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- Beecham, Ashley H, et al.
(författare)
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Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis.
- 2013
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:11, s. 1353-60
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Sawcer, Stephen, et al.
(författare)
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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
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Tidskriftsartikel (refereegranskat)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.
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| 3. |
- Sundqvist, Emilie
(författare)
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Common viruses and host gene interactions in multiple sclerosis
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Multiple sclerosis (MS) is a neurological disorder, characterised by demyelination and inflammation of the central nervous system, leading to sensory and motor symptoms. MS is thought to be complex disease, with both environmental and genetic risk factors underlying disease susceptibility. Epstein-Barr virus (EBV) and cytomegalovirus (CMV) infections are two environmental risk factors, one with a robust association to MS (EBV) and one where the results have been more inconclusive (CMV). The strongest genetic risk factors lies within the HLA genes, with HLA-DRB1*15 as the strongest susceptibility factor, and HLA-A*02, as the most protective genetic factor. In paper I, the role of EBV infection, and the interaction with HLA-DRB1*15 and HLA-A*02 was studied. Anti-EBNA1 IgG was measured, as was IgG antibodies towards 5 different epitopes of EBNA1. High levels of EBNA1 385-420 IgG antibodies were strongly associated with MS, independent of EBNA1 IgG antibody level. There was interaction on the additive scale between EBNA1 385-420 IgG and HLA-DRB1*15 and absence of HLA-A*02. In paper II, we tried to replicate findings by Simon et al, where they found interaction on the multiplicative scale between EBNA1 IgG levels and smoking (never/ever), but our analysis showed no such interaction. In paper III, the association between CMV and MS was studied, yielding a significant negative association between CMV and MS. To further validate our results, a meta-analysis of published retrospective studies was performed, which provided a similar negative association, supporting our results. In paper IV, the focus shifted from the association of viruses to MS, to dissecting the host genetic influence on anti-JCV seropositivity and anti-JCV antibody levels. JC virus is the virus responsible for Progressive multifocal leukoencephalopathy (PML), a rare but potentially fatal side-effect seen in MS-patients treated with natalizumab. A meta-analysis of three genome wide association studies performed in two sets of MS cases, one Scandinavian and one German, and a set of Swedish controls, strongly indicated that the HLA class II region was involved in regulating anti-JCV antibody response, and anti-JCV antibody levels. Analysis of classically named HLA-alleles supported these findings. The alleles in the DRB1*15-DQB1*06:02-DQA1*01:02-haplotype were all strongly negatively associated with anti-JCV antibody status and low anti-JCV antibody levels. The alleles in the DRB1*13-DQB1*06:02-DQA1*01:03-haplotype were positively associated with anti-JCV antibody status. Several non-HLA loci were suggestively associated with anti-JCV antibody status and anti-JCV antibody levels (p<0.0001). However, these findings will have to be replicated in an independent dataset. This thesis highlights the interactions between environmental and genetic factors in modulating MS risk. It also shows that the HLA genes have a central role in the susceptibility to JCV infection.
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| 4. |
- Sundqvist, Emilie, et al.
(författare)
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Lack of replication of interaction between EBNA1 IgG and smoking in risk for multiple sclerosis
- 2012
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 79:13, s. 1363-1368
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Tidskriftsartikel (refereegranskat)abstract
- Background: Epstein-Barr virus infection, smoking, HLA-A*02, and DRB1*15 have all been proposed as risk factors for multiple sclerosis (MS). In 2010, Simon et al. described an interaction on the multiplicative scale between EBNA1 immunoglobulin G (IgG) and smoking regarding risk of MS, a finding that we attempted to replicate. Methods: This Swedish case-control study consisted of patients with newly diagnosed MS and matched controls. Using logistic regression, we analyzed association to MS risk and interactions between EBNA1 IgG and smoking, HLA-DRB1*15, and A*02, respectively, on the multiplicative scale. In addition, we analyzed interactions on the additive scale using attributable proportion due to interaction (AP). Results: We did not observe any interaction on the multiplicative scale between EBNA1 IgG and any of the 3 risk factors, smoking, DRB1*15, or absence of A*02, although in a conditional analysis the interaction with absence of A*02 becomes significant. However, we observed interactions on the additive scale between EBNA1 IgG and DRB1*15 (AP = 0.34, 95% confidence interval 0.11-0.57, p = 5 x 10(-3)) and between EBNA1 IgG and absence of A*02 (AP = 0.36, 0.13-0.59, p = 2 x 10(-3)) but not between smoking and DRB1*15 and EBNA1 IgG. The interaction between EBNA1 IgG and DRB1*15 was not significant in the conditional analysis. Conclusion: We did not observe any interaction between EBNA1 IgG and smoking, regardless of scale used, and thus did not replicate the observations from Simon et al. Neurology (R) 2012;79:1363-1368
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