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Introduction This project aims to monitor human volunteers as they switch from heavy (>10 cigarette/day) tobacco smoking to electronic cigarette (EC) use. Monitoring of markers will comprise expired carbon monoxide, DNA methylation, oxytocin, cortisol, nicotine cotinine and tobacco specific nitrosamine levels in urine and saliva together with psychometric data. In addition electroencephalography will be used to search for electrical changes in the brain correlated with changes in the above markers after transition to EC use. Methods Volunteers were recruited and consented at St George’s University of London. Volunteers were allowed to select their own EC and e-fluid including nicotine concentration. Blood, saliva, urine and buccal cell samples and questionnaire data (nicotine dependence, withdrawal, anxiety, depression, mood, quality of life and sleep quality) were collected at baseline (day-2 and day-1) and throughout the 28-day EC trial (days 3,21,28) and EEG data (eyes open-eyes fixed-eyes closed, each 3 x 30s) were collected at baseline (day-1) and on EC day 21. Nicotine, cotinine, NNK, NNAL and NNN were determined by UHPLC-HESI-HRMS, 5methyl cytosine by HPLC and oxytocin and cortisol by ELISA. Results Urinary and salivary nicotine, cotinine and tobacco specific nitrosamines and expired carbon monoxide decrease significantly following transition to EC. Behavioural data have revealed modest changes in nicotine craving, nicotine withdrawal symptoms, social anxiety and sleep quality following the transition to e-cigarettes. Preliminary comparison of regional spectral power extracted from EEG data collected pre- and post- transition to e-cigarettes use has identified significant changes in specific spectral bands across the brain. Conclusions Switching to EC quickly induces beneficial changes in exposure to toxicants and psychometrics. Changes in regional spectral power observed by EEG vary will be correlated to these other biomarkers. Funding This work is supported by H2020 funding from the European Union and by a PHE-funded PhD studentship.

Aim To monitor how switching to e-cigarettes from cigarette smoking affects psychometric and clinical parameters and relapse rate over a period of 4 weeks. Methods Heavy smokers (≥10cig/day) attended 6 visits where psychometric parameters associated with craving, nicotine withdrawal symptoms, sleep and quality of life were monitored using well validated questionnaires. Heart rate and blood pressure were also measured at each visit. Visit 1 and 2 were baseline visits where smokers continued to smoke and then asked to quit and transition to e-cigarette use. The subsequent visits occurred 3, 7, 21 and 28 days after the quit date. Compliance was monitored via exhaled CO. Completed participants received weekly questionnaires for 12 months and two follow up calls 6 and 12 months after their final visit to monitor for relapse. Results One month relapse rate amongst eligible participants (n=29) was 28%. At 6 months (n=5), 40% used either e-cigarettes or nothing (non-relapsers) and 60% partially relapsed or were dual users. Repeated measures One-Way ANOVA(n=20) showed a significant effect for parameters: ‘irritability’ (p

Introduction Use of electronic cigarettes (ECs) has increased rapidly since they were introduced in Europe in 2006 especially in the UK. Claims have been made for a role in tobacco harm reduction and smoking cessation. Key to these claims is the ability of EC to maintain nicotine levels to limit cravings, withdrawal and nicotine dependence. Therefore, the aim of the current study is to monitor nicotine intake in heavy smokers (>10 cig/day, n=13 completed) transitioning from cigarette smoking to EC-only use whilst collecting psychometric data on nicotine dependence (Fagerstrom), withdrawal (Minnesota), anxiety, depression and sleep quality. Material and Methods Urine and saliva samples as well as psychometric questionnaire data were collected at baseline (visits 1 and 2) and at days 3, 7, 21 and 28 following start of EC use. An UHPLC-HESI-HRMS method was developed, validated and applied to the determination of nicotine and its main metabolite cotinine in urine and saliva. Results The baseline median (interquartile range) urinary nicotine and cotinine levels were determined as 1534 ng/mg creatinine (317-2478) and 2082 ng/mg creatinine (1727-3632), whereas salivary nicotine and cotinine levels were 145 ng/ml (26-265) and 329 ng/ml (198-440), respectively. One-way repeated measures Anova demonstrated a significant decrease in urinary nicotine and cotinine concentration from baseline at 3 post-transition visits. A significant reduction was also observed in salivary nicotine levels on days 3 and 21 after EC transition and in salivary cotinine levels at each post-transition visit compared to baseline. Both urge and strength of urges to smoke were significantly decreased by 28days compared to baseline. Conclusions These findings offer support that EC can be effective in reducing nicotine consumption and cravings for cigarettes, suggesting the potential use of EC as a smoking cessation tool. However, the inability to achieve levels of nicotine comparable to smokers may contribute to relapse. Funding Statement Funded by European Commission Horizon 2020 programme.