Multiple sclerosis is a disease affecting the central nervous system where the immune system is involved in its pathogenesis. Both the nervous and immune system represent the most daunting example of complexity in biology. Despite considerable research efforts, the knowledge and understanding of the interaction between these two complex systems and the cause of multiple sclerosis is still unknown. Gene expression analysis on bulk populations of immune cells and bulk tissue have been heretofore performed in attend to delineate the transcriptome changes in the disease. Nonetheless, in this type of analysis the differences in gene expression and variability between the different players (single cells) involved in this complex disease will remain masked.
The rapid development of single-cell analysis has revolutionized our ability to study the complexity of both the immune and nervous system at the single cell level. Individual cells are now classified by their transcriptome rather than by expression of classical cell type markers. Using state-of-the-art single-cell genomics methods, such as single-cell RNA sequencing (scRNA-seq), we identify, until now, unknown cell phenotypes and cell-cell interactions making use of unbiased bioinformatics methods. Overall, this allows us to gain deeper insights into the complexity of multiple sclerosis, as well as other complex neuroimmunological diseases.