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Background <p>Bacterial meningitis complicated by neurological complications (BMN) is a major cause of poor outcomes and mortality among children with bacterial meningitis. So far, the host-related mechanisms and diagnostic biomarkers of BMN and bacterial meningitis without neurological complications (BM) remain poorly understood and limited.</p> Methods <p>We implemented a two-stage cerebrospinal fluid (CSF) quantitative proteomics study involving three groups: children with BMN, BM, and diseases not involving the central nervous system(Ctrl). Initially, in the discovery cohort, data-independent acquisition (DIA) mass spectrometry was used for proteomic profiling on 242 CSF samples (77 BMN, 52 BM, and 113 Ctrl). Differentially expressed proteins (DEPs) were identified among the BMN/Ctrl, BM/Ctrl, and BMN/BM groups, followed by an analysis of their functional enrichment. Next, the parallel reaction monitoring (PRM) method was used to validate the essential DEPs identified during the DIA phase in a validation cohort of 196 subjects (94 BMN, 47 BM, and 55 Ctrl). Subsequently, the validated DEPs were further filtered to construct a PRM-based machine learning model that distinguishes between BMN and BM.</p> Results <p>A total of 1376 DEPs were identified in BM/Ctrl (757 upregulated, 619 downregulated), 1295 in BMN/Ctrl (745 upregulated, 550 downregulated), and 356 in BMN/BM(60 upregulated, 296 downregulated), respectively. The functional results indicate that the upregulated DEPs were primarily enriched in immunity, inflammation, complement, and phagocytosis in BMN/Ctrl and BM/Ctrl. Immunoglobulin production, phagocytosis, and the classical pathway of complement activation were further upregulated in BMN/BM. The downregulated DEPs are primarily enriched in cell adhesion, nervous system function, and synapses in BMN/Ctrl and BM/Ctrl; some were further enriched in BMN/BM. In addition, some of the innate immunity, translation, signal transduction, nervous system, and redox processes were mainly downregulated in BMN/BM. The PRM successfully verified 22 significant DEPs. Among them, UAB1, MTPN, ARHGDIB, IGHG3, and AMBP could be combined to distinguish BMN from BM, achieving an AUC of 0.998 in the training set and 0.824 in the validation set.</p> Conclusions <p>This study identified distinct CSF protein expression profiles in children with BMN, BM, and Ctrl, potentially enhancing our understanding of the molecular mechanisms underlying bacterial meningitis. These protein signatures help us distinguish bacterial meningitis from the Ctrl group. Furthermore, selected biomarkers could support the differentiation between BMN and BM.</p>

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Cerebrospinal fluid quantitative proteomic reveals potential mechanisms and biomarker candidates of children with bacterial meningitis complicated by neurological complications

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月11日

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  • Binglin Jian,
  • Jing Wei,
  • Liang Zhu,
  • Lingyun Guo,
  • Bing Hu,
  • Yue Xie,
  • Tianming Chen,
  • Bing Liu,
  • Wanrong Li,
  • Jidong Du,
  • Linlin Liu,
  • Xixi Zhang,
  • Wei Sun,
  • Zhengguang Guo,
  • Kaihu Yao,
  • Lulu Jia,
  • Gang Liu

摘要

Background

Bacterial meningitis complicated by neurological complications (BMN) is a major cause of poor outcomes and mortality among children with bacterial meningitis. So far, the host-related mechanisms and diagnostic biomarkers of BMN and bacterial meningitis without neurological complications (BM) remain poorly understood and limited.

Methods

We implemented a two-stage cerebrospinal fluid (CSF) quantitative proteomics study involving three groups: children with BMN, BM, and diseases not involving the central nervous system(Ctrl). Initially, in the discovery cohort, data-independent acquisition (DIA) mass spectrometry was used for proteomic profiling on 242 CSF samples (77 BMN, 52 BM, and 113 Ctrl). Differentially expressed proteins (DEPs) were identified among the BMN/Ctrl, BM/Ctrl, and BMN/BM groups, followed by an analysis of their functional enrichment. Next, the parallel reaction monitoring (PRM) method was used to validate the essential DEPs identified during the DIA phase in a validation cohort of 196 subjects (94 BMN, 47 BM, and 55 Ctrl). Subsequently, the validated DEPs were further filtered to construct a PRM-based machine learning model that distinguishes between BMN and BM.

Results

A total of 1376 DEPs were identified in BM/Ctrl (757 upregulated, 619 downregulated), 1295 in BMN/Ctrl (745 upregulated, 550 downregulated), and 356 in BMN/BM(60 upregulated, 296 downregulated), respectively. The functional results indicate that the upregulated DEPs were primarily enriched in immunity, inflammation, complement, and phagocytosis in BMN/Ctrl and BM/Ctrl. Immunoglobulin production, phagocytosis, and the classical pathway of complement activation were further upregulated in BMN/BM. The downregulated DEPs are primarily enriched in cell adhesion, nervous system function, and synapses in BMN/Ctrl and BM/Ctrl; some were further enriched in BMN/BM. In addition, some of the innate immunity, translation, signal transduction, nervous system, and redox processes were mainly downregulated in BMN/BM. The PRM successfully verified 22 significant DEPs. Among them, UAB1, MTPN, ARHGDIB, IGHG3, and AMBP could be combined to distinguish BMN from BM, achieving an AUC of 0.998 in the training set and 0.824 in the validation set.

Conclusions

This study identified distinct CSF protein expression profiles in children with BMN, BM, and Ctrl, potentially enhancing our understanding of the molecular mechanisms underlying bacterial meningitis. These protein signatures help us distinguish bacterial meningitis from the Ctrl group. Furthermore, selected biomarkers could support the differentiation between BMN and BM.