We highlighted what we believe are limitations to genetic risk prediction as well as the most important pitfalls to befall researchers and discussed how these can be avoided. Most problems occur in the validation stage, when data are not fully independent to those in the discovery phase, but care is also needed to ensure that the discovery and validation samples are representative of the population in which the predictor will be applied. Genomic prediction is already having a major impact in livestock selection programmes37 and has great potential for applications in plant breeding, preventative medicine strategies and clinical decision making. However, there are fundamental limitations to the predictive ability of a genetic predictor (see limitations 1 and 2) and so it is important that expectations are realistic and that the accuracy of genetic predictors are fairly evaluated. As sample sizes increase, predictors of genetic risk will have greater clinical utility, particularly in terms of identification of population strata at increased risk of disease as opposed to accurate predictive diagnosis for individuals.
