Human life expectancy has risen dramatically over the last 100 years due to medical and agricultural technological advances. Accompanying this rise in human life expectancy is an increasing prevalence of age-related chronic disease, which is further exacerbated with increasing food supplies and sedentary lifestyles. In contrast to the most common pre-industrialization causes of death (infections, accidents, starvation), today’s leading causes of death are those that slowly kill us over time – namely chronic age-related disease. In addition, different individuals display different susceptibilities to any of these diseases, which is largely driven by genetics, environment, and lifestyle factors. Until recently, identifying how these factors interact to influence disease susceptibility was difficult due to lack of data to disentangle their relationships and impact on disease.
Population-scale research initiatives combining molecular data and health outcomes, such as UK Biobank, provide significant opportunities to accelerate the implementation of preventative and precision health. The goal of this project is to identify novel predictors (or risk factors) of chronic disease risk, then use this information to develop algorithms to estimate the future disease risk at the individual patient level. This approach to preventative health would help physicians to identify a patient’s risk of disease earlier, prior to disease onset, and potentially mitigate future disease burden.