Mendelian randomisation and causal inference in observational epidemiology

Abstract

It is often unavoidable (and sometimes desirable) to use observational data to infer causality, but it may then be difficult to disentangle causation from association, especially in the presence of confounding. We would argue that some of the confusion and misleading interpretations of results from observational studies are partly due to the lack of a clear formal approach to distinguish between association and causation. Causal terminology is often used loosely in the medical literature. It is intended to convey more than a simple association between potential risk factors and their effects, but this is rarely made explicit. More formal approaches are based on the idea of a hypothetical intervention [43,44], which seems particularly suited to the present context where we have potential health interventions in mind. These formal approaches highlight the usefulness of Mendelian randomisation studies for inferring causality and enable precise specification of the key assumptions (as depicted in Figure 1) necessary for the method to be valid. Given the tendency of high-profile findings to persist in the literature, and influence public health and clinical policy, long after they have been formally refuted by RCT analyses [4], and given the expense and the scientific and ethical constraints of RCTs, it is fortunate that advances in biology, biotechnology, and epidemiology have provided us with an alternative tool, in the shape of Mendelian randomisation, that can help us to formally assess causality based on observational data. But the approach demands a sound understanding both of the underlying biomedicine and of the statistical assumptions invoked in its application. If it is used wisely, Mendelian randomisation could make a major contribution to our understanding of the aetiological architecture of complex diseases; but if it is used unthinkingly, it could sow seeds of confusion and set back progress in bioscience. This short article is aimed at encouraging the former and avoiding the latter.