Risk and protective factors for structural brain ageing in the eighth decade of life

Allostatic load measures in older adults with subjective cognitive decline and mild cognitive impairment: A cross-sectional analysis from the Brazilian Memory and Aging Study

INTRODUCTION

An increasing body of research suggests that stress and allostatic load are related to cognitive dysfunction and neurodegeneration.

OBJECTIVES

to determine the relationship between allostatic load (AL) and cognitive status in older adults classified with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

METHODOLOGY

Using the Brazilian Memory and Aging Study (BRAMS) database, we analyzed data from 57 older adults with SCD and MCI. Blood neuroendocrine (cortisol, DHEA-s), inflammatory (C-reactive protein, fibrinogen), metabolic (HbA1c, HDL-cholesterol, total cholesterol, creatinine), and cardiovascular (blood pressure, waist/hip ratio) were transformed into an AL index.

RESULTS

Despite a significant difference in the univariate analysis between waist/hip ratio (0.94 in the MCI group vs. 0, 88 in the SCD group, p = 0.03), total cholesterol levels (194 vs. 160, p = 0.02), and AL index (36.9 % in the MCI group vs. 27.2 % in the SCD group, p = 0.04), AL was not associated with SCD or MCI in the multivariate analysis.

CONCLUSION

Our data suggest that different profiles of AL in MCI compared to individuals with SCD could be due to cofounding factors. These findings need to be confirmed in longitudinal studies investigating profiles of AL changes at preclinical and prodromal stages of Alzheimer's disease.

Association between allostatic load and accelerated white matter brain aging: findings from the UK Biobank

White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29 years in association analysis and by 0.33 years in Mendelian analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64 years old, with no significant sex difference. This study demonstrated that higher chronic stress was significantly associated with accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.

Comprehensive allostatic load risk index is associated with increased frontal and left parietal white matter hyperintensities in mid-life cognitively healthy adults

To date, there is a considerable heterogeneity of methods to score Allostatic Load (AL). Here we propose a comprehensive algorithm (ALCS) that integrates commonly used approaches to generate AL risk categories and assess associations to brain structure deterioration. In a cohort of cognitively normal mid-life adults (n = 620, age 51.3 ± 5.48 years), we developed a comprehensive composite for AL scoring incorporating gender and age differences, high quartile approach, clinical reference values, and current medications, to then generate AL risk categories. Compared to the empirical approach (ALES), ALCS showed better model fit criteria and a strong association with age and sex. ALSC categories were regressed against brain and white matter hyperintensity (WMH) volumes. Higher AL risk categories were associated with increased total, periventricular, frontal, and left parietal WMH volumes, also showing better fit compared to ALES. When cardiovascular biomarkers were removed from the ALSC algorithm, only left-frontal WMHV remained associated with AL, revealing a strong vascular burden influencing the index. Our results agree with previous evidence and suggest that sustained stress exposure enhances brain deterioration in mid-life adults. Showing better fit than ALES, our comprehensive algorithm can provide a more accurate AL estimation to explore how stress exposure enhances age-related health decline.

Moderating effects of cognitive reserve on the relationship between brain structure and cognitive abilities in middle-aged and older adults

The cognitive reserve (CR) hypothesis is reinforced by negative moderating effects, suggesting that those with higher CR are less reliant on brain structure for cognitive function. Previous research on CR's moderating effects yielded inconsistent results, motivating our 3 studies using UK Biobank data. Study I examined five CR proxies' moderating effects on global, lobar, and regional brain-cognition models; study II extended study I by using a larger sample size; and study III investigated age-related moderating effects on the hippocampal regions. In study I, most moderating effects were negative and none survived the multiple comparison correction, but study II identified 13 global-level models with significant negative moderating effects that survived correction. Study III showed age influenced CR proxies' moderating effects in hippocampal regions. Our findings suggest that the effects of CR proxies on brain integrity and cognition varied depending on the proxy used, brain integrity indicators, cognitive domain, and age group. This study offers significant insights regarding the importance of CR for brain integrity and cognitive outcomes.

