A recent genome-wide association study reported five loci for which there was strong, but sub-genome-wide significant evidence for association with multiple sclerosis risk. The aim of this study was to evaluate the role of these potential risk loci in a large and independent data set of ? 20,000 subjects. We tested five single nucleotide polymorphisms rs228614 (MANBA), rs630923 (CXCR5), rs2744148 (SOX8), rs180515 (RPS6KB1), and rs6062314 (ZBTB46) for association with multiple sclerosis risk in a total of 8499 cases with multiple sclerosis, 8765 unrelated control subjects and 958 trios of European descent. In addition, we assessed the overall evidence for association by combining these newly generated data with the results from the original genome-wide association study by meta-analysis. All five tested single nucleotide polymorphisms showed consistent and statistically significant evidence for association with multiple sclerosis in our validation data sets (rs228614: odds ratio = 0.91, P = 2.4 × 10(-6); rs630923: odds ratio = 0.89, P = 1.2 × 10(-4); rs2744148: odds ratio = 1.14, P = 1.8 × 10(-6); rs180515: odds ratio = 1.12, P = 5.2 × 10(-7); rs6062314: odds ratio = 0.90, P = 4.3 × 10(-3)). Combining our data with results from the previous genome-wide association study by meta-analysis, the evidence for association was strengthened further, surpassing the threshold for genome-wide significance (P < 5 × 10(-8)) in each case. Our study provides compelling evidence that these five loci are genuine multiple sclerosis susceptibility loci. These results may eventually lead to a better understanding of the underlying disease pathophysiology.
Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
Recent advances in the identification of susceptibility genes and environmental exposures provide broad support for a post-infectious autoimmune basis for narcolepsy/hypocretin (orexin) deficiency. We genotyped loci associated with other autoimmune and inflammatory diseases in 1,886 individuals with hypocretin-deficient narcolepsy and 10,421 controls, all of European ancestry, using a custom genotyping array (ImmunoChip). Three loci located outside the Human Leukocyte Antigen (HLA) region on chromosome 6 were significantly associated with disease risk. In addition to a strong signal in the T cell receptor alpha (TRA@), variants in two additional narcolepsy loci, Cathepsin H (CTSH) and Tumor necrosis factor (ligand) superfamily member 4 (TNFSF4, also called OX40L), attained genome-wide significance. These findings underline the importance of antigen presentation by HLA Class II to T cells in the pathophysiology of this autoimmune disease.
Genome-wide association studies (GWAS), although efficient to detect genes involved in complex diseases, are not designed to measure the real effect of the genes. This is illustrated here by the example of IL2RA in multiple sclerosis (MS). Association between IL2RA and MS is clearly established, although the functional variation is still unknown: the effect of IL2RA might be better described by several SNPs than by a single one. This study investigates whether a pair of SNPs better explains the observed linkage and association data than a single SNP. In total, 522 trio families and 244 affected sib-pairs were typed for 26 IL2RA SNPs. For each SNP and pairs of SNPs, the phased genotypes of patients and controls were compared to determine the SNP set offering the best risk discrimination. Consistency between the genotype risks provided by the retained set and the identical by descent allele sharing in affected sib-pairs was assessed. After controlling for multiple testing, the set of SNPs rs2256774 and rs3118470, provides the best discrimination between the case and control genotype distributions (P-corrected=0.009). The relative risk between the least and most at-risk genotypes is 3.54 with a 95% confidence interval of [2.14-5.94]. Furthermore, the linkage information provided by the allele sharing between affected sibs is consistent with the retained set (P=0.80) but rejects the SNP reported in the literature (P=0.006). Establishing a valid modeling of a disease gene is essential to test its potential interaction with other genes and to reconstruct the pathophysiological pathways.
Single nucleotide polymorphisms (SNPs) rs429358 (?4) and rs7412 (?2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently.
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