Association of choroid plexus volume with brain atrophy and glucose metabolism in multiple system atrophy

Association of choroid plexus volume with brain atrophy and glucose metabolism 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 Association of choroid plexus volume with brain atrophy and glucose metabolism in multiple system atrophy Chae Jung Park, Yeeun Sun, Hyun-Jae Jeong, Han Kyu Na, So Hoon Yoon, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8240172/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 18 You are reading this latest preprint version Abstract The choroid plexus (CP), a component of the glymphatic system, is essential in homeostasis and producing cerebrospinal fluid. Roles of CP in multiple system atrophy (MSA) remains unclear. This study aimed to investigate the implication of the CP in MSA. This retrospective cross-sectional study included 87 MSA patients who underwent the Unified MSA Rating Scale (UMSARS), brain MRI, and 18 F-fluorodeoxyglucose PET scan, along with 84 healthy controls (HCs). Multivariate linear regression analyses were performed to examine the associations between CP volume (CPV) and UMSARS scores, as well as the volumes and cerebral metabolism. Compared with HCs, MSA had significantly reduced CPV (1.00 ± 0.27 vs. 1.30 ± 0.26, P < 0.001). CPV showed no association with UMSARS, however, it was positively correlated with regional cerebellar volumes. Smaller CPV was also associated with decreased cerebral metabolism in MSA-susceptible regions. Notably, CPV positively correlated with glucose metabolism in the brainstem (β = 0.110, P = 0.003) and cerebellar white matter (β = 0.080, P = 0.004). This study suggests that CPV is positively associated with disease burden in MSA, with CPV decreasing as disease severity increases. Further research is warranted to determine whether CPV could serve as a potential biomarker for MSA. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience multiple system atrophy choroid plexus brain atrophy brain glucose metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The choroid plexus (CP) is a highly vascularized structure located within the ventricles, composed of a network of capillaries lined by specialized epithelial cells. It is the principal source of cerebrospinal fluid (CSF) in the adult brain and plays a critical role in maintaining central nervous system homeostasis​. Through the continuous secretion of CSF (approximately 400–600 mL per day), the CP contributes to regulating intracranial pressure, delivering nutrients and hormones to the brain, and facilitating the clearance of metabolic waste via the glymphatic system 1 . Notably, CP-driven CSF flow is crucial for the glymphatic pathway of waste removal, and disruptions in CSF production can impair the clearance of neurotoxic metabolites​. Recent studies have demonstrated that an increase in CP volume (CPV) is closely associated with reduced glymphatic function 1 – 5 . An emerging body of evidence indicates that CPV is often increased in conditions associated with neurodegeneration, including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis, and frontotemporal dementia 3 , 6 – 8 . Furthermore, our previous studies have demonstrated that enlarged CPV is associated with longitudinal outcome in patients with AD and PD 9,10 . These findings support the notion that the CP undergoes structural changes in response to neurodegenerative pathology, and that CP volumetry may serve as an indirect indicator of disease burden in certain disorders. Multiple system atrophy (MSA) is a rare, rapidly progressive α-synucleinopathy characterized by a combination of parkinsonian features, cerebellar ataxia, autonomic failure, and pyramidal signs​. As in other neurodegenerative diseases, reduced glymphatic function has been reported in MSA; however, research specifically addressing CPV and CP function in this condition remains limited 11 . Given its role in CSF dynamics, waste clearance, and immune cell trafficking, CPV assessment in MSA represents a novel approach to exploring disease pathophysiology. In this study, we examined CPV in patients with MSA compared to healthy controls (HCs), and we further evaluated the relationship between CPV, motor symptoms, and imaging measures of disease severity—specifically, regional brain atrophy and hypometabolism. We hypothesized that the CP is structurally affected in MSA and that CPV correlates with the extent of neurodegeneration, thereby representing a potential imaging biomarker of disease burden. Result Demographic and clinical characteristics of the study participants This study included 87 patients with MSA and 84 HCs (Fig. 1 ). The mean age at the time of magnetic resonance imaging (MRI) was significantly lower in the MSA group compared with HCs, whereas sex distribution did not differ significantly between the groups. Among patients with MSA, the mean disease duration from symptom onset to MRI was 2.29 ± 1.46 years. The average UMSARS scores were 16.21 ± 8.51, 16.39 ± 8.29, and 1.94 ± 1.09 for Parts I, II, and IV, respectively. The cerebellar subtype (MSA-C) was more frequent than the parkinsonian subtype (MSA-P) (55.2% vs. 44.8%). The prevalence of vascular risk factors, including hypertension, diabetes mellitus, and dyslipidemia, did not differ significantly between the MSA and control groups (Table 1 ). Table 1 Demographic and imaging characteristics in patients with MSA and healthy controls Patients with MSA (n = 87) Healthy controls (n = 84) P Demographic characteristics Age at symptom onset, y 60.60 ± 8.80 - NA Age at MRI scan 62.88 ± 8.89 66.48 ± 9.40 0.011 Female 44 (50.6%) 46 (54.8%) 0.693 Symptom duration (onset to MRI scan), y 2.29 ± 1.46 - NA UMSARS Part I 16.21 ± 8.51 - NA Part II 16.39 ± 8.29 - NA Part IV 1.94 ± 1.09 - NA Subtype Parkinsonian type 39 (44.8%) - NA Cerebellar type 48 (55.2%) - NA Vascular risk factors Hypertension 56 (35.6%) 23 (27.4%) 0.319 Diabetes mellitus 17 (19.5%) 8 (9.5%) 0.102 Dyslipidemia 25 (28.7%) 21 (25.0%) 0.705 Volumetric MRI measures CP volume, ratio of ICV × 10 3 1.00 ± 0.27 1.30 ± 0.26 < 0.001 hippocampal volume, ratio of ICV × 10 3 5.21 ± 0.80 5.86 ± 0.57 < 0.001 LV volume, ratio of ICV × 10 3 20.38 ± 9.40 18.32 ± 9.06 0.147 WMH volume, ratio of ICV × 10 3 4.57 ± 6.87 2.76 ± 4.95 0.049 ICV, mL 1512.68 ± 197.84 1365.40 ± 135.42 < 0.001 Values are expressed as mean ± standard deviation or number (percentage). CP = choroid plexus; ICV = intracranial volume; LV = lateral ventricle; MRI = magnetic resonance imaging; MSA = multiple system atrophy; NA = not applicable/available; UMSARS = Unified Multiple System Atrophy Rating Scale; WMH = white matter hyperintensity. Imaging characteristics of the participants Volumetric MRI revealed that CPV was significantly smaller in the MSA group compared with controls. Hippocampal volume was also significantly reduced in patients with MSA. Although lateral ventricle volume (LVV) tended to be larger in the MSA group, the difference did not reach statistical significance. white matter hyperintensity volume (WMHV) was significantly greater in patients with. Notably, total volumes of intracranium (ICV) was markedly higher in the MSA group compared with controls (Table 1 ). When stratified by MSA subtype, patients with both MSA-P and MSA-C exhibited significantly reduced CPV and hippocampal volume compared with HCs, with no significant differences observed between the two subtypes. In contrast, no significant differences were observed in LVV or WMHV among the MSA-C, MSA-P, and control groups (Fig. 2 ). After adjusting for age at MRI scan and sex, multivariate linear regression confirmed that CPV remained significantly lower in both MSA-P (β = − 0.240, P < 0.001) and MSA-C (β = − 0.243, P < 0.001) compared with controls. Hippocampal volume was also significantly reduced in both subtypes, while LVV and WMHV were significantly higher, particularly in MSA-P. These findings indicate that volumetric alterations in MSA remain robust after controlling for demographic factors (Table 2 ). Table 2 Multivariate linear regression analysis for CPV in relation to brain volume measures CPV LVV Hippocampal volume WMHV Β SE t P β SE t P β SE t P β SE t P Intercept 0.366 0.134 2.735 0.007 -17.927 4.598 -3.899 < 0.001 7.887 0.339 23.27 < 0.001 -20.29 3.005 -6.752 < 0.001 Age 0.016 0.002 8.875 < 0.001 0.590 0.063 9.356 < 0.001 -0.041 0.005 -8.735 < 0.001 0.374 0.041 9.090 < 0.001 Sex -0.096 0.034 -2.871 0.005 -1.902 1.155 -1.646 0.102 0.433 0.085 5.088 < 0.001 -1.185 0.755 -1.569 0.119 Group HC Ref. Ref. Ref. Ref. MSA-P -0.240 0.042 -5.680 < 0.001 5.247 1.455 3.606 < 0.001 -0.899 0.107 -8.384 < 0.001 4.156 0.951 4.370 < 0.001 MSA-C -0.243 0.040 -6.007 < 0.001 3.165 1.388 2.280 0.024 -0.680 0.102 -6.648 < 0.001 2.258 0.907 2.489 0.014 Results of multivariate linear regression analysis for the CPV, LVV, hippocampal volume, or WMHV after controlling for age at MRI scan, sex, and group. CPV = choroid plexus volume; LVV = lateral ventricle volume; MRI = magnetic resonance imaging; HC = healthy control; MSA-P = multiple system atrophy-parkinsonian type; multiple system atrophy-cerebellar type; WMHV = white matter hyperintensity volume. Partial correlation analyses within