Multiple sclerosis is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study findings into therapeutics and effective preventive strategies has been limited to date. We used Summary-Data-Based Mendelian Randomisation to synthesise findings from public expression quantitative trait locus, methylation quantitative trait locus, and Multiple Sclerosis Genome-Wide Association Study datasets. By correlating the effects of methylation on multiple sclerosis, methylation on expression, and expression on multiple sclerosis susceptibility, we prioritise genetic loci with evidence of influencing multiple sclerosis susceptibility. We overlay these findings onto a list of ‘druggable’ genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and STRING to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr virus-infected B cells, Lymphoblastoid Cell Lines. We conducted a systematic review of prioritised genes using the Open Targets platform to identify completed and planned trials targeting prioritised genes in multiple sclerosis and related disease areas. Expression of 45 genes in peripheral blood was strongly associated with multiple sclerosis susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leukocyte signalling. We refined this prioritised gene list by restricting to loci where CpG site methylation was associated with multiple sclerosis susceptibility, with gene expression, and where expression was associated with multiple sclerosis susceptibility. This approach yielded a list of 15 prioritised druggable target genes for which there was evidence of a pathway linking methylation, expression, and multiple sclerosis. Five of these 15 genes are targeted by existing drugs and three were replicated in a smaller expression Quantitative Trait Loci dataset (CD40, MERTK, and PARP1). In Lymphoblastoid Cell Lines, this approach prioritised 7 druggable gene targets, of which only one was prioritised by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritised genes in disorders related to multiple sclerosis. We use public datasets and Summary data-based Mendelian randomisation to identify a list of prioritised druggable genetic targets in multiple sclerosis. We hope our findings could be translated into a platform for developing targeted preventive therapies.