Polygenic risk scores: a biased prediction?

A new study highlights the biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation. The design bias of workhorse tools used for research, particularly genotyping arrays, contributes to these distortions. To avoid further inequities in health outcomes, the inclusion of diverse populations in research, unbiased genotyping, and methods of bias reduction in PRS are critical.

Abstract licence: CC BY-NC-ND

1. 9.

   The UK Biobank resource with deep phenotyping and genomic data · 2018

2. 10.

   Genetic disease risks can be misestimated across global populations · 2018

8 more references, whose wording the paper’s licence keeps private.

• Public human microbiome data are dominated by highly developed countries · 2022

• Variable prediction accuracy of polygenic scores within an ancestry group · 2020

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