Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse mendelian randomization

Abstract

AbstractLifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR) = 1.15, 95% CI = 1.07 to 1.23, P = 7.8 × 10− 5) and diabetes (OR = 1.43, 95% CI = 1.31 to 1.56, P = 9.4 × 10− 15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR = 0.87, 95% CI = 0.78 to 0.97, P = 0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.