoc correction, and the nonparametric Kruskal-Wallis was used with Dunn\u0026rsquo;s post-hoc correction. Where applicable, Bonferroni correction was applied to adjust for multiple comparisons. For normally distributed data, results are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD); for non-normal data or non-parametric comparisons, the median and interquartile range (IQR) are reported. Boxplots display the median and IQR, with whiskers extending to 1.5\u0026times; IQR. Contingency tables were analysed using the Chi-square or Fisher\u0026rsquo;s exact test based on sample size. For correlation assessments, Spearman\u0026rsquo;s rank correlation was performed. Relative risk scores were calculated using MedCalc (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.medcalc.org/en/calc/relative_risk.php\u003c/span\u003e\u003cspan address=\"https://www.medcalc.org/en/calc/relative_risk.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). P-values are two-tailed and, unless otherwise stated, are nominal.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eSomatic\u003c/b\u003e \u003cb\u003eSNCA\u003c/b\u003e \u003cb\u003eCNVs are more frequent in MSA than controls and gains are enriched in MSA oligodendrocytes\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo explore whether somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs are associated with inclusion-bearing cells in MSA, we performed FISH using a custom-designed SureFISH 50kb \u003cem\u003eSNCA\u003c/em\u003e probe we previously used [14, 40] combined with immunofluorescence for SOX10, a well-established oligodendrocyte marker [42, 54], which is expressed across oligodendrocyte maturation stages [17] and α-synuclein to visualise inclusions. To characterise somatic losses of \u003cem\u003eSNCA\u003c/em\u003e, which cannot be reliably done on tissue sections due to sectioning artefacts, all experiments were done on isolated nuclei from fresh-frozen post-mortem brain tissue (workflow depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). FISH on isolated nuclei allowed us to also significantly reduce the exposure time to pepsin, a protease which is known to variably digest inclusions in MSA [64], therefore allowing for better epitope preservation. We found that, in MSA, α-synuclein inclusions are well-retained in nuclear preparations due to their perinuclear and/or nuclear localisation, with no significant difference observed between levels of inclusions on sections versus nuclei as detected by immunofluorescence for the same case and region (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.31, n\u0026thinsp;=\u0026thinsp;8, Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe final dataset included at least one brain region from 13 SND cases, 12 OPCA cases, and 15 controls. All three brain regions (putamen, cerebellum, substantia nigra) were analysed in 10 controls, 6 SND, and 7 OPCA cases. There were no statistically significant differences in mean age at death across groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Controls: 71.3 years; SND: 67.9 years; OPCA: 64.2 years, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.14) or in median post-mortem interval (PMI) (Controls: 46.6 hours; SND: 43.8 hours; OPCA: 67.5 hours, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.12). Sex distribution was comparable between groups (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.83). Among MSA subtypes, there were no significant differences in mean age at disease onset (SND: 61.8 years; OPCA: 57.1 years, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.14) or in disease duration (SND: 6.2 years; OPCA: 8.0 years, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.11). The overall median total cell count per region from each brain was 88, and the median SOX10⁺ cell count was 46. No significant differences were observed across total cell counts (Kruskal-Wallis \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.46) or SOX10⁺ cell counts (Kruskal-Wallis \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.15) analysed across groups within brain regions (Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eAll results divided by disease status, brain region and cell type are shown in Supplementary Table\u0026nbsp;2. Indicative images of oligodendrocytes with and without CNVs and inclusions are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb. We first quantified the percentage of SOX10⁺ cells with \u003cem\u003eSNCA\u003c/em\u003e gains in both MSA subtypes and controls by taking the average across the regions analysed. This revealed a significant difference in the percentage of SOX10⁺ gains in MSA, where they were enriched over threefold compared to controls (6.3% vs 2.0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). \u003cem\u003eSNCA\u003c/em\u003e gains in SOX10⁻ cells were also higher (5.7 vs 3.4%) however this was non-significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). We next assessed somatic \u003cem\u003eSNCA\u003c/em\u003e losses, which were even higher than gains, and significantly increased in MSA compared to controls in both SOX10\u003csup\u003e+\u003c/sup\u003e cells (12.5% vs 7.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and SOX10⁻ cells (11.1 vs 8.2%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These results indicate that somatic \u003cem\u003eSNCA\u003c/em\u003e gains and losses are both enriched in MSA, preferentially in oligodendrocytes, with less striking enrichment across SOX10⁻ cells.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of donor characteristics for the immuno-FISH cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAge at death (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePMI (hrs)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eAge at disease onset (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eDisease duration (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSex (M/F)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMedian [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMedian [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 [63\u0026ndash;75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.1\u0026thinsp;\u0026plusmn;\u0026thinsp;43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.6 [38.6\u0026ndash;96.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8 (53.3%) / 7 (46.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 [63\u0026ndash;72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.8 [36.8\u0026ndash;53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63 [57\u0026ndash;67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6 [5\u0026ndash;7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6 (46.2%) / 7 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOPCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.5 [57.8\u0026ndash;69.