Inflammatory Protein Landscape in the CSF of Mid- to Late- Stage Parkinson’s Disease: Associations with Motor Severity and Subtypes

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This study aimed to characterize the cerebrospinal fluid (CSF) inflammatory profile in mid- to late-stage PD patients and identify specific inflammatory proteins with potential clinical relevance to motor symptoms and disease severity. Methods: In this retrospective cross-sectional study, CSF samples were obtained from 25 patients with mid-to late- stage PD (mean disease duration: 10.24 ± 4.65 years) and 15 non-PD controls. The levels of 92 inflammation-related proteins were quantified using the Olink proximity extension assay (PEA). Based on the identified differentially expressed proteins (DEPs), we next compared inflammatory profiles between the postural instability and gait difficulty (PIGD, n = 10) and tremor-dominant (TD, n = 10) PD subtypes. Additionally, correlation analyses were performed between the DEPs and Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) scores to identify inflammatory biomarkers with potential clinical relevance. Results: Using the Olink platform, 28 DEPs were identified between the PD and non-PD groups ( p < 0.05). Subsequent protein–protein interaction network analysis identified IFN-γ as the central hub. Comparative analysis between the PIGD and TD subgroups revealed five DEPs (IFN-γ, ST1A1, TNFSF14, MMP-1, TRANCE) ( p < 0.05). Among all DEPs, IL-10RB (r = 0.440, p = 0.028), CD8A (r = 0.414, p = 0.039), and CXCL9 (r = 0.414, p = 0.040) showed the strongest correlations with UPDRS-III scores. Conclusion: This study identifies IFN-γ as the central hub protein within the CSF inflammatory network in mid- to late-stage PD and highlights specific T cell-related DEPs that are strongly associated with motor dysfunction. These proteins may represent potential targets for future anti-inflammatory therapies and serve as biomarkers for tracking disease progression. Parkinson’s disease inflammation motor impairment cerebrospinal fluid proteomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Parkinson’s disease (PD) is a progressive neurodegenerative disease pathologically characterized by Lewy body accumulations, inflammation, and the loss of dopaminergic (DA) neurons in the brain. Accumulating evidences have established neuroinflammation plays a vital role in the pathophysiological process of PD. 1 Clinically, PD is a highly heterogeneous disorder with diverse motor and non-motor manifestations. These distinct clinical phenotypes are associated with different disease progression and prognoses. For instance, patients with the postural instability and gait difficulty (PIGD) subtype typically experience more severe motor and non-motor symptoms and have poorer prognoses than those with the tremor-dominant (TD) phenotype. 2 This clinical diversity likely reflects underlying pathophysiological differences. While the progression and subtyping of PD are primarily delineated based on motor symptom evaluation, 3, 4 a potential association exists between neuroinflammation and impaired motor function in PD. 5, 6 Cerebrospinal fluid (CSF), given its anatomical proximity to the brain, serves as an ideal biofluid for investigating the pathophysiological process of PD. 7 However, due to the invasiveness of lumbar puncture, the application of CSF samples was less frequent in prior PD studies. A recent systematic review highlighted that among 26 CSF inflammatory factors of prior studies, only IL-1β has been consistently elevated in sporadic PD patients compared to healthy controls; changes in other key inflammatory markers such as IL-6, IL-8, and TNF-α remain inconclusive. 8 Thus, the comprehensive profiling of CSF inflammatory proteins is still needed to be clarified in PD. Proximity extension assay (PEA) is a novel technology enabling high-throughput, multiplex protein biomarker analysis. Olink PEA has gradually become a new choice for proteomics, which is based on the high sensitivity and specificity to achieve accurate detection of proteins. Specifically, the Olink inflammation panel quantifies 92 target proteins associated with cellular response to cytokine stimulus, inflammatory response, apoptotic process, MAPK cascade, cell adhesion, regulation of immune response, and other inflammatory activities. 9 – 11 This panel has been applied in CSF studies of PD in early stage or atypical parkinsonisms. 12 – 14 Nevertheless, it remains unclear which inflammatory factors are most critically associated with disease progression, particularly in the mid- to late stages of PD. This study aims to utilize the Olink inflammation panel to characterize the CSF inflammatory profile in mid-to late-stage PD and to evaluate the association between specific inflammation-related proteins and motor severity. Participants and Methods Figure 1 shows the workflow of this study. Collection of Participant Clinical Information and CSF samples All participants were recruited in this study at Jinan Central Hospital Affiliated to Shandong First Medical University between September 2024 and March 2025. The PD cohort included 25 patients who met the United Kingdom Parkinson’s Disease Society Brain Bank criteria and Hoehn-Yahr 3–4 stages of PD. Fifteen non-PD control subjects scheduled for surgical treatment were recruited based on the following inclusion criteria: i) patients with essential tremor or primary focal dystonia; ii) absence of infectious or autoimmune diseases; iii) absence of dysarthria or psychiatric disorders affecting expression; iiii) absence of significant cognitive impairment or psychiatric symptoms. Based on the Olink detection results, four non-PD controls with outlier samples exhibiting low protein expression levels were subsequently excluded. We collected the general demographic information of PD patients and non-PD controls, including gender, age, disease duration, age at onset, body mass index (BMI), presence or absence of diabetes mellitus (DM), and smoking status. For PD patients, the levodopa equivalent daily dose (LEDD) was calculated based on preoperative medication regimens. Motor function in PD patients was assessed during the “off” period using Part III of the Unified Parkinson’s Disease Rating Scale (UPDRS-III) 15 by two professional neurologists. The Hoehn and Yahr staging system was used to classify disease progression (stages 1-2.5: early stage; stages 3–5: mid-to late stage). 16 Clinical motor subtypes were classified according to the Stebbins method. 