UC Berkeley

The age-standardized incidence of cardiovascular disease in high-income countries has fallen precipitously from 844 cases per 100,000 in 1990 to 597 in 2019. However, this reduction in average incidence obscures significant disparities in risk by socioeconomic, genetic, biological, and health behavioral factors. To date, most studies of the risk factors for cardiovascular disease attempt to isolate the effect of a single risk factor. This single-exposure focus belies the dynamic interplay between genetics, socioeconomic status, and traditional health and health behavioral factors that ultimately determine an individual’s cardiovascular disease risk. This dissertation explores the ways in which different domains of risk interact to produce heterogeneous, individualized risk of cardiovascular disease.

The second chapter of this dissertation employs Mendelian randomization, an instrumental variable technique that uses random genetic variation as the instrument, to understand the causal effect of adiposity on cardiovascular disease incidence for individuals at different levels of socioeconomic status. Both high adiposity and low socioeconomic status increase cardiovascular disease risk. However, it is unclear whether the risk caused by an increase in adiposity is itself identical for individuals at varying levels of socioeconomic status or if, instead, individuals at lower levels of socioeconomic status face a greater risk from an increase in adiposity than their peers. If such a disparity did exist, it would imply that the risk implications of weight gain may differ by socioeconomic status. In UK Biobank data, we find that differences in risk in these Mendelian randomization models existed only for individuals with versus without a university degree. The differences in cardiovascular disease risk from higher body mass index by educational attainment or income – if they exist - are small in magnitude, though imprecisely estimated. The results for waist-to-hip ratio adjusted for body mass index, a measure of central adiposity, generally showed even smaller differences between socioeconomic groups.

The third chapter of this dissertation explores whether a health behavior related to lower cardiovascular disease risk, physical activity, might ameliorate some of the risk of coronary artery disease caused by an individual’s genetic predisposition. Specifically, I use wrist-worn accelerometer data combined with the most powerful polygenic risk score in the literature to determine how physical activity volume and intensity impact an individual’s risk of coronary artery disease at different levels of genetic risk. If individuals at higher risk benefit more from greater physical activity than their lower risk peers, this could imply that more personalized physical activity standards should be considered for at-risk patients.Physical activity volume and intensity each had significant independent associations with incident coronary artery disease, with physical activity intensity demonstrating the strongest association. However, no interactive effect of physical activity and genetic risk on coronary artery disease risk was found.

Future research should focus both on the impact of individual risk factors on cardiovascular disease risk and - particularly - how different risk factors and domains might contribute and interact to determine an individual’s overall cardiovascular disease risk. With the proliferation of large-scale cohort datasets such as the UK Biobank, the Million Veteran Program, and All of Us, researchers face an unprecedented opportunity to understand how every aspect of a person’s life from their social and built environment to their medical care access, genetic code, and health behaviors interconnect to determine disease risk.