An integrative study of genetic variants with brain tissue expression identifies viral etiology and potential drug targets of multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disorder leading to chronic disability. Brain lesions in MS commonly arise in normal-appearing white matter (NAWM). Genome-wide association studies (GWAS) have identified genetic variants associated with MS. Transcriptome alterations have been observed in case-control studies of NAWM. We developed a Cross-Dataset Evaluation (CDE) function for our network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS). We applied CDE to integrate publicly available MS GWAS summary statistics of 41,505 cases and controls with collectively 38 NAWM expression samples, using the human protein interactome as the reference network, to investigate biological underpinnings of MS etiology. We validated the resulting modules with colocalization of GWAS and expression quantitative trait loci (eQTL) signals, using GTEx Consortium expression data for MS-relevant tissues: 14 brain tissues and 4 immune-related tissues. Other network assessments included a drug target query and functional gene set enrichment analysis. CDE prioritized a MS NAWM network containing 55 unique genes. The gene list was enriched (p-value = 2.34 × 10-7) with GWAS-eQTL colocalized genes: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. The resultant network also included drug signatures of FDA-approved medications. Gene set enrichment analysis revealed the top functional term "intracellular transport of virus", among other viral pathways. We prioritize critical genes from the resultant network: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. Enriched drug signatures suggest potential drug targets and drug repositioning strategies for MS. Finally, we propose mechanisms of potential MS viral onset, based on prioritized gene set and functional enrichment analysis.