Abstract
AbstractPolygenic scores provide an indication of an individual’s genetic propensity for a trait within a test population. These scores are calculated using results from genetic analysis conducted in discovery populations. However, when the test and discovery populations have different ancestries, predictions are less accurate. As many genetic analyses are conducted using European populations, this hinders the potential for making predictions in many of the underrepresented populations in research. To address this, UP and Downstream Genetic scoring (UPDOG) was developed to consider the genetic architecture of both the discovery and test cohorts before calculating polygenic scores. UPDOG was tested across four ancestries and six phenotypes and benchmarked against five existing tools for polygenic scoring. In approximately two-thirds of cases UPDOG improved trans-ancestral prediction, although the increases were small. Maximising the efficacy of polygenic scores and extending it to the global population is crucial for delivering personalised medicine and universal healthcare equality.
Publisher
Cold Spring Harbor Laboratory