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Interpretation of genetic association studies in complex disease

The Pharmacogenomics Journal volume 2, pages 349–360 (2002)Cite this article

The potential of the genetic association approach for the identification of genetic variants that alter susceptibility to common complex disease is well recognised.1 This potential equally extends to the identification of genetic variants in genes coding drug-metabolising enzymes, transporters, receptors, and other drug targets that may determine inter-individual differences in drug responsiveness or the frequency of adverse drug reactions. Technological advances such as the availability of single nucleotide polymorphism (SNP) databases and affordable, very high throughput genotyping are set to extend the potential and improve the efficiency of association approaches. However, the very large number of genetic variants in the human genome2 and the lack of detailed knowledge about the molecular and biochemical processes involved in aetiology of complex diseases or in drug response suggest that it is very likely that many spurious associations will be found and reported. The great majority of reported associations have not led to new insights into complex disease or drug response mechanisms. Important exceptions include genetic variants whose effects are large enough to be identified by linkage analysis (eg), variants in NOD2 in Crohn's disease,3 APOE in Alzheimer's disease4 and factor V Leiden in deep venous thrombosis5) and genetic variants in the cytochrome P450 CYP3A5 gene, which contribute to variation in bio-availability and clearance of drugs such as HIV protease inhibitors and some cholesterol-lowering drugs, and can result in drug toxicity.6

The primary aim of these studies is to identify significant associations between genetic variants and disease states, physiological or disease traits or markers of drug response or toxicity and then to judge whether these associations are ‘causal’ (truly alter susceptibility to disease or drug response). However, deciding which statistically significant associations are indeed causal is likely to represent a major obstacle to successful ‘gene discovery’, at least until the time when molecular pathways from gene to disease become better understood. In this review we discuss the correct use and limitations of existing criteria for the interpretation of association studies.

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Acknowledgements

We would like to acknowledge helpful comments made by Dr Andrew Carothers and Professor Alan Wright, MRC Human Genetics Unit, Edinburgh; and the help of Rory Mitchell in preparing Figure 2. IR is supported by the UK Medical Research Council and grant funding from the Wellcome Trust.

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  1. Department of Community Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG, UK

    H Campbell & I Rudan

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Correspondence to H Campbell.

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Campbell, H., Rudan, I. Interpretation of genetic association studies in complex disease. Pharmacogenomics J 2, 349–360 (2002). https://doi.org/10.1038/sj.tpj.6500132

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