Dataset Information

Polygenic score for cigarette smoking is associated with ever electronic-cigarette use in a college-aged sample.

ABSTRACT:

Background and aims

Electronic cigarette use has escalated rapidly in recent years, particularly among youth. Little is known about the genetic influences on e-cigarette use. This study aimed to determine whether genetic risk for regular use of combustible cigarettes or for number of cigarettes smoked per day confers risk for ever e-cigarette use or frequency of e-cigarette use.

Design, setting, participants, and measurements

We used data from 9541 young adults from the Spit for Science longitudinal cohort study (2011-2019). Polygenic scores (PGS) of regular combustible cigarette use (PGS-RCU) and cigarettes per day (PGS-CPD) were constructed using summary statistics from the two largest available genome-wide association study (GWAS) meta-analysis of European ancestry and East Asian ancestry of combustible cigarette use and used to test whether the PGS of RCU or CPD predicted lifetime e-cigarette use and frequency of past 30-day e-cigarette use in a diverse sample of young adults of African (AFR), Admixed American (AMR), East Asian (EAS), European (EUR), and South Asian (SAS) ancestry.

Findings

The PGS-RCU was associated with lifetime e-cigarette use in the EUR sample (OR = 1.27, 95% CI = 1.19-1.36, P = 7.53 × 10^-12 ), but not in the other subsamples (ps > 0.12). This association remained significant after excluding regular combustible cigarette smokers (OR = 1.21, 95% CI = 1.12-1.31, P = 3.36 × 10^-6 ). There was no statistically significant association between PGS-CPD and lifetime e-cigarette use and neither the PGS-RCU nor the PGS-CPD were associated with frequency of e-cigarette use in the past 30 days in any of the subsamples.

Conclusions

Genetic factors associated with regular combustible cigarette use appear to be associated with ever e-cigarette use in young adults. We did not find evidence for shared genetic factors influencing heaviness of use of combustible cigarettes and current e-cigarette use frequency.

SUBMITTER: Cooke ME

PROVIDER: S-EPMC9875558 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Polygenic score for cigarette smoking is associated with ever electronic-cigarette use in a college-aged sample.

Cooke Megan E ME Clifford James S JS Do Elizabeth K EK Gilman Jodi M JM Maes Hermine H HH Peterson Roseann E RE Prom-Wormley Elizabeth C EC Evins A Eden AE Schuster Randi M RM

Addiction (Abingdon, England) 20211103 4

<h4>Background and aims</h4>Electronic cigarette use has escalated rapidly in recent years, particularly among youth. Little is known about the genetic influences on e-cigarette use. This study aimed to determine whether genetic risk for regular use of combustible cigarettes or for number of cigarettes smoked per day confers risk for ever e-cigarette use or frequency of e-cigarette use.<h4>Design, setting, participants, and measurements</h4>We used data from 9541 young adults from the Spit for S ...[more]

PMID: 34636095

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Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.

