Evaluating the causal effect of tobacco smoking on white matter brain aging: a two‐sample Mendelian randomization analysis in UK Biobank.
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. Design: Mendelian randomization (MR) analysis using two...
| Publicado en: | Addiction Vol. 118; no. 4; pp. 739 - 750 |
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| Autores principales: | , , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Apr2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162203275&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162203275 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Apr2023 vid: 118 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 162203275 160642876 162203275 162203275 10.1111/add.16088 162203275 ppf: 739 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Evaluating the causal effect of tobacco smoking on white matter brain aging: a two‐sample Mendelian randomization analysis in UK Biobank. aug: au: Mo, Chen Wang, Jingtao Ye, Zhenyao Ke, Hongjie Liu, Song Hatch, Kathryn Gao, Si Magidson, Jessica Chen, Chixiang Mitchell, Braxton D. Kochunov, Peter Hong, L. Elliot Ma, Tianzhou Chen, Shuo affil: Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore MD,, USA sug: subj: Smoking Complications White Matter Radiography Brain Physiopathology Aging Human Male Female Adult Middle Age Aged Epidemiology, Molecular Tissue Banks United Kingdom United Kingdom Non-Smokers Linear Regression Sensitivity and Specificity Prospective Studies Descriptive Statistics Comparative Studies Confidence Intervals Genetic Variation Questionnaires Tobacco Products Smoking Cessation Neuroradiography Methods Genetic Profile Funding Source Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: 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. 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. Setting: United Kingdom. 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]. 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. 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. 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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