RESUMEN
OBJECTIVE AND DESIGN: We investigated the involvement of Th17 cells and T-cell immunoglobulin and mucin domain 3 (TIM-3) in Guillain-Barré syndrome (GBS) in comparison to healthy subjects. MATERIALS AND SUBJECTS: Peripheral blood samples were obtained from 29 healthy subjects and 29 GBS patients. TREATMENT: Peripheral blood mononuclear cells (PBMCs) and CD4(+) T cells were stimulated with anti-CD3 and anti-CD28 mAbs, in the absence or presence of anti-TIM-3 mAb. METHODS: mRNA levels of TIM-3 and the transcription factor retinoic acid-related orphan receptor γt (RORγt) were determined by RT-PCR and were expressed relative to ß-actin mRNA (housekeeping gene). Serum IFN-γ and IL-17 levels were determined by ELISA. RESULTS: Compared to controls, relative TIM-3 mRNA levels were lower in both stimulated and unstimulated PBMCs from GBS patients. Unstimulated GBS CD4(+) T cells and GBS CD4+ T cells stimulated with anti-CD3 and CD28 mAbs had higher relative RORγt mRNA expression compared to controls. GBS CD4(+) T cells secreted significantly more IFN-γ and IL-17 in the presence of anti-TIM-3 mAb. GBS patients had (1) higher numbers of Th17, but not Th1 or Th2 cells in peripheral blood and (2) higher serum concentrations of IFN-γ and IL-17 compared to controls. CONCLUSION: TIM-3 may inhibit Th17 cell activation, thereby modulating their cytokine secretion patterns. Th17 cell differentiation, IL-17 levels, and TIM-3 regulation may be involved in the pathogenesis of GBS.
Asunto(s)
Diferenciación Celular/inmunología , Síndrome de Guillain-Barré/inmunología , Activación de Linfocitos , Proteínas de la Membrana/inmunología , Células Th17/inmunología , Adulto , Femenino , Síndrome de Guillain-Barré/sangre , Síndrome de Guillain-Barré/patología , Receptor 2 Celular del Virus de la Hepatitis A , Humanos , Interferón gamma/sangre , Interferón gamma/inmunología , Interleucina-17/sangre , Interleucina-17/inmunología , Masculino , Proteínas de la Membrana/biosíntesis , Persona de Mediana Edad , Miembro 3 del Grupo F de la Subfamilia 1 de Receptores Nucleares/biosíntesis , Miembro 3 del Grupo F de la Subfamilia 1 de Receptores Nucleares/inmunología , ARN Mensajero/biosíntesis , ARN Mensajero/inmunología , Células TH1/inmunología , Células TH1/metabolismo , Células TH1/patología , Células Th17/metabolismo , Células Th17/patología , Células Th2/inmunología , Células Th2/metabolismo , Células Th2/patología , Adulto JovenRESUMEN
Background: To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. Therefore, this study aims to comprehensively analyse and explore the molecular mechanisms and immunological features of Ferroptosis-related genes in the pathogenesis of AD. Materials and methods: We obtained the brain tissue dataset for AD from the GEO database and downloaded the Ferroptosis-related gene set from FerrDb for analysis. The most relevant Hub genes for AD were obtained using two machine learning algorithms (Least absolute shrinkage and selection operator (LASSO) and multiple support vector machine recursive feature elimination (mSVM-RFE)). The study of the Hub gene was divided into two parts. In the first part, AD patients were genotyped by unsupervised cluster analysis, and the different clusters' immune characteristics were analysed. A PCA approach was used to quantify the FRGscore. In the second part: we elucidate the biological functions involved in the Hub genes and their role in the immune microenvironment by integrating algorithms (GSEA, GSVA and CIBERSORT). Analysis of Hub gene-based drug regulatory networks and mRNA-miRNA-lncRNA regulatory networks using Cytoscape. Hub genes were further analysed using logistic regression models. Results: Based on two machine learning algorithms, we obtained a total of 10 Hub genes. Unsupervised clustering successfully identified two different clusters, and immune infiltration analysis showed a significantly higher degree of immune infiltration in type A than in type B, indicating that type A may be at the peak of AD neuroinflammation. Secondly, a Hub gene-based Gene-Drug regulatory network and a ceRNA regulatory network were successfully constructed. Finally, a logistic regression algorithm-based AD diagnosis model and Nomogram diagram were developed. Conclusion: Our study provides new insights into the role of Ferroptosis-related molecular patterns and immune mechanisms in AD, as well as providing a theoretical basis for the addition of diagnostic markers for AD.