3 Tremor and postural instability/gait dysfunction (PIGD) scores were derived from parts II and III of the UPDRS. Patients were categorized into three subtypes using the ratio method (tremor score/PIGD score): tremor-dominant (TD, ratio ≥ 1.15), PIGD-dominant (ratio ≤ 0.9), and indeterminate (ratio 0.9–1.15). Among the 25 PD patients, 10 were classified as PIGD, 10 as TD, and 5 as indeterminate. Approximately 1 ml of clear CSF was collected from each participant during craniotomy procedure of deep brain stimulation (DBS) surgery. All CSF samples were immediately centrifuged at 3000 rpm for 10 minutes at 4°C. The supernatant was aliquoted and stored at -80°C for subsequent analysis. Profiling of Inflammation-Related Biomarkers CSF samples from 25 PD patients and 15 non-PD controls were analyzed by using the Olink Proseek ® Multiplex Inflammation panel (Olink Proteomics, Uppsala, Sweden), which targets 92 inflammation proteins 10 , 11 . The PEA technology involves oligonucleotide-labeled antibody pairs binding to their respective target proteins. When bound in proximity, the attached oligonucleotides hybridize and undergo DNA polymerization, generating a unique PCR reporter sequence. These sequences were detected, amplified, and quantified using a microfluidic real-time PCR instrument (Signature Q100, LC-Bio Technology CO., Ltd., Hangzhou, China). Assay results were reported as Normalized Protein Expression (NPX) values, followed by log2 transformation. Quality control (QC) criteria were applied as follows: (1) For the entire assay plate, the internal QC standard deviation per sample was required to be < 0.2 NPX; (2) For individual samples, the deviation from the sample median was required to be < 0.3 NPX; samples exceeding this threshold were excluded. All 40 submitted samples passed QC successfully (100% pass rate). Protein detection required a target protein to be above the lower limit of detection (LLOD) (≥ 75% of samples). Using the Inflammation panel, 66 out of 92 target proteins met this criterion, yielding an average detection rate of 72%. A comprehensive list of all inflammatory proteins is provided in Supplementary Table 1. Statistical Analysis All statistical analyses were performed with SPSS 25.0 (IBM Corp., Armonk, NY, USA). The normality assumption for continuous variables was examined with the Kolmogorov–Smirnov test. Normally distributed continuous variables are expressed as mean ± standard deviation (SD), whereas categorical variables are presented as frequencies and percentages. Between-group comparisons were assessed using the independent-samples t-test for normally distributed data, the Mann–Whitney U test for non-normally distributed data, and the χ² or Fisher’s exact test for categorical variables. Pairwise associations were quantified using Pearson’s correlation coefficient for normally distributed variables and Spearman’s rank correlation coefficient for non-normally distributed variables. A two-tailed p-value < 0.05 was considered statistically significant. Differentially expressed proteins (DEPs) between groups were identified by using Olink NPX Signature 3.0. Statistical significance was defined as p < 0.05. Intergroup comparisons (PD vs . non-PD controls; TD vs . PIGD) were conducted using the Welch two-sample t-test. Multiple testing correction was applied using the Benjamini-Hochberg method. Results Baseline Characteristics This study initially enrolled 40 participants. Of these, 25 CSF samples of patients with PD and 11 CSF samples of non-PD controls qualified for Olink protein detection. The baseline clinical characteristics of the included participants were summarized in Table 1 . No significant differences were found between the two groups in terms of sex, age, disease duration, age at onset, BMI, DM, or smoking status. Among the 25 PD patients, 10 were classified as TD; 10 as PIGD; and 5 as indeterminate. Additionally, no significant differences were observed among these PD motor subtypes in gender, age, disease duration, age at onset, UPDRS-III scores, or LEDD (Table 2 ). Table 1 Baseline Characteristics of PD Patients and Non-PD Controls Sample Size PD Non-PD P Value N = 25 N = 11 Female, n (%) 17 (68.0) 7 (63.6) 1.000 Age (years) 60.08 ± 6.71 59.82 ± 10.5 0.941 Age at Onset (years) 49.84 ± 7.69 47.55 ± 11.13 0.478 Disease Duration (years) 10.24 ± 4.65 12.30 ± 15.40 0.0673 BMI (kg/m 2 ) 23.70 ± 4.34 24.48 ± 3.03 0.591 DM, n (%) 6 (24.0) 1 (9.1) 0.400 Smoking, n (%) 1 (4.0) 1 (9.1) 0.524 Abbreviations: DM, diabetes mellitus; BMI, body mass index; PD, Parkinson’s disease; PIGD, postural instability and gait difficulty-dominant. Table 2 Comparison of Clinical Indicators Among Different Motor Subtypes of PD Patients Sample Size TD PIGD Indeterminate P Value N = 10 N = 10 N = 5 Female, n (%) 5 (50.00) 6 (60.00) 5 (100.00) 0.254 Age (years) 57.70 ± 8.22 60.70 ± 3.62 63.60 ± 7.64 0.267 Age at Onset (years) 46.50 ± 8.53 51.80 ± 4.98 52.60 ± 9.40 0.209 Disease Duration (years) 11.20 ± 5.94 8.90 ± 3.60 11.00 ± 3.67 0.518 UPDRS- III (scores) 63.40 ± 23.34 48.10 ± 7.00 66.40 ± 22.83 0.102 LEDD (mg/day) 827.03 ± 358.88 885.15 ± 196.85 672.50 ± 233.59 0.396 Abbreviations: LEDD, levodopa equivalent daily dose; UPDRS-III, Unified Parkinson’s Disease Rating Scale -III. DEPs in PD vs . non-PD groups Analysis of 92 inflammation-related proteins identified 28 DEPs between the PD group and the non-PD control group. All 28 DEPs were significantly upregulated in the PD group, including CCL11, CCL25, CCL20, CD8A, TRAIL, IL-18R1, CD244, AXIN1, IFN-γ, CXCL11, IL-12B, MMP-1, TNFR3F9, MMP-10, MCP-4, FGF-19, CCL23, CD6, IL18, CD40, CASP-8, CXCL6, SCF, TRANCE, ST1A1, TNFSF-14, IL-10RB, CXCL9 (Fig. 2 A). The heatmap further illustrated the DEPs expressions across groups (Fig. 2 B). Within the protein-protein interaction (PPI) network constructed from the 28 DEPs, IFN-γ exhibited the highest degree score, indicating its central hub role (Fig. 3). DEPs in TD vs . PIGD subtypes We further compared CSF levels of the 28 DEPs between the PIGD and TD subtypes. This analysis revealed five DEPs that were significantly upregulated in the PIGD group compared to the TD group. Ranked by ascending p-value, these proteins were: ST1A1, IFN-γ, TRANCE, TNFSF-14, and MMP-1 (Fig. 4). Correlation between Inflammatory Protein Levels and Motor Severity in PD To investigate potential links between protein expression and motor symptoms severity, we performed correlation analyses between DEP levels and UPDRS-III scores. The results revealed moderate positive correlations for IL-10RB (r = 0.440, p = 0.028), CD8A (r = 0.414, p = 0.039), and CXCL9 (r = 0.414, p = 0.040), suggesting that elevated levels of these three proteins are associated with more severe motor symptoms in PD (Fig. 5 ). Discussion We utilized Olink technology to analyze CSF samples from mid-to late-stage PD and non-PD patients. Among the 92 inflammation-related proteins, 28 DEPs were identified between the PD and non-PD groups. Subsequent PPI network analysis pinpointed IFN-γ as the key hub protein. Comparative analysis within PD subgroups (PIGD vs. TD) revealed five DEPs: IFN-γ, ST1A1, TRANCE, MMP-1 and TNFSF14. Additionally, three proteins (IL-10RB, CD8A, and CXCL-9) showed correlation with UPDRS-III scores. Of the 28 DEPs, five inflammatory proteins (MMP-10, CCL23, IL-18R, CD8A, and FGF19) have been previously reported in CSF proteomic studies of PD patients. 12 – 14 Other factors such as TNFSF9 and CCL23 were also documented in plasma proteomic investigations. 17 Our study revealed a greater number of DEPs compared to previous CSF proteomic studies, which may be attributed to differences in cohort characteristics. 12 – 14 Specifically, our PD cohort exhibited longer disease durations and higher motor dysfunction scores, suggesting more advanced disease severity and potentially more pronounced neuroinflammation. Additionally, CSF samples in this study were obtained via cerebral dural puncture during craniotomy. This methodological approach may enhance the detection of inflammatory proteins, thereby providing a more accurate reflection of cerebral inflammation. 