the MSA group, controlling for age at MRI scan, sex, and symptom duration, revealed a significant positive association between CPV and LVV (r = 0.600, P < 0.001). In contrast, CPV was not significantly associated with hippocampal volume (r = − 0.204, P = 0.062) or WMHV (r = 0.100, P = 0.365). Given the significant association between CPV and LVV, subsequent analyses were adjusted for LVV as a covariate. Relationship between CPV and regional brain atrophy In the overall MSA cohort, CPV demonstrated significant positive correlations with both left and right cerebellar hemispheric structures, as well as midline vermian lobules, after adjusting for age, sex, symptom duration, and LVV. On the left side, CPV was positively associated with cerebellar white matter, lobules I–IV, lobule V, lobule VI, and lobule VIIIb. On the right side, significant associations were observed with cerebellar white matter, lobules I–IV, lobule V, and lobule VIIIb. Additionally, CPV was positively correlated with midline vermian structures, including vermis VI, VII, VIII, IX, and X. These associations remained statistically significant after false discovery rate (FDR) correction for multiple comparisons. In contrast, no significant associations were found between CPV and brainstem structures, including the pons and medulla. In subgroup analyses, these positive correlations were predominantly observed in patients with MSA-C, whereas associations in patients with MSA-P were weaker and generally not statistically significant (Fig. 3 ; supplementary Table 2). For other subcortical structures, multivariate linear regression analysis showed that CPV was positively associated with bilateral ventral diencephalon volume in the overall MSA group, and these associations remained significant after FDR correction. This relationship was also observed in the MSA-C subgroup, whereas no significant associations were observed in the MSA-P subgroup. No other subcortical structures, including the caudate, putamen, pallidum, thalamus, or nucleus accumbens, demonstrated significant associations with CPV after multiple comparisons (supplemental Table 3). Relationship between CPV and regional brain glucose metabolism Multivariate linear regression analysis revealed that higher CPV was significantly associated with increased regional glucose metabolism in several brain regions, after adjusting for age at MRI, sex, symptom duration, and LVV (supplemental Table 4). In the overall MSA cohort, CPV showed significant positive associations with Cerebral Metabolic Rate for Glucose (CMRglu) in the brainstem, cerebellar white matter, and bilateral thalamic and ventral diencephalic regions, including the left thalamus, right thalamus, left ventral diencephalon, and right ventral diencephalon. These associations remained significant after FDR correction for multiple comparisons. In subgroup analyses, CPV was positively associated with CMRglu in the brainstem and cerebellar cortex in the MSA-P subgroup, and with the brainstem, cerebellar white matter, left thalamus, and right ventral diencephalon in the MSA-C subgroup. However, none of these associations in the subtype analyses remained significant after FDR correction. No significant associations were observed between CPV and CMRglu in basal ganglia structures, including the caudate, putamen, pallidum, and nucleus accumbens, in any group (Fig. 4 ; supplemental Table 4). Relationship between CPV and motor symptoms In multivariate linear regression analyses, CPV was not significantly associated with clinical severity, as measured by either individual or total the Unified MSA Rating Scale (UMSARS) scores, in the overall cohort or within MSA subtypes (supplementary Table 5). Discussion In this study, we investigated the association between CPV, brain atrophy patterns, and cerebral metabolism in patients with MSA. The main findings were as follows: (1) CPV was reduced in patients with MSA compared to HCs. CPV in both the MSA-P and MSA-C subtypes was smaller than in HCs, although no inter-subtype differences were observed; (2) CPV was positively associated with regional atrophy of subcortical structures, which are particularly vulnerable in MSA; and (3) CPV was positively associated with rCMRglu in MSA-related subcortical structures. Collectively, these findings suggest that CPV is decreased in patients with MSA and is positively associated with MSA-related neurodegeneration, indicating that CP atrophy may reflect disease severity in these patients. We demonstrated that patients with MSA exhibit markedly reduced CPV compared with HCs. This finding stands in contrast to previous observations in other neurodegenerative diseases—notably PD and AD—where the CP has been reported to undergo volumetric enlargement 12 . The identification of CP atrophy in MSA is novel and suggests that the CP may respond differently to neuropathological processes in MSA than in PD or AD. To our knowledge, this is the first evidence that CPV is decreased in a neurodegenerative disorder, underscoring a disease-specific structural alteration that distinguishes MSA from the CP hypertrophy observed in AD, PD, and other neurodegenerative diseases 8 , 9 , 12 – 14 . The discrepant CPV changes observed between MSA and other neurodegenerative disorders likely reflect fundamental differences in underlying disease mechanisms and progression. In AD, CP enlargement and increased perfusion have been suggested as compensatory responses to protein accumulation 15 . whereas in MSA, CP atrophy may instead reflect exhaustion or degeneration. These findings have important implications for understanding the role of the CP in MSA. Similar to AD and PD, MSA is characterized by impaired protein clearance and has been linked to glymphatic system dysfunction 16 . The CP, as the primary source of CSF, is a critical component of the glymphatic clearance pathway, which facilitates the removal of metabolic waste products and aggregated proteins from the brain 17 – 19 . A reduction in CPV could therefore exacerbate glymphatic insufficiency in MSA by limiting CSF production and flow. Diminished CSF turnover may, in turn, hinder the clearance of toxic proteins and accelerate neurodegeneration. Conversely, chronic glymphatic impairment in MSA—with consequent retention of neurotoxic proteins and inflammatory mediators—might contribute to structural damage and atrophy of the CP over time. Thus, a bidirectional relationship may exist whereby CP atrophy and glymphatic dysfunction reinforce one another, creating a vicious cycle of reduced waste clearance and progressive neural injury. Our observation of CPV reduction introduces a new perspective on MSA pathophysiology, supporting the concept that disruption of the cerebral fluid homeostatic systems—of which the CP is an integral component—contributes to neurodegenerative disease progression. While these interpretations remain speculative, they underscore a plausible link between CP structural integrity and the cerebral capacity to maintain homeostasis in the context of MSA's aggressive pathology. In this study, CPV did not correlate with baseline clinical severity of motor symptoms in MSA. The lack of correlation with UMSARS may reflect the scale’s limited sensitivity to CP-related processes 20 . In contrast, CPV in our MSA cohort showed significant positive correlations with neuroimaging biomarkers. Patients with larger CPV exhibited less regional brain atrophy on MRI—particularly in the cerebellar hemispheres and vermis—and higher regional glucose metabolism on 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in areas vulnerable to MSA. In other words, a smaller CPV was associated with more severe neurodegeneration across both structural and metabolic measures. Given that CPV was reduced in patients with MSA compared with HCs, this pattern suggests that CPV may serve as an indirect index of disease burden in MSA. The cerebellum and brainstem are among the regions most affected in MSA, and it was within these areas that CPV correlations were most pronounced. In MSA-C, where ataxia and cerebellar atrophy predominate, the associations between CPV and preserved tissue volume were particularly robust. This may partly reflect differences in regional atrophy patterns; while putaminal and caudate volumes were reduced in MSA, their greater interindividual variability relative to cerebellar and brainstem structures likely attenuated correlations with CPV 21 . In contrast, the more consistent and pronounced posterior fossa atrophy in MSA-C may have facilitated clearer detection of associations between CP and involved structures. A potential interpretation is that CP atrophy progresses in parallel with cerebellar neurodegeneration, potentially due to shared pathogenic mechanisms or localized interactions (e.g., the fourth ventricle CP directly interfaces with cerebellar and brainstem structures). It is conceivable that a more intact CP confers neuroprotective effects, potentially by sustaining adequate CSF production, growth factor secretion, or immune surveillance, thereby mitigating tissue loss in connected regions 22 . Conversely, when CPV is reduced, these supportive functions may be compromised, leading to greater accumulation of