However, all of these methods are inadequate for polygenic risk prediction in non-European populations, because they consider training data from only a single population. Existing training data sets have much larger sample sizes in European populations, but the use of European training data for polygenic risk prediction in non-European populations reduces prediction accuracy, due to different patterns of linkage disequilibrium (LD) (or potentially due to different causal effects) (International Schizophrenia Consortium et al., 2009; Rosenberg et al., 2010; Scutari, Mackay, & Balding, 2016; Vilhjálmsson et al., 2015). For example, ref. (Vilhjálmsson et al., 2015) reported a relative decrease of 53-89% in schizophrenia risk prediction accuracy in Japanese and African-American populations compared to Europeans when applying PRS methods using European training data. An alternative is to use training data from the same population as the target population, but this would generally imply a much lower sample size, reducing prediction accuracy.