18 PPI analysis generated a conceptual network designating IFN-γ as the topologically central protein among the DEPs. IFN-γ, primarily secreted by activated T cells, has been demonstrated to promote inflammatory activation of astrocytes and microglia in PD animal models. 19 Among the DEPs, IL-18, IL-12, and CXCL-9 contribute to recruiting Th1 and CD8 + T cells to secrete IFN-γ. 20–23 Moreover, IFN-γ synergizes with inflammatory factors like TNF-α, IL-18, and SCF to promote T-cell maturation and activation. 24 – 26 These activated T cells, in turn, release inflammatory factors like CXCL-11, CXCL-9, and IFN-γ. 27 Collectively, the available evidence converges to theoretically nominate IFN-γ as the core inflammatory mediator within this network of DEPs. Accumulating evidence indicates that PD is a heterogeneous neurodegenerative disorder characterized by diverse clinicopathological phenotypes. Generally, the TD subtype is associated with a more benign disease course and slower progression, indicating a better prognosis than the PIGD subtype. 2 Our study demonstrated significantly elevated CSF levels of IFN-γ, ST1A1, TRANCE, TNFSF14, and MMP-1 in the PIGD group relative to the TD group. Given that IFN-γ (an inducer of MMP-1), ST1A1, TRANCE, and TNFSF14 are all linked to T cell maturation and activation, 28–30 our findings collectively suggest that T cell-mediated inflammation is strongly associated with more aggressive PD subtypes and unfavorable prognosis. We also observed positive correlations between UPDRS-III scores and the inflammatory proteins IL-10RB, CD8A, and CXCL9. IL-10RB serves as a receptor for both IL-10 and IFN-γ. Although IL-10 is generally considered an anti-inflammatory cytokine, elevated peripheral IL-10 levels in the peripheral blood of PD patients have been reported, suggesting that the significant upregulation of IL-10RB may represent a compensatory protective mechanism during the disease progression. 31 We observed that the elevated CSF CD8A level correlated positively with motor symptom severity in PD patients. This finding underscores the critical role of CD8 + T-cell infiltration in PD progression. 32 The prior study has demonstrated IFN-γ-induced T cell infiltration can upregulate the level of CXCL9 expression in cerebral astrocytes and microvascular endothelial cells under the autoimmune conditions. 33 The elevated CXCL9 level detected in our PD cohort further supports the dominant role of T-cell-mediated inflammation in PD pathophysiology. Our study still has limitations. First, the sample size was relatively modest. However, all recruited PD patients were in the mid- to late-stage disease and consistently exhibited good responses to PD medications, minimizing the likelihood of atypical PD or PD-plus syndrome. The use of cerebral dural puncture for CSF collection may better reflect brain pathophysiological states in PD. Second, the control group consisted of non-PD patients with essential tremor or primary focal dystonia rather than healthy individuals. Primary dystonia typically presents as a benign, slowly progressive motor disorder and is generally considered as a cerebral microstructural defect rather than a neurodegenerative disease. 34 , 35 Conclusion In summary, using Olink PEA proteomics, we quantified 92 inflammation-related proteins in CSF samples from 25 mid- to late-stage PD patients and 11 non-PD controls and identified 28 DEPs. Subsequent analyses established IFN-γ as the central hub protein within the inflammatory network and highlighted specific T cell-related DEPs that are strongly associated with motor dysfunction. These findings suggest that these proteins may serve as potential targets for future anti-inflammatory interventions and biomarkers for assessing disease progression. Declarations Ethics Approval and Informed Consent All protocols in this study have been approved by the Research Ethics Committee of Jinan Central Hospital Affiliated to Shandong First Medical University (20240924016) and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to the experiment. Acknowledgments This work was supported by grants from the Natural Science Foundation of Shandong Province (ZR2023MC203), Shandong Provincial Medical and Health Science and Technology Development Plan Project (202204040490)‌‌ and 2023 Jinan Healthcare Industry High-Level Talent Program. The authors gratefully thank Yan Xu from Hangzhou LC-BIO Co., Ltd for the technical assistance and help with the data analysis. Disclosure The authors report no conflicts of interest in this work. D ata Availability The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. Clinical Trial Number Not applicable. Consent for Publication Not applicable. Author Contributions Yukun Guo: Formal analysis, Writing - original draft, Writing – review and editing; Wenqing Liu: Data curation, Investigation; Weiting Bu: Investigation, Data curation; Ruoxi Wang: Investigation, Data curation; Daoqing Su: Resources, Supervision; Heng Li: Resources, Writing - original draft, Writing – review and editing. Funding Source Declaration This work was supported by grants from the Natural Science Foundation of Shandong Province (ZR2023MC203), Shandong Provincial Medical and Health Science and Technology Development Plan Project (202204040490)‌‌ and 2023 Jinan Healthcare Industry High-Level Talent Program. References Tansey MG, Wallings RL, Houser MC, et al. Inflammation and immune dysfunction in Parkinson disease. Nat Rev Immunol. 2022;22(11):657–73. Aleksovski D, Miljkovic D, Bravi D, et al. Disease progression in Parkinson subtypes: the PPMI dataset. Neurol Sci. 2018;39(11):1971–6. Stebbins GT, Goetz CG, Burn DJ, et al. 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Supplementary Files TableS1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Apr, 2026 Reviews received at journal 15 Apr, 2026 Reviews received at journal 11 Apr, 2026 Reviews received at journal 24 Mar, 2026 Reviewers agreed at journal 22 Mar, 2026 Reviewers agreed at journal 21 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Editor invited by journal 19 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 19 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9090757","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":610833724,"identity":"011ccd35-bef7-47b1-ae3e-e6a9caffd644","order_by":0,"name":"Yukun Guo","email":"","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yukun","middleName":"","lastName":"Guo","suffix":""},{"id":610833725,"identity":"8df395f0-687d-49ee-afd7-28808970022d","order_by":1,"name":"Wenqing Liu","email":"","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenqing","middleName":"","lastName":"Liu","suffix":""},{"id":610833731,"identity":"c8f47034-c9ba-4498-ae5a-80f81ca9268a","order_by":2,"name":"Weiting Bu","email":"","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiting","middleName":"","lastName":"Bu","suffix":""},{"id":610833732,"identity":"6b73240b-50e5-4973-a07d-b5fdac3ac3d3","order_by":3,"name":"Ruoxi