Cardiovascular risk assessment, such as with the Framingham risk and SCORE2 scores, is largely based on the analyses of cross-sectional measures of cardiovascular risk factors, such as high blood pressure, smoking and high LDL cholesterol levels. Importantly, these measures are often only taken when an individual visits a clinic and when there is a certain indication. However, cardiovascular disease develops over a long period of time as the consequence of cumulative and interacting exposures to these risk factors, which are not stable over time. Furthermore, these risk factor trajectories (e.g., weight trajectory, blood pressure trajectory) are likely to be dependent on early-life exposures, such as birth weight, weight at age 10, number of children. However, this is yet still poorly examined due to the availability of sufficient data and the availability of suitable analytical techniques which our team has been developing over the past years. Within this UK Biobank project, we aim to use the GP assessments to map different risk factor trajectories and aim to link these to incident cardiometabolic diseases later in life. These associations might differ for different generations. We hypothesize that the use of risk factor trajectories will be benefitting clinical care in the end due to improved risk prediction performance as more data is taking into account.
Research questions:
– Investigate the associations between genomic, generation, early-life (parental) risk factors and risk factor trajectories accross the life course.
– Examine the predictive performance of risk factor trajectories on cardiovascular disease, on top of established cardiovascular prediction scores.