International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. Email: brennan{at}iarc.fr
Genetic association studies for non-familial diseases typically focus on a particular candidate gene and one or more environmental exposures (geneenvironment interaction). The long term rationale of such studies appears to be that an accumulation of knowledge regarding susceptibility genes will allow us to identify high risk population subgroups. This in turn may subsequently allow the development of intervention strategies aimed at such high risk groups including modification of lifestyle habits and increased surveillance for those at most risk. However, the feasibility of this strategy is uncertain and indeed it may ultimately prove to be unfeasible, especially if there is a strong stochastic component inherent in the development of individual cases of a particular disease.
An alternative rationale for conducting genetic susceptibility studies is to use genetics to test specific hypotheses regarding the role of non-genetic exposures. The concept of Mendelian randomization has recently been discussed in some detail in the International Journal of Epidemiology,1 although the idea has been around for some time.2 As illustrated in the accompanying article, Katan pointed out over 15 years ago that the observed association between low cholesterol levels and increased cancer rates may have arisen through reverse causation.3 Specifically, pre-symptomatic cancers may have resulted in a reduction in cholesterol levels. The solution that Katan proposed for testing the causality of this association was to compare different polymorphisms of the apolipoprotein E (Apo E) gene between cases and controls. Apo E is partly responsible for clearance of cholesterol from plasma and the efficiency of this clearance varies according to different Apo E genotypes.4 Consequently, individuals with a genotype including the E2 allele have, on average, lower levels of cholesterol than individuals with genotypes comprising of other alleles. If low cholesterol levels are associated with cancer then we would expect cancer cases to be more likely to possess the E2 allele than non-cancer controls. Even if the observed association was due to confounding from other sources (e.g. cigarette smoking or as components of a low fat diet), the proposed Mendelian randomization analysis would be able to rule out this possibility.
What is therefore fundamental about a comparison based on Mendelian randomization is that, under certain assumptions, bias and confounding may reasonably be excluded as alternative explanations of an observed effect. In particular, the disease status of the cases cannot influence the exposure (one's genotype), an important form of bias in many casecontrol comparisons. Furthermore, because of Mendel's principal of independent inheritance, an individual's genotype for Apo E is unlikely to be associated with diet, other lifestyle characteristics, or even the vast majority of other genes, thus avoiding the potential for confounding. Such an experiment is akin to a randomized control trial where one randomly selected group is administered high cholesterol and the other low cholesterol. Ignoring the obvious ethical objections to such a trial, the Mendelian randomization experiment may actually be far superior to such a trial because it is a marker for lifelong exposure, and not simply exposure for the duration of the trial, and is not affected by lack of compliance, dropouts, and other problems associated with clinical trials. This concept therefore has the potential to remove bias and confounding as alternative explanations of observed effects from environmental, lifestyle, or endogenous exposures, the implications of which are far reaching.
Mendelian randomization studies are, however, susceptible to several potential problems.1 In particular, genes responsible for metabolization of the environmental or lifestyle agent must be known for a Mendelian randomization study to be feasible. Furthermore, functional polymorphisms must exist for the gene that result in appreciable inter-individual variation. Even when such functional polymorphisms exist a Mendelian randomization study may be flawed. This can occur if, (1) the gene has other functions (pleiotropy), (2) there is linkage disequilibrium with other genes that may influence the disease (genetic confounding), or (3) the gene influences behaviour. Finally, even if all the above conditions are satisfied, it is likely that any genetic effect will be moderate, and a large sample size will be required in order to protect against spurious results.
