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Educational attainment does not influence brain aging.
Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.
Association of Diet and Waist-to-Hip Ratio With Brain Connectivity and Memory in Aging.
IMPORTANCE: Epidemiological studies suggest that lifestyle factors are associated with risk of dementia. However, few studies have examined the association of diet and waist to hip ratio (WHR) with hippocampus connectivity and cognitive health. OBJECTIVE: To ascertain how longitudinal changes in diet quality and WHR during midlife are associated with hippocampal connectivity and cognitive function in later life. DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed data from participants in the Whitehall II Study at University College London (study inception: 1985) and Whitehall II Imaging Substudy at the University of Oxford (data collection: 2012-2016). Healthy participants from the Whitehall II Imaging Study with a mean age of 48 years at baseline to 70 years at magnetic resonance imaging (MRI) were included if they had information on diet from at least 1 wave, information on WHR from at least 2 waves, and good-quality MRI scans. Study analyses were completed from October 2019 to November 2024. EXPOSURES: Diet quality was measured in participants(mean age, 48 years at baseline to 60 years) using the Alternative Healthy Eating Index-2010 score, which was assessed 3 times across 11 years. WHR was measured 5 times over 21 years in participants aged 48 to 68 years. MAIN OUTCOMES AND MEASURES: White matter structural connectivity assessed using diffusion tensor imaging, hippocampal functional connectivity assessed using resting-state functional MRI, and cognitive performance measures. Brain imaging and cognitive tests were performed at a mean (SD) age of 70 (5) years. RESULTS: The final diet quality sample comprised 512 participants (403 males [78.7%]; mean [SD] age, 47.8 [5.2] years), and the final WHR sample included 664 participants (532 males [80.1%]; mean [SD] age, 47.7 [5.1] years). Better diet quality in midlife and from midlife to late life was associated with higher hippocampal functional connectivity to the occipital lobe and cerebellum (left hippocampus: 9176 mm3, P
Associations of aortic and carotid artery health with cerebrovascular markers and cognition in older adults from the Whitehall II imaging study.
BACKGROUND: Cardiovascular disease has been associated with an increased dementia risk, but the underlying mechanisms for this heart-brain link are unclear. This study sought to examine associations between aortic and carotid artery structure with cerebrovascular reactivity (CVR), white matter hyperintensities (WMHs), and cognition in later-life. METHODS: One hundred sixty three participants (25.8% female) from the Whitehall II Imaging cohort completed two examinations (M ± SD age 68.2 ± 4.4 at Wave-1 and 76.9 ± 4.5 at Wave-2) of neuropsychological assessments and 3T brain magnetic resonance imaging (MRI) FLAIR scans to quantify WMHs. Wave-2 additionally included vascular sonography of the aorta and carotid artery, and 3T functional MRI scans to measure CVR (mean % change BOLD signal change during a CO2 challenge). Wave-2 factor scores of aortic and carotid arterial diameters, stiffness, and compliance were the exposure variables. Midlife Framingham Cardiovascular Risk Score (FRS) measured before Wave-1 was a potential effect modifier. WMH volume, grey matter CVR, cognitive factor scores (episodic memory, working memory, executive function, visuospatial memory, fluency, lexical retrieval) at Wave-2, and changes in WMH and cognition between Wave-1 and Wave-2 were used as outcome variables. RESULTS: Larger aortic diameter (ß = 0.38, SE = 0.11) and greater aortic stiffness (ß = 0.27, SE = 0.10) were associated with larger carotid diameter, independently of body size. Higher midlife FRS was associated with larger aortic and carotid diameters and increased carotid stiffness in old age. We observed notable artery-brain associations, such that larger aortic (ß = 0.17, SE = 0.06) and carotid diameters (ß = 0.11, SE = 0.05) were associated with larger WMH lesion volumes at Wave-2. Larger aortic diameter (ß = 0.08 SE = 0.03) and lower carotid compliance (ß = - 0.06, SE = 0.02) at Wave-2 were also associated with greater longitudinal increases in WMH volumes over the preceding 9 years. Higher stiffness and lower compliance of the aorta and carotid were associated with worse cognitive outcomes across a range of domains, and these associations were moderated by midlife FRS. Larger carotid diameter was associated with higher cerebrovascular reactivity (ß = 0.02, SE = 0.01), suggesting a potential compensatory pathway. CONCLUSIONS: Adverse structural and functional changes in the aorta and carotid artery were inter-related and associated with vascular brain lesions, cerebrovascular reactivity, and poorer cognitive outcomes in older age.
Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later.
INTRODUCTION: The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. METHODS: In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. RESULTS: Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p
No moderating influence of education on the association between changes in hippocampus volume and memory performance in aging.
Contemporary accounts of factors that may modify the risk for age-related neurocognitive disorders highlight education and its contribution to a cognitive reserve. By this view, individuals with higher educational attainment should show weaker associations between changes in brain and cognition than individuals with lower educational attainment. We tested this prediction in longitudinal data on hippocampus volume and episodic memory from 708 middle-aged and older individuals using local structural equation modeling. This technique does not require categorization of years of education and does not constrain the shape of relationships, thereby maximizing the chances of revealing an effect of education on the hippocampus-memory association. The results showed that the data were plausible under the assumption that there was no influence of education on the association between change in episodic memory and change in hippocampus volume. Restricting the sample to individuals with elevated genetic risk for dementia (APOE ε4 carriers) did not change these results. We conclude that the influence of education on changes in episodic memory and hippocampus volume is inconsistent with predictions by the cognitive reserve theory.
Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts.
Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r = .37, p < 0.001; Denmark: r = .27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r = .10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.
Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable study of two cohorts of older adults
AbstractBackgroundModifiable risk factors have been shown to promote healthy brain ageing. However, most studies to date have focused on the relationship between a single risk factor and brain health. Given that risk factors do not occur in isolation, multivariable analyses may provide a more realistic model of the effects of modifiable lifestyle factors on brain ageing.MethodHere, the relationship between 9 modifiable lifestyle factors and 7 indices of brain structure were examined using canonical correlation analyses to identify a covariance pattern between lifestyle factors associated with dementia risk and MRI‐derived measures of brain structure. Analyses were first conducted on a Danish cohort of older adults (n = 251) and then cross‐validated in an independent cohort of older adults from the United Kingdom (n = 668).ResultsIn a 5‐fold cross‐validation analysis of the test dataset, a canonical correlation of 0.14 was observed between the lifestyle and brain variates. In the cross‐study validation, the lifestyle‐brain correlation was r = .10. In the Danish cohort, feelings of loneliness, BMI, depressive symptoms, and years of smoking were the primary contributors to the lifestyle variate (rs ≥ 0.3). In the British cohort, a different pattern of lifestyle factors was found to relate to brain structure the most (rs ≥ 0.3: physical activity, education, alcohol consumption, blood pressure and BMI).ConclusionIn both cohorts, we found that a latent of lifestyle factors was positively associated with age‐related measures of brain structure and this relationship was validated across cohorts of older adults. However, the covariance pattern between lifestyle and brain outcomes differed between datasets. Taken together, these findings highlight how future lifestyle interventions should be tailored to suit their target populations.
Inter‐ and intra‐individual variation in brain structural‐cognition relationships in aging
AbstractBackgroundThe sources of inter‐ and intra‐individual variability in age‐related cognitive decline remain poorly understood. We examined the association between 20‐year trajectories of cognitive decline and multimodal brain structure and morphology in older age.MethodWe used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid‐life (mean age = 53.2 ±4.9 years) and late‐life (mean age = 67.7 ± 4.9). Using non‐negative matrix factorisation, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities (Figure 1).ResultWe observed two latent variables describing distinct brain‐cognition associations. The first describes variations in 5 structural components associated with low mid‐life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid‐life performance in fluency and memory, but retention of multiple abilities (Figure 2). Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9) (Figure 3).ConclusionLongitudinal cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with distinct markers of cortical structure. Latent brain‐behaviour relationships predict future cognitive performance.
