The genetics of multiple sclerosis: an up-to-date review

Abstract

Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory-mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non-HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene-environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.

Figure 1. Non-MHC genetic variants associated MS susceptibility

This Figure depicts the allele frequencies in European controls of all MS associated variants and their respective OR for the risk allele (Table 1). It can be clearly seen that the effects of most risk alleles is modest. Almost half of the MS-associated alleles are common in Europeans (i.e. have a frequency higher than 50% in healthy individuals).

Figure 2. Biological pathways involved in MS susceptibility

Gene ontology (GO) analysis of genes associated with MS from the WTCCC2 study (6) and subsequent meta-analysis in 5,545 independent cases and 12,153 controls (128). A. Significant GO categories and their relationships. Categories (GO terms) are linked with an edge if they share at least two genes. Categories are colored by groups, defined by their overall similarity. The green group represents T cell function (most significant category is T cell activation), while the pink group represents B cell function (most significant category is B cell activation). B. The number of genes assigned to each term and their enrichment (red asterisks denotes significance after Bonferroni correction). C. Genes assigned to each term and their nominal significance for enrichment for both GO term and group.

Figure 3. The Multiple Sclerosis Genetic Burden (MSGB) Score

The GWAS approach opens possibilities for individual genetic risk score computations. The MSGB is based on an algorithm that incorporates each risk variant for a given individual and weighs each SNP according to its reported effect size. The MSGB score quantitatively represents the known MS genetic risk for each individual. This provides an opportunity to analyze patients in the context of whole populations allowing personalized care.