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.3\u0026thinsp;\u0026plusmn;\u0026thinsp;21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.5 [58.4\u0026ndash;86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57 [52-61.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7 [6\u0026ndash;10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5 (41.7%) / 7 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eANOVA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eKruskal-Wallis \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eStudent t-test \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eStudent t-test \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eChi-square \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDemographic and sample characteristics of control and MSA subgroups. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (standard deviation) and median [interquartile range]. PMI, post-mortem interval. SND, striatonigral degeneration. OPCA, olivopontocerebellar atrophy. N/A\u0026thinsp;=\u0026thinsp;not applicable.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003cb\u003eReference probe locus exhibits relative genomic stability in MSA compared to controls and also compared to\u003c/b\u003e \u003cb\u003eSNCA\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo assess whether the observed \u003cem\u003eSNCA\u003c/em\u003e CNVs reflect a locus-specific instability rather than a global genomic phenomenon, we omitted the α-synuclein staining and used a reference probe targeting chromosome 7 for most control experiments (n\u0026thinsp;=\u0026thinsp;29), and a subset of MSA (n\u0026thinsp;=\u0026thinsp;6) (representative images in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). SOX10⁺ reference gains were rare and comparable between MSA and controls (median 0% for controls, 0.5% for MSA, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) as were SOX10⁻ gains (median 0% for both, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Reference losses were higher but also showed no significant differences between MSA and controls for SOX10⁺ cells (median 3.4% vs. 3.0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) or SOX10⁻ cells (median 4.7% vs. 3.3%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Within SOX10⁺ cells, gains of both probes were found in only one cell in the MSA case and none in the control group. Among SOX10⁻ cells, gains of both probes were identified in a small number of control cells and were not detected in MSA. The median proportions of cells carrying both-probe losses were higher than for gains but were comparable between MSA and controls (SOX10⁺ = 1.2% vs 1.7%, SOX10⁻ = 1.3% vs 1.7%).\u003c/p\u003e \u003cp\u003eNext, to directly compare \u003cem\u003eSNCA\u003c/em\u003e with the reference locus, we performed paired analyses within the same case and region. In controls, \u003cem\u003eSNCA\u003c/em\u003e gains were significantly more frequent than reference gains in both SOX10\u003csup\u003e+\u003c/sup\u003e (1.9% vs 0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) and SOX10⁻ populations (2.9% vs 0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). In MSA, the same trend was observed in SOX10\u003csup\u003e+\u003c/sup\u003e gains, though the difference did not reach significance after correction (6.7% vs 0.5%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). There was no difference between SOX10⁻ \u003cem\u003eSNCA\u003c/em\u003e and reference gains (1.7 vs 0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). A similar pattern was observed for losses. In controls, \u003cem\u003eSNCA\u003c/em\u003e losses were significantly more frequent than reference losses in both SOX10⁺ (median\u0026thinsp;=\u0026thinsp;6.3% vs. 3.0%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) and SOX10⁻ populations (median\u0026thinsp;=\u0026thinsp;7.5% vs. 3.3%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). In MSA, \u003cem\u003eSNCA\u003c/em\u003e losses were likewise higher relative to reference losses in SOX10⁺ cells (median\u0026thinsp;=\u0026thinsp;12.0% vs. 3.4%) though this did not reach significance (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Similarly, in SOX10⁻ cells there was an increase in \u003cem\u003eSNCA\u003c/em\u003e losses compared to the reference though this was non-significant (median\u0026thinsp;=\u0026thinsp;13.1% vs. 4.7%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Overall, these results support the relative genomic stability of the reference probe locus, consistent with our previous findings [14, 38, 40] and indicate that CNVs are preferentially enriched at the \u003cem\u003eSNCA\u003c/em\u003e locus, including both gains and losses in controls.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSomatic\u003c/b\u003e \u003cb\u003eSNCA\u003c/b\u003e \u003cb\u003eGains in Oligodendrocytes Are Most Enriched in Severely Affected MSA Regions and Correlate with α-Synuclein Inclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGiven the distinct regional patterns of pathology in MSA subtypes, with predominant involvement of the putamen in SND, the cerebellum in OPCA, and the substantia nigra in both, we next assessed whether the frequency of somatic \u003cem\u003eSNCA\u003c/em\u003e gains in oligodendrocytes varies across these regions, as we had found in similar work without cell type characterisation [14] (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). In the OPCA subtype, significantly higher proportions of SOX10⁺ \u003cem\u003eSNCA\u003c/em\u003e gains were observed compared to controls in all three regions examined: cerebellum (median 8.7% vs. 3.0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), putamen (9.5% vs. 2.0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), and substantia nigra (8.4% vs. 2.4%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), In the SND subtype compared to controls, significant increases were observed in the putamen (7.3% vs. 2.0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01) and substantia nigra (6.4% vs. 2.4%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), but not in the cerebellum (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.27). When comparing \u003cem\u003eSNCA\u003c/em\u003e oligodendrocyte gain frequencies in a given region between MSA subtypes, we noted a 2.2-fold higher difference in OPCA cerebellum compared to SND cerebellum (8.7% vs 3.9%), however this was non-significant after correction (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). We noted no difference between SND and OPCA putamen (7.3% vs 9.5%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1). We next compared differentially affected regions within each MSA type. Within the SND group, we compared the putamen and cerebellum which revealed a 1.9-fold increase in SOX10⁺ gains in the putamen (7.3 vs 3.9%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). Within the OPCA group, there was no difference between the cerebellum and putamen (8.7% vs 9.5%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.40).