Wang","email":"","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ruoxi","middleName":"","lastName":"Wang","suffix":""},{"id":610833733,"identity":"73102063-2201-411b-85c1-87f30a7142a8","order_by":4,"name":"Daoqing Su","email":"","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Daoqing","middleName":"","lastName":"Su","suffix":""},{"id":610833734,"identity":"b0e51b24-2ff5-49c2-af39-82c4af75481f","order_by":5,"name":"Heng Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVRIiWNgGAWjYBACPgnG9o8fKmxI0MImwdzGLHEmjSQt7G0MvG2HSdEi3dj2QILtvL3BjRwDhp87iNEic7DdoIDnNrPkjBwDxt4zRDkssUFCQuI2G79EjgEzYxuxWngMzvGwkaKlTYIn4YAESbY0G0scSDaQ7HlWcLCXGC38EukPH378Z2dvcDx544OfxGhBAIEMgwMkaQDad/wBiTpGwSgYBaNgpAAAQh8wpC50lN4AAAAASUVORK5CYII=","orcid":"","institution":"Jinan Central Hospital","correspondingAuthor":true,"prefix":"","firstName":"Heng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-03-11 06:38:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9090757/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9090757/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105320612,"identity":"91bfeec9-85e2-4240-ae51-6eb5f975f7b8","added_by":"auto","created_at":"2026-03-24 17:17:19","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85224,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of DEPs identification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e CSF, cerebrospinal fluid;\u003cstrong\u003e \u003c/strong\u003eDEPs, differentially expressed proteins; PD, Parkinson’s disease; PIGD, postural instability and gait difficulty-dominant; PPI, protein-protein interaction; TD, tremor-dominant.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/3dfdc7cae8f806ddd90a96fc.jpeg"},{"id":105565881,"identity":"0918ef9b-01ec-4b3b-8d87-6607302ff7f3","added_by":"auto","created_at":"2026-03-27 12:54:40","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":578018,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed protein levels between patients with PD and non-PD control subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Box plot of 28 DEPs. (\u003cstrong\u003eB\u003c/strong\u003e) Heatmap of 28 DEPs. Significance levels: *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/88ebebe8a101fc0706940253.jpeg"},{"id":105564932,"identity":"d73b2cbb-34e3-42a9-810d-adf31b30a07e","added_by":"auto","created_at":"2026-03-27 12:51:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182479,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe protein-protein interaction network visualizes potential interactions between a group of proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe String DB database (\u003c/strong\u003e\u003ca href=\"http://string-db.org/\"\u003e\u003cstrong\u003ehttp://string-db.org/\u003c/strong\u003e\u003c/a\u003e\u003cstrong\u003e) was used to analyze the differential cerebrospinal fluid proteins between Parkinson’s disease (PD) and non-PD controls, revealing a potential protein–protein interaction network centered on IFN-γ and its related proteins.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/68411547d57f2858ffe1e6f6.png"},{"id":105320609,"identity":"38a92c5b-e0c9-4dd4-99d0-7f50c9af7db8","added_by":"auto","created_at":"2026-03-24 17:17:19","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":26873,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plot depicts 5 DEPs between PIGD and TD groups.\u003c/p\u003e\n\u003cp\u003eThe gray dashed line indicates an exploratory cutoff of p-value \u0026lt; 0.05. Red dots mark significantly upregulated proteins passing the exploratory threshold.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e DEPs, differentially expressed proteins; PIGD, postural instability and gait difficulty-dominant; TD, tremor-dominant.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/4a7201095cc8d8bb0e683e8f.jpeg"},{"id":105320613,"identity":"034367cc-bba3-4640-836d-3a7861690842","added_by":"auto","created_at":"2026-03-24 17:17:19","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":78269,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of correlation between DEPs and UPDRS-Ⅲ scores.\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) IL-10RB (r = 0.440, \u003cem\u003ep\u003c/em\u003e = 0.028). (\u003cstrong\u003eB\u003c/strong\u003e) CD8A (r = 0.414, \u003cem\u003ep\u003c/em\u003e = 0.039). (\u003cstrong\u003eC\u003c/strong\u003e) CXCL9 (r = 0.414, \u003cem\u003ep\u003c/em\u003e = 0.040).\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/8431bbd50dc147ea1fd14590.jpeg"},{"id":105570073,"identity":"ec7ecc06-4276-431c-97ca-5b12ea80b0b3","added_by":"auto","created_at":"2026-03-27 13:14:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1794141,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/1dcbbc4d-e7fd-473b-981b-79634db36187.pdf"},{"id":105564561,"identity":"fcc12549-4297-41f7-8efb-9e0aa498a325","added_by":"auto","created_at":"2026-03-27 12:50:02","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":24893,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9090757/v1/daa102413cdf964a4036ddbf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inflammatory Protein Landscape in the CSF of Mid- to Late- Stage Parkinson’s Disease: Associations with Motor Severity and Subtypes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson\u0026rsquo;s disease (PD) is a progressive neurodegenerative disease pathologically characterized by Lewy body accumulations, inflammation, and the loss of dopaminergic (DA) neurons in the brain. Accumulating evidences have established neuroinflammation plays a vital role in the pathophysiological process of PD.\u003csup\u003e1\u003c/sup\u003e Clinically, PD is a highly heterogeneous disorder with diverse motor and non-motor manifestations. These distinct clinical phenotypes are associated with different disease progression and prognoses. For instance, patients with the postural instability and gait difficulty (PIGD) subtype typically experience more severe motor and non-motor symptoms and have poorer prognoses than those with the tremor-dominant (TD) phenotype.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e This clinical diversity likely reflects underlying pathophysiological differences. While the progression and subtyping of PD are primarily delineated based on motor symptom evaluation,\u003csup\u003e3, 4\u003c/sup\u003e a potential association exists between neuroinflammation and impaired motor function in PD.\u003csup\u003e5, 6\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCerebrospinal fluid (CSF), given its anatomical proximity to the brain, serves as an ideal biofluid for investigating the pathophysiological process of PD.\u003csup\u003e7\u003c/sup\u003e However, due to the invasiveness of lumbar puncture, the application of CSF samples was less frequent in prior PD studies. A recent systematic review highlighted that among 26 CSF inflammatory factors of prior studies, only IL-1β has been consistently elevated in sporadic PD patients compared to healthy controls; changes in other key inflammatory markers such as IL-6, IL-8, and TNF-α remain inconclusive.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Thus, the comprehensive profiling of CSF inflammatory proteins is still needed to be clarified in PD.