In multiple sclerosis (MS), a relationship with viral infection has long been recognized, starting from clinical evidence of an association between infectious events and disease onset or relapse. Herpesviridae and human endogenous retroviruses (HERVs) are among the most studied viral families in MS. These exposures share the characteristic of being latent persisting infections with hidden or dormant phases that allow them to escape immune detection and reactivate upon exposure to several stimuli. Moreover, their preferential tropism for cells of the central nervous system (CNS) and immune system accounts for their plausible pathogenic role in neuroinflammation. Compartmentalized and persisting chronic inflammation within the CNS is a feature of MS, as compared with other forms of self-limiting demyelinating conditions. This has suggested the existence of a persistent agent (such as a latent virus) that sustains the pathogenic loop and determines consequent tissue damage, failure of reparative mechanisms, and accumulation of neurological deficits. This review aims to survey the literature on the relationship between viruses and MS, with special reference to the levels of complexity in the loop that can modify disease risk, namely non-genetic risk factors (including viral components) that interact with each other and with genetic variants, with possible effects on both the host and viral genome. We will also review the latest advances in therapeutic targeting virus-induced dysregulations in MS.

Genome-wide association studies have identified more than 200 multiple sclerosis (MS)-associated loci across the human genome over the last decade, suggesting complexity in the disease etiology. This complexity poses at least two challenges: the definition of an etiological model including the impact of nongenetic factors, and the clinical translation of genomic data that may be drivers for new druggable targets. We reviewed studies dealing with single genes of interest, to understand how MS-associated single nucleotide polymorphism (SNP) variants affect the expression and the function of those genes. We then surveyed studies on the bioinformatic reworking of genome-wide association studies (GWAS) data, with aggregate analyses of many GWAS loci, each contributing with a small effect to the overall disease predisposition. These investigations uncovered new information, especially when combined with nongenetic factors having possible roles in the disease etiology. In this context, the interactome approach, defined as “modules of genes whose products are known to physically interact with environmental or human factors with plausible relevance for MS pathogenesis”, will be reported in detail. For a future perspective, a polygenic risk score, defined as a cumulative risk derived from aggregating the contributions of many DNA variants associated with a complex trait, may be integrated with data on environmental factors affecting the disease risk or protection.