Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

A non-synonymous SNP within membrane metalloendopeptidase-like 1 (MMEL1) is associated with multiple sclerosis

Genes & Immunity volume 11, pages 660–664 (2010)Cite this article

Subjects

Abstract

Several single-nucleotide polymorphism (SNP) genome-wide association studies (GWASs) have been completed in multiple sclerosis (MS). Follow-up studies of the variants with the most promising rankings, especially when supplemented by informed candidate gene selection, have proven to be extremely successful. In this study we report the results of a multi-stage replication analysis of the putatively associated SNPs identified in the Wellcome Trust Case Control Consortium non-synonymous SNP (nsSNP) screen. In total, the replication sample consisted of 3444 patients and 2595 controls. A combined analysis of the nsSNP screen and replication data provides evidence implicating a novel additional locus, rs3748816 in membrane metalloendopeptidase-like 1 (MMEL1; odds ratio=1.16, P=3.54 × 10−6) in MS susceptibility.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1

Similar content being viewed by others

References

  1. Compston A, Coles A . Multiple sclerosis. Lancet 2008; 372: 1502–1517.

    Article  CAS  Google Scholar 

  2. Hogancamp WE, Rodriguez M, Weinshenker BG . The epidemiology of multiple sclerosis. Mayo Clin Proc 1997; 72: 871–878.

    Article  CAS  Google Scholar 

  3. Hauser SL, Oksenberg JR . The neurobiology of multiple sclerosis: genes, inflammation, and neurodegeneration. Neuron 2006; 52: 61–76.

    Article  CAS  Google Scholar 

  4. International Multiple Sclerosis Genetics Consortium (IMSGC). Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med 2007; 357: 851–862.

    Article  Google Scholar 

  5. Baranzini SE, Wang J, Gibson RA, Galwey N, Naegelin Y, Barkhof F et al. Genome-wide association analysis of susceptibility and clinical phenotype in multiple sclerosis. Hum Mol Genet 2009; 18: 767–778.

    Article  CAS  Google Scholar 

  6. ANZgene. Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20. Nat Genet 2009; 41: 824–828.

    Article  Google Scholar 

  7. Aulchenko YS, Hoppenbrouwers IA, Ramagopalan SV, Broer L, Jafari N, Hillert J et al. Genetic variation in the KIF1B locus influences susceptibility to multiple sclerosis. Nat Genet 2008; 40: 1402–1403.

    Article  CAS  Google Scholar 

  8. The Wellcome Trust Case Control Consortium. Genome-wide association study of 14 000 cases of seven common diseases and 3000 shared controls. Nature 2007; 447: 661–678.

    Article  Google Scholar 

  9. Ban M, Goris A, Lorentzen AR, Baker A, Mihalova T, Ingram G et al. Replication analysis identifies TYK2 as a multiple sclerosis susceptibility factor. Eur J Hum Genet 2009; 17: 1309–1313.

    Article  CAS  Google Scholar 

  10. Hunt KA, Zhernakova A, Turner G, Heap GA, Franke L, Bruinenberg M et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat Genet 2008; 40: 395–402.

    Article  CAS  Google Scholar 

  11. Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007; 39: 857–864.

    Article  CAS  Google Scholar 

  12. Raychaudhuri S, Remmers EF, Lee AT, Hackett R, Guiducci C, Burtt NP et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat Genet 2008; 40: 1216–1223.

    Article  CAS  Google Scholar 

  13. Ouimet T, Facchinetti P, Rose C, Bonhomme MC, Gros C, Schwartz JC . Neprilysin II: A putative novel metalloprotease and its isoforms in CNS and testis. Biochem Biophys Res Commun 2000; 271: 565–570.

    Article  CAS  Google Scholar 

  14. Huang JY, Bruno AM, Patel CA, Huynh AM, Philibert KD, Glucksman MJ et al. Human membrane metallo-endopeptidase-like protein degrades both beta-amyloid 42 and beta-amyloid 40. Neuroscience 2008; 155: 258–262.

    Article  CAS  Google Scholar 

  15. Barton A, Thomson W, Ke X, Eyre S, Hinks A, Bowes J et al. Rheumatoid arthritis susceptibility loci at chromosomes 10p15, 12q13 and 22q13. Nat Genet 2008; 40: 1156–1159.

    Article  CAS  Google Scholar 

  16. International Multiple Sclerosis Genetics Consortium (IMSGC). The expanding genetic overlap between multiple sclerosis and type I diabetes. Genes Immun 2009; 10: 11–14.

    Article  Google Scholar 

  17. Fung EY, Smyth DJ, Howson JM, Cooper JD, Walker NM, Stevens H et al. Analysis of 17 autoimmune disease-associated variants in type 1 diabetes identifies 6q23/TNFAIP3 as a susceptibility locus. Genes Immun 2009; 10: 188–191.

    Article  CAS  Google Scholar 

  18. Bifulco M, Laezza C, Stingo S, Wolff J . 2′,3′-Cyclic nucleotide 3′-phosphodiesterase: a membrane-bound, microtubule-associated protein and membrane anchor for tubulin. Proc Natl Acad Sci USA 2002; 99: 1807–1812.

    Article  CAS  Google Scholar 

  19. Lappe-Siefke C, Goebbels S, Gravel M, Nicksch E, Lee J, Braun PE et al. Disruption of Cnp1 uncouples oligodendroglial functions in axonal support and myelination. Nat Genet 2003; 33: 366–374.

