Author Of 1 Presentation
P0050 - Comparative transcriptomics of multiple sclerosis vs. viral infections, including SARS-CoV-2 (ID 1045)
Abstract
Background
There are accumulating evidence in the literature that viral infections provide an environmental trigger for the onset of multiple sclerosis (MS) in genetically susceptible individuals. Furthermore, viral infections may contribute to the progression of disability in MS, triggering relapses and promoting neurodgeneration. There are multiple studies assessing the effect of viral infections both in vitro and ex vivo. No study to date has performed a head to head comparison of transcriptomic modulations between MS and viral infections. Furthermore, no study to date has performed these comparisons with the novel coronavirus, SARS-CoV-2, whose neurotropism potential is still under scrutiny.
Objectives
The purpose of this study is to discover common pathways between multiple sclerosis and viral infections, including SARS-CoV-2, on a transcriptomic and functional level.
Methods
The Gene Expression Omnibus (GEO) database was inquired using a query containing the keywords “Virus”, “Multiple Sclerosis”, “Infection”. Included studies involved ex vivo samples of peripheral blood mononuclear cells (PBMCs) following a case – control design. For SARS-CoV-2, a gene signature extracted from a recent infection translatomics experiment (Bojkova et al, 2020) was used in over-representation analyses, and subsequently comapred with the signatures extracted from the MS datasets.
Results
The initial search retrieved 35 studies. Applying the predetermined inclusion criteria, 2 MS vs Healthy Controls (HC) studies and 3 studies of viral infection vs. HC (Dengue, SARS Coronavirus and Rotavirus infections). Multiple common, differentially expressed genes (DEGs) and associated significantly enriched pathways emerged between the MS vs viral infection subgroups. The “Epstein Barr infection” pathway was salient among MS-related viral infection pathways (False Discovery Rate (FDR) <0.05). Furthermore, comparative transcriptomics revealed 4 common gene signatures of 80 to 150 genes, associated with nuclear transport, neuroactive peptide binding and the spliceosome (FDR<0.0001). Comparisons between the MS datasets and the SARS-CoV-2 - host interactome revealed overlapping perturbations in pathways associated with neurodegeneration and mRNA surveillance pathways (FDR<0.05). Notably, a confirmatory analysis of the SARS-CoV-2 interactome with Enrichr, comapring said interactome with disease-control experiments in the Gene Expression Omnibus (GEO) databases revealed relapsing remitting MS among diseases with overlapping gene signatures (FDR<0.05).
Conclusions
Ours is the first study to directly compare viral infection mechanisms with the molecular pathophysiology of MS in a transcriptomic level. Our results indicate a “response to infection” phenotype in MS PBMCs, associated with alternative splicing and disruptions of transcriptional surveillance.