The refinement of genetic predictors of multiple sclerosis.

A recent genome wide association study (GWAS) demonstrated that more than 100 genetic variants influence the risk of multiple sclerosis (MS). We investigated what proportion of the general population can be considered at high genetic risk of MS, whether genetic information can be used to predict disease development and how the recently found genetic associations have influenced these estimates. We used summary statistics from GWAS in MS to estimate the distribution of risk within a large simulated general population. We profiled MS associated loci in 70 MS patients and 79 healthy controls (HC) and assessed their position within the distribution of risk in the simulated population. The predictive performance of a weighted genetic risk score (wGRS) on disease status was investigated using receiver operating characteristic statistics. When all known variants were considered, 40.8% of the general population was predicted to be at reduced risk, 49% at average, 6.9% at elevated and 3.3% at high risk of MS. Fifty percent of MS patients were at either reduced or average risk of disease. However, they showed a significantly higher wGRS than HC (median 13.47 vs 12.46, p = 4.08×10(-10)). The predictive performance of the model including all currently known MS associations (area under the curve = 79.7%, 95%CI = 72.4%-87.0%) was higher than that of models considering previously known associations. Despite this, considering the relatively low prevalence of MS, the positive predictive value was below 1%. The increasing number of known associated genetic variants is improving our ability to predict the development of MS. This is still unlikely to be clinically useful but a more complete understanding of the complexity underlying MS aetiology and the inclusion of environmental risk factors will aid future attempts of disease prediction.

Regulatory genomic regions active in immune cell types explain a large proportion of the genetic risk of multiple sclerosis.

There is little understanding of how genetic variants discovered in recent genome-wide association studies are involved in the pathogenesis of multiple sclerosis (MS). We aimed to investigate which chromatin states and cell types explain genetic risk in MS. We used genotype data from 1854 MS patients and 5164 controls produced by the International Multiple Sclerosis Genetics Consortium and Wellcome Trust Case Control Consortium. We estimated the proportion of phenotypic variance between cases and controls explained by cell-specific chromatin state and DNase I hypersensitivity sites (DHSs) using the Genome-wide Complex Trait Analysis software. A large proportion of variance was explained by single-nucleotide polymorphisms (SNPs) in strong enhancer (SE) elements of immortalized B lymphocytes (5.39%). Three independent SNPs located within SE showed suggestive evidence of association with MS: rs12928822 (odds ratio (OR)=0.81, 95% confidence interval (CI)=0.73-0.89, P=2.48E-05), rs727263 (OR=0.75, 95% CI=0.66-0.85, P=3.26E-06) and rs4674923 (OR=0.85, 95% CI=0.79-0.92, P=1.63E-05). Genetic variants located within DHSs of CD19+ B cells explained the greatest proportion of variance. Genetic variants influencing the risk of MS are located within regulatory elements active in immune cells. This study also identifies a number of immune cell types likely to be involved in the causal cascade and that carry important implications for future studies of therapeutic design.