Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20

Abstract

To identify multiple sclerosis (MS) susceptibility loci, we conducted a genome-wide association study (GWAS) in 1,618 cases and used shared data for 3,413 controls. We performed replication in an independent set of 2,256 cases and 2,310 controls, for a total of 3,874 cases and 5,723 controls. We identified risk-associated SNPs on chromosome 12q13-14 (rs703842, P = 5.4 x 10(-11); rs10876994, P = 2.7 x 10(-10); rs12368653, P = 1.0 x 10(-7)) and upstream of CD40 on chromosome 20q13 (rs6074022, P = 1.3 x 10(-7); rs1569723, P = 2.9 x 10(-7)). Both loci are also associated with other autoimmune diseases. We also replicated several known MS associations (HLA-DR15, P = 7.0 x 10(-184); CD58, P = 9.6 x 10(-8); EVI5-RPL5, P = 2.5 x 10(-6); IL2RA, P = 7.4 x 10(-6); CLEC16A, P = 1.1 x 10(-4); IL7R, P = 1.3 x 10(-3); TYK2, P = 3.5 x 10(-3)) and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15 (P = 0.001).

Genome‐wide association studies of multiple sclerosis

“…The three significant findings were simultaneously replicated in independent studies from the United Kingdom, the United States and the Nordic countries 31, 32. This opened the floodgates, with several successive studies GWAS and meta‐analysis followed in rapid succession, so that by 2011, common variants in 26 genomic loci had been associated with MS risk and independently replicated, but clearly only explained a fraction of MS risk attributable to genetic factors 33, 34, 35, 36, 37, 38, 39, 40, 41, 42. These studies collectively showed that non‐MHC MS risk alleles have modest effects on disease (odds ratios < 1.2) and that even larger sample sizes (over 10 000 cases and controls) would be needed to identify more loci 22.…”

“…This clinical course is unpredictable, and no tools for prognosis currently exist. Several studies have explored the genetic basis of clinical course, age of onset and severity, although no genome‐wide significant associations have been discovered 36, 37, 43, 74, 75, 76, 77. Whether more detailed disease parameters are more prone to error measurement, systematic differences across centres or simply not heritable remains to be determined, but a recent study showing that clinical scores can be predictive across centres suggests that lack of heritability is not the issue 78…”

Epigenetics: The missing link to understanding β-cell dysfunction in the pathogenesis of type 2 diabetes

“…Patients with T2D displayed enhanced methylation at 4 CpG (-234, -180, -102 and +63 relative to TSS) sites on the insulin promoter in islets, as compared with islets from non-diabetic patients, and methylation status of nine additional CpG sites were inversely correlated with insulin mRNA abundance. 96 Interestingly, when β-cell lines were exposed to high glucose conditions for 3 d, methylation status of the insulin promoter increased. 96 In the same study, authors found no relationship between aging and DNA methylation status, but did see a correlation between obesity and DNA methylation, acknowledging that sample size was a limiting factor in their analyses.…”

CD40 C/T-1 polymorphism plays different roles in Graves’ disease and Hashimoto’s thyroiditis: a meta-analysis

“…Subsequently, Blanco-Kelly et al replicated this effect in an independent MS cohort (1,564 patients and 2,948 controls) and corroborated the association of the minor allele of this polymorphism in MS risk (MS vs. Control: 29% vs. 27%, p =0.025) [55]. Including a recently performed genome-wide association study [56], they all proved that the susceptibility allele C described for GD or rheumatoid arthritis seemed to protect against MS and Crohn's disease (CD), suggestive of a different molecular mechanism involved in the aetiology of these conditions. Based on this knowledge, CD40 C/T-1 polymorphism can act as both the risk and protect factor in immune-mediated diseases.…”