We review here our current understanding of the genetic aetiology of the common complex neurological disease multiple sclerosis (MS). The strongest genetic risk factor for MS is the major histocompatibility complex which was identified in the 1970s. In 2011, after a number of genome-wide association studies have been completed and have identified approximately 20 new genes for MS, we ask the question—what is next for the genetics of MS?
Hermann Eichorst first recognized the familial clustering of multiple sclerosis (MS) late in the 19th century [
Progress in identifying the genes responsible has, historically, progressed at a glacial pace, despite the early success with the major histocompatibility complex (MHC) association. In 1972, MS was shown to be associated with the MHC [
Unfortunately far from it; the associated variants so far identified explain about 50% of the inherited risk of MS. There are several possible explanations as to the “missing” genetic basis of MS.
It is possible that the immune-related disease loci identified to date have more of an overall impact on MS risk than currently estimated. This can result when the marker SNP is an imperfect proxy for the actual causal mutation that led to the association signal. There is some evidence to support this hypothesis in complex disease. Recent resequencing of 63 GWAS-identified positional candidate genes in Crohn’s disease identified three novel low-frequency coding variants in the
Perhaps there are additional disease loci than the roughly 20 or so associated genes? These other susceptibility genes could be identified by even larger scale GWAS involving tens or hundreds of thousands of MS patients and controls. The GWAS published so far in MS have not exceeded 2000 patients in the initial (screening) phase. Statistical modelling has suggested that 12,627 SNPs explains approximately 3% of the variance in MS risk [
Another explanation may be that some disease loci may contain only rare variants. In order to identify these genes a sequencing-based approach would be required. In the past this was not possible given the cost and technology available; however recent advances in next-generation sequencing technologies (whole exome and whole genome sequencing) could rapidly facilitate the identification of these variants that would be too rare to be picked up by GWAS. These rare variants would be expected to be causal and have a relatively large effect on risk (i.e., OR > 3). The 1000-Genomes project has highlighted the fact that each of us has 250 to 300 loss-of-function variants in our genes [
SNPs are only one type of genetic variation. It has been observed that individual copies of the human genome contain large regions (tens to hundreds of kilobases in size) that are deleted, duplicated, or inverted relative to the reference sequence. These structural variants may contribute to MS aetiology but have not yet been adequately tested. However, a study by the Wellcome Trust Case Control Consortium observed that most common structural variation are well tagged by SNPs and so have been indirectly explored through genomewide SNP studies and therefore concluded that common structural variants are unlikely to contribute greatly to the genetic basis of common human diseases [
Moving on from single locus associations to consider biological systems, it may be that gene-gene and gene-environment interactions may play an important role in disease. Once patterns of association and interaction are better understood, the effects of specific gene and environmental exposures on developing MS may be significant. Indeed epistatic interactions exist between MHC haplotypes [
Epigenetic contributions may also play an important role in MS. Epidemiological data strongly hints at a parent-of-origin effect in MS [
As with all complex diseases, the genetics of MS has not yet been fully elucidated. While GWAS have been responsible for a wealth of new information these association studies have not provided all the answers for MS risk. We are now in an era of very exciting potential applications of sequencing technology. Next-generation sequencing platforms allow us to survey multiple levels of natural variation at unprecedented resolution and depth. As sequencing costs continue to decrease, and both laboratory and computational protocols improve, we will see ever increasing use of this technology, hopefully enabling us to completely unlock the complex genetic basis of MS. There is unlikely to have a single answer, with interactions, rare variants, epigenetic factors all likely to be contributing. Ultimately, well-performed functional studies will be required to understand how all these risk factors interact to predispose to MS. Against this it will be debated whether further genetic research will actually advance our understanding of MS. However, the motivation for future work is the need to understand disease mechanisms to derive safe and effective treatments and ultimately to prevent the disease.