The association between allostatic load and brain: A systematic review

Allostatic load (AL) refers to prolonged dysregulation related to chronic stress that affects brain regions such as the hippocampus, amygdala, and prefrontal cortex (PFC). Higher levels of AL have been associated with poor health outcomes, including psychiatric disorders, cognitive decline, and chronic somatic conditions. However, still little is known about the relationship between AL and the brain, and the mechanisms explaining the damaging effects of stress-related biological dysregulations. Therefore, we aimed to perform a systematic review of studies investigating the association of the AL index with brain structure and functioning in adult populations. PubMed/MEDLINE, CINAHL, Academic Search Complete and Web of Science were searched from their inception until August, 9th 2021. A total of 13 studies were included in the qualitative synthesis. There was a high between-study heterogeneity with respect to the methods used to calculate the AL index and brain parameters. All studies confirmed the associations between a higher AL index and alterations in various brain areas, especially: 1) the hippocampus, white matter volume, gray matter volume, and density in the older adults; 2) the cortex, fornix, hippocampus and choroid plexus in patients with schizophrenia spectrum disorders; and 3) whole-brain white matter tracts, cortical gray matter volume, and cortical thickness in overweight subjects. Overall, the findings of this systematic review imply that an elevated AL index might be associated with various neurostructural and neurofunctional alterations. Some of these associations may appear regardless of clinical or non-clinical populations being investigated (e.g., white matter tracts), whereas others may appear in specific populations (e.g., cortical thinning in overweight/obesity and schizophrenia spectrum disorders). However, additional studies utilizing a consistent approach to calculating the AL index are needed to extend these findings and indicate populations that are most vulnerable to the damaging effects of AL.

Cognitive Change Before Old Age (11 to 70) Predicts Cognitive Change During Old Age (70 to 82)

Identifying predictors of cognitive decline in old age helps us understand its mechanisms and identify those at greater risk. Here, we examined how cognitive change from ages 11 to 70 is associated with cognitive change at older ages (70 to 82 years) in the Lothian Birth Cohort 1936 longitudinal study (N = 1,091 at recruitment). Using latent-growth-curve models, we estimated rates of change from ages 70 to 82 in general cognitive ability (g) and in three cognitive domains: visuospatial, memory, and processing speed. We found that g accounted for 71.3% of interindividual change variance. Greater cognitive gain from ages 11 to 70 predicted slower decline in g over 12 subsequent years (β = 0.163, p = .001), independently of cognitive level in childhood and at age 70, and domain-specific change beyond g. These results contribute to the goal of identifying people at higher risk of age-related cognitive decline.

Increased allostatic load associated with ambient air pollution acting as a stressor: Cross-sectional evidence from the China multi-ethnic cohort study

BACKGROUND

Allostatic load measures the cumulative biological burden imposed by chronic stressors. Emerging experimental evidence supports that air pollution acting as a stressor activates the neuroendocrine system and then produces multi-organ effects, leading to allostatic load. However, relevant epidemiological evidence is limited.

OBJECTIVES

We aim to explore the relationships between chronic exposure to ambient air pollution (PM₁, PM_2.5, PM₁₀, and O₃) and allostatic load in Chinese adults.

METHODS

This cross-sectional study included 85,545 participants aged 30-79 from the baseline data of the China Multi-Ethnic Cohort (CMEC). Ambient air pollution levels were evaluated by a satellite-based random forest approach. The previous three-year average exposure concentrations were calculated for each participant based on the residential address. The outcome allostatic load was identified through the sum of the sex-specific scores of twelve biomarkers belonging to four major categories: cardiovascular, metabolic, anthropometric, and inflammatory parameters. We performed statistical analysis using a doubly robust approach which relies on inverse probability weighting and outcome model to adjust for confounding.

