Identifying risk factors for chronic diseases and multimorbidity in UK Biobank: a longitudinal cohort study

With the increases in the prevalence of chronic diseases (cardiovascular disease, stroke, diabetes, hypertension, cancer, precancerous lesions, obesity, etc) and aging, multimorbidity (two or more chronic morbidities) has become a global health problem. Therefore, it is critical to identify robust, sensitive, and accessible risk factors and biomarkers for chronic diseases and multimorbidity. Although there were several cohort studies identifying risk factors and biomarkers for the specific chronic disease, less cohort study has been published on multimorbidity. In addition, there is still a lack of sufficient and robust evidence on estimating the risk and mortality of specific chronic diseases and multimorbidity incorporating multiple levels of data on modifiable environmental, lifestyle, genetic, metabolic, the interactions of these factors, and the trajectory changes of these factors in a population-based prospective cohort. Therefore, we conceive of estimating the risk and mortality of specific chronic diseases and multimorbidity by incorporating core data, measures and multi-omics data in UK Biobank cohort.
In this study we aim to: (i) investigate the causal association among these specific chronic diseases with each other and the causal association of environmental factors with the specific chronic diseases and multimorbidity using Mendelian randomization instrumental variable analysis. (ii) estimate the associations of trajectory changes of modifiable environmental, metabolic factors and imaging with the risk and mortality of specific chronic diseases and multimorbidity. (iii) estimate the associations of modifiable environmental, genetic, metabolic, the interactions of these factors, and mediation effect with the risk and mortality of specific chronic diseases and multimorbidity. (iv) establish the genetic risk scores and risk prediction score incorporating genetics, metabolic and environmental factors for the specific chronic diseases and multimorbidity.
Project Duration: Around 3 years from the time we have received the data. Public Health Impact: Through this study, we will be able to identify robust, sensitive, and accessible risk factors and biomarkers of chronic diseases and multimorbidity by incorporating multi-omics data. which will help researchers comprehensively understand the development of chronic diseases and multimorbidity, and will be helpful in the precise and individual prevention of chronic diseases and multimorbidity.