Cardiovascular diseases, such as ischemic heart disease, hypertension, stroke, heart failure, peripheral artery disease, etc., are among the leading causes of mortality among adults. Identifying risk factors for these diseases is crucial for preventing or delaying complications and premature death.
Aims:
1. To comprehensively assess proteomic, metabolomic, genomic, and other omic factors, as well as imaging, environmental, lifestyle, psychosocial factors, etc., within the UK Biobank and their causal associations with cardiovascular diseases and comorbidities.
2. To evaluate the associations between trajectory changes in omic and non-omic risk factors, with the risk and mortality of cardiovascular diseases and multi-morbidity.
3. To develop risk prediction tools (e.g., models, scores, algorithms, etc.) that incorporate omic and non-omic factors for cardiovascular diseases and multi-morbidity.
4. To utilize advanced statistical methods (e.g., machine learning) to improve the accuracy and efficiency of identification and risk prediction of cardiovascular diseases and their comorbidities.
Scientific Rationale: Although numerous factors affecting the risk of cardiovascular diseases have been identified, many more remain undiscovered. Non-omic factors, including dietary habits, exercise behavior, sleep patterns, nutritional status, etc., are well known to influence these diseases. Additionally, the interactions between proteomic, metabolomic, genomic, and non-omic factors must be considered. Moreover, there is a lack of sufficient and robust evidence on estimating the risk and mortality of cardiovascular diseases by incorporating the trajectory changes of these factors in a population-based prospective cohort. The integration of advanced statistical methods and phenotyping techniques can further enhance the identification and prediction of cardiovascular diseases by uncovering complex patterns and relationships in the data. A better understanding of the factors affecting the likelihood of developing cardiovascular diseases is essential for creating novel and more effective approaches to disease prevention, diagnosis, and treatment. This project is expected to last for 36 months.
In addition, several other diseases (including metabolic, respiratory, digestive, neurological, renal diseases, and cancers) are known to have significant links and interactions with cardiovascular health. By comprehensively analyzing data on these related diseases, we can better inform the development of improved prevention strategies, targeted interventions, and personalized treatments for individuals at risk of multi-comorbidity.
Public Health Impact: Our study will enhance the understanding of the etiology of cardiovascular diseases and provide scientific evidence for early intervention and improved disease management. This will ultimately contribute to better public health outcomes by informing strategies to reduce the burden of cardiovascular diseases and their comorbidities.
