Genomic Screening in Multiple Sclerosis

  • P. Momigliano Richiardi
Part of the Topics in Neuroscience book series (TOPNEURO)


Multiple sclerosis (MS) is caused by an interplay of environmental and genetic factors. Their relative weight can be evaluated, as in all diseases, by three approaches: population epidemiology, twin concordance and family aggregation studies. Epidemiological studies point to environmental factors, likely one or more infectious agents, playing a major role as demonstrated by alteration of MS risk consequent to migration from high to low risk areas and viceversa and by occasional “epidemics” in small communities after contact with groups of individuals from high risk areas [1]. However, they also demonstrate the importance of genetic factors in that some ethnic groups maintain their relative resistance to MS even when they reside in areas where MS is common (e.g. Gypsies in Hungary, Blacks and Asians in USA, Maoris in New Zealand, and Lapps in Scandinavia [2]). Twin studies clearly demonstrate the role of genetic factors since monozygotic (MZ) concordance is substantially above dizygotic (DZ) concordance (25%–30% versus 3%), but also show the importance of the environment since the concordance level in MZ twins is well below 100%.


Multiple Sclerosis Experimental Autoimmune Encephalomyelitis Spinal Muscular Atrophy Experimental Allergic Encephalomyelitis Multiplex Family 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Kurtzke JF (1995) MS epidemiology world wide. One view of current status. Acta Neurol Scand S161: 23–33CrossRefGoogle Scholar
  2. 2.
    Ebers GC, Sadovnick AD (1993) The geographic distribution of multiple sclerosis: a review. Neuroepidemiology 12: 1–5PubMedCrossRefGoogle Scholar
  3. 3.
    Robertson NP, Fraser M, Deans J et al. (1996) Age-adjusted recurrence risks for relatives of patients with MS. Brain 119: 449–455PubMedCrossRefGoogle Scholar
  4. 4.
    Ebers GC, Sadovnick AD, Risch NJ and the Canadian Collaborative study Group (1995) Familial aggregation in MS is genetic. Nature 377: 150–151PubMedCrossRefGoogle Scholar
  5. 5.
    Sadovnick AD, Ebers GC, Dyment DA, Risch NJ and the Canadian Collaborative Study Group (1996) Evidence for genetic basis of MS. Lancet 347: 1728–1730PubMedCrossRefGoogle Scholar
  6. 6.
    Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273:1516–1517PubMedCrossRefGoogle Scholar
  7. 7.
    Scott WK, Pericak-Vance MA, Bell DA et al. (1997) Science 275:1327–1330PubMedCrossRefGoogle Scholar
  8. 8.
    Dyment DA, Sadnovich AD, Ebers GC (1997) Genetics of MS. Hum Mol Genet 6:1693–1698PubMedCrossRefGoogle Scholar
  9. 9.
    Kuokkanen S, Gschwend M, Rioux JD et al. (1997) Genomewide scan of MS in Finnish multiplex families. Am J Hum Genet 61: 1379–1387PubMedCrossRefGoogle Scholar
  10. 10.
    Lander ES, Kruglyak L (1995) Genetic dissection of complex traits: Guidelines for interpreting and reporting linkage results. Nat Genet 11:241–247PubMedCrossRefGoogle Scholar
  11. 11.
    Sundvall M, Jirholt J, Yang HT et al. (1995) Identification of murine loci associated with susceptibility to chronic experimental autoimmune encephalomyelitis. Nat Genet 10: 313–317PubMedCrossRefGoogle Scholar
  12. 12.
    Roth MP, Viratelle C, Dolbois L et al. (1998) A genome-wide search identifies susceptibility loci for experimental autoimmune encephalomyelitis on rat chromosomes 4 and 10. J Immunol (in press)Google Scholar
  13. 13.
    Sawcer S, Jones HB, Feakes R et al. (1996) A genome screen in multiple sclerosis reveals susceptibility loci on chromosome 6p21 and 17q22. Nat Genet 13: 464–468PubMedCrossRefGoogle Scholar
  14. 14.
    Haines JL, for The Multiple Sclerosis Genetics Group (1996) A complete genomic screen for multiple sclerosis underscores a role for the major histocompatibility complex. Nat Genet 13: 469–471PubMedCrossRefGoogle Scholar
  15. 15.
