TY - JOUR T1 - Genetic Prediction of Male Pattern Baldness JF - bioRxiv DO - 10.1101/072306 SP - 072306 AU - Saskia P Hagenaars AU - W David Hill AU - Sarah E Harris AU - Stuart J Ritchie AU - Gail Davies AU - David C Liewald AU - Catharine R Gale AU - David J Porteous AU - Ian J Deary AU - Riccardo E Marioni Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/08/31/072306.abstract N2 - Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent novel genetic loci associated with severe hair loss. By developing a prediction algorithm based entirely on common genetic variants, and applying it to an independent sample, we could discriminate accurately (AUC = 0.82) between those with no hair loss from those with severe hair loss. The results of this study might help identify those at the greatest risk of hair loss and also potential genetic targets for intervention. ER -