Smoking is associated with lower brain volume and cognitive differences: A large population analysis based on the UK Biobank

Discovery of High-Risk Clinical Factors That Accelerate Brain Aging in Adults: A Population-Based Machine Learning Study

Introduction: Brain age prediction using neuroimaging data and machine learning algorithms holds significant promise for gaining insights into the development of neurodegenerative diseases. The estimation of brain age may be influenced not only by the imaging modality but also by multidomain clinical factors. However, the degree to which various clinical factors in individuals are associated with brain structure, as well as the comprehensive relationship between these factors and brain aging, is not yet clear. Methods: In this study, multimodal brain magnetic resonance imaging data and longitudinal clinical information were collected from 964 participants in a population-based cohort with 16 years of follow-up in northern China. We developed a machine learning-based algorithm to predict multimodal brain age and compared the estimated brain age gap (BAG) differences among the 5 groups characterized by varying exposures to these high-risk clinical factors. We then estimated modality-specific brain age in the hypertension group based on hypertension-related regional imaging metrics. Results: The results revealed a significantly larger BAG estimated from multimodal neuroimaging in subjects with 4 or 5 risk factors compared to other groups, suggesting an acceleration of brain aging under cumulative exposure to multiple risk factors. The estimated T1-based BAG exhibited a significantly higher level in the hypertensive subjects compared to the normotensive individuals. Conclusion: Our study provides valuable insights into a range of health factors across lifestyle, metabolism, and social context that are reflective of brain aging and also contributes to the advancement of interventions and public health initiatives targeted at the general population aimed at promoting brain health.

Nongenetic and Genetic Factors Associated with White Matter Brain Aging: Exposome-Wide and Genome-Wide Association Study

BACKGROUND/OBJECTIVES

Human brain aging is a complex process that affects various aspects of brain function and structure, increasing susceptibility to neurological and psychiatric disorders. A number of nongenetic (e.g., environmental and lifestyle) and genetic risk factors are found to contribute to the varying rates at which the brain ages among individuals.

METHODS

In this paper, we conducted both an exposome-wide association study (XWAS) and a genome-wide association study (GWAS) on white matter brain aging in the UK Biobank, revealing the multifactorial nature of brain aging. We applied a machine learning algorithm and leveraged fractional anisotropy tract measurements from diffusion tensor imaging data to predict the white matter brain age gap (BAG) and treated it as the marker of brain aging. For XWAS, we included 107 variables encompassing five major categories of modifiable exposures that potentially impact brain aging and performed both univariate and multivariate analysis to select the final set of nongenetic risk factors.

RESULTS

We found current tobacco smoking, dietary habits including oily fish, beef, lamb, cereal, and coffee intake, length of mobile phone use, use of UV protection, and frequency of solarium/sunlamp use were associated with the BAG. In genetic analysis, we identified several SNPs on chromosome 3 mapped to genes IP6K1, GMNC, OSTN, and SLC25A20 significantly associated with the BAG, showing the high heritability and polygenic architecture of human brain aging.

CONCLUSIONS

The critical nongenetic and genetic risk factors identified in our study provide insights into the causal relationship between white matter brain aging and neurodegenerative diseases.

The Association Between Chronic Tobacco Smoking and Brain Alterations in Schizophrenia: A Systematic Review of Magnetic Resonance Imaging Studies

BACKGROUND AND HYPOTHESIS

The high co-occurrence of tobacco smoking in patients with schizophrenia spectrum disorders (SSD) poses a serious health concern, linked to increased mortality and worse clinical outcomes. The mechanisms underlying this co-occurrence are not fully understood.

STUDY DESIGN

Addressing the need for a comprehensive overview of the impact of tobacco use on SSD neurobiology, we conducted a systematic review of neuroimaging studies (including structural, functional, and neurochemical magnetic resonance imaging studies) that investigate the association between chronic tobacco smoking and brain alterations in patients with SSD.