RESULTS

Long-term exposure to ambient air pollution was significantly associated with an increased risk of allostatic load, with relative risk (95% confidence interval) of 1.040 (1.024, 1.057), 1.029 (1. 018, 1. 039), and 1.087 (1.074, 1.101) for each 10 μg/m³ increase in ambient PM_2.5, PM₁₀, and O₃, respectively. No significant relationship was observed between chronic exposure to PM₁ and allostatic load. The associations between air pollution and allostatic load are modified by some intrinsic factors and non-chemical stressors. The people with older, minority, lower education, and lower-income levels had a significantly higher allostatic load induced by air pollution.

CONCLUSIONS

Chronic exposure to ambient PM_2.5, PM₁₀, and O₃ may increase the allostatic load. This finding provides epidemiological evidence that air pollution may be a chronic stressor, leading to widespread physiological burdens.

Apolipoprotein E Genotype Moderation of the Association Between Physical Activity and Brain Health. A Systematic Review and Meta-Analysis

Introduction

Possession of one or two e4 alleles of the apolipoprotein E (APOE) gene is associated with cognitive decline and dementia risk. Some evidence suggests that physical activity may benefit carriers of the e4 allele differently.

Method

We conducted a systematic review and meta-analysis of studies which assessed APOE differences in the association between physical activity and: lipid profile, Alzheimer's disease pathology, brain structure and brain function in healthy adults. Searches were carried out in PubMed, SCOPUS, Web of Science and PsycInfo.

Results

Thirty studies were included from 4,896 papers screened. Carriers of the e4 allele gained the same benefit from physical activity as non-carriers on most outcomes. For brain activation, e4 carriers appeared to gain a greater benefit from physical activity on task-related and resting-state activation and resting-state functional connectivity compared to non-carriers. Post-hoc analysis identified possible compensatory mechanisms allowing e4 carriers to maintain cognitive function.

Discussion

Though there is evidence suggesting physical activity may benefit e4 carriers differently compared to non-carriers, this may vary by the specific brain health outcome, perhaps limited to brain activation. Further research is required to confirm these findings and elucidate the mechanisms.

Allostatic Load and Its Impact on Health: A Systematic Review

INTRODUCTION

Allostatic load refers to the cumulative burden of chronic stress and life events. It involves the interaction of different physiological systems at varying degrees of activity. When environmental challenges exceed the individual ability to cope, then allostatic overload ensues. Allostatic load is identified by the use of biomarkers and clinical criteria.

OBJECTIVE

To summarize the current knowledge on allostatic load and overload and its clinical implications based on a systematic review of the literature.

METHODS

PubMed, PsycINFO, Web of Science, and the Cochrane Library were searched from inception to December 2019. A manual search of the literature was also performed, and reference lists of the retrieved articles were examined.We considered only studies in which allostatic load or overload were adequately described and assessed in either clinical or non-clinical adult populations.

RESULTS

A total of 267 original investigations were included. They encompassed general population studies, as well as clinical studies on consequences of allostatic load/overload on both physical and mental health across a variety of settings.

CONCLUSIONS

The findings indicate that allostatic load and overload are associated with poorer health outcomes. Assessment of allostatic load provides support to the understanding of psychosocial determinants of health and lifestyle medicine. An integrated approach that includes both biological markers and clinimetric criteria is recommended.

Birth weight is associated with brain tissue volumes seven decades later but not with MRI markers of brain ageing

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Larger birth weight is associated with larger brain tissue volumes at age 73.

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Birth weight is not associated with age-associated brain features.

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Effect of birth weight on brain volumes is independent of overall body size.

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Early life growth is likely to confer brain tissue reserve in later life.

