The trajectory analysis and mendelian randomization of exposures (blood biomarkers etc.) on the risk of cardiovascular diseases

In recent years, the risk of chronic non-communicable diseases such as cardiovascular diseases has increased every year, posing a serious threat to the lives and health of patients. Therefore, it is urgent to prevent cardiovascular disease, reduce the incidence and mortality of cardiovascular disease.
The causes of cardiovascular disease are complex. Many studies have shown that blood biomarkers such as triglyceride and high-density lipoprotein are related to the risk of cardiovascular disease. However, most previous studies have focused on the relationship between blood biomarker levels and cardiovascular disease risk at a single point in time. Few studies have analyzed the trajectory of blood biomarkers and explored the relationship between them and cardiovascular disease. For example, tracking data of blood biomarkers obtained by multiple measurements of subjects in different years.For this kind of data, the common methods are repeated measurement an OVA, growth curve model and so on. Although these methods are effective in describing the general trend, there is a limitation in assuming that the general trend is the same. However, this assumption is often not met in reality. Many phenomena change over time and the trend is heterogeneous. For example, the index level of some people is increasing while that of others is decreasing. The trend and difference cannot be well described by the above methods. Currently, the trajectory Model is commonly used. This method can describe and fit subgroups of different development trends. Therefore, this study will evaluate the impact of different blood biomarker trajectories on cardiovascular disease risk.
At the same time, as a functional intermediate under environmental exposure, blood biomarkers can often reflect individual genetic composition and predict or influence the occurrence and development of diseases. In recent years, the study of blood metabolomics has provided many biomarkers and established reliable prediction models for the occurrence of cardiovascular diseases. However, many metabolites often only provide associations with disease occurrence, and the causal relationship is not clear. Mendelian randomization (MR) is a popular genetic epidemiological study design method that explores causality between exposure and outcome by using genetic variation as an instrumental variable. Therefore, this study will explore the causal relationship between blood biomarkers and cardiovascular disease through Mendelian randomization.