Project description:ImportanceThe risk of airflow limitation and chronic obstructive pulmonary disease (COPD) is influenced by combinations of cigarette smoking and genetic susceptibility, yet it remains unclear whether gene-by-smoking interactions are associated with quantitative measures of lung function.ObjectiveTo assess the interaction of cigarette smoking and polygenic risk score in association with reduced lung function.Design, setting, and participantsThis UK Biobank cohort study included UK citizens of European ancestry aged 40 to 69 years with genetic and spirometry data passing quality control metrics. Data was analyzed from July 2020 to March 2021.ExposuresPRS of combined forced expiratory volume in 1 second (FEV1) and percent of forced vital capacity exhaled in the first second (FEV1/FVC), self-reported pack-years of smoking, ever- vs never-smoking status, and current- vs former- or never-smoking status.Main outcomes and measuresFEV1/FVC was the primary outcome. Models were used to test for interactions with models, including the main effects of PRS, different smoking variables, and their cross-product terms. The association between pack-years of smoking and FEV1/FVC were compared for those in the highest vs lowest decile of estimated genetic risk for low lung function.ResultsWe included 319 730 individuals, of whom 24 915 (8%) had moderate-to-severe COPD cases, and 44.4% were men. Participants had a mean (SD) age 56.5 of (8.02) years. The PRS and pack-years were significantly associated with lower FEV1/FVC (PRS: β, -0.03; 95% CI, -0.031 to -0.03; pack-years: β, -0.0064; 95% CI, -0.0064 to -0.0063) and the interaction term (β, -0.0028; 95% CI, -0.0029 to -0.0026). A stepwise increment in estimated effect sizes for these interaction terms was observed per 10 pack-years of smoking exposure. The interaction of PRS with 11 to 20, 31 to 40, and more than 50 pack-years categories were β (interaction) -0.0038 (95% CI, -0.0046 to -0.0031); -0.013 (95% CI, -0.014 to -0.012); and -0.017 (95% CI, -0.019 to -0.016), respectively. There was evidence of significant interaction between PRS with ever- or never- smoking status (β, interaction; -0.0064; 95% CI, -0.0068 to -0.0060) and current or not-current smoking (β, interaction; -0.0091; 95% CI, -0.0097 to -0.0084). For any given level of pack-years of smoking exposure, FEV1/FVC was significantly lower for individuals in the tenth decile (ie, highest risk) than the first decile (ie, lowest risk) of genetic risk. For every 20 pack-years of smoking, those in the tenth decile compared with the first decile of genetic risk showed nearly a 2-fold reduction in FEV1/FVC.Conclusions and relevanceCOPD is characterized by diminished lung function, and our analyses suggest there is substantial interaction between genome-wide PRS and smoking exposures. While smoking was associated with decreased lung function across all genetic risk categories, the associations were strongest in individuals with higher estimated genetic risk.

Project description:ImportanceMany studies have reported a positive association of youth electronic cigarette (e-cigarette) use with subsequent cigarette smoking initiation, but it remains unclear whether e-cigarette use is associated with continued cigarette smoking after initiation.ObjectiveTo assess the association of youth baseline e-cigarette use with their continued cigarette smoking 2 years after initiation.Design, setting, and participantsThe Population Assessment of Tobacco and Health (PATH) Study is a national longitudinal cohort study. This sample consisted of youth who participated in waves 3, 4, and 5 of the study (wave 3 was from October 2015 to October 2016, wave 4 was from December 2016 to January 2018, and wave 5 was from December 2018 to November 2019) and had never used cigarettes (cigarette-naive) by wave 3. The current analysis used multivariable logistic regressions in August 2022 to assess the association between e-cigarette use among cigarette-naive adolescents aged 12 to 17 years in 2015 and 2016 and subsequent continued cigarette smoking. PATH uses audio computer-assisted self-interviewing and computer-assisted personal interviewing to collect data.ExposuresEver and current (past 30-day) use of e-cigarettes in wave 3.Main outcomes and measuresContinued cigarette smoking in wave 5 after initiating smoking in wave 4.ResultsThe current sample included 8671 adolescents who were cigarette naive in wave 3 and also participated in waves 4 and 5; 4823 of the participants (55.4%) were aged 12 to 14 years, 4454 (51.1%) were male, and 3763 (51.0%) were non-Hispanic White. Overall, regardless of e-cigarette use, few adolescents (362 adolescents [4.1%]) initiated cigarette smoking at wave 4, and even fewer (218 participants [2.5%]) continued smoking at wave 5. Controlling for multiple covariates, the adjusted odds ratio of baseline ever e-cigarette use, compared with never e-cigarette use, was 1.81 (95% CI, 1.03 to 3.18) for continued smoking measured as past 30-day smoking at wave 5. However, the adjusted risk difference (aRD) was small and not significant. The aRD was 0.88 percentage point (95% CI, -0.13 to 1.89 percentage points) for continued smoking, with the absolute risk being 1.19% (95% CI, 0.79% to 1.59%) for never e-cigarette users and 2.07% (95% CI, 1.01% to 3.13%) for ever e-cigarette users. Similar results were found using an alternative measure of continued smoking (lifetime ≥100 cigarettes and current smoking at wave 5) and using baseline current e-cigarette use as the exposure measure.Conclusions and relevanceIn this cohort study, absolute and relative measures of risks yielded findings suggesting very different interpretations of the association. Although there were statistically significant odds ratios of continued smoking comparing baseline e-cigarette users with nonusers, the minor risk differences between them, along with the small absolute risks, suggest that few adolescents are likely to continue smoking after initiation regardless of baseline e-cigarette use.

