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BackgroundMultiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers.MethodsMS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs.ResultsWe screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival.ConclusionIL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.

Background: The sphingosine-1-phosphate receptor (S1PR) modulator fingolimod (FTY720), which is commonly used as an immunomodulator in multiple sclerosis treatment, has recently been found to reduce pathological changes in the brain tissue of Alzheimer's disease (AD) animal models, but this has yet to be verified in human brain tissue. In this study, network pharmacology methods were applied to determine the potential pharmacological mechanisms of fingolimod in the frontal cortex of AD patients.Methods: The pharmacological macromolecular targets of fingolimod and fingolimod phosphate were downloaded from SwissTarget and DrugBank. Systematic intersection analysis of the expression profiles of brain frontal cortex tissues (423 AD tissues and 266 control tissues) was performed to obtain AD-associated fingolimod targets (F-ADGs). Immune cell infiltration analysis and a primary mouse cortical culture RNA-seq drug screen database were used to identify immune-related F-ADGs and cortex-related F-ADGs. Then, the expression values of F-ADGs were correlated with the disease severity score (MMSE score) of AD patients to identify severity-related F-ADGs. We also analyzed miRNA expression microarray data in the frontal cortex of AD patients associated with disease severity to obtain severity-related F-ADG-miRNAs.Results: A total of 188 F-ADGs were detected in the frontal cortices of AD patients and were enriched in biological processes such as synaptic signaling, inflammatory response, and response to oxygen-containing compounds. Eleven immune-related F-ADGs (like FPR1, BLNK.) and 17 cortex-related F-ADGs (like ALDH1L1, DUSP1.) were detected. Other F-ADGs, such as S1PR1 and GABBR2, although not classified into the above two categories, were still predicted by bioinformatics methods to play an important role in the development of AD. Two F-ADGs (GNAQ and MMP14) and 28 miRNAs (like miR- 323a-3p, miR-181a-5p.) were found to be associated with AD severity (MMSE 0-27 group). Fifteen F-ADGs (like ALDH1L1, FPR1, and IL6.) and 46 miRNAs (like miR-212-5p, miR-93-5p.) were found to be associated with mild or moderate dementia AD patients' severity (MMSE11-22 subgroup).Conclusions: Fingolimod may affect the brain frontal cortex function of AD patients in many different ways, such as affecting immune cell infiltration, nerve cell, or glial cell function, and synaptic function. miRNAs may also be involved. ALDH1L1, FPR1, S1PR1, and GABBR2 may be core drug targets.