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe relative enrichment of gains in the putamen compared to the cerebellum in SND, but lack of regional differences in SOX10⁺ \u003cem\u003eSNCA\u003c/em\u003e gains in OPCA, could suggest that our OPCA cohort had a less pronounced cerebellar predominance, with the putamen affected almost to the same extent. To assess this, we compared the proportion of SOX10⁺ α-synuclein⁺ cells in preferentially affected regions (OPCA: cerebellum; SND: putamen) versus lesser affected regions (OPCA: putamen; SND: cerebellum) (Supplementary Fig.\u0026nbsp;3). In OPCA cases, the median percentage of SOX10⁺ inclusions was 26.1% in the cerebellum and 17.7% in the putamen, reflecting a 1.5-fold difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12). In contrast, SND cases exhibited a more pronounced 3.1-fold regional difference, with median values of 35.9% in the putamen and 11.5% in the cerebellum (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07). These findings demonstrate that our OPCA cohort has more regionally extensive pathology than SND, and therefore regional patterns of CNVs, if related to disease, would be expected primarily in SND.\u003c/p\u003e \u003cp\u003eNext, we performed the same analysis for SOX10⁻ cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Significant differences in median percentages of gains were observed in the cerebellum and putamen of the OPCA group compared to controls (cerebellum: 7.9% vs. 3.2%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03; putamen: 8.3% vs. 2.3%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02). In the SND group, the difference between the putamen was not significant (5.7% vs. 2.3%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). A significant difference was observed in the cerebellum between OPCA and SND cases (7.9% vs 0%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), whereas no significant difference was found in the putamen. Interestingly, although the substantia nigra showed significant increases in SOX10\u003csup\u003e+\u003c/sup\u003e cells, there were no group differences for SOX10⁻ gains. Within each MSA subtype, we noted no differences across any of the regions (OPCA: ANOVA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.48; SND: Kruskal-Wallis \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21). These results reflect a similar but less pronounced regional trend for \u003cem\u003eSNCA\u003c/em\u003e gains in SOX10⁻ cells as there are for \u003cem\u003eSNCA\u003c/em\u003e gains in oligodendrocytes.\u003c/p\u003e \u003cp\u003eNext, to determine whether \u003cem\u003eSNCA\u003c/em\u003e gains in oligodendrocytes are associated with an increased risk of α-synuclein pathology at the single-cell level, we compared the proportion of SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes containing inclusions between cells with a \u003cem\u003eSNCA\u003c/em\u003e gain and those with copy number 2, stratified by brain region and MSA subtype (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This revealed a significant relative risk (RR) for presence of an α-synuclein inclusion with an oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gain in the preferentially affected region of each subtype (OPCA cerebellum, RR: 2.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, SND putamen. RR: 2.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and the substantia nigra (OPCA RR: 2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001; SND RR 1.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046), but not the less affected region in each MSA subtype (OPCA putamen, RR\u0026thinsp;=\u0026thinsp;1.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.63; SND cerebellum: RR\u0026thinsp;=\u0026thinsp;0.3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07). These findings support the hypothesis that \u003cem\u003eSNCA\u003c/em\u003e gains increase the susceptibility of individual oligodendrocytes to inclusion formation in predominantly affected regions. Consistent with this, the regional frequency of oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains was significantly correlated with the overall burden of GCIs in the most affected regions of each MSA subtype (rho\u0026thinsp;=\u0026thinsp;0.49, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), supporting a role for \u003cem\u003eSNCA\u003c/em\u003e gains in determining the regional distribution of pathology.\u003c/p\u003e \u003cp\u003eRecently, evidence suggested that neuronal inclusions may also be a key driver of early MSA pathogenesis [64]. We therefore additionally quantified the RR of \u003cem\u003eSNCA\u003c/em\u003e gains in inclusions within SOX10⁻ cells (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with the limitation that SOX10⁻ cells comprise a heterogeneous mix of cell types, likely neuronal in inclusion-bearing cells, but more diverse among non-inclusion-bearing cells. This analysis revealed a significant RR of 3.6 (p\u0026thinsp;=\u0026thinsp;0.002) for inclusions in SOX10⁻ cells with \u003cem\u003eSNCA\u003c/em\u003e gains in the cerebellum of OPCA cases. No other regions in OPCA or any regions in SND showed significant RR. However the low number of inclusion-bearing SOX10⁻ cells may have contributed to the lack of significance elsewhere.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative risk for α-synuclein inclusions in cells with and without somatic \u003cem\u003eSNCA\u003c/em\u003e gains.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMSA subtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eGains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCN2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eaSyn+\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eaSyn+\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eSOX10\u003csup\u003e+\u003c/sup\u003ecells\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCerebellum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.7\u0026ndash;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.07\u0026ndash;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePutamen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6\u0026ndash;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.7\u0026ndash;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.3\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.046*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSOX10⁻ cells\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCerebellum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.6\u0026ndash;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.1\u0026ndash;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePutamen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.1\u0026ndash;5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.2\u0026ndash;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6\u0026ndash;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05\u0026ndash;13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSOX10\u003csup\u003e+\u003c/sup\u003e and SOX10⁻ cells shown separately. The RR estimates with 95% confidence intervals (CI) and corresponding p-values are indicated. Statistically significant RR p-values (\u0026lt;\u0026thinsp;0.05) are highlighted with an asterisk (*).