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Diagnostic signatures and immune cell infiltration characteristics in anti-GABA B R encephalitis.
Journal of Neuroimmunology 2024 January 25
PURPOSE: Anti-gamma-aminobutyric acid B receptor (GABAB R) encephalitis is an uncommon form of autoimmune encephalitis associated with a poor prognosis and a high fatality rate. We aim to find diagnostic markers for anti- GABAB R encephalitis as well as the effects of immune cell infiltration on this pathology.
METHODS: For quantitative proteomic analysis, isobaric tags for relative and absolute quantitation were used in conjunction with LC-MS/MS analysis. To conduct functional correlation analyses, differentially expressed proteins (DEPs) were identified. Following that, we used bioinformatics analysis to screen for and determine the diagnostic signatures of anti- GABAB R encephalitis. ROC curves were used to evaluate the diagnostic values. To assess the inflammatory status of anti- GABAB R encephalitis, we used cell-type identification by estimating relative subsets of the RNA transcript (CIBERSORT) and explored the link between diagnostic markers and infiltrating immune cells.
RESULTS: Overall, 108 robust DEPs (47 upregulated and 61 downregulated) were identified, of which 11 were immune related. The most impressively enriched pathways were complemented and coagulation cascades, actin cytoskeleton regulation, and cholesterol metabolism; GSEA revealed that the enriched pathways were considerably differentially connected to immune modulation. Eleven immune-related DEPs were chosen for further investigation. We developed a novel diagnostic model based on CSF1R and AZGP1 serum levels using ROC analysis (area under the ROC curve = 1). M1 macrophages and activated natural killer cells are likely to play a role in course of anti- GABAB R encephalitis.
CONCLUSION: We identified CSF1R and AZGP1 are possible anti-GABAB R encephalitis diagnostic indicators, and immune cell infiltration may have a significant impact on the development and occurrence of anti- GABAB R encephalitis.
METHODS: For quantitative proteomic analysis, isobaric tags for relative and absolute quantitation were used in conjunction with LC-MS/MS analysis. To conduct functional correlation analyses, differentially expressed proteins (DEPs) were identified. Following that, we used bioinformatics analysis to screen for and determine the diagnostic signatures of anti- GABAB R encephalitis. ROC curves were used to evaluate the diagnostic values. To assess the inflammatory status of anti- GABAB R encephalitis, we used cell-type identification by estimating relative subsets of the RNA transcript (CIBERSORT) and explored the link between diagnostic markers and infiltrating immune cells.
RESULTS: Overall, 108 robust DEPs (47 upregulated and 61 downregulated) were identified, of which 11 were immune related. The most impressively enriched pathways were complemented and coagulation cascades, actin cytoskeleton regulation, and cholesterol metabolism; GSEA revealed that the enriched pathways were considerably differentially connected to immune modulation. Eleven immune-related DEPs were chosen for further investigation. We developed a novel diagnostic model based on CSF1R and AZGP1 serum levels using ROC analysis (area under the ROC curve = 1). M1 macrophages and activated natural killer cells are likely to play a role in course of anti- GABAB R encephalitis.
CONCLUSION: We identified CSF1R and AZGP1 are possible anti-GABAB R encephalitis diagnostic indicators, and immune cell infiltration may have a significant impact on the development and occurrence of anti- GABAB R encephalitis.
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