Birth weight, an indicator of fetal growth, is associated with cognitive outcomes in early life (which are predictive of cognitive ability in later life) and risk of metabolic and cardiovascular disease across the life course. Brain health in older age, indexed by MRI features, is associated with cognitive performance, but little is known about how variation in normal birth weight impacts on brain structure in later life. In a community dwelling cohort of participants in their early seventies we tested the hypothesis that birth weight is associated with the following MRI features: total brain (TB), grey matter (GM) and normal appearing white matter (NAWM) volumes; whiter matter hyperintensity (WMH) volume; a general factor of fractional anisotropy (gFA) and peak width skeletonised mean diffusivity (PSMD) across the white matter skeleton. We also investigated the associations of birth weight with cortical surface area, volume and thickness. Birth weight was positively associated with TB, GM and NAWM volumes in later life (β ≥ 0.194), and with regional cortical surface area but not gFA, PSMD, WMH volume, or cortical volume or thickness. These positive relationships appear to be explained by larger intracranial volume, rather than by age-related tissue atrophy, and are independent of body height and weight in adulthood. This suggests that larger birth weight is linked to more brain tissue reserve in older life, rather than age-related brain structural features, such as tissue atrophy or WMH volume.

Linking objective measures of physical activity and capability with brain structure in healthy community dwelling older adults

Maintaining high levels of daily activity and physical capability have been proposed as important constituents to promote healthy brain and cognitive aging. Studies investigating the associations between brain health and physical activity in late life have, however, mainly been based on self-reported data or measures designed for clinical populations. In the current study, we examined cross-sectional associations between physical activity, recorded by an ankle-positioned accelerometer for seven days, physical capability (grip strength, postural control, and walking speed), and neuroimaging based surrogate markers of brain health in 122 healthy older adults aged 65-88 years. We used a multimodal brain imaging approach offering complementary structural MRI based indicators of brain health: global white matter fractional anisotropy (FA) and mean diffusivity (MD) based on diffusion tensor imaging, and subcortical and global brain age based on brain morphology inferred from T1-weighted MRI data. In addition, based on the results from the main analysis, follow-up regression analysis was performed to test for association between the volume of key subcortical regions of interest (hippocampus, caudate, thalamus and cerebellum) and daily steps, and a follow-up voxelwise analysis to test for associations between walking speed and FA across the white matter Tract-Based Spatial Statistics (TBSS) skeleton. The analyses revealed a significant association between global FA and walking speed, indicating higher white matter integrity in people with higher pace. Voxelwise analysis supported widespread significant associations. We also found a significant interaction between sex and subcortical brain age on number of daily steps, indicating younger-appearing brains in more physically active women, with no significant associations among men. These results provide insight into the intricate associations between different measures of brain and physical health in old age, and corroborate established public health advice promoting physical activity.

Subcortical grey matter changes associated with motor symptoms evaluated by the Unified Parkinson's disease Rating Scale (part III): A longitudinal study in Parkinson's disease

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Decreased grey matter volume over time suggests a subcortical alteration in PD.

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Decreased volume in the thalamus may be related to the decline in motor skills.

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Increased volume in the pallidum may contribute to motor impairment.

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Structural changes in line with the model of basal ganglia-thalamocortical circuits.

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VBM and volumetry might capture complementary aspects of structural changes in PD.

Parkinson disease (PD) is characterized by motor deficits related to structural changes in the basal ganglia-thalamocortical circuits. However, it is still unclear the exact nature of the association between grey matter alterations and motor symptoms.

Therefore, the aim of our investigation was to identify the subcortical modifications associated with motor symptoms of PD over time - adopting voxel-based morphometry (VBM) and automated volumetry methods.

We selected fifty subjects with PD from the Parkinson’s Progression Markers Initiative (PPMI) database, who performed an MRI session at two time points: at baseline (i.e. at maximum 2 years after clinical diagnosis of PD) and after 48 months. Motor symptoms were assessed using the part III of the Unified Parkinson’s Disease Rating Scale at the two time points.

Our VBM and volumetric analyses showed a general atrophy in all subcortical regions when comparing baseline with 48 months. These findings confirmed previous observations indicating a subcortical alteration over time in PD. Furthermore, our findings supported the idea that a reduced volume in the thalamus and an increased volume in pallidum may be related to the decline in motor skills. These structural modifications are in accordance with the functional model of the basal ganglia-thalamocortical circuits controlling movements. Moreover, VBM and volumetry provided partially overlapping results, suggesting that these methods might capture complementary aspects of brain degeneration in PD.

