Key Points
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Genetic association analysis is a popular approach for identifying genetic variation that correlates with phenotypic variation, such as susceptibility to complex disease.
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Association studies have a chequered history. Many published studies cannot be reproduced, or be substantiated by linkage data.
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Genetic association occurs as a result of linkage disequilibrium (LD). But LD levels vary within the genome and between populations, making it difficult to predict the best sample populations for a particular study.
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The most popular sampling strategy is the case-control study. Selection of the control population is key to the success of this approach, and small sample sizes or poorly matched controls are sources of error in association studies.
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Prospective study designs can avoid the errors of case-control studies, but require large sample sizes. Family-based studies are also useful in overcoming errors due to population stratification.
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Multiple testing of the same population, or population subgroups, is another source of error.
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With the availability of the human genome sequence, and new methods for genotyping single nucleotide polymorphisms, association studies will become increasingly popular. Applications will include whole-genome screens and regional LD mapping.
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More rigorous study design, independent replication of data and careful attention to the effects of multiple testing are among the recommendations that will improve the value of association data in the future.
Abstract
Assessing the association between DNA variants and disease has been used widely to identify regions of the genome and candidate genes that contribute to disease. However, there are numerous examples of associations that cannot be replicated, which has led to scepticism about the utility of the approach for common conditions. With the discovery of massive numbers of genetic markers and the development of better tools for genotyping, association studies will inevitably proliferate. Now is the time to consider critically the design of such studies, to avoid the mistakes of the past and to maximize their potential to identify new components of disease.
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Acknowledgements
This work was supported by the Wellcome Trust and in part by a grant from the NIH (to L.R.C.). We wish to thank Dr Joe Terwilliger for critical review of this manuscript.
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Glossary
- POWER
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The probability of correctly rejecting the null hypothesis when it is truly false. For association studies, the power can be considered as the probability of correctly detecting a genuine association.
- GENETIC DRIFT
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The random fluctuation in allele frequencies as genes are transmitted from one generation to the next.
- POPULATION ADMIXTURE
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A population in which multiple subgroups are included. Admixture often refers to intermarriage/reproduction from different groups of individuals, but most simply is used to denote a population of subgroups having different allele frequencies (see population stratification).
- PROSPECTIVE COHORT
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Longitudinal study of individuals initially assessed for exposure to certain risk factors and then followed over time to evaluate the progression towards specific outcomes (often disease).
- LOCUS HETEROGENEITY
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The appearance of phenotypically similar characteristics resulting from mutations at different genetic loci. Differences in effect size or in replication between studies and samples are often ascribed to different loci leading to the same disease.
- POPULATION STRATIFICATION
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The presence of multiple subgroups with different allele frequencies within a population. The different underlying allele frequencies in sampled subgroups might be independent of the disease within each group, and they can lead to erroneous conclusions of linkage disequilibrium or disease relevance.
- TYPE I ERROR
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The probability of rejecting the null hypothesis when it is true. For association studies, Type I errors are manifest as false-positive reports of phenotype–genotype correlation.
- RISK RATIO
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A measure of association effect reflecting the probability of disease in people with a particular allele or genotype versus the probability of disease in those who do not have the particular genotype.
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Cardon, L., Bell, J. Association study designs for complex diseases. Nat Rev Genet 2, 91–99 (2001). https://doi.org/10.1038/35052543
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DOI: https://doi.org/10.1038/35052543
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