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

Jasmine N. Khouja, Eleanor Sanderson, Robyn E. Wootton, Amy E. Taylor, Billy A. Church, Rebecca C. Richmond, Marcus R. Munafò

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8 Citations (SciVal)

Abstract

The detrimental health effects of smoking are well-known, but the impact of regular nicotine use without exposure to the other constituents of tobacco is less clear. Given the increasing daily use of alternative nicotine delivery systems, such as e-cigarettes, it is increasingly important to understand and separate the effects of nicotine use from the impact of tobacco smoke exposure. Using a multivariable Mendelian randomisation framework, we explored the direct effects of nicotine compared with the non-nicotine constituents of tobacco smoke on health outcomes (lung cancer, chronic obstructive pulmonary disease [COPD], forced expiratory volume in one second [FEV-1], forced vital capacity [FVC], coronary heart disease [CHD], and heart rate [HR]). We used Genome-Wide Association Study (GWAS) summary statistics from Buchwald and colleagues, the GWAS and Sequencing Consortium of Alcohol and Nicotine, the International Lung Cancer Consortium, and UK Biobank. Increased nicotine metabolism increased the risk of COPD, lung cancer, and lung function in the univariable analysis. However, when accounting for smoking heaviness in the multivariable analysis, we found that increased nicotine metabolite ratio (indicative of decreased nicotine exposure per cigarette smoked) decreases heart rate (b =-0.30, 95% CI-0.50 to-0.10) and lung function (b =-33.33, 95% CI-41.76 to-24.90). There was no clear evidence of an effect on the remaining outcomes. The results suggest that these smoking-related outcomes are not due to nicotine exposure but are caused by the other components of tobacco smoke; however, there are multiple potential sources of bias, and the results should be triangulated using evidence from a range of methodologies.

Original languageEnglish
Article numbere1011157
JournalPlos Genetics
Volume20
Issue number2
Early online date9 Feb 2024
DOIs
Publication statusPublished - 9 Feb 2024

Data Availability Statement

Data required to replicate all study findings reported in the article are provided on Github at https://doi.org/10.5281/zenodo.10469666. Additionally, all numerical data for plots included in the manuscript can be found in the supplementary materials. All summary statistics can be found in the supplementary material.

Funding

This work is supported by the Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol (MC_UU_00032/01, MC_UU_00032/04, MC_UU_00032/07). The salary of REW is funded by the Norwegian South-Eastern Regional Health Authority (2020024). This work was supported by Cancer Research UK (grant number C18281/A29019) who fund the salary of JNK and RCR. The salary of AET is funded by the European Research Council Advanced Grant (ART-Health; Grant ERC number 101021566). This work is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

FundersFunder number
Medical Research Council

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

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