3. Epidemiology and Genetics

  1. Howard L. Weiner MD4,5,6 and
  2. James M. Stankiewicz MD4,5
  1. Philip L. De Jager MD, PhD1,2,3

Published Online: 23 FEB 2012

DOI: 10.1002/9781119963714.ch3

Multiple Sclerosis: Diagnosis and Therapy

Multiple Sclerosis: Diagnosis and Therapy

How to Cite

De Jager, P. L. (2012) Epidemiology and Genetics, in Multiple Sclerosis: Diagnosis and Therapy (eds H. L. Weiner and J. M. Stankiewicz), Wiley-Blackwell, Oxford, UK. doi: 10.1002/9781119963714.ch3

Editor Information

  1. 4

    Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA

  2. 5

    Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA

  3. 6

    Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, MA, USA

Author Information

  1. 1

    Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, MA, USA

  2. 2

    Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA

  3. 3

    Program in Medical & Population Genetics, Broad Institute of Harvard University, and Massachusetts Institute of Technology, Cambridge, MA, USA

Publication History

  1. Published Online: 23 FEB 2012
  2. Published Print: 6 APR 2012

ISBN Information

Print ISBN: 9780470654637

Online ISBN: 9781119963714

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Keywords:

  • Epstein–Barr virus;
  • smoking;
  • vitamin D;
  • genetic variation

Summary

During the past 10 years, a dramatic change has occurred in our understanding of multiple sclerosis (MS) genetic and environmental risks: the role of several environmental risks have been better characterized and a robust method to discover common variants of modest effect, the association study, has identified many variants associated with risk of MS. The integration of these genetic and environmental risk factors is beginning, and the convergence of the success of epidemiology and human genetics outlines an exciting field of future investigation where immunology, epidemiology, and genetics will now converge to allow insights into the sequence of molecular events that lead to the onset of MS. Given technologies and methods available today, it looks likely that this new generation of studies will quickly inform existing efforts to develop algorithms that support clinical decisions.