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Single nucleotide polymorphisms and the future of genetic epidemiology


  • Nicholas J Schork,

    1. Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA,
    2. Program for Population Genetics and Department of Biostatistics, Harvard University of Public Health, Boston, MA, USA,
    3. The Jackson Laboratory, Bar Harbor, ME, USA,
    4. The GENSET Corporation of La Jolla, CA, USA and GENSET, SA of Paris, France
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  • Daniele Fallin,

    1. Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA,
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  • Jerry S Lanchbury

    1. Molecular Immunogenetics, Department of Rheumatology, GKT School of Medicine, King's College, London, UK,
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Corresponding author: Nicholas J. Schork, Ph.D., The Genset Corporation, 875 Prospect Street, Suite 206, La Jolla, CA 92037, USA. Tel: +858 551 3000; fax: +858 551 3001; e-mail:


In this review, we consider the motivation behind contemporary Single Nucleotide Polymorphism (SNP) initiatives. Many of these initiatives are projected to involve large, population-based surveys. We therefore emphasize the utility of SNPs for genetic epidemiology studies. We start by offering an overview of genetic polymorphism and discuss the historical use of polymorphism in the identification of disease-predisposing genes via meiotic mapping. We next consider some of the unique aspects of SNPs, and their relative advantages and disadvantages in human population-based analyses. In this context, we describe and critique the following six different areas of application for SNP technologies:

  • • Gene discovery and mapping.
  • • Association-based candidate polymorphism testing.
  • • Diagnostics and risk profiling.
  • • Prediction of response to environmental stimuli, xenobiotics and diet.
  • • Homogeneity testing and epidemiological study design.
  • • Physiologic genomics.

We focus on key issues within each of these areas in an effort to point out potential problems that might plague the use of SNPs (or other forms of polymorphism) within them. However, we make no claim that our list of considerations are exhaustive. Rather, we believe that they may provide a starting point for further dialog about the ultimate utility of SNP technologies. In addition, although our emphasis is placed on applications of SNPs to the understanding of human phenotypes, we acknowledge that SNP maps and technologies applied to other species (e.g. the mouse genome, pathogen genomes, plant genomes, etc.) are also of tremendous interest.

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