Abstract
Multiple sclerosis (MS) is a leading cause of chronic neurological dysfunction in young to middle-aged adults, affecting approximately 2.5 million people worldwide. It is characterized by inflammation, multifocal demyelination, axonal loss, and white and gray matter gliosis. Autophagy is a highly conserved protein degradation pathway. Polymorphisms in autophagy-related genes have been implicated in a variety of autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, psoriasis and MS. However, the significance of autophagy in MS remains to be elucidated. This paper aims to explore the potential role of autophagy-related genes in MS diseases by using bioinformatics combined with machine learning methods. Finally, we obtained 9 autophagy genes with the highest correlation with MS, and further changes in these autophagy genes were verified in the experimental autoimmune encephalomyelitis (EAE) model and oligodendrocyte precursor cells (OPCs) engulfed myelin debris (MD). Combined with bioinformatic analysis and experimental data, Becn1 showed obvious expression abnormalities suggesting that this gene has vital functions in autophagy and MD engulfed by OPCs. This work will be of great significance for the further exploration of autophagy-related genes in demyelinating diseases.