| Title: | Assessing agreement between different polygenic risk scores in the UK Biobank |
| Journal: | Scientific Reports |
| Published: | 27 Jul 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35896674/ |
| DOI: | https://doi.org/10.1038/s41598-022-17012-6 |
| URL: | https://www.nature.com/articles/s41598-022-17012-6.pdf |
| Citations: | 16 (15 in last 2 years) as of 8 Aug 2024 |
Publication 10378
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Polygenic risk scores (PRS) are proposed for use in clinical and research settings for risk stratification. However, there are limited investigations on how different PRS diverge from each other in risk prediction of individuals. We compared two recently published PRS for each of three conditions, breast cancer, hypertension and dementia, to assess the stability of using these algorithms for risk prediction in a single large population. We used imputed genotyping data from the UK Biobank prospective cohort, limited to the White British subset. We found that: (1) 20% or more of SNPs in the first PRS were not represented in the more recent PRS for all three diseases, by the same SNP or a surrogate with R2 > 0.8 by linkage disequilibrium (LD). (2) Although the difference in the area under the receiver operating characteristic curve (AUC) obtained using the two PRS is hardly appreciable for all three diseases, there were large differences in individual risk prediction between the two PRS. For instance, for each disease, of those classified in the top 5% of risk by the first PRS, over 60% were not so classified by the second PRS. We found substantial discordance between different PRS for the same disease, indicating that individuals could receive different medical advice depending on which PRS is used to assess their genetic susceptibility. It is desirable to resolve this uncertainty before using PRS for risk stratification in clinical settings.</p>
5 Authors
- Lei Clifton
- Jennifer A. Collister
- Xiaonan Liu
- Thomas J. Littlejohns
- David J. Hunter
1 Application
| Application ID | Title |
|---|---|
| 33952 | Risk profiles for cancers; polygenic risk scores with and without non-genetic risk factors |
Enabling scientific discoveries that improve human health