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已发表论文
脑脊液蛋白质组学分析：迈向早期中枢神经系统感染生物标志物的识别
Authors Ding Y, Wang H, Li K, Zhao S, Li D
Received 27 September 2025
Accepted for publication 20 January 2026
Published 2 February 2026 Volume 2026:19 570645
DOI https://doi.org/10.2147/IDR.S570645
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Oliver Planz
Yumin Ding,1 Haiyu Wang,1 Kaixu Li,1 Shujing Zhao,1 Dehong Li2
1School of Public Health, Gansu University of Chinese Medicine, Lanzhou, Gansu, 730000, People’s Republic of China; 2Department of Blood Transfusion, Gansu Provincial Hospital, Lanzhou, Gansu, 730000, People’s Republic of China
Correspondence: Dehong Li, Department of Blood Transfusion, Gansu Provincial Hospital, Lanzhou, Gansu, 730000, People’s Republic of China, Tel +86-15117107318, Email ldh810109@126.com
Objective: Early diagnosis of central nervous system (CNS) infections remains challenging. The aim of this study was to explore and identify potential biomarkers of CNS infection by comparing cerebrospinal fluid (CSF) proteomic characteristics in patients with tuberculous meningitis (TBM), purulent meningitis (PM), and viral meningitis (VM), as well as in patients without CNS infections.
Methods: We conducted the first systematic 4D-DIA comparative proteomic analysis of CSF across TBM (N=6), PM (N=6), VM (N=12), and controls (N=12) using pooled samples. Differential proteins were identified, subjected to GO and KEGG enrichment analyses, and used to construct protein-protein interaction networks for hub protein identification.
Results: Proteomic analysis revealed significant differences in CSF protein expression profiles among three types of meningitis. In TBM patients, 53 specific proteins were identified, primarily involved in the complement and coagulation cascade as well as the COVID-19-related immune pathway. PPI network analysis highlighted FGA, FGB, C4BPA, and ADAMTS13 as hub proteins exhibiting notably significant expression levels in TBM patients. In PM patients, 9 proteins were identified, predominantly linked to phagosomes and B-cell receptor signaling, with COLEC11 and ESM1 showing significantly higher expression. In VM patients, 29 proteins were identified, mainly associated with complement and coagulation pathways, featuring higher levels of TMED7, MMP17, and CD81.
Conclusion: This study delineated the CSF protein profiles in patients with TBM, PM, VM, and non-CNS infections. We identified several potential biomarkers, including FGA, FGB, C4BPA, ADAMTS13, COLEC11, ESM1, TMED7, MMP17, and CD81. Additionally, we proposed hypothetical molecular mechanisms that may offer valuable diagnostic and therapeutic insights for CNS infections. Nonetheless, given that this is a preliminary exploratory study, further validation through multicenter, large-sample cohort studies and functional experiments is necessary to substantiate the clinical relevance and utility of these biomarkers prior to any potential application in clinical practice.
Keywords: cerebrospinal fluid, proteomics, central nervous system infection, early diagnosis, biomarkers
1School of Public Health, Gansu University of Chinese Medicine, Lanzhou, Gansu, 730000, People’s Republic of China; 2Department of Blood Transfusion, Gansu Provincial Hospital, Lanzhou, Gansu, 730000, People’s Republic of China
Correspondence: Dehong Li, Department of Blood Transfusion, Gansu Provincial Hospital, Lanzhou, Gansu, 730000, People’s Republic of China, Tel +86-15117107318, Email ldh810109@126.com
Objective: Early diagnosis of central nervous system (CNS) infections remains challenging. The aim of this study was to explore and identify potential biomarkers of CNS infection by comparing cerebrospinal fluid (CSF) proteomic characteristics in patients with tuberculous meningitis (TBM), purulent meningitis (PM), and viral meningitis (VM), as well as in patients without CNS infections.
Methods: We conducted the first systematic 4D-DIA comparative proteomic analysis of CSF across TBM (N=6), PM (N=6), VM (N=12), and controls (N=12) using pooled samples. Differential proteins were identified, subjected to GO and KEGG enrichment analyses, and used to construct protein-protein interaction networks for hub protein identification.
Results: Proteomic analysis revealed significant differences in CSF protein expression profiles among three types of meningitis. In TBM patients, 53 specific proteins were identified, primarily involved in the complement and coagulation cascade as well as the COVID-19-related immune pathway. PPI network analysis highlighted FGA, FGB, C4BPA, and ADAMTS13 as hub proteins exhibiting notably significant expression levels in TBM patients. In PM patients, 9 proteins were identified, predominantly linked to phagosomes and B-cell receptor signaling, with COLEC11 and ESM1 showing significantly higher expression. In VM patients, 29 proteins were identified, mainly associated with complement and coagulation pathways, featuring higher levels of TMED7, MMP17, and CD81.
Conclusion: This study delineated the CSF protein profiles in patients with TBM, PM, VM, and non-CNS infections. We identified several potential biomarkers, including FGA, FGB, C4BPA, ADAMTS13, COLEC11, ESM1, TMED7, MMP17, and CD81. Additionally, we proposed hypothetical molecular mechanisms that may offer valuable diagnostic and therapeutic insights for CNS infections. Nonetheless, given that this is a preliminary exploratory study, further validation through multicenter, large-sample cohort studies and functional experiments is necessary to substantiate the clinical relevance and utility of these biomarkers prior to any potential application in clinical practice.
Keywords: cerebrospinal fluid, proteomics, central nervous system infection, early diagnosis, biomarkers