In order to illustrate further the potential promise and limits of Mendelian randomization, two particular examples relevant to carcinogenesis are presented. Both of these examples focus on specific geneenvironment interaction relationships, although, as has been recently shown, Mendelian randomization studies of main effects are equally relevant.1
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Example 1: Isothiocyanate (ITC) consumption and lung cancer |
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Further causal evidence may however be provided by adopting a Mendelian randomization approach. ITC are known to be eliminated by glutathione-S-transferase (GST) enzymes, most notably GSTM1 and GSTT1. Both GSTM1 and GSTT1 genes have null alleles with homozygous null genotypes resulting in no enzyme being produced. Individuals who are homozygous for the inactive form for either one or both genes are likely to have higher ITC concentrations due to their reduced elimination capacity. Limited evidence for such a genotypephenotype relationship exists. Among a sample of 710 men from Shanghai recruited into a population cohort, those who had null inactive genotypes for both GSTM1 and GSTT1 were over twice as likely to have detectable levels of ITC than those who had at least one active allele (odds ratio [OR] = 2.0, 95% CI: 1.2, 3.2).8
In ideal circumstances, an analysis of ITC consumption between lung cancer cases and controls according to different GSTM1 and GSTT1 genotypes would serve as a hypothesis test for the role for ITC in lung cancer, based on the prediction of a greater role for ITC among GSTM1 and GSTT1 null individuals. However, GST genes are not ideal markers to use in a Mendelian randomization analysis as they exhibit pleiotropy, i.e. the genes have other important functions unrelated to ITC metabolism. In particular, both GSTM1 and GSTT1 are responsible for deactivating highly reactive polycyclic aromatic hydrocarbon (PAH) substrates, with the null genotypes resulting in higher PAH-related adducts and potentially a higher lung cancer risk.9 An overall analysis of GST and lung cancer may therefore not be able to distinguish between the potentially increased risk due to higher PAH exposure, and decreased risk associated with higher ITC levels, as PAH exposure may be related to diet (e.g. smokers may consume fewer vegetables). Possible solutions include attempting to adjust any analysis for the most likely source of PAH exposure, notably cigarette smoking, or restricting the analysis to never smokers, although this will not exclude other sources of PAH exposure.
Four studies have reported on the potential protective effect with ITC after stratifying by GSTM1 and GSTT1 status. In a case-control study of 232 male incident lung cancer cases and 710 matched controls, nested within a cohort of 18 244 men in Shanghai, ITC levels were measured in urine samples collected at recruitment.8 The protective effect of detectable ITC levels was only apparent among those with deletion of both GSTM1 and GSTT1 (OR = 0.28, 95% CI: 0.13, 0.57), after adjusting for smoking, and not apparent among those with at least one active GST gene (OR = 1.04, 95% CI: 0.60, 1.67). In a separate case-control study among women in Singapore, including 233 lung cancer cases and 187 hospital controls, high ITC levels were more protective among those with two null GST genes (OR = 0.47, 95% CI: 0.23, 0.95), than among those with at least one active allele (OR = 0.69, 95% CI: 0.41, 1.17), after adjusting for smoking.10 The greater effect for those with two null genotypes was more apparent among lifetime non-smokers (OR = 0.50, 95% CI: 0.23, 1.08, and 0.83, 95% CI: 0.47, 1.46 respectively) for whom no confounding by smoking was possible. In a separate US case-control study consisting of 503 incident lung cancer cases, and 465 controls, the protective effect of high ITC consumption was marginally greater among those null for both GST genes (OR = 0.46, 95% CI: 0.18, 1.12), than those positive for at least one GST gene (OR = 0.67, 95% CI: 0.50, 0.90), although both OR are unadjusted for smoking.11 Finally, a case-control study among 122 never-smoking lung cancer cases and 123 never-smoking controls reported a higher protective effect for high ITC consumption among GSTM1 null individuals (OR = 0.27, 95% CI: 0.06, 1.33) than GSTM1 positive individuals, (OR = 0.65, 95% CI: 0.16, 1.33).12
In summary, with respect to the extent that studies of ITC, GST and lung cancer have been able to avoid bias and confounding, the main problem is that the multiple role of GST genes means that the observed effect may still be confounded by exposure to PAH (Table 1). This situation is however still superior to traditional analyses as sources of PAH exposure can be adjusted for, and confounding from other dietary sources is still unlikely. Secondly, several of the studies suffer from a limited sample size resulting in non-significant differences. Other potential problems include uncertainty in the extent of the relationship between genotype and intermediate ITC levels, as this is based on limited information only.
