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Approved research

Mediation and Mendelian Randomization analyses to investigate the causal relationship between genetic variants, lung function and lung cancer risk

Principal Investigator: Dr Rayjean Hung
Approved Research ID: 23261
Approval date: November 1st 2016

Lay summary

Impaired lung function is associated with lung cancer, the leading cause of cancer death. It was previously shown that reduced lung function and lung cancer share common genetic pathways, however it remains unclear whether reduced lung function is an independent risk factor, a manifestation of lung damage due to smoking, etc, or an early stage of cancer development. To understand the role of impaired lung function in lung carcinogenesis, we propose to (1) investigate lung function predictors, including personal exposure history and early life factors; (2) test the its causal relationship with lung cancer; (3) decipher the direct and indirect effects through lung function on lung cancer risk. The proposed study will contribute towards UK Biobank goals of improving public health in several ways. This work will (i) provide new insight of the etiology of impaired lung function, which would have implications on multiple complex diseases; (ii) help to understand its role in lung cancer development by using robust methods for causal inference. These goals will be complemented by mediation analyses which can assess how individuals? genomic files may lead to impaired lung function and lung cancer through shared and/or independent pathways. Our findings will contribute to informed interventions aimed at susceptible populations with impaired lung function and establish risk prediction model for targeted population for lung cancer early detection. The proposed study will be carried out using genetic information and baseline UK Biobank data, including self-reported exposure and heath history and spirometry measures. The first stage of the analysis will identify genetic and non-genetic factors associated with impaired lung function. The genetic factors strongly associated with lung function will be then used as instrumental variables (IV) to evaluate the causal relationship between lung function and lung cancer. The association between the genetic instrument variables and lung cancer risk will be estimated in large, independent validation samples, such as the lung cancer OncoArray dataset. Lastly, we will carry out mediation analyses to estimate the proportion of the genetic and non-genetic factors that are associated with lung cancer risk acting through impaired pulmonary function mechanisms. The proposed study will utilize the full cohort with available baseline characteristics, genome-wide genotype data and spirometry measurements.