STUDY RESULTS

Eight structural and fourteen functional studies were included. Structural studies show widespread independent and additive reductions in gray matter in relation to smoking and SSD. The majority of functional studies suggest that smoking might be associated with improvements in connectivity deficits linked to SSD. However, the limited number of and high amount of cross-sectional studies, and high between-studies sample overlap prevent a conclusive determination of the nature and extent of the impact of smoking on brain functioning in patients with SSD. Overall, functional results imply a distinct neurobiological mechanism for tobacco addiction in patients with SSD, possibly attributed to differences at the nicotinic acetylcholine receptor level.

CONCLUSIONS

Our findings highlight the need for more longitudinal and exposure-dependent studies to differentiate between inherent neurobiological differences and the (long-term) effects of smoking in SSD, and to unravel the complex interaction between smoking and schizophrenia at various disease stages. This could inform more effective strategies addressing smoking susceptibility in SSD, potentially improving clinical outcomes.

The causal relationship between physical activity, sedentary behavior and brain cortical structure: a Mendelian randomization study

Physical activity and sedentary behavior, both distinct lifestyle behaviors associated with brain health, have an unclear potential relationship with brain cortical structure. This study aimed to determine the causal link between physical activity, sedentary behavior, and brain cortical structure (cortical surface area and thickness) through Mendelian randomization analysis. The inverse-variance weighted method was primarily utilized, accompanied by sensitivity analyses, to confirm the results' robustness and accuracy. Analysis revealed nominally significant findings, indicating a potential positive influence of physical activity on cortical thickness in the bankssts (β = 0.002 mm, P = 0.043) and the fusiform (β = 0.002 mm, P = 0.018), and a potential negative association of sedentary behavior with cortical surface area in the caudal middle frontal (β = -34.181 mm2, P = 0.038) and the pars opercularis (β = -33.069 mm2, P = 0.002), alongside a nominally positive correlation with the cortical surface area of the inferior parietal (β = 58.332 mm2, P = 0.035). Additionally, a nominally significant negative correlation was observed between sedentary behavior and cortical thickness in the paracentral (β = -0.014 mm, P = 0.042). These findings offer insights into how lifestyle behaviors may influence brain cortical structures, advancing our understanding of their interaction with brain health.

Association between pre-dementia psychiatric diagnoses and all-cause dementia is independent from polygenic dementia risks in the UK Biobank

BACKGROUND

Psychiatric disorders have been associated with higher risk for future dementia. Understanding how pre-dementia psychiatric disorders (PDPD) relate to established dementia genetic risks has implications for dementia prevention.

METHODS

In this retrospective cohort study, we investigated the relationships between polygenic risk scores for Alzheimer's disease (AD PRS), PDPD, alcohol use disorder (AUD), and subsequent dementia in the UK Biobank (UKB) and tested whether the relationships are consistent with different causal models.

FINDINGS

Among 502,408 participants, 9352 had dementia. As expected, AD PRS was associated with greater risk for dementia (odds ratio (OR) 1.62, 95% confidence interval (CI), 1.59-1.65). A total of 94,237 participants had PDPD, of whom 2.6% (n = 2519) developed subsequent dementia, compared to 1.7% (n = 6833) of 407,871 participants without PDPD. Accordingly, PDPD were associated with 73% greater risk of incident dementia (OR 1.73, 1.65-1.83). Among dementia subtypes, the risk increase was 1.5-fold for AD (n = 3365) (OR 1.46, 1.34-1.59) and 2-fold for vascular dementia (VaD, n = 1823) (OR 2.08, 1.87-2.32). Our data indicated that PDPD were neither a dementia prodrome nor a mediator for AD PRS. Shared factors for both PDPD and dementia likely substantially account for the observed association, while a causal role of PDPD in dementia could not be excluded. AUD could be one of the shared causes for PDPD and dementia.

INTERPRETATION

Psychiatric diagnoses were associated with subsequent dementia in UKB participants, and the association is orthogonal to established dementia genetic risks. Investigating shared causes for psychiatric disorders and dementia would shed light on this dementia pathway.

