Causal inference study to clarify the association between alcohol consumption, diabetes, cancer and cardiovascular disease paradox
Approved Research ID: 66486
Approval date: March 2nd 2022
The controversy over the association between alcohol consumption and cardiovascular disease is a researcher's concern and national concern. The best way to confirm causality is RCT(Randomised control trial). Still, it is challenging to implement as an ethical issue, and the Mendelian Randomization study is drawing attention as a new way to replace it.
Through a large-scale Korean cohort (KCPS-II) collected for about a decade, the study plans to analyze epidemiologically, taking into account known risk factors for cardiovascular diseases, such as drinking, smoking, age, physical activity, blood pressure, cholesterol, and blood sugar.
Of the approximately 150,000 people we have obtained blood samples, and consent forms, a genome-wide association study (GWAS) analysis will be conducted with the data of the subjects from which genetic data has been collected. Through this, we want to discover the genes associated with alcohol consumption.
The KCPS-II is a large-scale Korean cohort that includes blood samples collected from 2004 to 2013 and various clinical and health information. According to the data, not only the prevalence at the time of blood collection but also the new disease and death data that have occurred since then by follow-up observations. It is possible to discover the disease risk factors and biomarkers and construct them a disease prediction model for Koreans.
It is intended to construct a predictive model of cardiovascular disease using the fusion interaction of environmental factors, biomarkers, and genetic factors from epidemiological analysis of long-term collected cohort data.
Today, precise medical techniques tailored to individuals are required, and the need for multidisciplinary research is increasing. The predicted models built through this process will be verified using UK Biobank data targeting the European population.
Through UK biobank, which has large-scale genetic information, we expect cooperation and development on research methods to identify the relevance of disease via big data.
The interaction of various genetic-environment factors determines the occurrence of cardiovascular disease. A wide range of surveys and tests involving various variables are needed, and genetic information is required to discover Korean specific genetic factors.
Based on KCPS-II Biobank data meeting all these conditions, it is expected to play an essential role in evaluating the clinical usefulness of cardiovascular diseases as well as in the mechanism study of disease occurrence and the development of potential therapeutic materials.
In previous epidemiological studies, moderate alcohol consumption has been shown to play a decisive role in cardiovascular disease. Traditional epidemiological studies have several limitations, such as reverse causality. In order to solve this and infer causality, experiment-based RCT (Randomised control trial) should be implemented. However, it takes a long time, and enormous cost, and is also challenging to perform due to ethical issues. Therefore, Mendelian Randomization(MR) has been emerging as a research method that can replace RCT, which uses a genetic variant as an instrumental variable to identify causality. Such as to provide new drug development information through verification of the risk factor based on MR, to develop a predictive model of cardiovascular disease with high predictive power to identify risk population and also the interaction between smoking and drinking, a risk factor for cardiovascular disease. In this study research, the UK biobank's large cohort data can help compare the results from KCPS-II data. And confirm causality and conduct research on the differences between the Asian, White, and another ethnicity.
1) Understanding and securing UK Biobank data: Discussing new methodology and considering to apply to Korean Cancer Prevention Study(KCPS)-II Biobank
2) Epidemiologic analysis to explore risk factors of cardiovascular disease(GWAS analysis)
Exploring the risk factors of cardiovascular disease through the long-term follow-up KCPS-II Biobank
Performing epidemiological analysis considering the known risk factors such as smoking, age, physical activity, blood pressure, serum cholesterol level, and blood sugar level
3) Performing mendelian randomization(MR) analysis to reveal the relation of the paradox between alcohol consumption and cardiovascular disease
MR analysis can be performed as one of the methods to overcome the effects of confounding variables
MR analysis will be to be performed by using genetic variation related to drinking discovered through GWAS analysis as a tool variable.
4) Interaction analysis between smoking and alcohol consumption as risk factors of cardiovascular disease
5) Building a prediction model of cardiovascular disease based on interaction analysis of environmental factors, serum biomarkers, and genetic factors
6) Causal association analysis: alcohol and diabetes
7) Mediation analysis: alcohol, diabetes, and cardiovascular diseases
Technical statistics and methods of mechanical analysis, all statistical analyses will use various statistical packages, such as SAS 9.2 or 9.3 version, STATA, and R. The plug 1.09 program will be used for the Genome-Wide Association Study (GWAS). When establishing a predictive model, we will use software such as SAS, R, etc. to implement it.
In this study, the main exposure variable is alcohol consumption but we want to include lifestyle risk factors (smoking status, physical activities, body mass index..
We want to add the main outcome variables as CVD, chronic diseases involve (cancers, COPD, diabetes, etc.), mortality rate.
1) Perform epidemiological analysis of alcohol consumption, smoking status, lifestyle risk factor, CVD, chronic diseases involves (cancers, COPD, diabetes, etc.), the mortality rate
2) Epidemiological analysis to explore risk factors of cardiovascular disease, and the leading cause of cancer and mortality.
3) MR analysis will be to be performed by using genetic variation related to alcohol and smoking discovered through GWAS analysis as an instrumental variable.
4) Interaction analysis between smoking and alcohol consumption as risk factors of cardiovascular disease.
5) Causal association analysis (between alcohol consumption, smoking status, and CVD, cancer, mortality)