Microstructural differences in white matter tracts across middle to late adulthood: a diffusion MRI study on 7167 UK Biobank participants

White matter fiber tracts demonstrate heterogeneous vulnerabilities to aging effects. Here, we estimated age-related differences in tract properties using UK Biobank diffusion magnetic resonance imaging data of 7167 47- to 76-year-old neurologically healthy people (3368 men and 3799 women). Tract properties in terms of generalized fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were sampled on 76 fiber tracts; for each tract, age-related differences were estimated by fitting these indices against age in a linear model. This cross-sectional study demonstrated 4 age-difference patterns. The dominant pattern was lower generalized fractional anisotropy and higher axial diffusivity, radial diffusivity, and mean diffusivity with age, constituting 45 of 76 tracts, mostly involving the association, projection, and commissure fibers connecting the prefrontal lobe. The other 3 patterns constituted only 14 tracts, with atypical age differences in diffusion indices, and mainly involved parietal, occipital, and temporal cortices. By analyzing the large volume of diffusion magnetic resonance imaging data available from the UK Biobank, the study has provided a detailed description of heterogeneous age-related differences in tract properties over the whole brain which generally supports the myelodegeneration hypothesis.

Discovering correlates of age-related decline in a healthy late-midlife male birth cohort

Studies exploring age-related brain and cognitive change have identified substantial heterogeneity among individuals, but the underlying reasons for the differential trajectories remain largely unknown. We investigated cross-sectional and longitudinal associations between brain-imaging phenotypes (IDPs) and cognitive ability, and how these relations may be modified by common risk and protective factors. Participants were recruited from the 1953 Danish Male Birth Cohort (N=123), a longitudinal study of cognitive and brain ageing. Childhood IQ and socio-demographic factors are available for these participants who have been assessed regularly on multiple IDPs and behavioural factors in midlife. Using Pearson correlations and canonical correlation analysis (CCA), we explored the relation between 454 IDPs and 114 behavioural variables. CCA identified a single mode of population covariation coupling cross-subject longitudinal changes in brain structure to changes in cognitive performance and to a range of age-related covariates (r=0.92, Pcorrected < 0.001). Specifically, this CCA-mode indicated that; decreases in IQ and speed assessed tasks, higher rates of familial myocardial infarct, less physical activity, and poorer mental health are associated with larger decreases in whole brain grey matter and white matter. We found no evidence supporting the role of baseline scores as predictors of impending brain and behavioural change in late-midlife.

Cumulative Effects of Prior Concussion and Primary Sport Participation on Brain Morphometry in Collegiate Athletes: A Study From the NCAA-DoD CARE Consortium

Prior studies have reported long-term differences in brain structure (brain morphometry) as being associated with cumulative concussion and contact sport participation. There is emerging evidence to suggest that similar effects of prior concussion and contact sport participation on brain morphometry may be present in younger cohorts of active athletes. We investigated the relationship between prior concussion and primary sport participation with subcortical and cortical structures in active collegiate contact sport and non-contact sport athletes. Contact sport athletes (CS; N = 190) and matched non-contact sport athletes (NCS; N = 95) completed baseline clinical testing and participated in up to four serial neuroimaging sessions across a 6-months period. Subcortical and cortical structural metrics were derived using FreeSurfer. Linear mixed-effects (LME) models examined the effects of years of primary sport participation and prior concussion (0, 1+) on brain structure and baseline clinical variables. Athletes with prior concussion across both groups reported significantly more baseline concussion and psychological symptoms (all ps < 0.05). The relationship between years of primary sport participation and thalamic volume differed between CS and NCS (p = 0.015), driven by a significant inverse association between primary years of participation and thalamic volume in CS (p = 0.007). Additional analyses limited to CS alone showed that the relationship between years of primary sport participation and dorsal striatal volume was moderated by concussion history (p = 0.042). Finally, CS with prior concussion had larger hippocampal volumes than CS without prior concussion (p = 0.015). Years of contact sport exposure and prior concussion(s) are associated with differences in subcortical volumes in young-adult, active collegiate athletes, consistent with prior literature in retired, primarily symptomatic contact sport athletes. Longitudinal follow-up studies in these athletes are needed to determine clinical significance of current findings.

Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.

Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort

BACKGROUND

Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.

METHODS

Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.

RESULTS

CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.

CONCLUSIONS

Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

INTRODUCTION

Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.

METHODS

Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.

RESULTS

A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.

CONCLUSIONS

The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

No Evidence for Accelerated Aging-Related Brain Pathology in Treated Human Immunodeficiency Virus: Longitudinal Neuroimaging Results From the Comorbidity in Relation to AIDS (COBRA) Project

Background

Despite successful antiretroviral therapy, people living with human immunodeficiency virus (PLWH) experience higher rates of age-related morbidity, including abnormal brain structure, brain function, and cognitive impairment. This has raised concerns that PLWH may experience accelerated aging-related brain pathology.

Methods

We performed a multicenter longitudinal study of 134 virologically suppressed PLWH (median age, 56.0 years) and 79 demographically similar human immunodeficiency virus (HIV)-negative controls (median age, 57.2 years). To measure cognitive performance and brain pathology, we conducted detailed neuropsychological assessments and multimodality neuroimaging (T1-weighted, T2-weighted, diffusion magnetic resonance imaging [MRI], resting-state functional MRI, spectroscopy, arterial spin labeling) at baseline and at 2 years. Group differences in rates of change were assessed using linear mixed effects models.

Results

One hundred twenty-three PLWH and 78 HIV-negative controls completed longitudinal assessments (median interval, 1.97 years). There were no differences between PLWH and HIV-negative controls in age, sex, years of education, smoking or alcohol use. At baseline, PLWH had poorer global cognitive performance (P < .01), lower gray matter volume (P = .04), higher white matter hyperintensity load (P = .02), abnormal white matter microstructure (P < .005), and greater brain-predicted age difference (P = .01). Longitudinally, there were no significant differences in rates of change in any neuroimaging measure between PLWH and HIV-negative controls (P > .1). Cognitive performance was longitudinally stable in both groups.

Conclusions

We found no evidence that middle-aged PLWH, when receiving successful treatment, are at increased risk of accelerated aging-related brain changes or cognitive decline over 2 years.

Predictors of gait speed and its change over three years in community-dwelling older people

We aimed to assess whether and how changes in brain volume and increases in white matter hyperintensity (WMH) volume over three years predict gait speed and its change independently of demographics, vascular risk factors and physical status. We analyzed 443 individuals from the Lothian Birth Cohort 1936, at mean age 73 and 76 years. Gait speed at age 76 was predicted by age, grip strength and body mass index at mean age 73, three-year brain volume decrease and WMH volume increase, explaining 26.1% of variance. Decline in gait speed to age 76 was predicted by the same five variables explaining 40.9% of variance. In both analyses, grip strength and body mass index explained the most variance. A clinically significant decline in gait speed (≥ 0.1 m/s per year) occurred in 24.4%. These individuals had more structural brain changes. Brain volume and WMH changes were independent predictors of gait dysfunction and its three-year change, but the impact of malleable physical factors such as grip strength or body mass index was greater.

Discovering markers of healthy aging: a prospective study in a Danish male birth cohort

There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, P_corrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study.

What are the earlier life contributions to reserve and resilience?

The brain's structures and functions arise from a combination of developmental processes and interaction with environmental experiences, beginning in utero and continuing throughout the lifespan. Broadly, the process that we think of as "successful aging" likely has its foundation in early life and is continuously shaped as life experiences are programmed into the brain in response to a changing environment. Thus, individual lifestyle choices and interventions aimed at increasing cognitive reserve and resilience could change the course of cognitive aging. To determine the relative efficacy of these approaches, we will need to understand how the timing of these interventions (e.g., age, duration, frequency) influences cognitive capacity through the lifespan. Although analysis of age-related changes in cognitive function reveals a general decline at the population level, it has become clear that there is great individual variance in the extent to which cognitive function changes with advanced age. The factors responsible for the individual differences in cognitive decline are unclear, but uncovering them with new analytical tools, epigenetic approaches, and subpopulation studies will provide a roadmap toward enhancing reserve and resilience in the population at large and preserving cognitive function in a greater number of aging individuals.

