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A gene-centric approach to genome-wide association studies

Nature Reviews Genetics volume 7, pages 885–891 (2006)Cite this article

Abstract

Genic variants are more likely to alter gene function and affect disease risk than those that occur outside genes. Variants in genes, however, might not be sufficiently covered by the existing approaches to genome-wide association studies. Our analysis of the HapMap ENCODE data indicates that this concern is valid, and that an alternative approach that focuses on genic variants provides a more complete coverage of functionally important regions and a greater genotyping efficiency. We therefore argue that resources should be developed to make gene-centric genome-wide association studies feasible.

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Figure 1: Approaches to constructing SNP sets for genome-wide association studies.
Figure 2: Coverage of genic and non-genic SNPs by a quasi-random SNP set.
Figure 3: Coverage of genic SNPs by a non-genic SNP set.
Figure 4: Predicted power of genome-wide association studies using a quasi-random SNP set.
Figure 5: Relative efficiencies of approaches to genome-wide association studies.

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Acknowledgements

We thank N. Risch, D. Thomas, X. Liu and I. Cheng for their helpful comments, as well as L. Edblad and L. Woldin for assistance in the preparation of the manuscript. We also thank anonymous reviewers for their helpful suggestions. This work was supported by grants from the US National Institutes of Health.

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, and Center for Human Genetics, University of California, San Francisco, 94143-0794, California, USA

    Eric Jorgenson & John S. Witte

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  1. Eric Jorgenson
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  2. John S. Witte
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The authors declare no competing financial interests.

Supplementary information

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FURTHER INFORMATION

Affymetrix 500k Array Set

EntrezSNP

Ensembl

HapMap ENCODE

HapMart

International HapMap Project

National Institute of Environmental Health Science Environmental Genome Project

SeattleSNPs Program for Genomic Applications

Tagger

Wellcome Trust Exon Resequencing Project

Witte Laboratory Homepage

Glossary

Genome-wide significance criterion

The level of significance that an association must reach to reject the null hypothesis of no association, taking into account the large number of tests being conducted.

Linkage analysis

A method for localizing genes that is based on the co-inheritance of genetic markers and phenotypes in families over several generations.

Linkage disequilibrium

The non-random association of alleles of different linked polymorphisms in a population.

Minor allele frequency

The frequency of the less-common allele at a polymorphic locus. It has a value that lies between 0 and 0.5, and can vary between populations.

Multiple-hypothesis testing

The practice of testing more than one hypothesis within an experiment. As a result, the probability of an unusual result from within the entire experiment occurring by chance is higher than the individual probability for one test alone.

Odds ratio

A measurement of association that is commonly used in case–control studies. It is defined as the odds of exposure to the susceptible genetic variant in cases compared with that in controls. If the odds ratio is statistically significantly greater or less than one, then the genetic variant is associated with the disease.

Power

The probability of rejecting the null hypothesis when it is false. In genome-wide association studies, the null hypothesis is that there is no association between a variant and the phenotype of interest.

HapMap

A catalogue of common genetic variation in the human genome that was developed by the International HapMap Project.

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Jorgenson, E., Witte, J. A gene-centric approach to genome-wide association studies. Nat Rev Genet 7, 885–891 (2006). https://doi.org/10.1038/nrg1962

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