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSomatic\u003c/b\u003e \u003cb\u003eSNCA\u003c/b\u003e \u003cb\u003elosses show widespread regional distributions and relative risk of α-synuclein inclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHaving established overall \u003cem\u003eSNCA\u003c/em\u003e losses in MSA SOX10⁺ oligodendrocytes and SOX10⁻ cells, we next compared their levels across the cerebellum, putamen, and substantia nigra among OPCA, SND, and control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In SOX10⁺ cells, \u003cem\u003eSNCA\u003c/em\u003e losses were significantly more frequent in the cerebellum of OPCA cases (median 15.4%) and SND cases (13.0%) compared with controls (6.7%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, respectively). In the putamen, both OPCA (15.0%) and SND (13.7%) showed increased \u003cem\u003eSNCA\u003c/em\u003e losses versus controls (6.4%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01, respectively). In the substantia nigra, we observed a significant difference between SND and control (11.9% vs 6.5%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) but not OPCA (8.0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.72). Comparisons between SND and OPCA cases revealed no significant differences across any of the regions. Moreover, region-wise comparisons within each MSA subtype showed no significant differences (Kruskal-Wallis: OPCA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06; SND \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.77). For SOX10⁻ cells, \u003cem\u003eSNCA\u003c/em\u003e losses were significantly elevated in the cerebellum of SND (14.7%) compared to controls (4.3%, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), whereas the excess of OPCA losses was not significant (10.9%; adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1). In the putamen, \u003cem\u003eSNCA\u003c/em\u003e loss frequencies did not differ significantly between controls and either MSA subtype (controls: 8.8%; OPCA: 11.1%; SND: 15.6%). Similarly, the substantia nigra showed no significant group differences (SND: 10.5%; OPCA: 14.1%; controls: 9.1%). \u003cem\u003eSNCA\u003c/em\u003e loss frequencies were also comparable across regions within each MSA subtype (Kruskal-Wallis: OPCA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.36; SND \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.81). These results indicate that \u003cem\u003eSNCA\u003c/em\u003e losses in MSA do not show a clear regional predilection based on differential regional involvement in each subtype.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs we had shown a relationship of \u003cem\u003eSNCA\u003c/em\u003e gains with α-synuclein inclusions at the single cell level, we next assessed this for \u003cem\u003eSNCA\u003c/em\u003e losses. At the single-cell level, a significantly increased RR of \u003cem\u003eSNCA\u003c/em\u003e loss in oligodendrocytes with inclusions was observed in the substantia nigra of both MSA subtypes (RR 1.9, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003 SND, RR 2 OPCA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0008) and SND putamen (RR 1.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), however this was not observed in the OPCA cerebellum (RR 1.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As for non-oligodendrocytes, there was significant RR of \u003cem\u003eSNCA\u003c/em\u003e loss in cells with inclusions only in OPCA substantia nigra (RR 3.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), although there was a possible increased risk in all regions (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Combining all regions together leads to an overall RR for both SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes (OPCA RR: 1.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004; SND RR 1.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0007) and SOX10⁻ cells (OPCA RR: 2.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0006; SND RR 1.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07). These results suggest that, like \u003cem\u003eSNCA\u003c/em\u003e gains, losses are also associated with inclusions, but in a more widespread manner, without the clear cell-type and regional predilection seen for \u003cem\u003eSNCA\u003c/em\u003e gains.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative risk for α-synuclein inclusions in cells with and without somatic \u003cem\u003eSNCA\u003c/em\u003e losses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMSA subtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eLosses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCN2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eaSyn+\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eaSyn+\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSOX10\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e\u003cb\u003ecells\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCerebellum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.7\u0026ndash;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9\u0026ndash;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePutamen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.7\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.3\u0026ndash;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSOX10⁻ cells\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCerebellum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9\u0026ndash;5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9\u0026ndash;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePutamen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.5\u0026ndash;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOPCA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4\u0026ndash;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.7\u0026ndash;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe RR estimates with 95% confidence intervals (CI) and corresponding p-values are indicated. Statistically significant RR p-values (\u0026lt;\u0026thinsp;0.05) are highlighted with an asterisk (*).