Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

Abstract

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

Figure 1

Distribution of cases and controls. All cases and controls were drawn from populations with European ancestry; cases from 15 countries and controls from 8. A: numbers of case (red) and control (black) samples from each country. B: The projection of samples onto the first two principal components of genetic variation, with cases shown on the left and controls on the right. The axes are orientated to approximate to the geography, and samples are colour coded as indicated in the legend. We genotyped the cases (9772) and some Swedish controls (527) using the Illumina Human 660-Quad platform, and the UK controls (5175, the WTCCC2 common control set^,) using the Illumina 1.2M platform. All other controls were genotyped externally using various Illumina genotyping systems (see Supplementary Information).

Figure 2

Regions of the genome showing association to multiple sclerosis. Columns from left to right: evidence for association from the linear mixed model analysis of the discovery data (thresholded at −log₁₀(p) = 12). Non-MHC regions containing associated SNPs are shown in red and are labelled with the rsID (bold for newly identified loci, black for strong evidence, grey for previously reported) and risk allele of the most significant SNP. * indicates that the locus contains a secondary SNP signal. Odds ratio and 95% confidence intervals estimated from the meta-analysis of the discovery and replication data (+ indicates estimates for previously-known loci from discovery data only). Risk allele frequency estimates in each of the control populations used in the study (each is shown as a vertical bar on a scale from 0 to 1 going left to right). For each region of association the number of genes is reported, and where non-zero a candidate gene is given. Black dots indicate that the candidate gene is physically the nearest gene included in the “immune system process” GO term. When the most-significant SNP tags a SNP predicted to have an impact on the function of the candidate gene this is indicated. Where such a SNP exists, the gene involved is selected as the candidate gene; otherwise the nearest gene is selected unless there are strong biological reasons for a different choice. The final column indicates SNPs which are correlated (r² > 0.1) with SNPs reported to be associated with other autoimmune (AI) diseases (abbreviations: RA = Rheumatoid arthritis; CeD = Celiac disease; UC = Ulcerative colitis; CrD = Crohns’s disease; T1D = Type 1 diabetes; PS = Psoriasis). An interactive version of the figure is available at www.well.ox.ac.uk/wtccc2/ms.

Figure 3

Graphical representation of the T helper cell differentiation pathway. The figure is derived from an image generated by Ingenuity Pathway Analysis (IPA) software version 8.8 (Ingenuity Systems, Inc., Redwood City, CA, USA). Alpha-numeric labels indicate the individual genes and gene complexes (nodes) included in the pathway (note some are included more than once). Coloured nodes are those containing a gene implicated by proximity to a SNP showing evidence of association. Red: in bold or grey in Figure 2 (plus MHC class II region and TNFα); Orange: other loci in Figure 2 or discovery P value < 1×10^−4.5 and consistent replication data. Yellow: Discovery P value < 1×10⁻³. Other molecules (proteins, vitamins etc.) may also be of relevance in these processes but are not included here as they are not currently listed as being part of this particular pathway in the IPA database.

Figure 4

Results for the main MHC alleles. A: Forest plots for each of the primary HLA alleles (HLA-A*02:01, DRB1*15:01, DRB1*03:01 and DRB1*13:03) showing consistency of effect across the populations and combined OR of 0.73, 3.1, 1.26 and 2.4 respectively (whiskers indicate 95% confidence intervals). B: The genealogical trees estimated for DRB1 (top) and HLA-A (bottom). These trees were constructed using classical HLA and SNP typing data available from the HapMap CEU haplotype data. Each left hand branch of the tree terminates on a set of haplotypes carrying a particular HLA allele. The coloured dots indicate the mostly likely locations for a disease-associated mutation as predicted by the GENECLUSTER program. In the DRB1 tree, the blue dot captures a risk effect attributable to all haplotypes carrying the *15:01 allele. The green dot captures a risk effect carried by all haplotypes carrying the *03:01 allele and the red dot captures a risk effect on haplotypes carrying *13:03 or *08:01. In the HLA-A plot, the orange dot is a protective mutation lying at the root of all *02:01, *02:05, *02:06 and *68:01 alleles. The blue dot in brackets denotes a branch containing those *03:01 haplotypes that also carry DRB1*15:01; the GENECLUSTER prediction here is thus a reflection, due to linkage disequilibrium of the risk attributable to DRB1*15:01. The terminal branches are labelled with the allele carried by the haplotype and its frequency.