TY - JOUR
T1 - A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk
AU - Jermy, Bradley
AU - Läll, Kristi
AU - Wolford, Brooke N.
AU - Wang, Ying
AU - Zguro, Kristina
AU - Cheng, Yipeng
AU - Kanai, Masahiro
AU - Kanoni, Stavroula
AU - Yang, Zhiyu
AU - Hartonen, Tuomo
AU - Monti, Remo
AU - Wanner, Julian
AU - Youssef, Omar
AU - Lippert, Christoph
AU - van Heel, David
AU - Okada, Yukinori
AU - McCartney, Daniel L.
AU - Hayward, Caroline
AU - Marioni, Riccardo E.
AU - Furini, Simone
AU - Renieri, Alessandra
AU - Martin, Alicia R.
AU - Neale, Benjamin M.
AU - Hveem, Kristian
AU - Mägi, Reedik
AU - Palotie, Aarno
AU - Heyne, Henrike
AU - Mars, Nina
AU - Ganna, Andrea
AU - Ripatti, Samuli
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - 116 Chemical sciences
U2 - 10.1038/s41467-024-48938-2
DO - 10.1038/s41467-024-48938-2
M3 - Article
C2 - 38866767
AN - SCOPUS:85195954865
SN - 2041-1723
VL - 15
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5007
ER -