Correlation between neutrophil-to-lymphocyte ratio and severity of myasthenia gravis in adults: A retrospective study.

BACKGROUND: The study aimed to explore the clinical value of neutrophil-to-lymphocyte (NLR) in evaluating myasthenia gravis (MG) severity and the correlation between NLR and the Quantitative Myasthenia Gravis Score (QMGS). METHODS: This study included 128 patients with MG and 116 healthy controls. We completed Myasthenia Gravis Foundation of America (MGFA) classification for patients with MG, and defined MGFA I, II, and III as mild MG and MGFA IV and V as severe MG. The NLR of the patients were calculated, and statistical analysis was performed, with statistical significance set at P < 0.05. When pairwise comparisons between patients with mild MG, severe MG, and the healthy controls were performed, P < 0.017 was considered statistically significant under Bonferroni correction. RESULTS: NLR was significantly higher in patients with severe MG than in those with mild MG [2.90(2.41-5.83) vs 1.72(1.38-2.51), P = 0.000] and in the healthy controls [2.90(2.41-5.83) vs 1.65(1.34-1.91), P = 0.000]. NLR was independently associated with severe MG. The cut-off value of NLR for differentiating mild MG from severe MG was 2.37, and the sensitivity and specificity were 0.900 and 0.815, respectively. The results of Spearman test showed that NLR was positively correlated with QMGS in mild MG. NLR tended to be correlated QMGS in patients with severe MG, but the difference was not statistically significant. CONCLUSION: NLR may be a helpful marker for identifying patients with severe MG. NLR can also be used to further evaluate disease severity, especially for mild MG.

Cerebrospinal fluid cells immune landscape in multiple sclerosis.

BACKGROUND: Multiple Sclerosis (MS) is a potentially devastating autoimmune neurological disorder, which characteristically induces demyelination of white matter in the brain and spinal cord. METHODS: In this study, three characteristics of the central nervous system (CNS) immune microenvironment occurring during MS onset were explored; immune cell proportion alteration, differential gene expression profile, and related pathways. The raw data of two independent datasets were obtained from the ArrayExpress database; E-MTAB-69, which was used as a derivation cohort, and E-MTAB-2374 which was used as a validation cohort. Differentially expressed genes (DEGs) were identified by the false discovery rate (FDR) value of < 0.05 and |log2 (Fold Change)|> 1, for further analysis. Then, functional enrichment analyses were performed to explore the pathways associated with MS onset. The gene expression profiles were analyzed using CIBERSORT to identify the immune type alterations involved in MS disease. RESULTS: After verification, the proportion of five types of immune cells (plasma cells, monocytes, macrophage M2, neutrophils and eosinophils) in cerebrospinal fluid (CSF) were revealed to be significantly altered in MS cases compared to the control group. Thus, the complement and coagulation cascades and the systemic lupus erythematosus (SLE) pathways may play critical roles in MS. We identified NLRP3, LILRB2, C1QB, CD86, C1QA, CSF1R, IL1B and TLR2 as eight core genes correlated with MS. CONCLUSIONS: Our study identified the change in the CNS immune microenvironment of MS cases by analysis of the in silico data using CIBERSORT. Our data may assist in providing directions for further research as to the molecular mechanisms of MS and provide future potential therapeutic targets in treatment.