    Article  CAS  Google Scholar 

  20. Scarisbrick IA, Blaber SI, Lucchinetti CF, Genain CP, Blaber M, Rodriguez M . Activity of a newly identified serine protease in CNS demyelination. Brain 2002; 125 (Part 6): 1283–1296.

    Article  CAS  Google Scholar 

  21. Scarisbrick IA, Linbo R, Vandell AG, Keegan M, Blaber SI, Blaber M et al. Kallikreins are associated with secondary progressive multiple sclerosis and promote neurodegeneration. Biol Chem 2008; 389: 739–745.

    Article  CAS  Google Scholar 

  22. Liu K, Li QZ, Delgado-Vega AM, Abelson AK, Sanchez E, Kelly JA et al. Kallikrein genes are associated with lupus and glomerular basement membrane-specific antibody-induced nephritis in mice and humans. J Clin Invest 2009; 119: 911–923.

    Article  CAS  Google Scholar 

  23. Evans PD, Gilbert SL, Mekel-Bobrov N, Vallender EJ, Anderson JR, Vaez-Azizi LM et al. Microcephalin, a gene regulating brain size, continues to evolve adaptively in humans. Science 2005; 309: 1717–1720.

    Article  CAS  Google Scholar 

  24. Purcell S, Cherny SS, Sham PC . Genetic power calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 2003; 19: 149–150.

    Article  CAS  Google Scholar 

  25. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001; 50: 121–127.

    Article  CAS  Google Scholar 

  26. Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983; 13: 227–231.

    Article  CAS  Google Scholar 

  27. Steemers FJ, Chang W, Lee G, Barker DL, Shen R, Gunderson KL . Whole-genome genotyping with the single-base extension assay. Nat Methods 2006; 3: 31–33.

    Article  CAS  Google Scholar 

  28. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D et al. PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 2007; 81: 559–575.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank the many multiple sclerosis patients and healthy individuals who participated in this study and the International Multiple Sclerosis Genetics Consortium (IMSGC, https://www.imsgc.org/) for providing the network through which we were able to collaborate. This work was supported by the Medical Research Council (G0700061) and MRC programme grant (U.1052.00.012.00001.01), the National Institute of Health (R01 NS049477 and NS032830) and the Cambridge NIHR Biomedical Research Centre. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. We acknowledge the use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council Grant G0000934 and the Wellcome Trust Grant 068545/Z/02. JLM was supported by a grant from the National Multiple Sclerosis Society (RG4201-A-1). PLD is a Harry Weaver Neuroscience Scholar of the National MS Society. LB is supported by a PhD Lagrange Fellowship. SD is supported by the FISM grant (2008/R/11).

Author information

Author notes

  1. M Ban, J L McCauley and R Zuvich: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Clinical Neuroscience, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK

    M Ban, A Baker, A Kemppinen, A Compston & S Sawcer

  2. Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA

    J L McCauley & M A Pericak-Vance

  3. Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, TN, USA

    R Zuvich, D Sexton & J Haines

  4. Department of Medical Sciences and Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy

    L Bergamaschi & S D'Alfonso

  5. University of Newcastle, John Hunter Hospital, Newcastle, New South Wales, Australia

    M Cox & J Lechner-Scott

  6. Laboratory of Molecular Medicine and Biotechnology, Don C Gnocchi Foundation IRCCS, S Maria Nascente, Milan, Italy

    F R Guerini

  7. MRC Biostatistics Unit, Cambridge, UK

    F Dudbridge & J Wason

  8. Department of Neurology, University Hospital of Wales, Heath Park, Cardiff, UK

    N P Robertson

  9. Program in Translational NeuroPsychiatric Genomics, Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

    P L De Jager

  10. Broad Institute, Cambridge, MA, USA

    P L De Jager

  11. Department of Neurology, Yale University School of Medicine, New Haven, CT, USA

    D A Hafler

  12. Division of Epidemiology, School of Public Health, University of California at Berkeley, Berkeley, CA, USA

    L F Barcellos

  13. Harvard NeuroDiscovery Center, Harvard Medical School, Boston, MA, USA

    A J Ivinson

  14. Department of Neurology, University of California San Francisco, San Francisco, CA, USA

    J R Oksenberg & S L Hauser

Authors
  1. M Ban
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J L McCauley
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R Zuvich
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A Baker
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. L Bergamaschi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M Cox
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A Kemppinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. S D'Alfonso
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. F R Guerini
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. J Lechner-Scott
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. F Dudbridge
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. J Wason
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. N P Robertson
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. P L De Jager
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. D A Hafler
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. L F Barcellos
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. A J Ivinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. D Sexton
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. J R Oksenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. S L Hauser
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. M A Pericak-Vance
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. J Haines
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. A Compston
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. S Sawcer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M Ban.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies the paper on Genes and Immunity website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ban, M., McCauley, J., Zuvich, R. et al. A non-synonymous SNP within membrane metalloendopeptidase-like 1 (MMEL1) is associated with multiple sclerosis. Genes Immun 11, 660–664 (2010). https://doi.org/10.1038/gene.2010.36

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/gene.2010.36

Keywords

This article is cited by

Search

Advanced search

Quick links