Associations of cigarette smoking with gray and white matter in the UK Biobank

Gray, Joshua C.; Thompson, Matthew; Benca-Bachman, Chelsie E.; Murphy, Mikela; Palmer, Rohan

doi:10.31234/osf.io/wyvnm

Cited by 9 publications

(13 citation statements)

References 31 publications

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“…At the brain level, grip strength revealed mostly significant positive correlations with brain volume, which aligns with previous evidence at the global level [23]. As the global GMV is a general reflection of health status and GM atrophy is a signature of neurodegeneration [27,28], the identified association pattern may suggest that having stronger muscular strength also relates to better overall brain health [22]. Furthermore, given that many regional GM associations reach a significant effect after controlling for the total ICV, it implies that grip strength may exert a region-specific beneficial effect on brain structure.…”

Section: Discussionsupporting

confidence: 89%

“…These findings increased current understanding on the use of grip strength not only as a proxy of physical fitness but also as a malleable indicator for health status in detecting early impairment of specific domains. Unsurprisingly, some of the associations were small and likely due in part to the fact that we controlled for numerous demographic, socioeconomic, and anthropometric measures that are expected to co-occur with health status [50,51] and muscular strength [27]. Consequently, the association effects should be interpreted as the relevance of grip strength to these mental health outcomes beyond the contribution of covariates [28].…”

Section: Discussionmentioning

confidence: 96%

“…As per previous UK Biobank studies [8,27,28], we excluded participants who reported any of the listed severe neurological conditions/incidents (Additional file 1: Table S1). Additional exclusion criteria included missing MRI or relevant behavioral/demographic data.…”

Section: Cohort and Participantsmentioning

confidence: 99%

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Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

Jiang

Westwater

Noble

et al. 2022

BMC Med

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Background Grip strength is a widely used and well-validated measure of overall health that is increasingly understood to index risk for psychiatric illness and neurodegeneration in older adults. However, existing work has not examined how grip strength relates to a comprehensive set of mental health outcomes, which can detect early signs of cognitive decline. Furthermore, whether brain structure mediates associations between grip strength and cognition remains unknown. Methods Based on cross-sectional and longitudinal data from over 40,000 participants in the UK Biobank, this study investigated the behavioral and neural correlates of handgrip strength using a linear mixed effect model and mediation analysis. Results In cross-sectional analysis, we found that greater grip strength was associated with better cognitive functioning, higher life satisfaction, greater subjective well-being, and reduced depression and anxiety symptoms while controlling for numerous demographic, anthropometric, and socioeconomic confounders. Further, grip strength of females showed stronger associations with most behavioral outcomes than males. In longitudinal analysis, baseline grip strength was related to cognitive performance at ~9 years follow-up, while the reverse effect was much weaker. Further, baseline neuroticism, health, and financial satisfaction were longitudinally associated with subsequent grip strength. The results revealed widespread associations between stronger grip strength and increased grey matter volume, especially in subcortical regions and temporal cortices. Moreover, grey matter volume of these regions also correlated with better mental health and considerably mediated their relationship with grip strength. Conclusions Overall, using the largest population-scale neuroimaging dataset currently available, our findings provide the most well-powered characterization of interplay between grip strength, mental health, and brain structure, which may facilitate the discovery of possible interventions to mitigate cognitive decline during aging.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 96%

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Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

Jiang

Westwater

Noble

et al. 2022

BMC Med

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“…Moreover, smoking duration linked with reduced total volume of white matter. It is also associated with reduction in fractional anisotropy in cingulate gyrus 64 . Lamb/mutton intake was also positively associated with brain-PAD in some tract groups.…”

Section: Discussionmentioning

confidence: 96%

Brain Age Estimation at Tract Group Level and its Association with Daily Life Measures, Cardiac Risk Factors and Genetic Variants

Salih

Galazzo

Raisi‐Estabragh

et al. 2021

Preprint

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Brain age can be estimated using different MRI modalities including diffusion MRI. Recent studies demonstrated that white matter (WM) tracts that share the same function might experience similar alterations. Therefore, in this work, we sought to investigate such issue focusing on five WM bundles holding that feature that is Association, Brainstem, Commissural, Limbic and Projection fibers, respectively. For each tract group, we estimated brain age for 15335 healthy participants from United Kingdom Biobank relying on diffusion MRI image derived endophenotypes, Bayesian ridge regression modeling and 10 fold-cross validation. Furthermore, we estimated brain age for an ensemble model that gathers all the considered white matter bundles. Association analysis was subsequently performed between the estimated brain age delta as resulting from the six models, that is for each tract group as well as for the ensemble model, and 38 daily life style measures, 14 cardiac risk factors and cardiovascular magnetic resonance imaging features and genetic variants. Our study revealed that the limbic tracts experience less brain aging compared to other tract groups, Brainstem tracts ages relatively faster while the other tract groups present similar brain aging patterns. The model achieved 5.86 mean absolute error (MAE) for brainstem, 5.08 for limbic tracts and around 5.2 for the other three tract groups while, the ensemble model 4.55. Moreover, the results suggest that limbic tracts are more affected by daily lifestyle factors than the other tract groups. Lastly, two SNPs were significantly (p-value < 5E-8) associated with brain age delta in projection fibers. Those SNPs are mapped to HIST1H1A and SLC17A3 genes.

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“…Neuroimaging studies of cigarette smoking and brain regions of interest (ROIs) consistently show that higher levels of cigarette smoking are related to thinner cortex and smaller subcortical volumes [4][5][6][7][8][9]. A UK Biobank study comprising approximately 20 000 participants reported smaller total gray matter volume in long-term smokers [10]. Smokers seeking treatment for tobacco use have shown smaller cerebellar volumes relative to nonsmokers [11].…”

Section: Introductionmentioning

confidence: 99%

Long‐term associations of cigarette smoking in early mid‐life with predicted brain aging from mid‐ to late life

et al. 2021

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Background and aims Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid‐life would have older than predicted brain age 16–28 years later. Design Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid‐life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid‐life) and 68 years (early old age). Early mid‐life alcohol use was also evaluated. Setting Population‐based United States sample. Participants/cases Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves. Measurements Self‐reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain‐Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age—predicted brain age) acquired at average ages 56 (n = 493; 2002–08), 62 (n = 408; 2009–14) and 68 (n = 499; 2016–19). Findings In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = −0.144, P = 0.012, 95% confidence interval (CI) = –0.257, −0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = −0.166, P = 0.001, 95% CI = –0.261, –0.070) with additional influences at age 62 (β = −0.115, P = 0.005, 95% CI = –0.195, –0.036). Age 40 alcohol did not predict age 68 PBAD. Within‐twin‐pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD. Conclusions Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.

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Associations of cigarette smoking with gray and white matter in the UK Biobank

Cited by 9 publications

References 31 publications

Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

Brain Age Estimation at Tract Group Level and its Association with Daily Life Measures, Cardiac Risk Factors and Genetic Variants

Long‐term associations of cigarette smoking in early mid‐life with predicted brain aging from mid‐ to late life

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