Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction

The accuracy of polygenic risk scores (PRSs) to predict complex diseases increases with the training sample size. PRSs are generally derived based on summary statistics from large meta-analyses of multiple genome-wide association studies (GWASs). However, it is now common for researchers to have access to large individual-level data as well, such as the UK Biobank data. To the best of our knowledge, it has not yet  been explored how best to combine both types of data (summary statistics and individual-level data) to optimize polygenic prediction.

Source: The American Journal of Human Genetics - May 7, 2021 Category: Genetics & Stem Cells Authors: Clara Albi ñana, Jakob Grove, John J. McGrath, Esben Agerbo, Naomi R. Wray, Cynthia M. Bulik, Merete Nordentoft, David M. Hougaard, Thomas Werge, Anders D. Børglum, Preben Bo Mortensen, Florian Privé, Bjarni J. Vilhjálmsson Tags: Article Source Type: research