Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci (original) (raw)

References

1. Hauser, S.L. & Oksenberg, J.R. The neurobiology of multiple sclerosis: genes, inflammation, and neurodegeneration. Neuron 52, 61–76 (2006).
   Article CAS Google Scholar
2. Barcellos, L.F. et al. Heterogeneity at the HLA-DRB1 locus and risk for multiple sclerosis. Hum. Mol. Genet. 15, 2813–2824 (2006).
   Article CAS Google Scholar
3. Yeo, T.W. et al. A second major histocompatibility complex susceptibility locus for multiple sclerosis. Ann. Neurol. 61, 228–236 (2007).
   Article Google Scholar
4. Hafler, D.A. et al. Risk alleles for multiple sclerosis identified by a genomewide study. N. Engl. J. Med. 357, 851–862 (2007).
   Article CAS Google Scholar
5. Rubio, J.P. et al. Replication of KIAA0350, IL2RA, RPL5 and CD58 as multiple sclerosis susceptibility genes in Australians. Genes Immun. 9, 624–630 (2008).
   Article CAS Google Scholar
6. International Multiple Sclerosis Genetics Consortium. Refining genetic associations in multiple sclerosis. Lancet Neurol. 7, 567–569 (2008).
7. Ramagopalan, S.V., Anderson, C., Sadovnick, A.D. & Ebers, G.C. Genomewide study of multiple sclerosis. N. Engl. J. Med. 357, 2199–2200 (2007).
   Article CAS Google Scholar
8. Baranzini, S.E. et al. Genome-wide association analysis of susceptibility and clinical phenotype in multiple sclerosis. Hum. Mol. Genet. 18, 767–778 (2009).
   Article CAS Google Scholar
9. Frazer, K.A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).
   Article CAS Google Scholar
10. Li, Y. & Abecasis, G.R. Rapid haplotype reconstruction and missing genotype inference. Am. J. Hum. Genet. S79, 2290 (2006).
    Google Scholar
11. de Bakker, P.I. et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 17, R122–R128 (2008).
    Article CAS Google Scholar
12. Burton, P.R. et al. Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants. Nat. Genet. 39, 1329–1337 (2007).
    Article CAS Google Scholar
13. Aulchenko, Y.S. et al. Genetic variation in the KIF1B locus influences susceptibility to multiple sclerosis. Nat. Genet. 40, 1402–1403 (2008).
    Article CAS Google Scholar
14. de Bakker, P.I. et al. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat. Genet. 38, 1166–1172 (2006).
    Article CAS Google Scholar
15. De Jager, P.L. et al. The role of the CD58 locus in multiple sclerosis. Proc. Natl. Acad. Sci. USA 106, 5264–5269 (2009).
    Article CAS Google Scholar
16. Hoffmann, L.A. et al. TNFRSF1A R92Q mutation in association with a multiple sclerosis-like demyelinating syndrome. Neurology 70, 1155–1156 (2008).
    Article CAS Google Scholar
17. Kumpfel, T. et al. Late-onset tumor necrosis factor receptor-associated periodic syndrome in multiple sclerosis patients carrying the TNFRSF1A R92Q mutation. Arthritis Rheum. 56, 2774–2783 (2007).
    Article Google Scholar
18. Aksentijevich, I. et al. The tumor-necrosis-factor receptor-associated periodic syndrome: new mutations in TNFRSF1A, ancestral origins, genotype-phenotype studies, and evidence for further genetic heterogeneity of periodic fevers. Am. J. Hum. Genet. 69, 301–314 (2001).
    Article CAS Google Scholar
19. Wildemann, B. et al. The tumor-necrosis-factor-associated periodic syndrome, the brain, and tumor-necrosis-factor-alpha antagonists. Neurology 68, 1742–1744 (2007).
    Article CAS Google Scholar
20. Jenne, D.E. et al. The low-penetrance R92Q mutation of the tumour necrosis factor superfamily 1A gene is neither a major risk factor for Wegener's granulomatosis nor multiple sclerosis. Ann. Rheum. Dis. 66, 1266–1267 (2007).
    Article Google Scholar
21. Pedchenko, T.V., Park, G.Y., Joo, M., Blackwell, T.S. & Christman, J.W. Inducible binding of PU.1 and interacting proteins to the Toll-like receptor 4 promoter during endotoxemia. Am. J. Physiol. Lung Cell. Mol. Physiol. 289, L429–L437 (2005).
    Article CAS Google Scholar
22. Lee, C.H. et al. Regulation of the germinal center gene program by interferon (IFN) regulatory factor 8/IFN consensus sequence-binding protein. J. Exp. Med. 203, 63–72 (2006).
    Article CAS Google Scholar
23. Hassan, N.J. et al. CD6 regulates T-cell responses through activation-dependent recruitment of the positive regulator SLP-76. Mol. Cell. Biol. 26, 6727–6738 (2006).
    Article CAS Google Scholar
24. Castro, M.A. et al. Extracellular isoforms of CD6 generated by alternative splicing regulate targeting of CD6 to the immunological synapse. J. Immunol. 178, 4351–4361 (2007).
