CSF proteomics identifies candidate biomarkers for distinguishing meningitis types
A 4D-DIA proteomic analysis of cerebrospinal fluid compared protein profiles across tuberculous, purulent, and viral meningitis. Each meningitis type showed a distinct protein signature, with hub proteins including FGA, FGB, and ADAMTS13 in TBM, COLEC11 and ESM1 in purulent meningitis, and CD81 in viral meningitis. While preliminary and requiring large-cohort validation, these markers could eventually improve early differential diagnosis of CNS infections.
The original study
Proteomic Analysis of Cerebrospinal Fluid: Toward the Identification of Biomarkers for Early Central Nervous System Infection.
- Authors
- Ding Y, Wang H, Li K, Zhao S, Li D
- Journal
- Infection and drug resistance
- PMID
- 41877912
Original abstract
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.