Brain change trajectories in healthy adults correlate with Alzheimer's related genetic variation and memory decline across life.
Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer's disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2-7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer's Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.
Association between cannabis use and brain structure and function: an observational and Mendelian randomisation study.
BACKGROUND: Cannabis use during adolescence and young adulthood has been associated with brain harm, yet despite a rapid increase in cannabis use among older adults in the past decade, the impact on brain health in this population remains understudied. OBJECTIVE: To explore observational and genetic associations between cannabis use and brain structure and function. METHODS: We examined 3641 lifetime cannabis users (mean (SD) age 61.0 (7.1) years) and 12 255 controls (mean (SD) age 64.5 (7.5) years) from UK Biobank. Brain structure and functional connectivity were measured using multiple imaging-derived phenotypes. Associations with cannabis use were assessed using multiple linear regression controlling for potential confounds. Bidirectional two-sample Mendelian randomisation analyses were used to investigate potential causal relationships. FINDINGS: Cannabis use was associated with multiple measures of brain structure and function. Participants with a history of cannabis use had poorer white matter integrity, as assessed by lower fractional anisotropy and higher mean diffusivity in the genu of the corpus callosum, as well as weaker resting-state functional connectivity in brain regions underlying the default mode and central executive networks. Mendelian randomisation analyses found no support for causal relationships underlying associations between cannabis use and brain structure or function. CONCLUSIONS: Associations between lifetime cannabis use and brain structure and function in later life are probably not causal in nature and might represent residual confounding. CLINICAL IMPLICATIONS: Cannabis use is associated with differences in brain structure and function. Further research is needed to understand the mechanisms underlying these associations, which do not appear to be causal.
Biomarkers.
BACKGROUND: Cerebrovascular reactivity (CVR) is implicated in the progression of dementia, though the underlying mechanisms is not understood. This study examines the relationships between CVR and brain structure and cognitive decline, moderated by mid-life dementia risk. METHOD: 163 participants from the Whitehall-II cohort underwent neuropsychological testing and MRI, including T1-weighted, FLAIR, and DTI sequences, at two phases (Phase-I: mean age=68.2±4.4; Phase-II: mean age=76.9±4.5). CVR was quantified via BOLD response to 5% CO2 only at Phase-II. Linear regression tested the Phase-II and Phase-I to Phase-II associations between CVR and brain and cognitive outcomes (Table 1), alongside its interaction with dementia risks. Post-hoc analysis clarified the extent of these associations among different risk groups. RESULT: Tables 2 and 3 list significant cross-sectional and longitudinal results, respectively. At Phase-II, global CVR was positively associated with volume of left nucleus accumbens, and temporoparietal junction (p<0.03). Parietal CVR was positively associated with left hippocampus volume (p=0.03). These associations were more pronounced in the low-risk group. Temporal CVR was related to thalamus volume (p<0.05) across all participants, with associations of the right thalamus exclusive to the high-risk group (p=0.03). Longitudinally, lower global and regional CVR at Phase-II was linked to greater reduction in temporoparietal junction volume (p<0.04). In high-risk individuals, lower frontal, parietal, or global CVR was linked to larger volume declines in total grey matter or right thalamus respectively (p<0.05). Across all participants, lower parietal CVR at follow-up was linked to greater FA reductions and RD increases between examinations in the corpus callosum (p=0.02) and to greater declines in FA and increases in MD, RD, and L1 in the cingulum bundle (p<0.04), with these effects being more pronounced in the low-risk group. At Phase-II, lower parietal and temporal CVR was associated with worse fluency and intelligence, respectively, in high-risk individuals (p<0.05). Lower frontal CVR was linked to more executive function decline in the low-risk group over-time (p=0.03). CONCLUSION: This study highlights the differential impacts of global and regional CVR on brain structure and cognitive changes dependent on mid-life dementia risks, which provides evidence for CVR as a potential biomarker for dementia and age-related cognitive change.