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Example 2: Acetaldehyde exposure and head and neck cancer |
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Seven case-control studies have reported on the relationship between ADH1C and head and neck cancer. Briefly, the first study among 76 alcoholics (21 oropharyngeal cancers, 18 laryngeal cancers and 37 controls) reported an increased risk for the ADH1C*1/1 genotype for all cancers (OR = 3.6, 95% CI: 0.7, 10.0) that was most apparent for laryngeal cancer (OR = 6.1, 95% CI: 1.3, 28.6).16 The second study was particularly appealing as it indicated that heavy alcohol drinkers with the fast ADH1C*1/1 genotype were at a tenfold increased risk of oral/pharyngeal cancer (OR = 40.1, 95% CI: 5.4, 296) when compared with heavy drinkers with the ADH1C*2/2 genotype (OR = 4.4, 95% CI: 0.6, 33.3).17 These results were however based on relatively small numbers and were not replicated in any of the five subsequent studies.1822 A pooled analysis using the original data from all seven studies reported a similar increased risk of head and neck cancer among current drinkers with the ADH1C*1/1 genotype (OR = 2.94, 95% CI: 1.71, 5.05) and the ADH1C*2/2 genotype; (OR = 2.85, 95% CI: 1.62, 5.00).14
In the one study that has reported on ADH1B and head and neck cancer, 16 oral/pharyngeal and 18 laryngeal alcoholic cases were compared with 526 alcoholic controls.23 Instead of an increased risk being observed for the fast metabolizing ADH1B*2/2 genotype, an increased risk was observed for possession of either the ADH1B*1/1 or ADH1B*1/2 genotype for both oral/pharyngeal cancer (OR = 5.48, 95% CI: 1.77, 17.0) and laryngeal cancer (OR = 6.57, 95% CI: 1.62, 21.3). These findings were contrary to the original hypothesis that fast metabolism of alcohol would lead to an increased peak of acetaldehyde exposure and therefore greater risk. An alternative explanation of the results is that possession of the ADH1B*2/2 genotype modifies alcohol behaviour due to the increased occurrence of a toxic reaction due to high acetaldehyde levels. Even though all subjects were classified as alcoholics it is possible that alcoholics with the ADH1B*2/2 genotype are not able to tolerate higher levels of alcohol, resulting in confounding by alcohol consumption.
Although the potential relationship between acetaldehyde and head and neck cancer would appear to be a good candidate for Mendelian randomization studies, several problems are apparent (Table 1). The seven studies on ADH1C contained few individuals in the high consumption category and illustrate the importance of conducting large studies in order to obtain consistent results. Furthermore, the one study on ADH1B illustrates the possibility for a genotype to modify behaviour and therefore introduce confounding. The lack of in vivo data on the genotypephenotype relationship is also problematic, especially as this may be of much interest with respect to different patterns of drinking (e.g. binge drinking verses drinking at mealtime). Finally, although other susceptibility genes for head and neck cancer are not known to exist in the chromosomal region that includes ADH1B and ADH1C, it is likely that there is some linkage disequilibrium between the two genes.24
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Summary and implications |
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Regarding other potential problems, pleiotropy, or the multiple function of individual genes, only becomes a problem if another compound being metabolized by a gene also affects the risk for the disease under question, and the two compounds are associated, resulting in confounding. If this function is known then it may be possible to adjust for the effect of the secondary compound. Possibilities for such confounding are however likely to be much more limited than those encountered with lifestyle or environmental exposures. Confounding may also occur if the gene influences the potential for exposure, such as that with ADH1B and alcohol consumption. Such situations are likely to be restricted to individuals with an increased genetic tendency to experience a toxic reaction against a particular substance, or to addictive tendencies that are at least partially genetically regulated, e.g. by nicotine and dopamine receptor genes.26 Similarly, genetic confounding may occur via linkage disequilibrium with other causal genes in the close vicinity of the gene under study. Again, the potential for this is likely to be limited.
The final limitation of Mendelian randomization studies is one shared by traditional randomized controlled trials, i.e. the lack of replicability of studies due to their small sample size. While Mendelian randomization studies will clearly allow for a focussed testing of specific hypotheses, it will be important not to forget the lessons of the first generation of genetic association studies: that results based on small sample sizes are more likely to confuse than enlighten.
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Acknowledgments |
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References |
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