Abstract
The genetic liability to a complex phenotype can be assessed using polygenic risk scores (PRSs) and is calculated as the sum of genotypes weighted by effect-size estimates derived from summary statistics of genome-wide association study (GWAS) data. Due to different allele frequencies (AFs) and linkage disequilibrium (LD) patterns across populations, PRSs developed in one population drop drastically in predictive performance when transferred to another. One of the major factors contributing to AF and LD heterogeneity is genetic drift, which acts strongly during population bottlenecks and is influenced by the dominance of certain alleles. In particular, because causal variants on empirical data are typically not known, the presence of population-specific LD patterns will strongly affect the transferability of PRS models. In this work, we therefore conducted demographic simulations to investigate the influence of the dominance coefficient on the transferability of PRSs among European, African, and Asian populations. By modifying the length and size of the bottleneck leading to the split of Eurasian and African populations, we gain a deeper understanding of the underlying dynamics. Finally, we illustrate that in our simulations, PRS models that are adapted to the underlying dominance coefficient can substantially increase the prediction performance in out-of-target populations.