\u003c/p\u003e \u003cp\u003eProximity extension assay (PEA) is a novel technology enabling high-throughput, multiplex protein biomarker analysis. Olink PEA has gradually become a new choice for proteomics, which is based on the high sensitivity and specificity to achieve accurate detection of proteins. Specifically, the Olink inflammation panel quantifies 92 target proteins associated with cellular response to cytokine stimulus, inflammatory response, apoptotic process, MAPK cascade, cell adhesion, regulation of immune response, and other inflammatory activities.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e This panel has been applied in CSF studies of PD in early stage or atypical parkinsonisms.\u003csup\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 Nevertheless, it remains unclear which inflammatory factors are most critically associated with disease progression, particularly in the mid- to late stages of PD. This study aims to utilize the Olink inflammation panel to characterize the CSF inflammatory profile in mid-to late-stage PD and to evaluate the association between specific inflammation-related proteins and motor severity.\u003c/p\u003e"},{"header":"Participants and Methods","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the workflow of this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection of Participant Clinical Information and CSF samples\u003c/h2\u003e \u003cp\u003e All participants were recruited in this study at Jinan Central Hospital Affiliated to Shandong First Medical University between September 2024 and March 2025. The PD cohort included 25 patients who met the United Kingdom Parkinson\u0026rsquo;s Disease Society Brain Bank criteria and Hoehn-Yahr 3\u0026ndash;4 stages of PD. Fifteen non-PD control subjects scheduled for surgical treatment were recruited based on the following inclusion criteria: i) patients with essential tremor or primary focal dystonia; ii) absence of infectious or autoimmune diseases; iii) absence of dysarthria or psychiatric disorders affecting expression; iiii) absence of significant cognitive impairment or psychiatric symptoms. Based on the Olink detection results, four non-PD controls with outlier samples exhibiting low protein expression levels were subsequently excluded.\u003c/p\u003e \u003cp\u003eWe collected the general demographic information of PD patients and non-PD controls, including gender, age, disease duration, age at onset, body mass index (BMI), presence or absence of diabetes mellitus (DM), and smoking status. For PD patients, the levodopa equivalent daily dose (LEDD) was calculated based on preoperative medication regimens. Motor function in PD patients was assessed during the \u0026ldquo;off\u0026rdquo; period using Part III of the Unified Parkinson\u0026rsquo;s Disease Rating Scale (UPDRS-III) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003eby two professional neurologists. The Hoehn and Yahr staging system was used to classify disease progression (stages 1-2.5: early stage; stages 3\u0026ndash;5: mid-to late stage).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Clinical motor subtypes were classified according to the Stebbins method.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Tremor and postural instability/gait dysfunction (PIGD) scores were derived from parts II and III of the UPDRS. Patients were categorized into three subtypes using the ratio method (tremor score/PIGD score): tremor-dominant (TD, ratio\u0026thinsp;\u0026ge;\u0026thinsp;1.15), PIGD-dominant (ratio\u0026thinsp;\u0026le;\u0026thinsp;0.9), and indeterminate (ratio 0.9\u0026ndash;1.15). Among the 25 PD patients, 10 were classified as PIGD, 10 as TD, and 5 as indeterminate.\u003c/p\u003e \u003cp\u003eApproximately 1 ml of clear CSF was collected from each participant during craniotomy procedure of deep brain stimulation (DBS) surgery. All CSF samples were immediately centrifuged at 3000 rpm for 10 minutes at 4\u0026deg;C. The supernatant was aliquoted and stored at -80\u0026deg;C for subsequent analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProfiling of Inflammation-Related Biomarkers\u003c/h3\u003e\n\u003cp\u003eCSF samples from 25 PD patients and 15 non-PD controls were analyzed by using the Olink Proseek \u0026reg; Multiplex Inflammation panel (Olink Proteomics, Uppsala, Sweden), which targets 92 inflammation proteins\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The PEA technology involves oligonucleotide-labeled antibody pairs binding to their respective target proteins. When bound in proximity, the attached oligonucleotides hybridize and undergo DNA polymerization, generating a unique PCR reporter sequence. These sequences were detected, amplified, and quantified using a microfluidic real-time PCR instrument (Signature Q100, LC-Bio Technology CO., Ltd., Hangzhou, China). Assay results were reported as Normalized Protein Expression (NPX) values, followed by log2 transformation.\u003c/p\u003e \u003cp\u003eQuality control (QC) criteria were applied as follows: (1) For the entire assay plate, the internal QC standard deviation per sample was required to be \u0026lt;\u0026thinsp;0.2 NPX; (2) For individual samples, the deviation from the sample median was required to be \u0026lt;\u0026thinsp;0.3 NPX; samples exceeding this threshold were excluded. All 40 submitted samples passed QC successfully (100% pass rate). Protein detection required a target protein to be above the lower limit of detection (LLOD) (\u0026ge;\u0026thinsp;75% of samples). Using the Inflammation panel, 66 out of 92 target proteins met this criterion, yielding an average detection rate of 72%.\u003c/p\u003e \u003cp\u003eA comprehensive list of all inflammatory proteins is provided in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed with SPSS 25.0 (IBM Corp., Armonk, NY, USA). The normality assumption for continuous variables was examined with the Kolmogorov\u0026ndash;Smirnov test. Normally distributed continuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), whereas categorical variables are presented as frequencies and percentages. Between-group comparisons were assessed using the independent-samples t-test for normally distributed data, the Mann\u0026ndash;Whitney U test for non-normally distributed data, and the χ\u0026sup2; or Fisher\u0026rsquo;s exact test for categorical variables. Pairwise associations were quantified using Pearson\u0026rsquo;s correlation coefficient for normally distributed variables and Spearman\u0026rsquo;s rank correlation coefficient for non-normally distributed variables. A two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eDifferentially expressed proteins (DEPs) between groups were identified by using Olink NPX Signature 3.0. Statistical significance was defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Intergroup comparisons (PD \u003cem\u003evs\u003c/em\u003e. non-PD controls; TD \u003cem\u003evs\u003c/em\u003e. PIGD) were conducted using the Welch two-sample t-test. Multiple testing correction was applied using the Benjamini-Hochberg method.