Elucidate the causal roles of smoking on human diseases using large genetic datasets linked with health records
Principal Investigator: Dr Xiaowei Zhan
Approved Research ID: 21237
Approval date: January 15th 2017
Smoking is harmful for health. Yet, for some traits e.g. Parkinson?s disease, smoking is associated with reduced risk. It is of interest to explore the causal effect of smoking for many human diseases. For this proposal, we will 1.) derive better models of nicotine/toxin uptake combining multiple smoking related traits; 2) develop an efficient method for association analysis that can simultaneously process multiple traits in large datasets and 3) comprehensively evaluate the causal roles of smoking/nicotine addiction on a myriad of traits UK Biobank has been developed as a major research resource to improving the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses. Smoking is a modifiable risk factor. Our research will help advance our understanding on the causal impact of smoking addiction on a myriad of human diseases. These results will be extremely informative for refining tobacco regulatory policies, accurately assessing individual level disease risk, and designing personalized prevention and treatment plans for human diseases. Software tools we will develop for efficient association analysis will also benefit other users of the UK Biobank data. We will make use of the UK biobank dataset to identify genetic variant associated with a variety of smoking related traits, and develop a better predictive model of nicotine/toxin intake from smoking behavioral traits. We will also analyze genetic association with a variety of human disease traits and apply Mendelian randomization to understand the causal roles of smoking related toxin intake on these diseases. We request access to the full cohort.