Characterization of White Matter Hyperintensities in Large-Scale MRI-Studies

Background: White matter hyperintensities of presumed vascular origin (WMH) are a common finding in elderly people and a growing social malady in the aging western societies. As a manifestation of cerebral small vessel disease, WMH are considered to be a vascular contributor to various sequelae such as cognitive decline, dementia, depression, stroke as well as gait and balance problems. While pathophysiology and therapeutical options remain unclear, large-scale studies have improved the understanding of WMH, particularly by quantitative assessment of WMH. In this review, we aimed to provide an overview of the characteristics, research subjects and segmentation techniques of these studies.

Methods: We performed a systematic review according to the PRISMA statement. One thousand one hundred and ninety-six potentially relevant articles were identified via PubMed search. Six further articles classified as relevant were added manually. After applying a catalog of exclusion criteria, remaining articles were read full-text and the following information was extracted into a standardized form: year of publication, sample size, mean age of subjects in the study, the cohort included, and segmentation details like the definition of WMH, the segmentation method, reference to methods papers as well as validation measurements.

Results: Our search resulted in the inclusion and full-text review of 137 articles. One hundred and thirty-four of them belonged to 37 prospective cohort studies. Median sample size was 1,030 with no increase over the covered years. Eighty studies investigated in the association of WMH and risk factors. Most of them focussed on arterial hypertension, diabetes mellitus type II and Apo E genotype and inflammatory markers. Sixty-three studies analyzed the association of WMH and secondary conditions like cognitive decline, mood disorder and brain atrophy. Studies applied various methods based on manual (3), semi-automated (57), and automated segmentation techniques (75). Only 18% of the articles referred to an explicit definition of WMH.

Discussion: The review yielded a large number of studies engaged in WMH research. A remarkable variety of segmentation techniques was applied, and only a minority referred to a clear definition of WMH. Most addressed topics were risk factors and secondary clinical conditions. In conclusion, WMH research is a vivid field with a need for further standardization regarding definitions and used methods.

Defining Cognitive Reserve and Implications for Cognitive Aging

PURPOSE OF REVIEW

The aim of this review is to summarize current conceptual models of cognitive reserve (CR) and related concepts and to discuss evidence for these concepts within the context of aging and Alzheimer's disease.

RECENT FINDINGS

Evidence to date supports the notion that higher levels of CR, as measured by proxy variables reflective of lifetime experiences, are associated with better cognitive performance, and with a reduced risk of incident mild cognitive impairment/dementia. However, the impact of CR on longitudinal cognitive trajectories is unclear and may be influenced by a number of factors. Although there is promising evidence that some proxy measures of CR may influence structural brain measures, more research is needed. The protective effects of CR may provide an important mechanism for preserving cognitive function and cognitive well-being with age, in part because it can be enhanced throughout the lifespan. However, more research on the mechanisms by which CR is protective is needed.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE

Several imaging modalities, including T1-weighted structural imaging, diffusion tensor imaging, and functional MRI can show chronological age related changes. Employing machine learning algorithms, an individual's imaging data can predict their age with reasonable accuracy. While details vary according to modality, the general strategy is to: (1) extract image-related features, (2) build a model on a training set that uses those features to predict an individual's age, (3) validate the model on a test dataset, producing a predicted age for each individual, (4) define the "Brain Age Gap Estimate" (BrainAGE) as the difference between an individual's predicted age and his/her chronological age, (5) estimate the relationship between BrainAGE and other variables of interest, and (6) make inferences about those variables and accelerated or delayed brain aging. For example, a group of individuals with overall positive BrainAGE may show signs of accelerated aging in other variables as well. There is inevitably an overestimation of the age of younger individuals and an underestimation of the age of older individuals due to "regression to the mean." The correlation between chronological age and BrainAGE may significantly impact the relationship between BrainAGE and other variables of interest when they are also related to age. In this study, we examine the detectability of variable effects under different assumptions. We use empirical results from two separate datasets [training = 475 healthy volunteers, aged 18-60 years (259 female); testing = 489 participants including people with mood/anxiety, substance use, eating disorders and healthy controls, aged 18-56 years (312 female)] to inform simulation parameter selection. Outcomes in simulated and empirical data strongly support the proposal that models incorporating BrainAGE should include chronological age as a covariate. We propose either including age as a covariate in step 5 of the above framework, or employing a multistep procedure where age is regressed on BrainAGE prior to step 5, producing BrainAGE Residualized (BrainAGER) scores.