    Article CAS Google Scholar
25. Hafler, D.A. et al. Immunologic responses of progressive multiple sclerosis patients treated with an anti-T-cell monoclonal antibody, anti-T12. Neurology 36, 777–784 (1986).
    Article CAS Google Scholar
26. Sarrias, M.R. et al. CD6 binds to pathogen-associated molecular patterns and protects from LPS-induced septic shock. Proc. Natl. Acad. Sci. USA 104, 11724–11729 (2007).
    Article CAS Google Scholar
27. Hunt, K.A. et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat. Genet. 40, 395–402 (2008).
    Article CAS Google Scholar
28. Barrett, J.C. et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nat. Genet. 40, 955–962 (2008).
    Article CAS Google Scholar
29. Graham, R.R. et al. Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus. Nat. Genet. 40, 1059–1061 (2008).
    Article CAS Google Scholar
30. Raychaudhuri, S. et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat. Genet. 40, 1216–1223 (2008).
    Article CAS Google Scholar
31. Musone, S.L. et al. Multiple polymorphisms in the TNFAIP3 region are independently associated with systemic lupus erythematosus. Nat. Genet. 40, 1062–1064 (2008).
    Article CAS Google Scholar
32. Nair, R.P. et al. Genome-wide scan reveals association of psoriasis with IL-23 and NF-κB pathways. Nat. Genet. 41, 199–204 (2009).
    Article CAS Google Scholar
33. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).
    Article CAS Google Scholar
34. van Baarsen, L.G. et al. A subtype of multiple sclerosis defined by an activated immune defense program. Genes Immun. 7, 522–531 (2006).
    Article CAS Google Scholar
35. Degre, M., Dahl, H. & Vandvik, B. Interferon in the serum and cerebrospinal fluid in patients with multiple sclerosis and other neurological disorders. Acta Neurol. Scand. 53, 152–160 (1976).
    Article CAS Google Scholar
36. Stranger, B.E. et al. Genome-wide associations of gene expression variation in humans. PLoS Genet. 1, e78 (2005).
    Article Google Scholar
37. Greenberg, S.A. et al. Interferon-α/β-mediated innate immune mechanisms in dermatomyositis. Ann. Neurol. 57, 664–678 (2005).
    Article CAS Google Scholar
38. van der Pouw Kraan, T.C. et al. Rheumatoid arthritis subtypes identified by genomic profiling of peripheral blood cells: assignment of a type I interferon signature in a subpopulation of patients. Ann. Rheum. Dis. 66, 1008–1014 (2007).
    Article CAS Google Scholar
39. Baechler, E.C. et al. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proc. Natl. Acad. Sci. USA 100, 2610–2615 (2003).
    Article CAS Google Scholar
40. van Oosten, B.W. et al. Increased MRI activity and immune activation in two multiple sclerosis patients treated with the monoclonal anti-tumor necrosis factor antibody cA2. Neurology 47, 1531–1534 (1996).
    Article CAS Google Scholar
41. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/MRI Analysis Group. TNF neutralization in MS: results of a randomized, placebo-controlled multicenter study. Neurology 53, 457–465 (1999).
42. Siddiqui, M.A. & Scott, L.J. Spotlight on infliximab in Crohn disease and rheumatoid arthritis. BioDrugs 20, 67–70 (2006).
    Article Google Scholar
43. De Jager, P.L. et al. Integrating risk factors: HLA-DRB1*1501 and Epstein-Barr virus in multiple sclerosis. Neurology 70, 1113–1118 (2008).
    Article CAS Google Scholar
44. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
    Article CAS Google Scholar
45. McDonald, W.I. et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50, 121–127 (2001).
    Article CAS Google Scholar
46. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
    Article CAS Google Scholar
47. Bienias, J.L., Beckett, L.A., Bennett, D.A., Wilson, R.S. & Evans, D.A. Design of the Chicago Health and Aging Project (CHAP). J. Alzheimers Dis. 5, 349–355 (2003).
    Article Google Scholar
48. Gauthier, S.A., Glanz, B.I., Mandel, M. & Weiner, H.L. A model for the comprehensive investigation of a chronic autoimmune disease: the multiple sclerosis CLIMB study. Autoimmun. Rev. 5, 532–536 (2006).
    Article CAS Google Scholar
49. Miller, D., Barkhof, F., Montalban, X., Thompson, A. & Filippi, M. Clinically isolated syndromes suggestive of multiple sclerosis, part 2: non-conventional MRI, recovery processes, and management. Lancet Neurol. 4, 341–348 (2005).
    Article CAS Google Scholar