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSNCA\u003c/b\u003e \u003cb\u003egains reflect an intrinsic case-level propensity for gains in other cell types and other brain regions associated with younger age of disease onset\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAs we had seen apparent inter-individual variability in our CNV analysis, we explored whether this variability reflects a case-level propensity rather than being restricted to region-specific pathology. We first examined within-individual patterns of oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains across brain regions by performing pairwise Spearman\u0026rsquo;s rank correlation analyses between the most and lesser affected brain regions within each case, revealing a significant positive correlation (rho\u0026thinsp;=\u0026thinsp;0.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). To determine whether cases with higher mosaicism in oligodendrocytes also had higher mosaicism in other cell types, we compared the frequency of \u003cem\u003eSNCA\u003c/em\u003e gains in SOX10⁺ and SOX10⁻ cells across all regions, which also showed a significant positive correlation in MSA (rho\u0026thinsp;=\u0026thinsp;0.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb) but not in controls (rho\u0026thinsp;=\u0026thinsp;0.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2). Taken together, this supports the idea that \u003cem\u003eSNCA\u003c/em\u003e gains may represent an intrinsic, case-level tendency in MSA, across regions and cell types. We performed the same analysis for \u003cem\u003eSNCA\u003c/em\u003e losses. No significant correlations were observed between SOX10⁺ and SOX10⁻ cells (rho = -0.002, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1). Losses did, however, show a strong correlation between the most and lesser affected regions (rho\u0026thinsp;=\u0026thinsp;0.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003cp\u003eGiven the previous observation in PD of a negative correlation between age of onset and \u003cem\u003eSNCA\u003c/em\u003e gains in the key affected region, the substantia nigra, and cell type (dopaminergic neurons) [38] we wondered whether such a relationship might exist for MSA. We investigated whether SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains were associated with age of onset by taking the average percentage per case across the regions analysed. This revealed a significant negative correlation (rho = -0.45, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) for age of disease onset (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), which was not observed for SOX10⁻ \u003cem\u003eSNCA\u003c/em\u003e gains (rho = -0.12, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.58) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). There was no significant correlation with age of death (rho = -0.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09), disease duration (rho\u0026thinsp;=\u0026thinsp;0.10, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.63), or PMI (rho\u0026thinsp;=\u0026thinsp;0.27, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19). We did not detect any significant associations between \u003cem\u003eSNCA\u003c/em\u003e losses in SOX10\u003csup\u003e+\u003c/sup\u003e and SOX10⁻ cells and these clinical parameters (Supplementary Table\u0026nbsp;3). These results suggests that oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains, but not \u003cem\u003eSNCA\u003c/em\u003e gains or losses in SOX10⁻ cells, may have a role in determining onset age.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eDNA double-stranded breaks are enriched in MSA oligodendrocytes and are associated with α-synuclein pathology\u003c/h3\u003e\n\u003cp\u003eTo investigate whether DSBs are associated with MSA pathology, we performed immunofluorescence staining for γH2AX phosphorylated at Ser139, an established marker of DSBs [32], in at least one region from three controls, three SND cases, and five OPCA cases (demographics summarised in Supplementary Table\u0026nbsp;4). Subsets of experiments included γH2AX with either α-synuclein or SOX10 (Supplementary Table\u0026nbsp;5), as simultaneous detection of all three markers was not possible due to species overlap and secondary antibody compatibility. We observed two γH2AX staining patterns, diffuse pan-nuclear staining and bright foci (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Pan-nuclear γH2AX signalling has been attributed to clustered DNA damage associated with several pathogenic cellular responses such as apoptosis and replication stress [12, 35, 37], as well as more non-specific physiological responses such as increased cellular activity [50]. Accordingly, we focused on analysing the discrete γH2AX foci, irrespective of pan-nuclear staining, as these are more reliable indicators of an active downstream DNA damage response.\u003c/p\u003e \u003cp\u003eFirst, to determine if the DSB response is altered in MSA compared to controls, we classified cells with one or more foci as γH2AX\u003csup\u003e+\u003c/sup\u003e. Across all brain regions analysed, the median percentage of γH2AX\u003csup\u003e+\u003c/sup\u003e cells was significantly higher in MSA than in controls (6.0% vs 2.2%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb), indicating an increase in DNA damage response activity. To identify the affected cell populations, we performed an immunofluorescence experiment with SOX10 on two controls (cerebellum and SN from one, putamen from the other), two OPCA (cerebellum or SN from each) and two SND (cerebellum and SN from both). This revealed a significant enrichment of DSBs in oligodendrocytes in MSA versus controls (14.4% vs 5.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec) indicating that DSBs are present in cell types known to be vulnerable in MSA. We also noted a slightly higher level of γH2AX\u003csup\u003e+\u003c/sup\u003e in SOX10⁻ cells than in controls (3.1% vs 1.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed), however this difference was non-significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.30). This pattern suggests that the DSB response is enriched within oligodendroglial populations.\u003c/p\u003e \u003cp\u003eWe next assessed whether DSB accumulation was linked to α-synuclein pathology. Paired comparisons revealed significantly more γH2AX foci in α-synuclein+ nuclei than α-synuclein\u0026ndash; nuclei (22.2% vs 14.9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee), suggesting a strong association between α-synuclein aggregation and DSB burden at the single-cell level. This finding is consistent with previous reports in DLB, where γH2AX accumulation and p53 activation occur in neurons with nuclear α-synuclein [26]. Finally, we examined whether DSB burden varied across brain regions with differential involvement in MSA. Due to the small number of paired samples, statistical comparisons were performed at the group level rather than within-case pairs. Overall, γH2AX levels were 3.7-fold higher in the more affected regions compared with less affected regions (18.8% vs 5.1%) although this did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.11).