ArticleAddiction (Abingdon, England)2023
Evaluating the causal effect of tobacco smoking on white matter brain aging: a two-sample Mendelian randomization analysis in UK Biobank.
Article in Addiction (Abingdon, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 27 citations in OpenAlex.
- Lifestyle risk factors of white matter brain aging: Evidence, potential mechanisms, and future direction.Neural regeneration research · 2026Article
- Bidirectional genetic and phenotypic links between smoking and striatal iron content involving dopaminergic and inflammatory pathways.Addiction (Abingdon, England) · 2026Article
- Deep learning-based brain age predicts stroke recurrence in acute ischemic cerebrovascular disease.NPJ digital medicine · 2025Article
- Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2025Article
- Association between allostatic load and accelerated white matter brain aging: findings from the UK Biobank.American journal of epidemiology · 2025Article
- Smoking can increase the risk of osteoarthritis in European women.Scientific reports · 2025Article
- Neural Networks and Chemical Messengers: Insights into Tobacco Addiction.Brain topography · 2025Article
- Article
- Cross-Sectional Brain Age Assessments Are Limited in Predicting Future Brain Change.Human brain mapping · 2025Article
- Anterior and posterior cerebral white matter show different patterns of microstructural alterations in young adult smokers.Brain imaging and behavior · 2025Article
- Article
- Alcohol, smoking, and brain structure: common or substance specific associations.medRxiv : the preprint server for health sciences · 2024Article
- TIPS: a novel pathway-guided joint model for transcriptome-wide association studies.Briefings in bioinformatics · 2024Article
- Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.Neurology · 2024Article
- Association between allostatic load and accelerated white matter brain aging: findings from the UK Biobank.medRxiv : the preprint server for health sciences · 2024Article
- Causal relationships involving brain imaging-derived phenotypes based on UKB imaging cohort: a review of Mendelian randomization studies.Frontiers in neuroscience · 2024Review
- An in-depth association analysis of genetic variants within nicotine-related loci: Meeting in middle of GWAS and genetic fine-mapping.Molecular and cellular neurosciences · 2023Article
- Comparison of Machine Learning Models for Brain Age Prediction Using Six Imaging Modalities on Middle-Aged and Older Adults.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
Abstract
BACKGROUND AND
aimsTobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging.
designMendelian randomization (MR) analysis using two non-overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis.
settingUnited Kingdom.
participantsThe study cohort included 23 624 subjects [10 665 males and 12 959 females with a mean age of 54.18 years, 95% confidence interval (CI) = 54.08, 54.28]. MEASUREMENTS: Genetic variants were selected as instrumental variables under the MR analysis assumptions: (1) associated with the exposure; (2) influenced outcome only via exposure; and (3) not associated with confounders. The exposure smoking status (current versus never smokers) was measured by questionnaires at the initial visit (2006-10). The other exposure, cigarettes per day (CPD), measured the average number of cigarettes smoked per day for current tobacco users over the life-time. The outcome was the 'brain age gap' (BAG), the difference between predicted brain age and chronological age, computed by training machine learning model on a non-overlapping set of never smokers.
findingsThe estimated BAG had a mean of 0.10 (95% CI = 0.06, 0.14) years. The MR analysis showed evidence of positive causal effect of smoking behaviors on BAG: the effect of smoking is 0.21 (in years, 95% CI = 6.5 × 10
conclusionsThere appears to be a significant causal effect of smoking on the brain age gap, which suggests that smoking prevention can be an effective intervention for accelerated brain aging and the age-related decline in cognitive function.
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