FUNDING

US NIH (K08AG054727).

Prior infections are associated with smaller hippocampal volume in older women

Accumulating evidence suggests that infections may play a major role in Alzheimer's disease (AD), however, mechanism is unclear, as multiple pathways may be involved. One possibility is that infections could contribute to neurodegeneration directly by promoting neuronal death. We explored relationships between history of infections and brain hippocampal volume (HV), a major biomarker of neurodegeneration, in a subsample of the UK Biobank (UKB) participants. Infectious disease diagnoses were based on ICD10 codes. The left/right HV was measured by the magnetic resonance imaging (MRI) in cubic millimeters and normalized. Analysis of variance (ANOVA), Welch test, and regression were used to examine statistical significance. We found that HV was significantly lower in women aged 60-75, as well as 65-80, years, with history of infections, compared to same age women without such history. The effect size increased with age faster for the left vs. right HV. Results for males didn't reach statistical significance. Results of our study support a major role of adult infections in neurodegeneration in women. The detrimental effect of infections on HV became stronger with age, in line with declining resilience and increasing brain vulnerability to stressors due to aging. The faster increase in the effect size observed for the left vs. right HV may indicate that female verbal memory degrades faster over time than visual-spatial memory. The observed sex difference may reflect a higher vulnerability of female brain to infection-related factors, which in turn may contribute to a higher risk of AD in women compared to men.

The interaction effects of age, APOE and common environmental risk factors on human brain structure

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

The potential role of gray matter volume differences in the association between smoking and depression: A narrative review

Tobacco use and major depression are both leading contributors to the global burden of disease and are also highly comorbid. Previous research indicates bi-directional causality between tobacco use and depression, but the mechanisms that underlie this causality are unclear, especially for the causality from tobacco use to depression. Here we narratively review the available evidence for a potential causal role of gray matter volume in the association. We summarize the findings of large existing neuroimaging meta-analyses, studies in UK Biobank, and the Enhancing NeuroImaging Genetics through MetaAnalysis (ENIGMA) consortium and assess the overlap in implicated brain areas. In addition, we review two types of methods that allow us more insight into the causal nature of associations between brain volume and depression/smoking: longitudinal studies and Mendelian Randomization studies. While the available evidence suggests overlap in the alterations in brain volumes implicated in tobacco use and depression, there is a lack of research examining the underlying pathophysiology. We conclude with recommendations on (genetically-informed) causal inference methods useful for studying these associations.

Association of smoking with brain gray and white matter volume: a Mendelian randomization study

BACKGROUND

Observational studies have found a significant association between smoking and smaller gray matter volume, but this finding was limited by the reverse causality bias and possible confounding factors. Therefore, we conducted a Mendelian randomization (MR) study to explore the causal association of smoking with brain gray and white matter volume from a genetic perspective, and to investigate the possible mediators influencing the association.

METHODS

Smoking initiation (ever being a regular smoker) was used as the primary exposure from the GWAS & Sequencing Consortium of Alcohol and Nicotine use in up to 1,232,091 individuals of European descent. Their associations with brain volume were acquired from a recent genome-wide association study of brain imaging phenotypes conducted among 34,298 individuals of the UK Biobank. The random-effects inverse-variance weighted method was applied as the main analysis. Multivariable MR analysis was performed to assess the potential interference of confounding factors on causal effect.

RESULTS

Genetic liability to smoking initiation was significantly associated with lower gray matter volume (beta, -0.100; 95% CI, -0.156 to -0.043; P=5.23×10-4) but not with white matter volume. Multivariable MR results suggested that the association with lower gray matter volume might be mediated by alcohol drinking. Regarding localized gray matter volume, genetic liability to smoking initiation was associated with lower gray matter volume in left superior temporal gyrus, anterior division and right superior temporal gyrus, posterior division.

CONCLUSIONS

This MR study supports the association between smoking and lower gray matter volume, and highlights the importance of never smoking.