Machine Learning Model for Predicting Risk of Primary Sj?gren's syndrome using N7-methylguanosine-related Genes

The current study aimed to delve deeper into the intricate role of N7-methylguanosine (m7G) regulators in the etiology and pathogenesis of primary Sjögren's syndrome (PSS). PSS is a chronic autoimmune disease characterized by the inflammation of salivary and lacrimal glands, leading to dry eyes and mouth. Despite its prevalence and impact on patient quality of life, the underlying mechanisms of PSS remain incompletely understood. To address this knowledge gap, we utilized bioinformatics techniques and the powerful extreme gradient boosting decision tree algorithm to identify key m7G-related genes from publicly available datasets. Specifically, we analyzed datasets GSE7451, GSE40611, and GSE84844, which are rich in genetic expression data and accessible through the Gene Expression Omnibus database. From these datasets, we identified six crucial m7G-related genes that are potentially involved in PSS pathogenesis. These genes were then employed to develop a prediction model that can accurately assess the risk of PSS. The model, based on the identified genes, showed promising results with high accuracy, AUC, sensitivity, and specificity in the training set. This indicates its potential in clinical settings to aid in the early diagnosis and risk stratification of PSS patients. Furthermore, we employed the single-sample gene set enrichment analysis (ssGSEA) method to gain insights into the immune landscape of PSS. This approach allowed us to assess the abundance of immune infiltration cells in PSS samples, providing a comprehensive understanding of the immune response patterns and potential mechanisms underlying PSS pathogenesis. Our findings suggest that m7G methylation may play a pivotal role in PSS through immune-mediated mechanisms, indicating its importance in the etiology and progression of the disease. Specifically, our study highlights the crucial role of m7G regulators in PSS pathogenesis. These regulators could potentially serve as therapeutic targets for future immunotherapy strategies. By understanding their role in PSS, we can develop more targeted and effective treatment options for patients with this debilitating disease. In conclusion, the current study provides valuable insights into the role of m7G methylation and its regulators in PSS pathogenesis. Our findings not only deepen our understanding of PSS immunology but also pave the way for the development of more effective treatment strategies for PSS patients.