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we build upon growing evidence implicating somatic \u003cem\u003eSNCA\u003c/em\u003e copy number gains in MSA by defining their cellular distribution, regional patterns, and relationship to \u0026alpha;-synuclein inclusions. We show that \u003cem\u003eSNCA\u003c/em\u003e gains are increased in MSA relative to controls, particularly in SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes, the glial cell type predominantly affected by \u0026alpha;-synuclein pathology. Within each subtype, oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains tend to be high in regions that are selectively vulnerable, namely the cerebellum in OPCA and putamen in SND, and the substantia nigra in both. At the single-cell level, oligodendrocyte gains are associated with a 2-fold increased relative risk for \u0026alpha;-synuclein inclusions in affected regions, an association that was reflected at the regional level, where the frequency of gains correlated with the overall burden of \u0026alpha;-synuclein pathology. These results, taken together with the association between higher oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gain burden and earlier age of disease onset, are supportive of a role in MSA pathogenesis, possibly by locally raising the intracellular \u0026alpha;-synuclein to pathogenic thresholds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe regional distribution of oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains differ between MSA subtypes. In SND, gains are enriched in the putamen relative to the cerebellum, consistent with the established regional predilection of pathology in this subtype. In contrast, in OPCA, oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains are present at comparable levels in the cerebellum and putamen. In line with this, we found that the burden of GCIs in our cohort is 3-fold higher in SND in the putamen compared to the cerebellum, but only 1.5-fold higher in OPCA in the cerebellum compared to putamen. This may reflect the broader regional pathology seen in OPCA, where severe cerebellar and putaminal involvement often coexist [20], although, we cannot exclude sampling bias or small sample size effects contributing to the pattern observed in our samples.\u003c/p\u003e\n\u003cp\u003eWe also detect excess gains in SOX10⁻ cells consistent with our prior reports of neuronal \u003cem\u003eSNCA\u003c/em\u003e mosaicism in MSA cingulate cortex and substantia nigra [38, 40] which may also contribute to disease pathogenesis. Neuronal inclusions are becoming more widely recognised as early events in MSA pathogenesis [64]. However, as we did not include neuronal markers in the present study, we cannot definitively assign SOX10⁻ cells with inclusions to a neuronal lineage. Further experiments using neuronal markers with \u0026alpha;-synuclein would be necessary to assess this.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCase-level analyses reveal that the level of \u003cem\u003eSNCA\u003c/em\u003e gains in MSA is positively correlated across other brain regions and between SOX10\u003csup\u003e+\u003c/sup\u003e oligodendrocytes and SOX10⁻ cells within the same individual, suggesting that these somatic gains reflect an intrinsic, case-specific propensity that is not observed in controls. These relationships may be consistent with an early clonal origin that produces descendant cells across multiple regions or cell types, supporting a model in which a subset of MSA patients may have pre-existing somatic \u003cem\u003eSNCA\u003c/em\u003e mosaicism for gains that increases the likelihood of developing \u0026alpha;-synuclein aggregation in later life. However, we cannot rule out the other possibility of a general increased susceptibility to \u003cem\u003eSNCA\u003c/em\u003e copy number variation within MSA, in which case individual cells may carry unique rather than shared CNVs, with different size and distinct breakpoints. While the former could be characterised fully by deep long read whole genome sequencing (WGS), the latter would require single cell WGS. This is presently limited generally to megabase-scale CNVs [21] and could thus miss smaller events, although we did detect one in our pilot MSA single cell WGS study [40]. Long read single cell WGS could detect events of all sizes, and was recently reported in the brain in a small study including MSA [19]. While these findings strengthen the case for a pathogenic role of somatic \u003cem\u003eSNCA\u003c/em\u003e gains in MSA, our protocol on isolated nuclei also allowed the characterisation of somatic \u003cem\u003eSNCA\u003c/em\u003e losses. Losses are higher in MSA, and exhibit a more widespread distribution across cell-types and regions, with a variable but overall positive association with \u0026alpha;-synuclein pathology, but no correlation with onset age or disease duration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCollectively, these observations raise important questions regarding the timing and origin of these CNVs, which cannot be resolved with the current data. Gains and losses can arise through distinct mechanisms. Large-scale gains are most likely to reflect mitotic errors such as chromosome mis-segregation or DNA replication defects, and are typically clonal [5, 16]. This raises the likelihood that such gains occur prior to MSA pathogenesis, as the cells known to form \u0026alpha;-synuclein inclusions are mostly post-mitotic, although we cannot exclude their emergence during low-level clonal expansion of glial progenitors in disease progression. We also cannot rule out that gains arise secondarily in post-mitotic cells, potentially through rare mechanisms such as cell-cycle re-entry and localised DNA synthesis, which has been reported in other neurodegenerative diseases [39, 48]. Importantly, gains and losses may sometimes occur concomitantly during non-allelic homologous recombination (NAHR), resulting in one daughter cell with a duplication and another with a reciprocal deletion [49], a process that could contribute to the mixed patterns of CNVs we observe. A somatic \u003cem\u003eSNCA\u003c/em\u003e loss on the other hand could occur post-mitotically secondary to DNA damage in the form of DSBs, rather than a primary event. DSBs can lead to widespread genomic deletions, which is particularly relevant in the brain as the main pathway for