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Acknowledgements

P.L.D. is a Harry Weaver Neuroscience Scholar Award of the National MS Society (NMSS); he is also a William C. Fowler Scholar in Multiple Sclerosis Research and is supported by a National Institute of Neurological Disorders and Stroke (NINDS) K08 grant, NS46341. D.A.H. is a Jacob Javits Scholar of the US National Institutes of Health; he is also supported by NINDS P01 AI039671, R01 NS049477, R01NS046630, NMSS Collaborative MS Research Award and NMSS RG3567A. The International MS Genetics Consortium is supported by R01NS049477. L.P. is supported by an NMSS fellowship grant (FG1665-A-1). The genome-wide data on the BWH subjects and the RNA data on MS and CIS subjects from the CLIMB study were generated as part of a collaboration with Affymetrix, Inc. We thank the Myocardial Infarction Genetics Consortium (MIGen) study for the use of their genotype data as control data in our study. The MIGen study was funded by the US National Institutes of Health and National Heart, Lung, and Blood Institute's STAMPEED genomics research program and a grant from the National Center for Research Resources. We acknowledge use of genotype data from the British 1958 Birth Cohort DNA collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. We thank R. Lincoln and R. Gomez for expert specimen management at UCSF as well as A. Santaniello for database management. We thank the Accelerated Cure Project for its work in collecting samples from subjects with MS and for making these samples available to MS investigators. We also thank the following clinicians for contributing to sample collection efforts: Accelerated Cure project, E. Frohman, B. Greenberg, P. Riskind, S. Sadiq, B. Thrower and T. Vollmer; Washington University, B.J. Parks and R.T. Naismith. Finally, we thank the Brigham & Women's Hospital PhenoGenetic Project for providing DNA samples from healthy subjects that were used in the replication effort of this study.

