Integrative Bioinformatics Analysis Reveals Novel Blood-Based Biomarkers In Multiple Sclerosis Samples

Multiple sclerosis (MS), a complex neurological disease, affects more than 2 million people worldwide and causes a wide variety of symptoms, making it especially hard to diagnose. Characterized by neurodegeneration of the myelin sheath in the CNS caused by an autoimmune reponse, MS can cause symptoms such as fatigue, tremor, pain, and inflammatory lesions. Therefore, it is beneficial to consider blood-based biomarkers as a noninvasive, cost-effective approach to elucidating the mechanisms behind MS and designing potential therapies for the condition. Prior studies have shown that immune biomarkers for MS can be found in cerebrospinal fluid and saliva, so in this study, peripheral blood samples were analyzed from three different studies found on the GEO database. After rigorous filtration and overlapping gene analysis, a list of 325 DEGs was identified for further analysis. LRPPC, FNIP2, APOOL, COQ7, C15or57, ACTB and TP53 were identified as the top hub genes and overlapping genes betwen the dataset based on their relative interactions in the differentially expressed pathways from a STRING network with k-means clustering applied. Further PANTHER analysis revealed "regulation of killing of cells of another organism" (autophagic) and "MHC binding pathways" to be significantly overrepresented in the MS samples. Several other mitochondrial functions, cell cycle checkpoints, and transcription factors (CCAAT) were also found to be upregulated. This novel study, which used integrative bioinformatics analysis to cross-analyze three separate studies could provide valuable insights on the autoimmune and degenerative mechanisms behind MS. Overall, these biomarkers can provide additional evidence for development of rapid diagnostic kits or a permanent cure of MS in the future.