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

Abstract

AbstractPolygenic Scores (PGSs) offer the ability to predict genetic risk for complex disease across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant for clinical and public health decision making, it is important to account for any varying effects due to common risk factors such as age and sex. Here, we develop a novel framework to estimate for cumulative incidences over the life course and produce country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases by integrating PGS associations from 7 studies in 4 countries (N=1,197,129) with disease incidences from the Global Burden of Disease. PGSs had a significant sex-specific effect for 5 diseases (asthma, hip osteoarthritis, gout, coronary heart disease, type 2 diabetes) with all but type 2 diabetes exhibiting a larger effect in men. PGS had a larger effect in younger individuals for 13 diseases, with the effects decreasing linearly with age. We showed 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. For T2D, men and women in the top 1% reached the threshold aged 24.8 (95% CI: 22.5 – 27.6) and 22.3 (95% CI: 20.0 – 25.3) respectively. Individuals in the bottom 1% of PGS did not reach the risk threshold by age 80. Our easily extendable framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting 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 disease.