pathology and consequent atrophy and hypometabolism in MSA-vulnerable regions. While causality cannot be established from our data, the clear association between higher CPV and better-preserved brain structure and function reinforces the idea that CP integrity is closely linked to overall brain health in MSA. Our cross-sectional baseline analysis may have been underpowered to detect subtle clinical correlations, or the temporal window during which CP changes align with motor symptom progression may be narrow. Future longitudinal studies are needed to determine whether CPV has prognostic value for clinical progression, even if it does not reflect symptom severity at a single time point. This study has some limitations and highlights future directions. First, our analysis was cross-sectional, which limits insight into the temporal dynamics of CP changes in MSA. We cannot determine whether CP atrophy represents a cause or a consequence of advanced neurodegeneration, or how early in the disease course it emerges. Longitudinal studies are needed to track CPV over time in MSA—for instance, to evaluate whether accelerated CPV loss parallels clinical deterioration or whether baseline CPV could stratify patients by prognosis. Second, although no consensus currently exists regarding the optimal reference region for FDG-PET in MSA, we selected the paracentral lobule based on prior findings indicating that its CMRglu is relatively spared in patients with MSA 23 . While the paracentral lobule has previously been used as a reference region in AD studies 24 , this approach has not yet been applied in MSA. Since the choice of reference region can significantly influence the interpretation of regional glucose metabolism, particularly in disorders with widespread neurodegeneration, future work is needed to systematically evaluate and validate optimal normalization strategies for FDG-PET analysis in MSA. Third, given the rarity of MSA, our sample size—although relatively large for an MSA cohort—may still limit generalizability. Our cohort included both MSA-P and MSA-C subtypes across a range of disease durations; while we observed consistent CPV reductions across subtypes, subtle differences may have been overlooked. Replication of our findings in independent MSA cohorts, as well as direct comparisons with other synucleinopathies (e.g., comparing CPV in MSA vs. idiopathic PD directly), would further strengthen the evidence for a unique involvement of the CP in MSA. In summary, we found that CPV was significantly decreased in patients with MSA compared with HCs, a contrasting pattern to that reported in PD and AD 3,18,25,26 . Furthermore, smaller CPVs in MSA were associated with greater brain atrophy and hypometabolism, suggesting that CP atrophy may serve as a marker of higher disease burden. Our findings highlight the CP as an essential and previously under-recognized contributor to MSA pathophysiology. Future studies integrating neuroimaging, biological, and clinical approaches are warranted to validate CPV as a potential imaging biomarker and to elucidate its mechanistic links to neurodegeneration in MSA. Methods Participants We consecutively recruited 87 patients with MSA and 84 HCs from the Movement Disorders Outpatient Clinic of the Yonsei University Health System between 2008 and 2020. Patients with MSA were diagnosed with either clinically established MSA (n = 64) or clinically probable MSA (n = 23), according to the diagnostic criteria for MSA 27 . All patients underwent the Unified MSA Rating Scale (UMSARS; parts I–IV), brain MRI, and FDG-PET scan within 6 months. UMSARS was used to assess disease severity at the time of MRI acquisition. Total UMSARS score was defined as the sum of UMSARS-I (historical), UMSARS-II (motor examination), and UMSARS-IV (global disability scale) subscores. The diagnosis of MSA was further supported by structural and/or functional imaging findings, including atrophy on MRI of the putamen, middle cerebellar peduncle, pons, or cerebellum, as well as hypometabolism on FDG-PET in the putamen, brainstem, or cerebellum. None of the patients carried mutations in the SCA 1, 2, 3, 6, 7, 8, and 17 genes. None of the HCs (n = 84) reported cognitive impairment, and all demonstrated normal cognitive function according to the Korean version of the Mini-Mental State Examination and comprehensive neuropsychological testing. This study was approved by the Institutional Review Board of Yonsei University Severance Hospital (IRB No. 4-2024-1425 for patients with MSA; IRB No. 4-2015-0551 for HCs). All methods involving participants were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki. The requirement for informed consent was waived for patients with MSA due to the retrospective nature of the study; informed consent for participation was obtained from all HCs. MRI acquisition and analysis All scans were acquired with a Philips 3.0T scanner (Philips Intera; Philips Medical System, Best, The Netherlands) with a SENSE head coil (SENSE factor = 2). A high-resolution, T1-weighted MRI volume data set was obtained from all subjects with a 3-dimensional T1-TFE sequence configured with the following acquisition parameters: axial acquisition with a 224 × 256 matrix; 256 × 256 reconstructed matrix with 182 slices; 220-mm field of view; 0.98 × 0.98 × 1.2mm3 voxels; 4.6 ms echo time; 9.6 ms repetition time; 8° flip angle; and 0mm slice gap. We used automated segmentation based on the same method as in our previous study, in which the accuracy of this approach was validated. 12 Automated segmentation of brain regions and the cortical thickness values of each region were extracted using FastSurfer, which is a fast and extensively validated deep-learning pipeline for the fully automated processing of structural human brain MRIs. 28 This software enabled whole-brain segmentation into 95 classes within 50 seconds per subject. The details of this program and its validity have been shown elsewhere ( https://deep-mi.org/research/fastsurfer/ ). A representative automatic segmentation of the CP using FastSurfer is shown in online supplementary Fig. 1. In a subset of 30 patients, we manually segmented the CPV to assess inter-method reliability. One neuroradiologist (C.J.P., with six years of experience) manually segmented the CP in the lateral ventricle in the 3D T1-weighted volumetric images using 3D Slicer version 5.0.3 ( https://www.slicer.org ). From these images, the ICV, LVV, WMHV, hippocampus, amygdala, basal ganglia, thalamus, ventral diencephalon, pons, and medulla were obtained. Further, detailed sub-segmentation of cerebellum was performed to achieve volumetric results of crus, lobules, vermis, and white matter. All final automatic segmentation results were checked and approved by a single neuroradiologist (C.J.P.) without subsequent manual correction. The regional volumes were expressed as the ratio of the regional volume to the total ICV (ratio of ICV × 10 3 ). Acquisition and quantitative analyses of 18 F-FP-CIT PET FDG-PET scans were performed using a Discovery 600 scanner (General Electric Healthcare, Milwaukee, MI, USA). FDG-PET scans were performed according to the following protocol: Approximately 4.1 MBq/kg (body weight) 18 F-FDG was administered intravenously to the patient. After a 60-minute uptake period, PET images were acquired for 15 minutes. A spiral computed tomography scan was performed for attenuation correction with a 0.8 second rotation time at 60 mA and 120 kVp, and with 3.75 mm section thickness, 0.625 mm collimation, and 9.375 mm table feed per rotation. FDG-PET images were reconstructed using the ordered subset expectation maximization algorithm with 4 iterations and 32 subsets. To assess brain glucose metabolism in each participant using FDG-PET imaging, Statistical Parametric Mapping 12 (SPM12; Wellcome Trust Centre for Neuroimaging, London, UK) and in-house software implemented in MATLAB R2021a (MathWorks, Natick, MA) were used. Structural MRI images were segmented and spatially normalized to the Montreal Neurological Institute (MNI) space for each participant. The FDG-PET images were co-registered to the corresponding T1-weighted images. The Standard uptake value ratio (SUVR) of FDG-PET was calculated by overlaying a participant-specific composite volume of interest (VOI) onto the FDG PET images. The SUVR images were generated using the uptake value of paracentral lobule as the reference. The paracentral lobule was chosen as the reference region based on comparative analyses with 60 age- and sex-matched HCs, in which it was the only region showing no statistically significant difference in raw FDG uptake, unlike other cortical and subcortical areas that demonstrated marked differences (online supplementary table 1 ). The preprocessed SUVR images were smoothed using a 6mm full-width at half maximum (FWHM) Gaussian kernel. Statistical analysis The baseline clinical and imaging characteristics of the study participants were analyzed using independent t-tests or one-way ANOVA for continuous variables when normality was confirmed by the Shapiro-Wilk test; otherwise, non-parametric tests such as the Mann–Whitney U test or Kruskal–Wallis test were applied. Categorical variables were analyzed using the chi-square or Fisher's exact tests, as appropriate. Normality of distribution was assessed using Shapiro-Wilk test. Partial correlation analyses, adjusted for age and sex, were conducted within the MSA group to examine the relationships between CPV and other imaging parameters including LVV, hippocampal volume, and WMHV. To identify the independent effect of CPV on motor symptoms assessed using UMSARS total scores at initial visit, multivariate linear regression analysis was performed after adjusting for age at symptom onset, sex, symptom duration, and LVV. Multivariate linear regression analyses for regional brain atrophy and CMRglu were performed to explore the effect of CPV on MSA-related neurodegeneration after adjusting for age at symptom onset, sex, symptom duration, and LVV. The FDR method was used to correct multiple tests. Statistical analyses were performed using the R software (v4.0, http://www.r-project.org ). Results with a two-tailed P value < 0.05 were considered statistically significant. Declarations Acknowledgements We acknowledge the Korea government (MSIT) for assistance and support. Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00209580). Author contributions C.J.P., Y.S., S.H.J., and P.H.L. conceptualized and designed the study. Y.S., H.K.N., S.K.L., Y.H.S., and P.H.L contributed to the acquisition of the data. C.J.P., Y.S., H.J.J., C.H.L., and S.H.J. contribute to analysis of the data. C.J.P., Y.S., S.H.J., and P.H.L. drafted and/or revised the manuscript. S.H.J., and P.H.L. is the gaudrantor. Data availability statement Data generated or analyzed during the study are available from the corresponding author by request. Competeing interests The authors declare no conflicts of interest. There are no financial disclosures. Supplementary Information The online version contains supplementary material available References Kratzer, I., Ek, J. & Stolp, H. 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1","display":"","copyAsset":false,"role":"figure","size":3617638,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of the study sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCBS = Corticobasal syndrome, GSS = Gerstmann–Sträussler–Scheinker syndrome, MSA = Multiple system atrophy, MSA-P = Multiple system atrophy-parkinsonian type, MSA-C = Multiple system atrophy-cerebellar type, PD = Parkin disease, PSP = Progressive supranuclear palsy.\u003c/p\u003e","description":"","filename":"Fig01.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/1a7bc52071a3a0112e47e3ec.jpg"},{"id":98074567,"identity":"85e23486-b43e-4e6d-9c52-b63871f08eb7","added_by":"auto","created_at":"2025-12-12 13:28:02","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":762445,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRain-cloud plots of MR volumetric imaging markers, including CPV, LVV, hippocampal volume, and WMHV in the HC, MSA-P, and MSA-C groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMR = magnetic resonance; CPV = choroid plexus volume; LVV = lateral ventricle volume; WMHV = white matter hyperintensity volume; MSA-P = multiple system atrophy-parkinsonian type; multiple system atrophy-cerebellar type; *** uncorrected \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001;\u003c/p\u003e\n\u003cp\u003e**** uncorrected \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig02.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/52d2c4b15cb030727e142fa5.jpg"},{"id":98074565,"identity":"02478217-b407-44dc-b598-410d1dff5ec1","added_by":"auto","created_at":"2025-12-12 13:28:02","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":477713,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between CPV and cerebellar brain volumes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegions showing a significant association between CPV and regional cerebellar volume are visualized on a cerebellar heatmap template, with color indicating t-values derived from a multivariate linear regression model in (A) all patients with MSA, (B) patients with MSA-P, and (C) patients with MSA-C. CPV = choroid plexus volume; MSA = multiple system atrophy; MSA-P = multiple system atrophy-parkinsonian type; multiple system atrophy-cerebellar type.\u003c/p\u003e","description":"","filename":"Fig03.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/86610cf8aeb1740ef0af7719.jpg"},{"id":98074571,"identity":"3cdc4c75-fff3-4883-86d3-a5e6467727e6","added_by":"auto","created_at":"2025-12-12 13:28:02","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":508723,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between CPV and subcortical cerebral glucose metabolism.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegions showing a significant association between CPV and subcortical cerebral glucose metabolism are visualized on the aseg subcortical atlas, with color indicating t-values derived from a multivariate linear regression model in patients with MSA. CPV = choroid plexus volume; MSA = multiple system atrophy.\u003c/p\u003e","description":"","filename":"Fig04.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/63fb61830fcdda418f90fbaf.jpg"},{"id":100617638,"identity":"d12d256c-eb51-4d71-bf36-c09c46ff527b","added_by":"auto","created_at":"2026-01-19 17:54:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6328616,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/35679097-2235-453c-9503-2a42dc89ab0d.pdf"},{"id":98428772,"identity":"3e5e3135-7ece-4ac3-887d-77e0d11e5ee8","added_by":"auto","created_at":"2025-12-17 16:42:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":178917,"visible":true,"origin":"","legend":"","description":"","filename":"03Supplementalmaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8240172/v1/5f8e9a044ca724bdbfa39c6d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of choroid plexus volume with brain atrophy and glucose metabolism in multiple system atrophy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe choroid plexus (CP) is a highly vascularized structure located within the ventricles, composed of a network of capillaries lined by specialized epithelial cells. It is the principal source of cerebrospinal fluid (CSF) in the adult brain and plays a critical role in maintaining central nervous system homeostasis​. Through the continuous secretion of CSF (approximately 400\u0026ndash;600 mL per day), the CP contributes to regulating intracranial pressure, delivering nutrients and hormones to the brain, and facilitating the clearance of metabolic waste via the glymphatic system \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Notably, CP-driven CSF flow is crucial for the glymphatic pathway of waste removal, and disruptions in CSF production can impair the clearance of neurotoxic metabolites​. Recent studies have demonstrated that an increase in CP volume (CPV) is closely associated with reduced glymphatic function \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAn emerging body of evidence indicates that CPV is often increased in conditions associated with neurodegeneration, including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis, and frontotemporal dementia \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Furthermore, our previous studies have demonstrated that enlarged CPV is associated with longitudinal outcome in patients with AD and PD \u003csup\u003e9,10\u003c/sup\u003e. These findings support the notion that the CP undergoes structural changes in response to neurodegenerative pathology, and that CP volumetry may serve as an indirect indicator of disease burden in certain disorders.\u003c/p\u003e\u003cp\u003eMultiple system atrophy (MSA) is a rare, rapidly progressive α-synucleinopathy characterized by a combination of parkinsonian features, cerebellar ataxia, autonomic failure, and pyramidal signs​. As in other neurodegenerative diseases, reduced glymphatic function has been reported in MSA; however, research specifically addressing CPV and CP function in this condition remains limited \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Given its role in CSF dynamics, waste clearance, and immune cell trafficking, CPV assessment in MSA represents a novel approach to exploring disease pathophysiology. In this study, we examined CPV in patients with MSA compared to healthy controls (HCs), and we further evaluated the relationship between CPV, motor symptoms, and imaging measures of disease severity\u0026mdash;specifically, regional brain atrophy and hypometabolism. We hypothesized that the CP is structurally affected in MSA and that CPV correlates with the extent of neurodegeneration, thereby representing a potential imaging biomarker of disease burden.\u003c/p\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDemographic and clinical characteristics of the study participants\u003c/h2\u003e\u003cp\u003eThis study included 87 patients with MSA and 84 HCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age at the time of magnetic resonance imaging (MRI) was significantly lower in the MSA group compared with HCs, whereas sex distribution did not differ significantly between the groups. Among patients with MSA, the mean disease duration from symptom onset to MRI was 2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 years. The average UMSARS scores were 16.21\u0026thinsp;\u0026plusmn;\u0026thinsp;8.51, 16.