Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci - PubMed (original) (raw)

. 2011 Dec;70(6):897-912.

doi: 10.1002/ana.22609.

Bayer Pharma MS Genetics Working Group; Steering Committees of Studies Evaluating IFNβ-1b and a CCR1-Antagonist; ANZgene Consortium; GeneMSA; International Multiple Sclerosis Genetics Consortium; Federica Esposito, Joachim Reischl, Stephan Lehr, David Bauer, Jürgen Heubach, Rupert Sandbrink, Christoph Pohl, Gilles Edan, Ludwig Kappos, David Miller, Javier Montalbán, Chris H Polman, Mark S Freedman, Hans-Peter Hartung, Barry G W Arnason, Giancarlo Comi, Stuart Cook, Massimo Filippi, Douglas S Goodin, Douglas Jeffery, Paul O'Connor, George C Ebers, Dawn Langdon, Anthony T Reder, Anthony Traboulsee, Frauke Zipp, Sebastian Schimrigk, Jan Hillert, Melanie Bahlo, David R Booth, Simon Broadley, Matthew A Brown, Brian L Browning, Sharon R Browning, Helmut Butzkueven, William M Carroll, Caron Chapman, Simon J Foote, Lyn Griffiths, Allan G Kermode, Trevor J Kilpatrick, Jeanette Lechner-Scott, Mark Marriott, Deborah Mason, Pablo Moscato, Robert N Heard, Michael P Pender, Victoria M Perreau, Devindri Perera, Justin P Rubio, Rodney J Scott, Mark Slee, Jim Stankovich, Graeme J Stewart, Bruce V Taylor, Niall Tubridy, Ernest Willoughby, James Wiley, Paul Matthews, Filippo M Boneschi, Alastair Compston, Jonathan Haines, Stephen L Hauser, Jacob McCauley, Adrian Ivinson, Jorge R Oksenberg, Margaret Pericak-Vance, Stephen J Sawcer, Philip L De Jager, David A Hafler, Paul I W de Bakker

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Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci

Nikolaos A Patsopoulos et al. Ann Neurol. 2011 Dec.

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Abstract

Objective: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci.

Methods: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease.

Results: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934(T) at 3p24.1 (odds ratio [OR], 1.17; p = 1.6 × 10(-8)) near EOMES, rs2150702(G) in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p = 3.3 × 10(-8)), and rs6718520(A) in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p = 3.4 × 10(-8)). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 × 10(-6) , some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1).

Interpretation: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

Copyright © 2011 American Neurological Association.

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Figures

Figure 1

Figure 1. Manhattan plot for the meta-analysis genome-wide – log(p-values) (fixed effects)

X axis displays the 22 autosomal chromosomes and Y axis the –log(p-values) per SNP. The red line represents the genome-wide significance level (5×10−8)

Figure 2

Figure 2. Regional association plots for the newly identified genome-wide significant loci and respective forest plots

(A, B) rs170934 in EOMES, (C, D) rs2150702 in MLANA, and (E, F) rs6718520 near THADA. Regional plots: The X axis plots 1 million basepairs around the most statistically significant (index) SNP, which is highlighted by a large red diamond. r2 of a given SNP with the index SNP is illustrated with the intensity of the red color. The blue line represents the recombination rate. Each square represents one SNP. Forest Plots: The per-datasets’ weights are from the fixed effects meta-analysis. The p-value is for the Cohran’s Q test for statistical heterogeneity. INFO score is an imputation quality metric, corresponding to the ratio of observed vs. expected allele frequency. Values greater of 0.8 indicate high imputation quality. Genotyped SNPs have a value of 1. SNPs that were genotyped in a given dataset are marked with an asterisk.

Figure 3

Figure 3. Overlap of the genetic architecture of MS with that of other inflammatory diseases

(A) Percentage of non-MHC genome-wide significant (P<5×10−8) SNPs of inflammatory diseases that are non-statistically significant (NS), or significant in the same direction (SD) or the opposite direction (OD) in the current MS meta-analysis. CE: celiac disease, CD: Crohn’s disease, UC: ulcerative colitis, IBD: inflammatory bowel diseases (CD+UC), PSO: psoriasis, RA: rheumatoid arthritis, SLE: systemic lupus erythematosus, T1D: type 1 diabetes, T2D: type 2 diabetes, HE: height, LI: lipids, MI: myocardial infraction. NS: non-statistically significant, OD: opposite direction of effects, SD: same direction of effects. (B) Regional association plot for the TAGAP gene. All SNPs report –lop(p-values) from the MS meta-analysis, besides the 3 ones indicated by the respective disease names. The p-values reported for these 3 SNPs come from the respective original publications. The T1D and CE SNP is rs1738074, whereas the RA one is rs212389.

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References

    1. Hauser SL, Oksenberg JR. The neurobiology of multiple sclerosis: genes, inflammation, and neurodegeneration. Neuron. 2006;52:61–76. - PubMed
    1. Hafler DA, Compston A, et al. International Multiple Sclerosis Genetics Consortium. Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med. 2007;357:851–62. - PubMed
    1. De Jager PL, Jia X, Wang J, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41:776–782. - PMC - PubMed
    1. Sanna S, Pitzalis M, Zoledziewska M, et al. Variants within the immunoregulatory CBLB gene are associated with multiple sclerosis. Nat Genet. 2010;42:495–7. - PMC - PubMed
    1. The Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20. Nat Genet. 2009;41:824–828. - PubMed

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