| Title: | A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk |
| Journal: | Nature Communications |
| Published: | 12 Jun 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38866767/ |
| DOI: | https://doi.org/10.1038/s41467-024-48938-2 |
| URL: | https://www.nature.com/articles/s41467-024-48938-2.pdf |
| Citations: | 4 (4 in last 2 years) as of 8 Aug 2024 |
Publication 11869
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 (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.</p>
15 Keywords
- Adult
- Age Factors
- Aged
- Diabetes Mellitus, Type 2
- Female
- Genetic Predisposition to Disease
- Global Burden of Disease
- Humans
- Incidence
- Male
- Middle Aged
- Multifactorial Inheritance
- Risk Assessment
- Risk Factors
- Sex Factors
30 Authors
- Bradley Jermy
- Kristi Läll
- Brooke N. Wolford
- Ying Wang
- Kristina Zguro
- Yipeng Cheng
- Masahiro Kanai
- Stavroula Kanoni
- Zhiyu Yang
- Tuomo Hartonen
- Remo Monti
- Julian Wanner
- Omar Youssef
- Christoph Lippert
- David van Heel
- Yukinori Okada
- Daniel L. McCartney
- Caroline Hayward
- Riccardo E. Marioni
- Simone Furini
- Alessandra Renieri
- Alicia R. Martin
- Benjamin M. Neale
- Kristian Hveem
- Reedik Mägi
- Aarno Palotie
- Henrike Heyne
- Nina Mars
- Andrea Ganna
- Samuli Ripatti
1 Application
| Application ID | Title |
|---|---|
| 78537 | International consortium for integrative genomics prediction (INTERVENE) |
Enabling scientific discoveries that improve human health