The most basic means of incorporating genetic information in risk prediction is via family history, which has predictive accuracy proportional to both the heritability and prevalence of disease (the AUC of a single sibling family history is , where K is the prevalence and λS the sibling relative risk, see Supplementary Methods for derivation). The information from a single affected sibling, for instance, predicts Crohn's disease with AUC of 0.56 (10). Prediction based on molecular measurements of genotype began with common loci of unusually large effect, such as the HLA effect in autoimmune diseases like type 1 diabetes [which alone gives an AUC of 0.85 (11)], rheumatoid arthritis and lupus or the effect of APOE in Alzheimer's. Many of these loci were identified in the pre-GWAS era by linkage studies, which further mark them as exceptions in complex disease genetics. Rare high penetrance mutations (such as BRCA1 and BRCA2 for breast cancer), while obviously very important to the families who carry them, are of surprisingly little value in population-level prediction (12,13). BRCA1/2 population screening has an AUC of only 0.52,
