Bioinformatics approach reveals the critical role of the NOD-like receptor signaling pathway in COVID-19-associated multiple sclerosis syndrome.

Multiple sclerosis (MS) is a kind of central nervous system (CNS) autoimmune disease, which mainly damages nerves, the brain, and the spinal cord. Recently, several clinical cases reported the relativity between Coronavirus Disease 2019 (COVID-19) and the development of MS, but the mechanism of how COVID-19 affects the occurrence of MS was still not clear. It is bioinformatics technology that we use to explore the potential association at the gene level. The genetic information related to the two diseases was collected from the DisGNET platform for functional protein network analysis and used STRING to identify the complete gene set. The protein-protein interaction (PPI) network was analyzed by STRING. Finally, in the GEO database, we selected peripheral blood mononuclear cell (PBMC) RNA sequencing data (GSE164805, GSE21942) from COVID-19 patients and MS patients to verify the potential cross mechanism between the two diseases. The similar gene set of immune or inflammation existed between the patients with COVID-19 and ones with MS, including L2RA, IFNG, IL1B, NLRP3, and TNF. Interaction network analysis among proteins revealed that IL1B, P2RX7, IFNB1, IFNB1, TNF, and CASP1 enhanced the network connectivity between the combined gene set of COVID-19 and MS associated with NOD-like receptor (NLR) signaling. The involvement of NLR signaling in both diseases was further confirmed by comparing peripheral blood monocyte samples from COVID-19 and MS patients. Activation of NLR signaling was found in both COVID-19 and MS. The PBMC samples analyses also indicated the involvement of the NLR signaling pathway. Taken together, our data analyses revealed that the NLR signaling pathway might play a critical role in the COVID-19-related MS.