DSB repair in post-mitotic cells, NHEJ, is known to be error-prone [34, 44]. To explore this possibility, and to contextualise the \u003cem\u003eSNCA\u003c/em\u003e CNV landscape within a broader framework of possible genomic instability, we explored DNA DSBs using \u0026gamma;H2AX. We found widespread DNA DSB accumulation in MSA, with \u0026gamma;H2AX foci enriched in SOX10 oligodendrocytes, and in cells with \u0026alpha;-synuclein inclusions. This finding suggests an association between \u0026alpha;-synuclein aggregation and activation of DNA DSB repair within the oligodendroglial population in MSA. This may also occur in neurons, as shown in Lewy body diseases [26, 56], although we cannot determine this in MSA, as we did not separate neurons from other SOX10⁻ cells. We therefore hypothesise that somatic \u003cem\u003eSNCA\u003c/em\u003e losses are secondary to disease progression, and may result from mis-repaired DSBs. To conclusively determine, however, whether \u003cem\u003eSNCA\u003c/em\u003e losses results from DSBs, would require combining FISH with \u0026gamma;H2AX immunofluorescence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis leads to the question of whether the propensity of the \u003cem\u003eSNCA\u003c/em\u003e gene to acquire CNVs in MSA reflects specific instability of that gene, which has been suggested to be within a fragile site [47], or whether genome-wide somatic CNVs, known to occur in healthy brain cells [33], are enriched in MSA. The overall higher frequency of \u003cem\u003eSNCA\u003c/em\u003e CNVs in controls relative to the reference probe suggests that the \u003cem\u003eSNCA\u003c/em\u003e locus itself may be inherently prone to structural instability, independent of disease status, consistent with previous work showing minimal gains of other reference probes [14, 38]. The reference probe in our study was equally affected by CNVs (predominantly losses) in MSA and controls, arguing against an overall tendency for CNVs in MSA. Our pilot single cell WGS of large CNVs genome-wide did detect them in ~30% of MSA cells, including a putaminal neuron with extensive nuclear inclusions and large-scale genomic losses encompassing \u003cem\u003eSNCA\u003c/em\u003e, likely to have arisen by NHEJ [40]. Larger scWGS will be required, however, to determine if genome-wide CNVs are enriched in MSA.\u003c/p\u003e\n\u003cp\u003eAnother limitation is that, while we propose sustained overexpression of \u003cem\u003eSNCA\u003c/em\u003e mRNA as the mechanism by which gains contribute to pathogenesis, we have not demonstrated this. An increase in \u003cem\u003eSNCA\u003c/em\u003e mRNA in MSA oligodendrocytes has been reported previously through quantitative reverse transcription PCR, though these results were non-significant [2]. More recently, a higher level of \u003cem\u003eSNCA\u003c/em\u003e transcripts was found in oligodendrocytes with inclusions using RNAScope, though the numbers of cases analysed were limited [25]. It thus remains unclear whether \u003cem\u003eSNCA\u003c/em\u003e mRNA is increased in MSA, especially across individual cell types. Ideally, methods assessing DNA and RNA in the same cell would clarify these relationships. While \u003cem\u003ein situ\u003c/em\u003e approaches are limited by DNA-RNA cross-reactivity, sequencing of the DNA and RNA of the same nucleus [60], although challenging, is becoming possible, including in the human brain [8]. Nonetheless, RNA measurements still only represent a snapshot at the point of death of cells surviving in a disease environment, rather than reflect long-term expression patterns, and are influenced by both pre-mortem and post-mortem changes [11, 58].\u003c/p\u003e\n\u003cp\u003eWhile our findings strongly implicate somatic \u003cem\u003eSNCA\u003c/em\u003e gains as contributors to MSA pathology, it is important to acknowledge that these gains may represent only one facet of a multifactorial disease. Somatic mosaicism may serve as a \u0026ldquo;first hit\u0026rdquo; or modifier that increases vulnerability to \u0026alpha;-synuclein aggregation. Supporting this, we did not find an association of \u003cem\u003eSNCA\u003c/em\u003e gains with \u0026alpha;-synuclein inclusions in the OPCA putamen, despite high levels of \u003cem\u003eSNCA\u003c/em\u003e gains. Furthermore, both somatic \u003cem\u003eSNCA\u003c/em\u003e gains and losses have been identified in neurologically healthy individuals from the UK Biobank data, though some of these had reported blood-based cancers, therefore it is unclear if they would be found also in the brain, and others were younger than the typical age of onset for MSA or PD [4]. Similarly, individuals with germline \u003cem\u003eSNCA\u003c/em\u003e multiplications typically develop a clinical picture resembling PD rather than MSA, and do not always contain GCIs [24]. These observations suggest that \u003cem\u003eSNCA\u003c/em\u003e copy number variation alone is unlikely to be sufficient to cause MSA, but may act as a contributory or permissive factor whose pathogenicity depends on additional influences, such as cell-type\u0026ndash;specific stress, environmental risk factors, coexisting inherited as yet unidentified genetic variants, or indeed other somatic mutations. Such mutations could arise within the brain or originate in the periphery, including in the context of clonal haematopoiesis of indeterminate potential, an age-related process recently reported to be associated with MSA [29].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNonetheless, our findings reinforce the rationale for therapeutic approaches that lower \u0026alpha;-synuclein levels, including antibody-based and antisense strategies already in development [3]. The enrichment of somatic \u003cem\u003eSNCA\u003c/em\u003e gains in affected cells also supports the value of using \u003cem\u003eSNCA\u003c/em\u003e overexpression approaches, either alone or alongside other perturbations, to explore how increased \u0026alpha;-synuclein dosage interacts with additional cellular processes. More broadly, our results point to somatic variation as a contributor to non-heritable genetic risk in MSA and helps advance our understanding of its aetiology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eZane Jaunmuktane is a member of the Acta editorial board, but was not involved in the assessment or decision-making process for this manuscript. The other authors report no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.M. Sample preparation, data collection, statistical analysis, manuscript writing. E.K.E. Experimental supervision and manuscript revision. D.P.R. Experimental supervision and manuscript revision. Z.J. Providing human brain samples and neuropathological characterisation, manuscript revision and supervision of the project. C.P. Conception and design, manuscript revision, and overall supervision of the project.