B3450 - Predicting comprehensive smoking behaviours using epigenetic risk scores - 24/01/2020

B number: 
B3450
Principal applicant name: 
Ryan Langdon | ICEP (UK)
Co-applicants: 
Dr Matthew Suderman, Dr Paul Yousefi, Dr Rebecca Richmond
Title of project: 
Predicting comprehensive smoking behaviours using epigenetic risk scores
Proposal summary: 

The negative health risks of exposure to cigarette smoke are well known; including personal, second-hand and foetal exposure during pregnancy.
These health risks, in addition to a high prevalence in the UK and worldwide, make accurate measurement of smoking status an important factor in most epidemiological studies.

DNA methylation appears to provide reliable and long-term markers of tobacco smoke exposure. In fact, it is possible to use combinations of methylation levels at smoking-associated CpG sites to not only differentiate among current, former and never smokers but to also detect smoking intensity, number of smoking years and time since cessation. These aspects of smoking aren't necessarily captured in questionnaire-based responses for a given study. Even if they were, they might not be reliable and may even be misreported. For example, saying you smoke 20 cigarettes a day doesn't say how deep you inhale those cigarettes or whether the brand matters. Moreover, you might be a current smoker but say you're not a smoker out of guilt. Methylation provides a continuous measure (0-100%) in response to various aspects of smoking (rather than "yes/no"), and objectively shows a response to smoking, so can overcome these issues.

Recently, a study by Leffondre found a comprehensive measure of smoking history that incorporated intensity, duration, and time since cessation (including the half-life of the effect of stopping smoking). We will use ARIES DNA methylation data to develop predictors of smoking behaviour using this index, which we will compare against self-reported smoking behaviour from questionnaires and ALSPAC cotinine data. We hope to derive a comprehensive prediction model of smoking which can be applied to other cohorts. Methylation may be able to be used in the absence of self-report data, or more importantly, help improve prediction of diseases which are caused by smoking.

Impact of research: 
This research aims to investigate the efficacy of using DNA methylation as an objective biomarker for comprehensive smoking history, potentially being used as tool for estimating the extent of misreporting in self-reported smoking behaviours and, to a greater extent, to be used to improve prediction of smoking-related adverse health outcomes where methylation data is available.
Date proposal received: 
Wednesday, 22 January, 2020
Date proposal approved: 
Wednesday, 22 January, 2020
Keywords: 
Epidemiology, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Statistical methods, Biological samples -e.g. blood, cell lines, saliva, etc., Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Environment - enviromental exposure, pollution, Epigenetics, Fathers, Mothers - maternal age, menopause, obstetrics, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc., Offspring, Statistical methods