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Author notes

1. Stephen L Hauser, David A Hafler and Jorge R Oksenberg: These authors contributed equally to this work.

Authors and Affiliations

1. Division of Molecular Immunology, Department of Neurology, Center for Neurologic Diseases, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
   Philip L De Jager, Linda Ottoboni, Susan Romano, Howard L Weiner & David A Hafler
2. Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA
   Philip L De Jager, Linda Ottoboni & Rebeccah Briskin
3. Program in Medical & Population Genetics, Broad Institute of Harvard University and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
   Philip L De Jager, Paul I W de Bakker, Linda Ottoboni, Soumya Raychaudhuri, Dong Tran, Cristin Aubin, Mark J Daly & David A Hafler
4. Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
   Xiaoming Jia & Paul I W de Bakker
5. Department of Neurology and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, USA
   Joanne Wang, Sergio E Baranzini, Stephen L Hauser & Jorge R Oksenberg
6. Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, USA
   Joanne Wang, Stephen L Hauser & Jorge R Oksenberg
7. Rush Alzheimer Disease Center & Department of Neurological Sciences, Rush University, Chicago, Illinois, USA
   Neelum T Aggarwal & Denis Evans
8. Department of Neurology, Washington University, St. Louis, Missouri, USA
   Laura Piccio & Anne H Cross
9. Division of Immunology, Department of Medicine, Allergy and Rheumatology, Brigham and Women's Hospital, Boston, Massachusetts, USA
   Soumya Raychaudhuri
10. Miami Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, Florida, USA
    Jacob L McCauley & Margaret A Pericak-Vance
11. Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
    Jonathan L Haines
12. Hammersmith Hospital and Department of Clinical Neurosciences, GlaxoSmithKline Clinical Imaging Centre, Imperial College, London
    Rachel A Gibson & Paul M Matthews
13. Department of Neurology, University Hospital Basel, Basel, Switzerland
    Yvonne Naeglin & Ludwig Kappos
14. Department of Neurology, Vrije Universiteit Medical Centre, Amsterdam, The Netherlands
    Bernard Uitdehaag & Chris Polman
15. Department of Social Medicine, University of Bristol, Bristol, UK
    Wendy L McArdle
16. Division of Community Health sciences, St. George's, University of London, London, UK
    David P Strachan
17. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
    Mark J Daly
18. Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
    Alastair Compston & Stephen J Sawcer

Authors

1. Philip L De Jager
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2. Xiaoming Jia
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3. Joanne Wang
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4. Paul I W de Bakker
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5. Linda Ottoboni
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6. Neelum T Aggarwal
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7. Laura Piccio
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8. Soumya Raychaudhuri
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9. Dong Tran
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10. Cristin Aubin
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11. Rebeccah Briskin
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12. Susan Romano
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13. Sergio E Baranzini
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14. Jacob L McCauley
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15. Margaret A Pericak-Vance
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16. Jonathan L Haines
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17. Rachel A Gibson
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18. Yvonne Naeglin
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19. Bernard Uitdehaag
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20. Paul M Matthews
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21. Ludwig Kappos
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22. Chris Polman
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23. Wendy L McArdle
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24. David P Strachan
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25. Denis Evans
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26. Anne H Cross
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27. Mark J Daly
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28. Alastair Compston
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29. Stephen J Sawcer
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30. Howard L Weiner
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31. Stephen L Hauser
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32. David A Hafler
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33. Jorge R Oksenberg
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International MS Genetics Consortium

Contributions

P.L.D., D.A.H., S.L.H., P.M.M. and J.R.O. designed the study. P.L.D. and J.R.O. wrote the manuscript. P.I.W.d.B., P.L.D., S.R., M.J.D., D.T., J.W., S.E.B. and X.J. performed analytical work. P.I.W.d.B., X.J. and M.J.D. developed the meta-analysis method while S.R. developed the subject matching algorithm. L.O. and P.L.D. performed the quality control analysis and quantitative trait analysis of the RNA from MS PBMC samples. C.A. generated and processed genotype data for analysis. P.L.D., N.T.A., L.P., R.B., R.A.G., P.M.M., Y.N., L.K., B.U., C.P., W.L.M., D.P.S., D.E., A.H.C., A.C., S.J.S., H.L.W., S.L.H., J.R.O. and D.A.H. contributed to DNA sample collection and genetic data. J.L.M., M.A.P.-V. and J.L.H. contributed to the interpretation of the results. All authors have read and contributed to the manuscript.

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Correspondence toPhilip L De Jager.

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De Jager, P., 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 41, 776–782 (2009). https://doi.org/10.1038/ng.401

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• Received: 08 December 2008
• Accepted: 21 May 2009
• Published: 14 June 2009
• Issue Date: July 2009
• DOI: https://doi.org/10.1038/ng.401