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...

Descripción completa

Detalles Bibliográficos
Publicado en:Addiction Vol. 118; no. 4; pp. 739 - 750
Autores principales: 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
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell Apr2023
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