Systemic and cerebrospinal fluid biomarkers for tuberculous meningitis identification and treatment monitoring

Author:

Yao Xiang-Ping12ORCID,Hong Jian-Chen3,Jiang Zai-Jie1,Pan Yu-Ying1,Liu Xiao-Feng4,Wang Jun-Mei1,Fan Rui-Jie1,Yang Bi-Hui1,Zhang Wei-Qing4,Fan Qi-Chao5,Li Li-Xiu6,Lin Bi-Wei1ORCID,Zhao Miao12ORCID

Affiliation:

1. Department of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University , Fuzhou, China

2. Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University , Fuzhou, China

3. Department of Gastrointestinal Surgery, The First Affiliated Hospital, Fujian Medical University , Fuzhou, China

4. Department of Laboratory Medicine, The First Affiliated Hospital, Fujian Medical University , Fuzhou, China

5. Department of Infectious Disease, The First Affiliated Hospital, Fujian Medical University , Fuzhou, China

6. Department of Oncology, Fuzhou Pulmonary Hospital of Fujian , Fuzhou, China

Abstract

ABSTRACT Tuberculous meningitis (TBM) is a severe infectious disease affecting the central nervous system, causing high mortality and disability. However, current diagnostic methods for TBM using cerebrospinal fluid (CSF) lack sensitivity and predictive biomarkers for prognosis. We conducted a study on cytokine profiles in CSF and serum samples from TBM patients to identify disease-specific biomarkers. Patients were categorized into three groups: TBM ( n = 17), cryptococcal meningitis ( n = 10), and non-infection ( n = 6), and cytokine levels were quantified using a 48-plex panel. After treatment, we observed a significant reduction in the levels of 12 cytokines, indicating their potential use as biomarkers for treatment monitoring. Among them, monokine induced by interferon-γ (MIG) and interleukin-18 showed significant differences in serum or CSF cytokine levels compared to the control groups. CSF levels of MIG in TBM patients were negatively correlated with the CSF/blood glucose ratio ( r = −0.4728, P = 0.0475). Positive correlations were found between CSF leukocyte counts and several cytokines, including fibroblast growth factor-basic, granulocyte colony-stimulating factor (G-CSF), monocyte chemotactic protein-3, macrophage inflammatory protein 1 alpha (MIP-1α), and tumor necrosis factor alpha. G-CSF and MIP-1α were also positively correlated with CSF protein levels. Receiver operating characteristic curve analysis revealed that MIG exhibited the highest area under the curve of 0.92 [95% confidence interval (CI) 0.82–1.00] with a sensitivity of 0.85 (95% CI 0.58–0.97) and a specificity of 0.87 (95% CI 0.62–0.98), making it a promising diagnostic biomarker for TBM. Our study provides valuable insights into TBM’s pathogenesis and identifies potential biomarkers for diagnosis and evaluating treatment monitoring. IMPORTANCE Tuberculous meningitis is a life-threatening infection with high mortality and disability rates. Current diagnostic methods using cerebrospinal fluid (CSF) samples have limited sensitivity and lack predictive biomarkers for evaluating prognosis. This study’s findings reveal excessive activation of the immune response during tuberculous meningitis (TBM) infection. Notably, a strong negative correlation was observed between CSF levels of monokine induced by interferon-γ (MIG) and the CSF/blood glucose ratio in TBM patients. MIG also exhibited the highest area under the curve with high sensitivity and specificity. This study suggests that MIG may serve as a novel biomarker for differentiating TBM infection in CSF or serum, potentially leading to improved diagnostic accuracy and better patient outcomes.

Funder

MOST | National Natural Science Foundation of China

Joint Funds for the Innovation of Science and Technology, Fujian Province

Startup Fund for Scientific Research of Fujian Medical University

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Cell Biology,Microbiology (medical),Genetics,General Immunology and Microbiology,Ecology,Physiology

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