Multiple sclerosis (OMIM 126200) 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.1 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;2,3 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.4 Modestly powered Genome-Wide Association Studies (GWAS)5-10 have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects play a key role in disease susceptibility.11 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 9772 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 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 over-represented amongst those mapping close to the identified loci and particularly implicate T helper cell differentiation in the pathogenesis of multiple sclerosis.

BackgroundTechniques enabling targeted re-sequencing of the protein coding sequences of the human genome on next generation sequencing instruments are of great interest. We conducted a systematic comparison of the solution-based exome capture kits provided by Agilent and Roche NimbleGen. A control DNA sample was captured with all four capture methods and prepared for Illumina GAII sequencing. Sequence data from additional samples prepared with the same protocols were also used in the comparison.ResultsWe developed a bioinformatics pipeline for quality control, short read alignment, variant identification and annotation of the sequence data. In our analysis, a larger percentage of the high quality reads from the NimbleGen captures than from the Agilent captures aligned to the capture target regions. High GC content of the target sequence was associated with poor capture success in all exome enrichment methods. Comparison of mean allele balances for heterozygous variants indicated a tendency to have more reference bases than variant bases in the heterozygous variant positions within the target regions in all methods. There was virtually no difference in the genotype concordance compared to genotypes derived from SNP arrays. A minimum of 11× coverage was required to make a heterozygote genotype call with 99% accuracy when compared to common SNPs on genome-wide association arrays.ConclusionsLibraries captured with NimbleGen kits aligned more accurately to the target regions. The updated NimbleGen kit most efficiently covered the exome with a minimum coverage of 20×, yet none of the kits captured all the Consensus Coding Sequence annotated exons.

Genetic risk for multiple sclerosis (MS) is thought to involve both common and rare risk alleles. Recent GWAS and subsequent meta-analysis have established the critical role of the HLA locus and identified new common variants associated to MS. These variants have small odds ratios (ORs) and explain only a fraction of the genetic risk. To expose potentially rare, high-impact alleles, we conducted a GWAS of 68 distantly related cases and 136 controls from a high-risk internal isolate of Finland with increased prevalence and familial occurrence of MS. The top 27 loci with p < 10(-4) were tested in 711 cases and 1029 controls from Finland, and the top two findings were validated in 3859 cases and 9110 controls from more heterogeneous populations. SNP (rs744166) within the STAT3 gene was associated to MS (p = 2.75 x 10(-10), OR 0.87, confidence interval 0.83-0.91). The protective haplotype for MS in STAT3 is a risk allele for Crohn disease, implying that STAT3 represents a shared risk locus for at least two autoimmune diseases. This study also demonstrates the potential of special isolated populations in search for variants contributing to complex traits.