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CONFERENCE PROCEEDING
Monitoring the transition from cigarette smoking to vaping using exposure, biochemical, brain dynamics and psychometric markers: The SmokeFreeBrain Study
1
Public Health England, UK
2
St George’s University of London, UK
3
Aristotle University of Thessaloniki, Greece
4
AAI Scientific Cultural Services Ltd., Nicosia, Cyprus
Publication date: 2018-06-13
Tob. Prev. Cessation 2018;4(Supplement):A83
KEYWORDS
ABSTRACT
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.
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.
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| eISSN: | 2459-3087 |
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