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eThis study initially enrolled 40 participants. Of these, 25 CSF samples of patients with PD and 11 CSF samples of non-PD controls qualified for Olink protein detection. The baseline clinical characteristics of the included participants were summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant differences were found between the two groups in terms of sex, age, disease duration, age at onset, BMI, DM, or smoking status. Among the 25 PD patients, 10 were classified as TD; 10 as PIGD; and 5 as indeterminate. Additionally, no significant differences were observed among these PD motor subtypes in gender, age, disease duration, age at onset, UPDRS-III scores, or LEDD (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eBaseline Characteristics of PD Patients and Non-PD 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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-PD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.08\u0026thinsp;\u0026plusmn;\u0026thinsp;6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.82\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at Onset (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.84\u0026thinsp;\u0026plusmn;\u0026thinsp;7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.55\u0026thinsp;\u0026plusmn;\u0026thinsp;11.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.30\u0026thinsp;\u0026plusmn;\u0026thinsp;15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.70\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e DM, diabetes mellitus; BMI, body mass index; PD, Parkinson\u0026rsquo;s disease; PIGD, postural instability and gait difficulty-dominant.\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\u003eComparison of Clinical Indicators Among Different Motor Subtypes of PD Patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePIGD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndeterminate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (60.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.60\u0026thinsp;\u0026plusmn;\u0026thinsp;7.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at Onset (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.50\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.60\u0026thinsp;\u0026plusmn;\u0026thinsp;9.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPDRS- III (scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63.40\u0026thinsp;\u0026plusmn;\u0026thinsp;23.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.40\u0026thinsp;\u0026plusmn;\u0026thinsp;22.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEDD (mg/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e827.03\u0026thinsp;\u0026plusmn;\u0026thinsp;358.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e885.15\u0026thinsp;\u0026plusmn;\u0026thinsp;196.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e672.50\u0026thinsp;\u0026plusmn;\u0026thinsp;233.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e LEDD, levodopa equivalent daily dose; UPDRS-III, Unified Parkinson\u0026rsquo;s Disease Rating Scale -III.\u003c/p\u003e\u003cp\u003e \u003cb\u003eDEPs in PD\u003c/b\u003e \u003cb\u003evs\u003c/b\u003e. \u003cb\u003enon-PD groups\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnalysis of 92 inflammation-related proteins identified 28 DEPs between the PD group and the non-PD control group. All 28 DEPs were significantly upregulated in the PD group, including CCL11, CCL25, CCL20, CD8A, TRAIL, IL-18R1, CD244, AXIN1, IFN-γ, CXCL11, IL-12B, MMP-1, TNFR3F9, MMP-10, MCP-4, FGF-19, CCL23, CD6, IL18, CD40, CASP-8, CXCL6, SCF, TRANCE, ST1A1, TNFSF-14, IL-10RB, CXCL9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The heatmap further illustrated the DEPs expressions across groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Within the protein-protein interaction (PPI) network constructed from the 28 DEPs, IFN-γ exhibited the highest degree score, indicating its central hub role (Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDEPs in TD\u003c/b\u003e \u003cb\u003evs\u003c/b\u003e. \u003cb\u003ePIGD subtypes\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe further compared CSF levels of the 28 DEPs between the PIGD and TD subtypes. This analysis revealed five DEPs that were significantly upregulated in the PIGD group compared to the TD group. Ranked by ascending p-value, these proteins were: ST1A1, IFN-γ, TRANCE, TNFSF-14, and MMP-1 (Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation between Inflammatory Protein Levels and Motor Severity in PD\u003c/h2\u003e \u003cp\u003eTo investigate potential links between protein expression and motor symptoms severity, we performed correlation analyses between DEP levels and UPDRS-III scores. The results revealed moderate positive correlations for IL-10RB (r\u0026thinsp;=\u0026thinsp;0.440, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028), CD8A (r\u0026thinsp;=\u0026thinsp;0.414, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039), and CXCL9 (r\u0026thinsp;=\u0026thinsp;0.414, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040), suggesting that elevated levels of these three proteins are associated with more severe motor symptoms in PD (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe utilized Olink technology to analyze CSF samples from mid-to late-stage PD and non-PD patients. Among the 92 inflammation-related proteins, 28 DEPs were identified between the PD and non-PD groups. Subsequent PPI network analysis pinpointed IFN-γ as the key hub protein. Comparative analysis within PD subgroups (PIGD \u003cem\u003evs.\u003c/em\u003e TD) revealed five DEPs: IFN-γ, ST1A1, TRANCE, MMP-1 and TNFSF14. Additionally, three proteins (IL-10RB, CD8A, and CXCL-9) showed correlation with UPDRS-III scores.\u003c/p\u003e \u003cp\u003eOf the 28 DEPs, five inflammatory proteins (MMP-10, CCL23, IL-18R, CD8A, and FGF19) have been previously reported in CSF proteomic studies of PD patients.\u003csup\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 Other factors such as TNFSF9 and CCL23 were also documented in plasma proteomic investigations.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Our study revealed a greater number of DEPs compared to previous CSF proteomic studies, which may be attributed to differences in cohort characteristics.\u003csup\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 Specifically, our PD cohort exhibited longer disease durations and higher motor dysfunction scores, suggesting more advanced disease severity and potentially more pronounced neuroinflammation. Additionally, CSF samples in this study were obtained via cerebral dural puncture during craniotomy. This methodological approach may enhance the detection of inflammatory proteins, thereby providing a more accurate reflection of cerebral inflammation.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePPI analysis generated a conceptual network designating IFN-γ as the topologically central protein among the DEPs. IFN-γ, primarily secreted by activated T cells, has been demonstrated to promote inflammatory activation of astrocytes and microglia in PD animal models.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Among the DEPs, IL-18, IL-12, and CXCL-9 contribute to recruiting Th1 and CD8\u0026thinsp;+\u0026thinsp;T cells to secrete IFN-γ.\u003csup\u003e20\u0026ndash;23\u003c/sup\u003e Moreover, IFN-γ synergizes with inflammatory factors like TNF-α, IL-18, and SCF to promote T-cell maturation and activation.