Using Mendelian Randomisation to investigate the causal effects of caffeine and smoking on health outcomes.
This research aims to investigate whether observed associations between caffeine and smoking and health outcomes are causal. We will use Mendelian randomisation methods, using genetic variants associated with caffeine consumption and smoking as proxies for measured exposures. We will investigate the role of caffeine consumption and smoking in the following outcome measures: cardiovascular and metabolic disease (including diagnoses of coronary heart disease, stroke and diabetes and intermediate traits such as glucose, lipids and blood pressure), mental health outcomes (including diagnoses of depression, anxiety, psychosis and dementia), cognitive function, lung function, asthma and allergy, kidney function, liver function and thyroid function. The proposed research will help to further understanding of the role of caffeine consumption and smoking in disease outcomes, which will inform prevention and treatment strategies. Knowledge of causal effects of caffeine will help to inform public health messages regarding caffeine intake. Knowledge of the causal effects of smoking will be important for strategies for reducing the harmful effects of smoking in those unable to quit. This work may also contribute to the development of novel treatments by identifying pathways through which caffeine intake and smoking contribute to disease. We will use Mendelian randomisation methods to look at the associations of genetic variants that are associated with caffeine consumption and smoking behaviour with health outcomes of interest. Due to the way that genes are passed from parents to offspring, which is essentially random, genetic variants that are associated with caffeine intake or smoking behaviour will not be associated with other lifestyle factors (unlike reported caffeine consumption and smoking). Additionally, health outcomes cannot affect the genes that an individual is born with so we do not need to worry about the possibility of reverse causality. This work will be undertaken in the full cohort, N?500,000.
|Lead investigator:||Dr Amy Taylor|
|Lead institution:||University of Bristol|