Abstract
Inherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Previous work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the longitudinal relationship between genetic relative risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic relative risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their relative risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying relative risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic relative risk. The predominant pattern shows genetic risk factors having the greatest relative impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants, although the magnitude and form of the decrease varies among diseases. As a consequence, for diseases where genetic relative risk decreases over age, genetic risk factors have stronger explanatory power among younger populations, compared to older ones. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction.
Highlights
Many studies have demonstrated the potential utility of using genetic risk factors for predicting individual risk of common diseases, ranging from heart disease [1,2] to breast cancer [3] and auto-immune conditions [4]
By applying the methods to data from the UK Biobank, a prospective study of 500,000 people, we show that there is a tendency for genetic relative risk to decline with increasing age
To compare our results using different set of variants, we used variants reported in the GWAS Catalog [23] for two traits, “hypertension” and “coronary heart disease”, and inferred genetic risk profiles on the respective ICD-10 codes, I10 and I25.1
Summary
Many studies have demonstrated the potential utility of using genetic risk factors for predicting individual risk of common diseases, ranging from heart disease [1,2] to breast cancer [3] and auto-immune conditions [4]. Genetic analyses of quantitative traits including blood pressure, lipid levels and BMI have identified genetic variants whose effect size changes with age [12–16]. These results raise the possibility that genetic risk factors may play larger or smaller roles in influencing risk of disease during different age intervals. The longitudinal analysis of disease risk has to account appropriately for the impact of selection that arises in age-stratified analyses; even under a time-invariant proportional hazards model, those entering the disease state earliest will tend to be those with the highest burden of risk factors. This can be problematic when not all risk factors are measured, as hidden risk factors can act to apparently dilute relative risk over time [17–19]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