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.29, and 1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09 for Parts I, II, and IV, respectively. The cerebellar subtype (MSA-C) was more frequent than the parkinsonian subtype (MSA-P) (55.2% vs. 44.8%). The prevalence of vascular risk factors, including hypertension, diabetes mellitus, and dyslipidemia, did not differ significantly between the MSA and control groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\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\u003eDemographic and imaging characteristics in patients with MSA and healthy controls\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatients with MSA (n\u0026thinsp;=\u0026thinsp;87)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHealthy controls (n\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDemographic characteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at symptom onset, y\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.60\u0026thinsp;\u0026plusmn;\u0026thinsp;8.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at MRI scan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.48\u0026thinsp;\u0026plusmn;\u0026thinsp;9.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (50.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (54.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSymptom duration (onset to MRI scan), y\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUMSARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePart I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.21\u0026thinsp;\u0026plusmn;\u0026thinsp;8.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePart II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePart IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParkinsonian type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (44.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebellar type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (55.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVascular risk factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56 (35.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (27.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.319\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (19.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (9.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDyslipidemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (28.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVolumetric MRI measures\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCP volume, ratio of ICV \u0026times; 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehippocampal volume, ratio of ICV \u0026times; 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLV volume, ratio of ICV \u0026times; 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.38\u0026thinsp;\u0026plusmn;\u0026thinsp;9.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.32\u0026thinsp;\u0026plusmn;\u0026thinsp;9.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.147\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWMH volume, ratio of ICV \u0026times; 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICV, mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1512.68\u0026thinsp;\u0026plusmn;\u0026thinsp;197.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1365.40\u0026thinsp;\u0026plusmn;\u0026thinsp;135.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or number (percentage).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eCP\u0026thinsp;=\u0026thinsp;choroid plexus; ICV\u0026thinsp;=\u0026thinsp;intracranial volume; LV\u0026thinsp;=\u0026thinsp;lateral ventricle; MRI\u0026thinsp;=\u0026thinsp;magnetic resonance imaging; MSA\u0026thinsp;=\u0026thinsp;multiple system atrophy; NA\u0026thinsp;=\u0026thinsp;not applicable/available; UMSARS\u0026thinsp;=\u0026thinsp;Unified Multiple System Atrophy Rating Scale; WMH\u0026thinsp;=\u0026thinsp;white matter hyperintensity.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImaging characteristics of the participants\u003c/h3\u003e\n\u003cp\u003eVolumetric MRI revealed that CPV was significantly smaller in the MSA group compared with controls. Hippocampal volume was also significantly reduced in patients with MSA. Although lateral ventricle volume (LVV) tended to be larger in the MSA group, the difference did not reach statistical significance. white matter hyperintensity volume (WMHV) was significantly greater in patients with. Notably, total volumes of intracranium (ICV) was markedly higher in the MSA group compared with controls (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). When stratified by MSA subtype, patients with both MSA-P and MSA-C exhibited significantly reduced CPV and hippocampal volume compared with HCs, with no significant differences observed between the two subtypes. In contrast, no significant differences were observed in LVV or WMHV among the MSA-C, MSA-P, and control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for age at MRI scan and sex, multivariate linear regression confirmed that CPV remained significantly lower in both MSA-P (β = \u0026minus;\u0026thinsp;0.240, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and MSA-C (β = \u0026minus;\u0026thinsp;0.243, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with controls. Hippocampal volume was also significantly reduced in both subtypes, while LVV and WMHV were significantly higher, particularly in MSA-P. These findings indicate that volumetric alterations in MSA remain robust after controlling for demographic factors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\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\u003eMultivariate linear regression analysis for CPV in relation to brain volume measures\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"17\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eCPV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eLVV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\u003cp\u003eHippocampal volume\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e\u003cp\u003eWMHV\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eΒ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c16\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c17\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-17.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-3.899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e7.887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e23.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-20.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e3.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e-6.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e9.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e-8.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e9.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e0.034\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-1.646\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e5.088\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-1.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e0.755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e-1.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMSA-P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e-8.384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e4.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e0.951\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e4.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMSA-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.388\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e-6.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e2.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e0.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e2.489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"17\"\u003eResults of multivariate linear regression analysis for the CPV, LVV, hippocampal volume, or WMHV after controlling for age at MRI scan, sex, and group. CPV\u0026thinsp;=\u0026thinsp;choroid plexus volume; LVV\u0026thinsp;=\u0026thinsp;lateral ventricle volume; MRI\u0026thinsp;=\u0026thinsp;magnetic resonance imaging; HC\u0026thinsp;=\u0026thinsp;healthy control; MSA-P\u0026thinsp;=\u0026thinsp;multiple system atrophy-parkinsonian type; multiple system atrophy-cerebellar type; WMHV\u0026thinsp;=\u0026thinsp;white matter hyperintensity volume.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePartial correlation analyses within the MSA group, controlling for age at MRI scan, sex, and symptom duration, revealed a significant positive association between CPV and LVV (r\u0026thinsp;=\u0026thinsp;0.600, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, CPV was not significantly associated with hippocampal volume (r = \u0026minus;\u0026thinsp;0.204, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.062) or WMHV (r\u0026thinsp;=\u0026thinsp;0.100, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.365). Given the significant association between CPV and LVV, subsequent analyses were adjusted for LVV as a covariate.