Local True Discovery Rate Weighted Polygenic Scores Using GWAS Summary Data

A polygenic score is commonly derived using genome-wide genotype data to summarize the genetic contribution to a particular disease at the individual level. Usually it is constructed as a linear combination of SNP genotype weighted by the SNP-wise regression coefficient of the SNP to the phenotype using SNPs with p values smaller than a particular threshold. Commonly a range of thresholds are used which can pose problems with multiple comparisons as well as over-fitting. Here, an alternative weighting scheme is proposed, making use of the local true discovery rate, estimated from summary statistics. Two methods of estimation are proposed-maximum likelihood and kernel density estimation. Simulation studies using real and artificial data suggest this new weighting scheme is highly comparable with standard polygenic scores using the best possible p value threshold in prediction, even though this threshold is not normally known in practice.