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was funded by the Multiple System Atrophy Trust. We thank the patients and their relatives for their invaluable contribution through brain donation. We thank UCL Queen Square Brain Bank administrative and technical staff for their assistance.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll code used to generate the statistical analyses and figures in this study is available on GitHub at https://github.com/caoimhemorley/somatic-SNCA-CNV-FISH-analysis. All raw cell counts and summarised datasets supporting the findings of this study are provided in the Supplementary Materials. Representative images are included in the figures, and additional raw image data are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbeliovich A, Schmitz Y, Fari\u0026ntilde;as I, Choi-Lundberg D, Ho WH, Castillo PE, Shinsky N, Garcia Verdugo JM, Armanini M, Ryan A, Hynes M, Phillips H, Sulzer D, Rosenthal A (2000) Mice Lacking \u0026alpha;-Synuclein Display Functional Deficits in the Nigrostriatal Dopamine System. Neuron 25:239\u0026ndash;252. doi: 10.1016/S0896-6273(00)80886-7\u003c/li\u003e\n\u003cli\u003eAsi YT, Simpson JE, Heath PR, Wharton SB, Lees AJ, Revesz T, Houlden H, Holton JL (2014) Alpha‐synuclein mRNA expression in oligodendrocytes in MSA. Glia 62:964\u0026ndash;970. doi: 10.1002/glia.22653\u003c/li\u003e\n\u003cli\u003eBendetowicz D, Fabbri M, Sirna F, Fernagut PO, Foubert-Samier A, Saulnier T, Le Traon AP, Proust-Lima C, Rascol O, Meissner WG (2024) Recent Advances in Clinical Trials in Multiple System Atrophy. Curr Neurol Neurosci Rep 24:95\u0026ndash;112. doi: 10.1007/s11910-024-01335-0\u003c/li\u003e\n\u003cli\u003eBlauwendraat C, Makarious MB, Leonard HL, Bandres-Ciga S, Iwaki H, Nalls MA, Noyce AJ, Singleton AB (2021) A population scale analysis of rare SNCA variation in the UK Biobank. Neurobiol Dis 148:105182. doi: 10.1016/j.nbd.2020.105182\u003c/li\u003e\n\u003cli\u003eBurssed B, Zamariolli M, Bellucco FT, Melaragno MI (2022) Mechanisms of structural chromosomal rearrangement formation. 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NPJ Parkinsons Dis 4:18. doi: 10.1038/S41531-018-0054-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aneu","sideBox":"Learn more about [Acta Neuropathologica](https://link.springer.com/journal/401)","snPcode":"401","submissionUrl":"https://submission.springernature.com/new-submission/401/3","title":"Acta Neuropathologica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multiple system atrophy, alpha-synuclein, somatic mutation, CNV, mosaicism, SNCA","lastPublishedDoi":"10.21203/rs.3.rs-8701777/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8701777/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMultiple system atrophy (MSA) is a rapidly progressive synucleinopathy of unknown aetiology with neuronal and oligodendroglial α-synuclein inclusions. We previously reported somatic copy number variants (CNVs), specifically gains, of \u003cem\u003eSNCA\u003c/em\u003e (encoding α-synuclein) in MSA brains. Here, we expand on this work by combining fluorescent \u003cem\u003ein situ\u003c/em\u003e hybridisation for \u003cem\u003eSNCA\u003c/em\u003e on isolated nuclei with α-synuclein and SOX10 immunofluorescence, to assess oligodendrocyte-specific \u003cem\u003eSNCA\u003c/em\u003e gains and losses, and their relationship with inclusions across differentially affected regions in two MSA subtypes: striatonigral degeneration (SND) and olivopontocerebellar atrophy (OPCA). Analysis of 13 SND, 12 OPCA, and 15 control brains demonstrated significantly higher somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs, both gains and losses, in MSA oligodendrocytes compared with controls (gains: 6.3% vs 2.0%; losses: 12.5% vs 7.4%,\u003cem\u003e p \u003c/em\u003e\u0026lt; 0.0001 for both). Oligodendrocyte \u003cem\u003eSNCA\u003c/em\u003e gains were high in the preferentially affected regions (putamen in SND, cerebellum in OPCA), where they were associated with a two-fold increased relative risk of α-synuclein inclusions in the same cell (p \u0026lt; 0.0001). Higher gain burden correlated with earlier disease onset (rho = -0.45,\u003cem\u003e p \u003c/em\u003e= 0.03). Oligodendrocyte \u003cem\u003eSNCA \u003c/em\u003elosses, conversely, showed less regional predilection, limited association with inclusions, and no correlation with onset age. As double strand DNA breaks have been reported in Lewy body diseases, and may cause deletions, we used immunofluorescence for γH2AX to explore their prevalence in MSA in a subset of experiments. The proportion of γH2AX-positive cells was significantly higher in MSA than controls, both overall (6.0% vs 2.2%, \u003cem\u003ep \u003c/em\u003e= 0.049) and in oligodendrocytes (14.4% vs 5.5%, p = 0.02), and also in inclusion-bearing cells (22.2% vs 14.9%, p = 0.02). These findings define the oligodendrocyte-specific patterns of somatic \u003cem\u003eSNCA\u003c/em\u003e CNVs in MSA, support a role for gains in MSA pathogenesis, and demonstrate the presence of \u003cem\u003eSNCA\u003c/em\u003elosses and DNA double strand breaks which require further investigation.\u003c/p\u003e","manuscriptTitle":"Oligodendroglial somatic SNCA copy number gains are associated with inclusions and disease onset in multiple system atrophy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 17:55:11","doi":"10.21203/rs.3.rs-8701777/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-22T18:29:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-20T11:35:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-06T00:55:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255098076234065753707826824090611797537","date":"2026-01-29T00:33:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204856916010948237477070372759169245046","date":"2026-01-28T21:19:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T16:02:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-28T15:25:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-28T11:06:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Neuropathologica","date":"2026-01-26T15:06:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aneu","sideBox":"Learn more about [Acta Neuropathologica](https://link.springer.com/journal/401)","snPcode":"401","submissionUrl":"https://submission.springernature.com/new-submission/401/3","title":"Acta Neuropathologica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3134240b-40f1-46eb-ab91-c5da26b6fc3c","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-02-22T18:38:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 17:55:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8701777","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8701777","identity":"rs-8701777","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}