| Title: | Evaluating the causal effect of tobacco smoking on white matter brain aging: a two-sample Mendelian randomization analysis in UK Biobank |
| Journal: | Addiction |
| Published: | 7 Dec 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36401354/ |
| DOI: | https://doi.org/10.1111/add.16088 |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443605 |
| Citations: | 9 (9 in last 2 years) as of 8 Aug 2024 |
Publication 10789
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Abstract
BACKGROUND AND AIMS: Tobacco 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.</p>
DESIGN: Mendelian 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.</p>
SETTING: United Kingdom.</p>
PARTICIPANTS: The 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].</p>
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.</p>
FINDINGS: The 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 × 10-3 , 0.41; P-value = 0.04), and the effect of CPD is 0.16 year/cigarette (UKB: 95% CI = 0.06, 0.26; P-value = 1.3 × 10-3 ; GSCAN: 95% CI = 0.02, 0.31; P-value = 0.03). The sensitivity analyses showed consistent results.</p>
CONCLUSIONS: There 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.</p>
11 Keywords
- Aging
- Biological Specimen Banks
- Female
- Humans
- Male
- Mendelian Randomization Analysis
- Middle Aged
- Smoking
- Tobacco Smoking
- United Kingdom
- White Matter
14 Authors
- Chen Mo
- Jingtao Wang
- Zhenyao Ye
- Hongjie Ke
- Song Liu
- Kathryn Hatch
- Si Gao
- Jessica Magidson
- Chixiang Chen
- Braxton D. Mitchell
- Peter Kochunov
- L. Elliot Hong
- Tianzhou Ma
- Shuo Chen
Enabling scientific discoveries that improve human health