Project description:ImportanceThe electronic cigarette (EC) has become popular among smokers who wish to reduce their tobacco use levels or quit smoking, but its effectiveness as a cessation aid is uncertain.ObjectiveTo examine the association of regular EC use with the number of cigarettes smoked per day, smoking cessation among current smokers, and smoking relapse among former smokers.Design, setting, and participantsThe CONSTANCES (Consultants des Centres d'Examens de Santé) cohort study, based in France, began recruiting participants January 6, 2012, and is currently ongoing. Participants were enrolled in CONSTANCES through 2015, and included 5400 smokers (mean [SD] follow-up of 23.4 [9.3] months) and 2025 former smokers (mean [SD] follow-up of 22.1 [8.6] months) at baseline who quit smoking in 2010, the year in which ECs were introduced in France, or afterward. Analyses were performed from February 8, 2017, to October 15, 2018.Main outcomes and measuresThe association between EC use and the number of cigarettes smoked during follow-up was studied using mixed regression models. The likelihood of smoking cessation was studied using Poisson regression models with robust sandwich variance estimators. The association between EC use and smoking relapse among former smokers was studied using Cox proportional hazards regression models. All statistical analyses were adjusted for sociodemographic characteristics, duration of follow-up, and smoking characteristics.ResultsAmong the 5400 daily smokers (2906 women and 2494 men; mean [SD] age, 44.9 [12.4] years), regular EC use was associated with a significantly higher decrease in the number of cigarettes smoked per day compared with daily smokers who did not use ECs (-4.4 [95% CI, -4.8 to -3.9] vs -2.7 [95% CI, -3.1 to -2.4]), as well as a higher adjusted relative risk of smoking cessation (1.67; 95% CI, 1.51-1.84]). At the same time, among the 2025 former smokers (1004 women and 1021 men; mean [SD] age, 43.6 [12.1] years), EC use was associated with an increase in the rate of smoking relapse among former smokers (adjusted hazard ratio, 1.70; 95% CI, 1.25-2.30).Conclusions and relevanceThis study's findings suggest that, among adult smokers, EC use appears to be associated with a decrease in smoking level and an increase in smoking cessation attempts but also with an increase in the level of smoking relapse in the general population after approximately 2 years of follow-up.

Project description:The microbiome has increasingly been linked to cancer. Little is known about the lung and oral cavity microbiomes in smokers, and even less for electronic cigarette (EC) users, compared with never-smokers. In a cross-sectional study (n = 28) of smokers, EC users, and never-smokers, bronchoalveolar lavage and saliva samples underwent metatranscriptome profiling to examine associations with lung and oral microbiomes. Pairwise comparisons assessed differentially abundant bacteria species. Total bacterial load was similar between groups, with no differences in bacterial diversity across lung microbiomes. In lungs, 44 bacteria species differed significantly (FDR < 0.1) between smokers/never-smokers, with most decreased in smokers. Twelve species differed between smokers/EC users, all decreased in smokers of which Neisseria sp. KEM232 and Curvibacter sp. AEP1-3 were observed. Among the top five decreased species in both comparisons, Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae were observed. In the oral microbiome, 152 species were differentially abundant for smokers/never-smokers, and 17 between smokers/electronic cigarette users, but only 21 species were differentially abundant in both the lung and oral cavity. EC use is not associated with changes in the lung microbiome compared with never-smokers, indicating EC toxicity does not affect microbiota. Statistically different bacteria in smokers compared with EC users and never-smokers were almost all decreased, potentially due to toxic effects of cigarette smoke. The low numbers of overlapping oral and lung microbes suggest that the oral microbiome is not a surrogate for analyzing smoking-related effects in the lung.Prevention relevanceThe microbiome affects cancer and other disease risk. The effects of e-cig usage on the lung microbiome are essentially unknown. Given the importance of lung microbiome dysbiosis populated by oral species which have been observed to drive lung cancer progression, it is important to study effects of e-cig use on microbiome.

Dataset Information

Polygenic score for cigarette smoking is associated with ever electronic-cigarette use in a college-aged sample.

Background and aims

Design, setting, participants, and measurements

Findings

Conclusions

Publications

Polygenic score for cigarette smoking is associated with ever electronic-cigarette use in a college-aged sample.

Similar Datasets

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