    Ebers GC, Kukay K, Bulman DE et al. (1996) A full genome screen in multiple sclerosis. Nat Genet 13:472–476PubMedCrossRefGoogle Scholar
  16. 16.
    Kuokkanen S, Sundvall M, Terwilliger JD et al. (1996) A putative vulnerability locus to multiple sclerosis maps to 5pl4-pl2 in a region syntenic to the murine locus Eae2. Nat Genet 13: 477–480PubMedCrossRefGoogle Scholar
  17. 17.
    Nisticò L.Buzzetti R.Pritchard LE et al. (1996) The CTLA-4 gene region of chromosome 2q33 is linked to, and associated with, type 1 diabetes. Hum Mol Genet 5:1075–1080PubMedCrossRefGoogle Scholar
  18. 18.
    Marron MP, Raffel LJ, Garchon HJ et al. (1997) Insulin-dependent diabetes mellitus (IDDM) is associated with CTLA-4 polymorphisms in multiple ethnic groups. Hum Mol Genet 6:1275–1282PubMedCrossRefGoogle Scholar
  19. 19.
    Piazza A, Mayr WR, Contu L et al. (1985) Genetic and population structure of four Sardinian villages. Ann Hum Genet 49: 47–63PubMedCrossRefGoogle Scholar
  20. 20.
    Rosati G, Aiello I, Pirastu MI et al. (1996) Epidemiology of MS in north-western Sardinia: further evidence for higher frequency in Sardinians compared to other Italians. Neuroepidemiology 15:10–19PubMedCrossRefGoogle Scholar
  21. 21.
    Kotsa K, Watson PF, Weetman AP (1997) A CTLA-4 gene polymorphism is associated with both Graves’ disease and autoimmune hypothyroidism. Clin Endocrinol 46:551–554CrossRefGoogle Scholar
  22. 22.
    Poser CM, Paty DW, Scheinberg L (1983) New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Ann Neurol 13: 227–231PubMedCrossRefGoogle Scholar
  23. 23.
    Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. Am J Hum Genet 58:1347–1363PubMedGoogle Scholar
  24. 24.
    Davis S, Schroeder M, Goldin LR, Weeks DE (1996) Nonparametric simulation-based statistics for detecting linkage in general pedigrees. Am J Hum Genet. 58: 867–880PubMedGoogle Scholar
  25. 25.
    Davis S, Goldin LR, Weeks DE (1997) SimIBD: A powerful robust non-parametric method for detecting linkage in general pedigrees. In: Pawlowitzki I-H, Edwards JH, Thompson EA (eds) Genetic mapping of disease genes. Academic, San Diego, pp 189–204Google Scholar
  26. 26.
    Collins A, Frezal J, Teague J, Morton NE (1996) A metric map of humans: 23,500 loci in 850 bands. Proc Natl Acad Sci USA 93:14771–14775 ( Scholar
  27. 27.
    Marrosu MG, Murru MR, Costa G et al. (1997) Multiple sclerosis in Sardinia is associated and in linkage disequilibrium with HLA-DR3 and -DR4 alleles. Am J Hum Genet 61: 454–457PubMedCrossRefGoogle Scholar
  28. 28.
    Becker KG, Simon RM, Bailey-Wilson JE et al. (1998) Clustering of non-major histo-compatibility complex susceptibility candidate loci in human autoimmune diseases. Proc Natl Acad Sci USA 95: 9979–9984PubMedCrossRefGoogle Scholar
  29. 29.
    Thompson EA, Neel JV (1997) Allelic disequilibrium and allele frequency distribution as a function of social and demographic history. Am J Hum Genet 60:197–204PubMedGoogle Scholar
  30. 30.
    Oefner PJ, Underhill PA (1998) DNA mutation detection using denaturing high performance liquid chromatography (DHPLC). In: Current protocols in human genetics. John Wiley & Sons, New York (in press)Google Scholar
  31. 31.
    Hudson TJ, Stein LD, Gerety SS et al. (1995) An STS-based map of the human genome. Science 270:1945–1954PubMedCrossRefGoogle Scholar
  32. 32.
    Kruglyak L (1997) The use of a genetic map of biallelic markers in linkage studies. Nat Genet 17: 21–24PubMedCrossRefGoogle Scholar
  33. 33.
    Wang DG, Fan JB, Siao CJ et al. (1998) Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science 280:1077–1082PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Italia 1999

Authors and Affiliations

  • P. Momigliano Richiardi
    • 1
  1. 1.Department of Medical SciencesUniversity of Eastern Piedmont A. AvogadroNovaraItaly

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