| Title: | Stability of polygenic scores across discovery genome-wide association studies |
| Journal: | Human Genetics and Genomics Advances |
| Published: | 21 Jan 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35199043/ |
| DOI: | https://doi.org/10.1016/j.xhgg.2022.100091 |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841810 |
| Citations: | 26 (13 in last 2 years) as of 8 Aug 2024 |
Publication 12596
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 scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.</p>
8 Authors
- Laura M. Schultz
- Alison K. Merikangas
- Kosha Ruparel
- Sébastien Jacquemont
- David C. Glahn
- Raquel E. Gur
- Ran Barzilay
- Laura Almasy
1 Application
| Application ID | Title |
|---|---|
| 40980 | Rare deleterious CNVs share some overlapping effects on brain structure. |
Enabling scientific discoveries that improve human health