\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e These activated T cells, in turn, release inflammatory factors like CXCL-11, CXCL-9, and IFN-γ.\u003csup\u003e27\u003c/sup\u003e Collectively, the available evidence converges to theoretically nominate IFN-γ as the core inflammatory mediator within this network of DEPs.\u003c/p\u003e \u003cp\u003eAccumulating evidence indicates that PD is a heterogeneous neurodegenerative disorder characterized by diverse clinicopathological phenotypes. Generally, the TD subtype is associated with a more benign disease course and slower progression, indicating a better prognosis than the PIGD subtype.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Our study demonstrated significantly elevated CSF levels of IFN-γ, ST1A1, TRANCE, TNFSF14, and MMP-1 in the PIGD group relative to the TD group. Given that IFN-γ (an inducer of MMP-1), ST1A1, TRANCE, and TNFSF14 are all linked to T cell maturation and activation,\u003csup\u003e28\u0026ndash;30\u003c/sup\u003e our findings collectively suggest that T cell-mediated inflammation is strongly associated with more aggressive PD subtypes and unfavorable prognosis.\u003c/p\u003e \u003cp\u003eWe also observed positive correlations between UPDRS-III scores and the inflammatory proteins IL-10RB, CD8A, and CXCL9. IL-10RB serves as a receptor for both IL-10 and IFN-γ. Although IL-10 is generally considered an anti-inflammatory cytokine, elevated peripheral IL-10 levels in the peripheral blood of PD patients have been reported, suggesting that the significant upregulation of IL-10RB may represent a compensatory protective mechanism during the disease progression.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e We observed that the elevated CSF CD8A level correlated positively with motor symptom severity in PD patients. This finding underscores the critical role of CD8\u0026thinsp;+\u0026thinsp;T-cell infiltration in PD progression.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e The prior study has demonstrated IFN-γ-induced T cell infiltration can upregulate the level of CXCL9 expression in cerebral astrocytes and microvascular endothelial cells under the autoimmune conditions.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e The elevated CXCL9 level detected in our PD cohort further supports the dominant role of T-cell-mediated inflammation in PD pathophysiology.\u003c/p\u003e \u003cp\u003eOur study still has limitations. First, the sample size was relatively modest. However, all recruited PD patients were in the mid- to late-stage disease and consistently exhibited good responses to PD medications, minimizing the likelihood of atypical PD or PD-plus syndrome. The use of cerebral dural puncture for CSF collection may better reflect brain pathophysiological states in PD. Second, the control group consisted of non-PD patients with essential tremor or primary focal dystonia rather than healthy individuals. Primary dystonia typically presents as a benign, slowly progressive motor disorder and is generally considered as a cerebral microstructural defect rather than a neurodegenerative disease.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, using Olink PEA proteomics, we quantified 92 inflammation-related proteins in CSF samples from 25 mid- to late-stage PD patients and 11 non-PD controls and identified 28 DEPs. Subsequent analyses established IFN-γ as the central hub protein within the inflammatory network and highlighted specific T cell-related DEPs that are strongly associated with motor dysfunction. These findings suggest that these proteins may serve as potential targets for future anti-inflammatory interventions and biomarkers for assessing disease progression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Informed Consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll protocols in this study have been approved by the Research Ethics Committee of Jinan Central Hospital Affiliated to Shandong First Medical University (20240924016) and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to the experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Natural Science Foundation of Shandong Province (ZR2023MC203), Shandong Provincial Medical and Health Science and Technology Development Plan Project (202204040490)\u0026zwnj;\u0026zwnj; and 2023 Jinan Healthcare Industry High-Level Talent Program. The authors gratefully thank Yan Xu from Hangzhou LC-BIO Co., Ltd for the technical assistance and help with the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003cstrong\u003eata Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYukun Guo: Formal analysis, Writing - original draft, Writing \u0026ndash; review and editing; Wenqing Liu: Data curation, Investigation; Weiting Bu: Investigation, Data curation; Ruoxi Wang: Investigation, Data curation; Daoqing Su: Resources, Supervision; Heng Li: Resources, Writing - original draft, Writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003eSource Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Natural Science Foundation of Shandong Province (ZR2023MC203), Shandong Provincial Medical and Health Science and Technology Development Plan Project (202204040490)\u0026zwnj;\u0026zwnj; and 2023 Jinan Healthcare Industry High-Level Talent Program. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTansey MG, Wallings RL, Houser MC, et al. 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Proximity extension assay testing reveals novel diagnostic biomarkers of atypical parkinsonian syndromes. J Neurol Neurosurg Psychiatry. 2019;90(7):768\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedersen CC, Ushakova A, Skogseth RE et al. Inflammatory Biomarkers in Newly Diagnosed Patients With Parkinson Disease and Related Neurodegenerative Disorders. Neurol Neuroimmunol Neuroinflamm. 2023;10(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoetz CG, Tilley BC, Shaftman SR, et al. Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology. 1967;17(5):427\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHepp DH, van Wageningen TA, Kuiper KL, et al. Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease. Int J Mol Sci. 2023;24:19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMogi M, Harada M, Narabayashi H, et al. Interleukin (IL)-1 beta, IL-2, IL-4, IL-6 and transforming growth factor-alpha levels are elevated in ventricular cerebrospinal fluid in juvenile parkinsonism and Parkinson's disease. Neurosci Lett. 1996;211(1):13\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e!!!. INVALID CITATION !!! 16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDinarello CA. Interleukin-18. Methods. 1999;19(1):121\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrinchieri G. Interleukin-12 and the regulation of innate resistance and adaptive immunity. Nat Rev Immunol. 2003;3(2):133\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, Wang Y, Le Q, et al. The IFN-γ-CXCL9/CXCL10-CXCR3 axis in vitiligo: Pathological mechanism and treatment. Eur J Immunol. 2024;54(4):e2250281.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKondo T, Takata H, Takiguchi M. Functional expression of chemokine receptor CCR6 on human effector memory CD8\u0026thinsp;+\u0026thinsp;T cells. Eur J Immunol. 