very small. It follows that each individual will carry a different, probably unique, portfolio of risk alleles. Whereas common risk variants have size too small to be used individually as risk predictors, profiles based on many associated genetic variants could provide useful predictions of genetic risk [3],[4]. We define genetic risk as the risk of disease given an individual's unique multi-locus genotype; genetic risk remains unchanged throughout an individual's lifetime and so could be predicted at birth prior to exposure to many environmental risk factors. Indeed, such risk predictions could be age specific, for example, risk of type 2 diabetes at 10 years, 20 years or 50 years if genomic profile sets based on empirical data were available for these scenarios which have age-specific genetic epidemiologies. As more variants are identified in the coming years, there will be increasing interest in the prospects of genomic profiling. It has been argued that genomic profiles should be assessed in terms of their clinical validity as diagnostic classifiers [5],[6]. The receiver operator characteristic (ROC) curve [7] is a well established tool for determining the efficacy of clinical diagnostic and prognostic tests in correctly classifying diseased and non-diseased individuals and has been used in
