Estimating the health impact of nicotine exposure by dissecting the effects of nicotine versus non-nicotine constituents of tobacco smoke: A multivariable Mendelian randomisation study

Disentangling the effects of nicotine versus non-nicotine constituents of tobacco smoke on major depressive disorder: A multivariable Mendelian randomisation study

BACKGROUND AND AIMS

There is growing evidence that tobacco smoking causes depression, but it is unclear which constituents of tobacco smoke (e.g. nicotine, carbon monoxide) may be responsible. We used Mendelian randomisation (MR) to measure the independent effect of nicotine on depression, by adjusting the effect of circulating nicotine exposure [via nicotine metabolite ratio (NMR)] for the overall effect of smoking heaviness [via cigarettes per day (CPD)] to account for the non-nicotine constituents of tobacco smoke.

DESIGN

Univariable MR and multivariable MR (MVMR) were used to measure the total and independent effects of genetic liability to NMR and CPD on major depressive disorder (MDD). Our primary method was inverse variance weighted (IVW) regression, with other methods as sensitivity analyses.

SETTING AND PARTICIPANTS

For the exposures, we used genome-wide association study (GWAS) summary statistics among European ancestry individuals for CPD (n = 143 210) and NMR (n = 5185). For the outcome, a GWAS of MDD stratified by smoking status was conducted using individual-level data from UK Biobank (n = 35 871-194 881).

MEASUREMENTS

Genetic variants associated with NMR (n = 6) and CPD (n = 53).

FINDINGS

Univariable MR-IVW indicated a causal effect of CPD on MDD [odds ratio (OR) = 1.13, 95% confidence interval (CI) = 1.04-1.23, P = 0.003] but no clear evidence for an effect of NMR on MDD (OR = 0.98, 95% CI = 0.97-1.00, P = 0.134). MVMR indicated a causal effect of CPD on MDD when accounting for NMR (IVW: OR = 1.19, 95% CI = 1.03-1.37, P = 0.017; Egger: OR = 1.13, 95% CI = 0.89-1.43, P = 0.300) and weak evidence of a small effect of NMR on MDD when accounting for CPD (IVW: OR = 0.98, 95% CI = 0.96-1.00, P = 0.057; Egger: OR = 0.98, 95% CI = 0.96-1.00, P = 0.038).

CONCLUSIONS

The role of nicotine exposure in risk of depression cannot be entirely dismissed. However, the causal effect of tobacco smoking increasing depression risk appears to be largely independent of circulating nicotine exposure, which implies the role of alternative causal pathways.

New-generation nicotine delivery products require new approaches to research

Toxicological and epidemiological studies suggest that new-generation nicotine delivery products will reduce the harmful exposures associated with combustible cigarettes and toxic forms of smokeless tobacco products. However, enhanced study designs are needed to support epidemiological research that was more appropriate when the ways of consuming nicotine were limited and methods to assess causality in less than decades were unavailable. Given their different perspectives and scientific capabilities, progress in THR requires deeper and transparent engagement between industry scientists and those in academia that rigorously applies conflicts of interest norms.

Evaluating the impact of smoking on the risk of dry eye disease: a two-sample Mendelian randomization study

Dry Eye Disease (DED) is a common condition worldwide, with smoking being recognized as a possible aggravating factor. Although observational studies have indicated a potential correlation, the findings have been inconclusive. In the study, Mendelian randomization (MR) analysis is used to investigate this potential causal relationship. Adhering to STROBE-MR guidelines, a MR analysis was conducted using genetic instrumental variables from Genome-wide association studies (GWAS). The research investigated the impact of various smoking-related exposures (regular smoking, lifetime smoking, smoking intensity, and smoking cessation) on DED as an outcome. Three distinct methodologies were employed: the inverse variance weighted (IVW) method, the MR-Egger method, and the weighted median (WM) method. To ensure the robustness of the MR results, sensitivity analyses were conducted. In MR analyses, it was observed that both lifetime smoking and regular smoking were associated with a significant increase in the risk of DED (IVW method: P < 0.05). The results indicated that the odds ratios (ORs) for lifetime smoking and regular smoking in relation to DED were 1.757 (95% CI 1.021-3.025) and 2.121 (95% CI 1.017-4.423), respectively. However, there was no significant correlation found between smoking intensity, cessation, and the risk of DED. This study presents genetic evidence indicating that long-term smoking could potentially be a causal risk factor for DED. Subsequent research will need to conduct specifically designed randomized controlled trials to further investigate this association.

Online quantification of nicotine in e-cigarette aerosols by vacuum ultraviolet photoionization mass spectrometry

The growing popularity of e-cigarettes and the associated risks of nicotine addiction present a new challenge to global public health security. Measuring the nicotine levels in e-cigarette aerosols is essential to assess the safety of e-cigarettes. In this study, a rapid in situ method was developed for online quantification of nicotine in e-cigarette aerosols by using a homemade vacuum ultraviolet photoionization aerosol mass spectrometer (VUV-AMS). E-cigarette liquids with different nicotine concentrations were prepared to generate aerosols containing different levels of nicotine, which were employed as the calibration sources for nicotine quantification by VUV-AMS. The results showed that the mass concentration of nicotine in e-cigarette aerosols has a good linear relationship with its signal intensity in the mass spectrum, and the limits of detection and quantitation of nicotine by VUV-AMS were found to be 2.0 and 6.2 μg per puff respectively. Then the online method was utilized to measure five commercial e-cigarettes, and their nicotine yields were determined to be between 31 and 188 μg per puff with the nicotine fluxes from 7.7 to 70 μg s-1, agreeing with the results of the gas chromatography with a flame ionization detector (GC-FID). This study demonstrated the feasibility and advantages of VUV-AMS for quick quantification of nicotine in e-cigarette aerosols within seconds.