\u003c/p\u003e\n\u003ch3\u003eRelationship between CPV and regional brain atrophy\u003c/h3\u003e\n\u003cp\u003eIn the overall MSA cohort, CPV demonstrated significant positive correlations with both left and right cerebellar hemispheric structures, as well as midline vermian lobules, after adjusting for age, sex, symptom duration, and LVV. On the left side, CPV was positively associated with cerebellar white matter, lobules I\u0026ndash;IV, lobule V, lobule VI, and lobule VIIIb. On the right side, significant associations were observed with cerebellar white matter, lobules I\u0026ndash;IV, lobule V, and lobule VIIIb. Additionally, CPV was positively correlated with midline vermian structures, including vermis VI, VII, VIII, IX, and X. These associations remained statistically significant after false discovery rate (FDR) correction for multiple comparisons. In contrast, no significant associations were found between CPV and brainstem structures, including the pons and medulla. In subgroup analyses, these positive correlations were predominantly observed in patients with MSA-C, whereas associations in patients with MSA-P were weaker and generally not statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; supplementary Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor other subcortical structures, multivariate linear regression analysis showed that CPV was positively associated with bilateral ventral diencephalon volume in the overall MSA group, and these associations remained significant after FDR correction. This relationship was also observed in the MSA-C subgroup, whereas no significant associations were observed in the MSA-P subgroup. No other subcortical structures, including the caudate, putamen, pallidum, thalamus, or nucleus accumbens, demonstrated significant associations with CPV after multiple comparisons (supplemental Table\u0026nbsp;3).\u003c/p\u003e\n\u003ch3\u003eRelationship between CPV and regional brain glucose metabolism\u003c/h3\u003e\n\u003cp\u003eMultivariate linear regression analysis revealed that higher CPV was significantly associated with increased regional glucose metabolism in several brain regions, after adjusting for age at MRI, sex, symptom duration, and LVV (supplemental Table\u0026nbsp;4). In the overall MSA cohort, CPV showed significant positive associations with Cerebral Metabolic Rate for Glucose (CMRglu) in the brainstem, cerebellar white matter, and bilateral thalamic and ventral diencephalic regions, including the left thalamus, right thalamus, left ventral diencephalon, and right ventral diencephalon. These associations remained significant after FDR correction for multiple comparisons.\u003c/p\u003e\u003cp\u003eIn subgroup analyses, CPV was positively associated with CMRglu in the brainstem and cerebellar cortex in the MSA-P subgroup, and with the brainstem, cerebellar white matter, left thalamus, and right ventral diencephalon in the MSA-C subgroup. However, none of these associations in the subtype analyses remained significant after FDR correction.\u003c/p\u003e\u003cp\u003eNo significant associations were observed between CPV and CMRglu in basal ganglia structures, including the caudate, putamen, pallidum, and nucleus accumbens, in any group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; supplemental Table\u0026nbsp;4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eRelationship between CPV and motor symptoms\u003c/h3\u003e\n\u003cp\u003eIn multivariate linear regression analyses, CPV was not significantly associated with clinical severity, as measured by either individual or total the Unified MSA Rating Scale (UMSARS) scores, in the overall cohort or within MSA subtypes (supplementary Table\u0026nbsp;5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated the association between CPV, brain atrophy patterns, and cerebral metabolism in patients with MSA. The main findings were as follows: (1) CPV was reduced in patients with MSA compared to HCs. CPV in both the MSA-P and MSA-C subtypes was smaller than in HCs, although no inter-subtype differences were observed; (2) CPV was positively associated with regional atrophy of subcortical structures, which are particularly vulnerable in MSA; and (3) CPV was positively associated with rCMRglu in MSA-related subcortical structures. Collectively, these findings suggest that CPV is decreased in patients with MSA and is positively associated with MSA-related neurodegeneration, indicating that CP atrophy may reflect disease severity in these patients.\u003c/p\u003e\u003cp\u003eWe demonstrated that patients with MSA exhibit markedly reduced CPV compared with HCs. This finding stands in contrast to previous observations in other neurodegenerative diseases\u0026mdash;notably PD and AD\u0026mdash;where the CP has been reported to undergo volumetric enlargement \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The identification of CP atrophy in MSA is novel and suggests that the CP may respond differently to neuropathological processes in MSA than in PD or AD. To our knowledge, this is the first evidence that CPV is decreased in a neurodegenerative disorder, underscoring a disease-specific structural alteration that distinguishes MSA from the CP hypertrophy observed in AD, PD, and other neurodegenerative diseases \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe discrepant CPV changes observed between MSA and other neurodegenerative disorders likely reflect fundamental differences in underlying disease mechanisms and progression. In AD, CP enlargement and increased perfusion have been suggested as compensatory responses to protein accumulation \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. whereas in MSA, CP atrophy may instead reflect exhaustion or degeneration. These findings have important implications for understanding the role of the CP in MSA. Similar to AD and PD, MSA is characterized by impaired protein clearance and has been linked to glymphatic system dysfunction \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The CP, as the primary source of CSF, is a critical component of the glymphatic clearance pathway, which facilitates the removal of metabolic waste products and aggregated proteins from the brain \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. A reduction in CPV could therefore exacerbate glymphatic insufficiency in MSA by limiting CSF production and flow. Diminished CSF turnover may, in turn, hinder the clearance of toxic proteins and accelerate neurodegeneration. Conversely, chronic glymphatic impairment in MSA\u0026mdash;with consequent retention of neurotoxic proteins and inflammatory mediators\u0026mdash;might contribute to structural damage and atrophy of the CP over time. Thus, a bidirectional relationship may exist whereby CP atrophy and glymphatic dysfunction reinforce one another, creating a vicious cycle of reduced waste clearance and progressive neural injury. Our observation of CPV reduction introduces a new perspective on MSA pathophysiology, supporting the concept that disruption of the cerebral fluid homeostatic systems\u0026mdash;of which the CP is an integral component\u0026mdash;contributes to neurodegenerative disease progression. While these interpretations remain speculative, they underscore a plausible link between CP structural integrity and the cerebral capacity to maintain homeostasis in the context of MSA's aggressive pathology.\u003c/p\u003e\u003cp\u003eIn this study, CPV did not correlate with baseline clinical severity of motor symptoms in MSA. The lack of correlation with UMSARS may reflect the scale\u0026rsquo;s limited sensitivity to CP-related processes \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In contrast, CPV in our MSA cohort showed significant positive correlations with neuroimaging biomarkers. Patients with larger CPV exhibited less regional brain atrophy on MRI\u0026mdash;particularly in the cerebellar hemispheres and vermis\u0026mdash;and higher regional glucose metabolism on \u003csup\u003e18\u003c/sup\u003eF-fluorodeoxyglucose (FDG) positron emission tomography (PET) in areas vulnerable to MSA. In other words, a smaller CPV was associated with more severe neurodegeneration across both structural and metabolic measures. Given that CPV was reduced in patients with MSA compared with HCs, this pattern suggests that CPV may serve as an indirect index of disease burden in MSA. The cerebellum and brainstem are among the regions most affected in MSA, and it was within these areas that CPV correlations were most pronounced. In MSA-C, where ataxia and cerebellar atrophy predominate, the associations between CPV and preserved tissue volume were particularly robust. This may partly reflect differences in regional atrophy patterns; while putaminal and caudate volumes were reduced in MSA, their greater interindividual variability relative to cerebellar and brainstem structures likely attenuated correlations with CPV \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In contrast, the more consistent and pronounced posterior fossa atrophy in MSA-C may have facilitated clearer detection of associations between CP and involved structures. A potential interpretation is that CP atrophy progresses in parallel with cerebellar neurodegeneration, potentially due to shared pathogenic mechanisms or localized interactions (e.g., the fourth ventricle CP directly interfaces with cerebellar and brainstem structures). It is conceivable that a more intact CP confers neuroprotective effects, potentially by sustaining adequate CSF production, growth factor secretion, or immune surveillance, thereby mitigating tissue loss in connected regions \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Conversely, when CPV is reduced, these supportive functions may be compromised, leading to greater accumulation of pathology and consequent atrophy and hypometabolism in MSA-vulnerable regions. While causality cannot be established from our data, the clear association between higher CPV and better-preserved brain structure and function reinforces the idea that CP integrity is closely linked to overall brain health in MSA. Our cross-sectional baseline analysis may have been underpowered to detect subtle clinical correlations, or the temporal window during which CP changes align with motor symptom progression may be narrow. Future longitudinal studies are needed to determine whether CPV has prognostic value for clinical progression, even if it does not reflect symptom severity at a single time point.