The demonstration that the FTO
gene is convincingly associated with obesity opens up several forms of follow-up study. First, the gene variant may be used to examine the causal nature of the relationship between obesity and clinical outcomes where this is in doubt, such as some cancers. This Mendelian Randomization or instrumental variable approach is limited by the effect size of the gene variant on obesity and the strength of the association between obesity and the clinical outcome of interest (30
). The FTO
association was originally discovered in a study of type 2 diabetes, and as the association between the gene variant and obesity fully explains the association between the variant and type 2 diabetes in an adjusted model, this can be used as an argument that the relationship between obesity and type 2 diabetes is causal. Of course, there was little doubt about this even before this study, not only because of the availability of randomized controlled trial data (31
), but also because of the very high magnitude of association between obesity and diabetes (32
). It is this very strong level of association that makes it possible to use the instrumental variable approach because as Frayling et al.
) demonstrated, the magnitude of the gene effect is itself quite small. Thus although this Mendelian Randomization approach might seem appealing, it is unlikely to be successful in resolving uncertainties about causality for outcomes of obesity where the likely level of association is much weaker than for type 2 diabetes.
The observation of the association of FTO
with obesity also opens questions about whether the impact of the variant on obesity is manifest through an association on dietary intake or energy expenditure, or both. Energy intake is difficult to assess in free-living individuals even with techniques involving weighed measurement of food (33
). In the context of monogenic causes of obesity in children, studies have been possible on ad libitum
energy intake when children are offered unlimited food availability (34
). These have demonstrated clear evidence that individuals with mutations in leptin (LEP
), neurotrophic tyrosine kinase receptor type 2 (TRKB
), brain-derived neurotrophic factor (BDNF
), and MC4R
genes have elevated energy intake compared to controls. In the case of FTO
, the likelihood magnitude of effect on energy intake is likely to be much smaller if it were present at all, and it is highly unlikely that one could observe such a small effect in a study that used imprecise measures. It is therefore probable that one would need to conduct smaller more intensive physiological studies in which special measurement of behaviors such as ad libitum
energy intake were made. For common variants such as FTO
, it would be possible to conduct such studies and then undertake the genotyping on all people recruited. For rarer variants, it may be more efficient because of the expense of the phenotyping to create a framework for selecting people for more detailed physiological studies on the basis of genotype. Various examples now exist of biobanks that have the requisite structure and ethical approvals to allow studies to be conducted but, to date, few examples of the scientific output from this approach have been published (35
The possibility of selecting individuals by phenotype makes it possible not only to undertake physiological studies to generate information about the biological pathway to the outcome of interest, but also allows the design of experimental studies that can investigate whether there is a differential response to intervention by genotype for the major outcome of interest. This is a question that is highly relevant clinically, as the demonstration that people with varying genetic background responded differently to a lifestyle intervention would be a stepping stone to the introduction of targeted intervention. However, the prospect of selecting people by genotype for such a study is limited, as one would need a very strong prior likelihood of success before embarking on an expensive long-term trial that followed people up to a relevant clinical outcome. Much more likely is the retrospective examination of differential response by genotype in existing lifestyle intervention studies. The problem here is one of power. In the case of type 2 diabetes, the strongest genetic variant is transcription factor 7-like 2 (TCF7L2
). The impact of this variant on risk of progression to diabetes has been examined in the large randomized controlled trial, the Diabetes Prevention Program, which randomized high risk individuals with impaired glucose tolerance to metformin, lifestyle, or placebo arms (37
). Even though it was possible to show in this sizeable study with 3,234 people randomized that there was a materially different impact of the genetic variant on risk of progression to diabetes by randomized group, the interaction term itself was not statistically significant. Thus this suggests that this very strong study design should be restricted to the examination of a few key hypotheses. A combined approach using large-scale observational epidemiological studies to inform which gene–lifestyle interactions to examine in intervention studies would be appropriate.