2007;37(1):54\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarhood B, Najafi M, Mortezaee K. CD8(+) cytotoxic T lymphocytes in cancer immunotherapy: A review. J Cell Physiol. 2019;234(6):8509\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLandy E, Carol H, Ring A, et al. Biological and clinical roles of IL-18 in inflammatory diseases. Nat Rev Rheumatol. 2024;20(1):33\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang T, Langley KE, Gourley WK, et al. Stem cell factor (SCF) can regulate the activation and expansion of murine intraepithelial lymphocytes. Cytokine. 2000;12(3):272\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnnunziato F, Romagnani C, Romagnani S. The 3 major types of innate and adaptive cell-mediated effector immunity. J Allergy Clin Immunol. 2015;135(3):626\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTamai K, Ishikawa H, Mauviel A, et al. Interferon-gamma coordinately upregulates matrix metalloprotease (MMP)-1 and MMP-3, but not tissue inhibitor of metalloproteases (TIMP), expression in cultured keratinocytes. J Invest Dermatol. 1995;104(3):384\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWan LY, Huang HH, Zhen C, et al. Distinct inflammation-related proteins associated with T cell immune recovery during chronic HIV-1 infection. Emerg Microbes Infect. 2023;12(1):2150566.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheung TC. Modulation of T cell proliferation through the LIGHT-HVEM-BTLA cosignaling pathway. Recent Pat DNA Gene Seq. 2009;3(3):177\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRathnayake D, Chang T, Udagama P. Selected serum cytokines and nitric oxide as potential multi-marker biosignature panels for Parkinson disease of varying durations: a case-control study. BMC Neurol. 2019;19(1):56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaliano-Landeira J, Torra A, Vila M, et al. CD8 T cell nigral infiltration precedes synucleinopathy in early stages of Parkinson's disease. Brain. 2020;143(12):3717\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarter SL, M\u0026uuml;ller M, Manders PM, et al. Induction of the genes for Cxcl9 and Cxcl10 is dependent on IFN-gamma but shows differential cellular expression in experimental autoimmune encephalomyelitis and by astrocytes and microglia in vitro. Glia. 2007;55(16):1728\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanabe LM, Kim CE, Alagem N, et al. Primary dystonia: molecules and mechanisms. Nat Rev Neurol. 2009;5(11):598\u0026ndash;609.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarbon M, Eidelberg D. Abnormal structure-function relationships in hereditary dystonia. Neuroscience. 2009;164(1):220\u0026ndash;9.\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, inflammation, motor impairment, cerebrospinal fluid, proteomics","lastPublishedDoi":"10.21203/rs.3.rs-9090757/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9090757/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e Parkinson’s disease is a progressive neurodegenerative disorder in which neuroinflammation is recognized as a contributor to clinical progression. This study aimed to characterize the cerebrospinal fluid (CSF) inflammatory profile in mid- to late-stage PD patients and identify specific inflammatory proteins with potential clinical relevance to motor symptoms and disease severity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn this retrospective cross-sectional study, CSF samples were obtained from 25 patients with mid-to late- stage PD (mean disease duration: 10.24 ± 4.65 years) and 15 non-PD controls. The levels of 92 inflammation-related proteins were quantified using the Olink proximity extension assay (PEA). Based on the identified differentially expressed proteins (DEPs), we next compared inflammatory profiles between the postural instability and gait difficulty (PIGD, n = 10) and tremor-dominant (TD, n = 10) PD subtypes. Additionally, correlation analyses were performed between the DEPs and Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) scores to identify inflammatory biomarkers with potential clinical relevance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Using the Olink platform, 28 DEPs were identified between the PD and non-PD groups (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05). Subsequent protein–protein interaction network analysis identified IFN-γ as the central hub. Comparative analysis between the PIGD and TD subgroups revealed five DEPs (IFN-γ, ST1A1, TNFSF14, MMP-1, TRANCE) (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05). Among all DEPs, IL-10RB (r = 0.440, \u003cem\u003ep\u003c/em\u003e= 0.028), CD8A (r = 0.414, \u003cem\u003ep\u003c/em\u003e = 0.039), and CXCL9 (r = 0.414, \u003cem\u003ep\u003c/em\u003e = 0.040) showed the strongest correlations with UPDRS-III scores.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study identifies IFN-γ as the central hub protein within the CSF inflammatory network in mid- to late-stage PD and highlights specific T cell-related DEPs that are strongly associated with motor dysfunction. These proteins may represent potential targets for future anti-inflammatory therapies and serve as biomarkers for tracking disease progression.\u003c/p\u003e","manuscriptTitle":"Inflammatory Protein Landscape in the CSF of Mid- to Late- Stage Parkinson’s Disease: Associations with Motor Severity and Subtypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 17:17:14","doi":"10.21203/rs.3.rs-9090757/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-16T11:40:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-15T16:35:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-11T10:27:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T16:16:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61981737424872115547213786479599950803","date":"2026-03-22T07:35:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95715030158389855152348212402478866066","date":"2026-03-22T02:52:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165746470631077064481880560465067101254","date":"2026-03-20T16:16:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231482689126727465678363548628243851390","date":"2026-03-20T15:01:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3891664688889215336234168232902820672","date":"2026-03-20T14:06:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"250651576600536218640462922539649717346","date":"2026-03-20T03:50:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T22:53:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T22:50:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-19T16:33:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-19T15:57:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neurology","date":"2026-03-19T14:54:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"425af3d8-4e58-4488-8041-f8f313d3d5af","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T04:38:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 17:17:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9090757","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9090757","identity":"rs-9090757","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}