\u003c/p\u003e\u003cp\u003eThis study has some limitations and highlights future directions. First, our analysis was cross-sectional, which limits insight into the temporal dynamics of CP changes in MSA. We cannot determine whether CP atrophy represents a cause or a consequence of advanced neurodegeneration, or how early in the disease course it emerges. Longitudinal studies are needed to track CPV over time in MSA\u0026mdash;for instance, to evaluate whether accelerated CPV loss parallels clinical deterioration or whether baseline CPV could stratify patients by prognosis. Second, although no consensus currently exists regarding the optimal reference region for FDG-PET in MSA, we selected the paracentral lobule based on prior findings indicating that its CMRglu is relatively spared in patients with MSA \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. While the paracentral lobule has previously been used as a reference region in AD studies \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, this approach has not yet been applied in MSA. Since the choice of reference region can significantly influence the interpretation of regional glucose metabolism, particularly in disorders with widespread neurodegeneration, future work is needed to systematically evaluate and validate optimal normalization strategies for FDG-PET analysis in MSA. Third, given the rarity of MSA, our sample size\u0026mdash;although relatively large for an MSA cohort\u0026mdash;may still limit generalizability. Our cohort included both MSA-P and MSA-C subtypes across a range of disease durations; while we observed consistent CPV reductions across subtypes, subtle differences may have been overlooked. Replication of our findings in independent MSA cohorts, as well as direct comparisons with other synucleinopathies (e.g., comparing CPV in MSA vs. idiopathic PD directly), would further strengthen the evidence for a unique involvement of the CP in MSA.\u003c/p\u003e\u003cp\u003eIn summary, we found that CPV was significantly decreased in patients with MSA compared with HCs, a contrasting pattern to that reported in PD and AD \u003csup\u003e3,18,25,26\u003c/sup\u003e. Furthermore, smaller CPVs in MSA were associated with greater brain atrophy and hypometabolism, suggesting that CP atrophy may serve as a marker of higher disease burden. Our findings highlight the CP as an essential and previously under-recognized contributor to MSA pathophysiology. Future studies integrating neuroimaging, biological, and clinical approaches are warranted to validate CPV as a potential imaging biomarker and to elucidate its mechanistic links to neurodegeneration in MSA.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eWe consecutively recruited 87 patients with MSA and 84 HCs from the Movement Disorders Outpatient Clinic of the Yonsei University Health System between 2008 and 2020. Patients with MSA were diagnosed with either clinically established MSA (n\u0026thinsp;=\u0026thinsp;64) or clinically probable MSA (n\u0026thinsp;=\u0026thinsp;23), according to the diagnostic criteria for MSA \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. All patients underwent the Unified MSA Rating Scale (UMSARS; parts I\u0026ndash;IV), brain MRI, and FDG-PET scan within 6 months. UMSARS was used to assess disease severity at the time of MRI acquisition. Total UMSARS score was defined as the sum of UMSARS-I (historical), UMSARS-II (motor examination), and UMSARS-IV (global disability scale) subscores. The diagnosis of MSA was further supported by structural and/or functional imaging findings, including atrophy on MRI of the putamen, middle cerebellar peduncle, pons, or cerebellum, as well as hypometabolism on FDG-PET in the putamen, brainstem, or cerebellum. None of the patients carried mutations in the SCA 1, 2, 3, 6, 7, 8, and 17 genes. None of the HCs (n\u0026thinsp;=\u0026thinsp;84) reported cognitive impairment, and all demonstrated normal cognitive function according to the Korean version of the Mini-Mental State Examination and comprehensive neuropsychological testing. This study was approved by the Institutional Review Board of Yonsei University Severance Hospital (IRB No. 4-2024-1425 for patients with MSA; IRB No. 4-2015-0551 for HCs). All methods involving participants were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki. The requirement for informed consent was waived for patients with MSA due to the retrospective nature of the study; informed consent for participation was obtained from all HCs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMRI acquisition and analysis\u003c/h2\u003e\u003cp\u003eAll scans were acquired with a Philips 3.0T scanner (Philips Intera; Philips Medical System, Best, The Netherlands) with a SENSE head coil (SENSE factor\u0026thinsp;=\u0026thinsp;2). A high-resolution, T1-weighted MRI volume data set was obtained from all subjects with a 3-dimensional T1-TFE sequence configured with the following acquisition parameters: axial acquisition with a 224 \u0026times; 256 matrix; 256 \u0026times; 256 reconstructed matrix with 182 slices; 220-mm field of view; 0.98 \u0026times; 0.98 \u0026times; 1.2mm3 voxels; 4.6 ms echo time; 9.6 ms repetition time; 8\u0026deg; flip angle; and 0mm slice gap. We used automated segmentation based on the same method as in our previous study, in which the accuracy of this approach was validated. \u003csup\u003e12\u003c/sup\u003e Automated segmentation of brain regions and the cortical thickness values of each region were extracted using FastSurfer, which is a fast and extensively validated deep-learning pipeline for the fully automated processing of structural human brain MRIs. \u003csup\u003e28\u003c/sup\u003e This software enabled whole-brain segmentation into 95 classes within 50 seconds per subject. The details of this program and its validity have been shown elsewhere (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://deep-mi.org/research/fastsurfer/\u003c/span\u003e\u003cspan address=\"https://deep-mi.org/research/fastsurfer/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). A representative automatic segmentation of the CP using FastSurfer is shown in online supplementary Fig.\u0026nbsp;1. In a subset of 30 patients, we manually segmented the CPV to assess inter-method reliability. One neuroradiologist (C.J.P., with six years of experience) manually segmented the CP in the lateral ventricle in the 3D T1-weighted volumetric images using 3D Slicer version 5.0.3 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.slicer.org\u003c/span\u003e\u003cspan address=\"https://www.slicer.