Alcohol use and dementia in diverse populations (F96)
Background: The impact of alcohol use on dementia risk remains contentious. Methodological limitations of previous studies have made distinguishing causation from con- founding difficult. Mendelian randomization is a quasi- experimental method that can estimate causal effects via genetics. Methods: We estimated dose-response relationships be- tween alcohol and dementia in observational and genetic analyses. First, we pooled and harmonized individual-level phenotype data from two prospective cohort studies: the US Million Veteran Program (MVP) and UK Biobank (UKB; mean follow-up 4 and 12 years respectively). Associations were examined using Cox regression analysis and results combined using random-effects meta-analysis. We compared these findings with genetic associations between alcohol use and dementia (calculated de novo) using data from 2.4 mil- lion participants using Mendelian randomization. Results: 559,559 participants (247,136 from MVP and 312,423 from UKB) aged 56-72 years old at baseline were included in observational analyses. 14,540 developed dementia and 48,034 died during follow-up. Observational as- sociations between alcohol and dementia were U-shaped, meaning that non-drinkers, heavy (> 40 drinks per week) drinkers (hazard ratio = 1.41 [1.15 to 1.74]) and dependent drinkers (1.51 [1.42-1.60]) were all at higher dementia risk compared with light drinkers. In contrast, genetic analyses revealed a monotonically increasing association between alcohol dose and dementia, with no evidence supporting a protective effect of any level of drinking. A two-fold in- crease in genetically-predicted alcohol use disorder prevalence was associated with a 16 % increase in dementia cases (IVW OR = 1.16 [1.03-1.30]), and a one standard deviation in- crease in log-transformed drinks per week was associated with a 15% increase (IVW OR = 1.15[1.03-1.27]). Discussion: Alcohol consumption has a causal role for dementia. Halving the population prevalence of alcohol use disorder would lead to a 16% reduction in dementia cases.
No significant association between self-reported physical activity and brain volumes in women and men from five European cohorts.
Various studies have reported an association between physical activity and grey matter volumes. Some studies have suggested that this relationship may be moderated by sex, yet the direction is still under debate. Focusing on hippocampus and dorsolateral prefrontal cortex (dlPFC), we tested whether the association between regional grey matter volumes and self-reported physical activity differs between women and men. We examined this interaction in five European cohorts from the Lifebrain consortium (n = 1809; age range: 18-88 years). Effect sizes were first determined by linear models run separately for each cohort, then pooled across datasets in a random-effects meta-analysis. Contrary to our hypotheses, there was no evidence of a relationship between physical activity and hippocampal or dlPFC volumes, nor was there a moderation by sex. Our null findings raise the question of whether self-report questionnaires of physical activity, which commonly feature in big datasets, are sufficiently sensitive to capture a-presumably modest-association between physical activity levels and grey matter outcomes. We conclude that the reliance on self-report questionnaires of physical activity is sub-optimal for brain-behaviour analyses.
Nuclei-specific hypothalamus networks predict a dimensional marker of stress in humans.
The hypothalamus is part of the hypothalamic-pituitary-adrenal axis which activates stress responses through release of cortisol. It is a small but heterogeneous structure comprising multiple nuclei. In vivo human neuroimaging has rarely succeeded in recording signals from individual hypothalamus nuclei. Here we use human resting-state fMRI (n = 498) with high spatial resolution to examine relationships between the functional connectivity of specific hypothalamic nuclei and a dimensional marker of prolonged stress. First, we demonstrate that we can parcellate the human hypothalamus into seven nuclei in vivo. Using the functional connectivity between these nuclei and other subcortical structures including the amygdala, we significantly predict stress scores out-of-sample. Predictions use 0.0015% of all possible brain edges, are specific to stress, and improve when using nucleus-specific compared to whole-hypothalamus connectivity. Thus, stress relates to connectivity changes in precise and functionally meaningful subcortical networks, which may be exploited in future studies using interventions in stress disorders.