A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

• Published in: Nature communications Vol. 15; no. 1; pp. 5007 - 14
• Main Authors: Jermy, Bradley, Läll, Kristi, Wolford, Brooke N., Wang, Ying, Zguro, Kristina, Cheng, Yipeng, Kanai, Masahiro, Kanoni, Stavroula, Yang, Zhiyu, Hartonen, Tuomo, Monti, Remo, Wanner, Julian, Youssef, Omar, Lippert, Christoph, van Heel, David, Okada, Yukinori, McCartney, Daniel L., Hayward, Caroline, Marioni, Riccardo E., Furini, Simone, Renieri, Alessandra, Martin, Alicia R., Neale, Benjamin M., Hveem, Kristian, Mägi, Reedik, Palotie, Aarno, Heyne, Henrike, Mars, Nina, Ganna, Andrea, Ripatti, Samuli
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 12.06.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 45/23; 45/43; 631/208/721; 692/499; Adult; Age; Age Factors; Aged; Cardiovascular disease; Cardiovascular diseases; Coronary artery disease; Decision making; Diabetes mellitus (non-insulin dependent); Diabetes Mellitus, Type 2 - epidemiology; Diabetes Mellitus, Type 2 - genetics; Estimates; Female; Genetic Predisposition to Disease; Global Burden of Disease; Gout; Health risk assessment; Health risks; Heart diseases; Humanities and Social Sciences; Humans; Incidence; Male; Middle Aged; multidisciplinary; Multifactorial Inheritance - genetics; Osteoarthritis; Prediction models; Public health; Risk; Risk Assessment - methods; Risk Factors; Science; Science (multidisciplinary); Sex; Sex Factors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-48938-2

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. Here the authors present a framework for estimating disease risk using PGS accounting for country, age and sex. They find that PGSs have a significant sex-specific effect on common diseases, and their effect is typically larger in young individuals.