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). From these images, the ICV, LVV, WMHV, hippocampus, amygdala, basal ganglia, thalamus, ventral diencephalon, pons, and medulla were obtained. Further, detailed sub-segmentation of cerebellum was performed to achieve volumetric results of crus, lobules, vermis, and white matter. All final automatic segmentation results were checked and approved by a single neuroradiologist (C.J.P.) without subsequent manual correction. The regional volumes were expressed as the ratio of the regional volume to the total ICV (ratio of ICV \u0026times; 10\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAcquisition and quantitative analyses of \u003csup\u003e18\u003c/sup\u003eF-FP-CIT PET\u003c/h2\u003e\u003cp\u003eFDG-PET scans were performed using a Discovery 600 scanner (General Electric Healthcare, Milwaukee, MI, USA). FDG-PET scans were performed according to the following protocol: Approximately 4.1 MBq/kg (body weight) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003eF-FDG was administered intravenously to the patient. After a 60-minute uptake period, PET images were acquired for 15 minutes. A spiral computed tomography scan was performed for attenuation correction with a 0.8 second rotation time at 60 mA and 120 kVp, and with 3.75 mm section thickness, 0.625 mm collimation, and 9.375 mm table feed per rotation. FDG-PET images were reconstructed using the ordered subset expectation maximization algorithm with 4 iterations and 32 subsets. To assess brain glucose metabolism in each participant using FDG-PET imaging, Statistical Parametric Mapping 12 (SPM12; Wellcome Trust Centre for Neuroimaging, London, UK) and in-house software implemented in MATLAB R2021a (MathWorks, Natick, MA) were used. Structural MRI images were segmented and spatially normalized to the Montreal Neurological Institute (MNI) space for each participant. The FDG-PET images were co-registered to the corresponding T1-weighted images. The Standard uptake value ratio (SUVR) of FDG-PET was calculated by overlaying a participant-specific composite volume of interest (VOI) onto the FDG PET images. The SUVR images were generated using the uptake value of paracentral lobule as the reference. The paracentral lobule was chosen as the reference region based on comparative analyses with 60 age- and sex-matched HCs, in which it was the only region showing no statistically significant difference in raw FDG uptake, unlike other cortical and subcortical areas that demonstrated marked differences (online supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The preprocessed SUVR images were smoothed using a 6mm full-width at half maximum (FWHM) Gaussian kernel.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe baseline clinical and imaging characteristics of the study participants were analyzed using independent t-tests or one-way ANOVA for continuous variables when normality was confirmed by the Shapiro-Wilk test; otherwise, non-parametric tests such as the Mann\u0026ndash;Whitney U test or Kruskal\u0026ndash;Wallis test were applied. Categorical variables were analyzed using the chi-square or Fisher's exact tests, as appropriate. Normality of distribution was assessed using Shapiro-Wilk test. Partial correlation analyses, adjusted for age and sex, were conducted within the MSA group to examine the relationships between CPV and other imaging parameters including LVV, hippocampal volume, and WMHV.\u003c/p\u003e\u003cp\u003eTo identify the independent effect of CPV on motor symptoms assessed using UMSARS total scores at initial visit, multivariate linear regression analysis was performed after adjusting for age at symptom onset, sex, symptom duration, and LVV. Multivariate linear regression analyses for regional brain atrophy and CMRglu were performed to explore the effect of CPV on MSA-related neurodegeneration after adjusting for age at symptom onset, sex, symptom duration, and LVV. The FDR method was used to correct multiple tests.\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using the R software (v4.0, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Results with a two-tailed \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the Korea government (MSIT) for assistance and support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00209580).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.J.P., Y.S., S.H.J., and P.H.L. conceptualized and designed the study. Y.S., H.K.N., S.K.L., Y.H.S., and P.H.L contributed to the acquisition of the data. C.J.P., Y.S., H.J.J., C.H.L., and S.H.J. contribute to analysis of the data. C.J.P., Y.S., S.H.J., and P.H.L. drafted and/or revised the manuscript. S.H.J., and P.H.L. is the gaudrantor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData generated or analyzed during the study are available from the corresponding author by request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeteing interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest. There are no financial disclosures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe online version contains supplementary material available\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKratzer, I., Ek, J. \u0026amp; Stolp, H. The molecular anatomy and functions of the choroid plexus in healthy and diseased brain. \u003cem\u003eBiochim. Biophys. 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FastSurfer - A fast and accurate deep learning based neuroimaging pipeline. \u003cem\u003eNeuroimage\u003c/em\u003e \u003cb\u003e219\u003c/b\u003e, 117012. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2020.117012\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2020.117012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"multiple system atrophy, choroid plexus, brain atrophy, brain glucose metabolism","lastPublishedDoi":"10.21203/rs.3.rs-8240172/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8240172/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe choroid plexus (CP), a component of the glymphatic system, is essential in homeostasis and producing cerebrospinal fluid. Roles of CP in multiple system atrophy (MSA) remains unclear. This study aimed to investigate the implication of the CP in MSA.\u003c/p\u003e\u003cp\u003eThis retrospective cross-sectional study included 87 MSA patients who underwent the Unified MSA Rating Scale (UMSARS), brain MRI, and \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003eF-fluorodeoxyglucose PET scan, along with 84 healthy controls (HCs). Multivariate linear regression analyses were performed to examine the associations between CP volume (CPV) and UMSARS scores, as well as the volumes and cerebral metabolism.\u003c/p\u003e\u003cp\u003eCompared with HCs, MSA had significantly reduced CPV (1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27 vs. 1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CPV showed no association with UMSARS, however, it was positively correlated with regional cerebellar volumes. Smaller CPV was also associated with decreased cerebral metabolism in MSA-susceptible regions. Notably, CPV positively correlated with glucose metabolism in the brainstem (β\u0026thinsp;=\u0026thinsp;0.110, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and cerebellar white matter (β\u0026thinsp;=\u0026thinsp;0.080, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003cp\u003eThis study suggests that CPV is positively associated with disease burden in MSA, with CPV decreasing as disease severity increases. Further research is warranted to determine whether CPV could serve as a potential biomarker for MSA.\u003c/p\u003e","manuscriptTitle":"Association of choroid plexus volume with brain atrophy and glucose metabolism in multiple system atrophy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 13:27:52","doi":"10.21203/rs.3.rs-8240172/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-15T07:21:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-14T18:24:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247844961583009886676522969942616349894","date":"2025-12-14T18:23:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193077007539254771849383555307475631751","date":"2025-12-14T13:41:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-12T08:29:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140203608014732932590375421460258308017","date":"2025-12-11T22:37:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214866031226416648727204952237878954623","date":"2025-12-11T21:22:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103923732096870651465317181235960251621","date":"2025-12-11T20:44:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136230657183680346888200849673992850218","date":"2025-12-11T14:55:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34682076026849445518994996662158355620","date":"2025-12-11T09:19:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128156241530594616155612610330836972987","date":"2025-12-10T08:01:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173612552707083726316762229708754951809","date":"2025-12-09T14:10:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217202950669759730260830388211215366089","date":"2025-12-09T10:06:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T08:56:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-09T08:53:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T07:51:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-05T12:15:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-05T12:07:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"333baf14-87ac-43c9-882c-3f84344c8b4b","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":59517728,"name":"Health sciences/Biomarkers"},{"id":59517729,"name":"Health sciences/Diseases"},{"id":59517730,"name":"Health sciences/Medical research"},{"id":59517731,"name":"Health sciences/Neurology"},{"id":59517732,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2026-01-19T17:23:51+00:00","versionOfRecord":{"articleIdentity":"rs-8240172","link":"https://doi.org/10.1038/s41598-026-35850-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-16 16:30:14","publishedOnDateReadable":"January 16th, 2026"},"versionCreatedAt":"2025-12-12 13:27:52","video":"","vorDoi":"10.1038/s41598-026-35850-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-35850-6","workflowStages":[]},"version":"v1","identity":"rs-8240172","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8240172","identity":"rs-8240172","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}