Effect of Ibuprofen on BrainAGE: A Randomized, Placebo-Controlled, Dose-Response Exploratory Study

BACKGROUND

The age of a person's brain can be estimated from structural brain images using an aggregate measure of variation in morphology across the whole brain. The brain age gap estimation (BrainAGE) score is computed as the difference between kernel-estimated brain age and chronological age. In this exploratory study, we investigated the application of the BrainAGE measure to identify potential novel effects of pharmacological agents on brain morphology.

METHODS

Twenty healthy participants (23-47 years of age) completed three structural magnetic resonance imaging scans 45 minutes after administration of placebo or 200 or 600 mg of ibuprofen in a double-blind, crossover study. An externally derived BrainAGE model from a sample of 480 healthy participants was used to examine the acute effect of ibuprofen on temporary neuroanatomical changes in healthy individuals.

RESULTS

The BrainAGE model produced age prediction for each participant with a mean absolute error of 6.7 years between the estimated and chronological age. The intraclass correlation coefficient for BrainAGE was 0.96. Relative to placebo, 200 and 600 mg of ibuprofen significantly decreased BrainAGE by 1.18 and 1.15 years, respectively (p < .05). The trained BrainAGE model identified the medial prefrontal cortex to be the strongest age predictor.

CONCLUSIONS

BrainAGE is a potentially useful construct to examine neurological effects of therapeutic drugs. Ibuprofen temporarily reduces BrainAGE by approximately 1 year, which is likely due to its acute anti-inflammatory effects.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

Cardiovascular symptoms and longitudinal declines in processing speed differentially predict cerebral white matter lesions in older adults

It is well established that cerebral white matter lesions (WML), present in the majority of older adults, are associated with cardiovascular and cerebrovascular diseases and also with cognitive decline. However, much less is known about how WML are related to other important individual characteristics and about the generality vs. brain region-specificity of WML. In a longitudinal study of 112 community-dwelling adults (age 50-71 years at study entry), we used a machine learning approach to evaluate the relative strength of 52 variables in association with WML burden. Variables included socio-demographic, lifestyle, and health indices-as well as multiple cognitive abilities (modeled as latent constructs using factor analysis)-repeatedly measured at three- to six-year intervals. Greater chronological age, symptoms of cardiovascular disease, and processing speed declines were most strongly linked to elevated WML burden (accounting for ∼49% of variability in WML). Whereas frontal lobe WML burden was associated both with elevated cardiovascular symptoms and declines in processing speed, temporal lobe WML burden was only significantly associated with declines in processing speed. These latter outcomes suggest that age-related WML-cognition associations may be etiologically heterogeneous across fronto-temporal cerebral regions.

Allostatic load as a predictor of grey matter volume and white matter integrity in old age: The Whitehall II MRI study

The allostatic load index quantifies the cumulative multisystem physiological response to chronic everyday stress, and includes cardiovascular, metabolic and inflammatory measures. Despite its central role in the stress response, research of the effect of allostatic load on the ageing brain has been limited. We investigated the relation of mid-life allostatic load index and multifactorial predictors of stroke (Framingham stroke risk) and diabetes (metabolic syndrome) with voxelwise structural grey and white matter brain integrity measures in the ageing Whitehall II cohort (N = 349, mean age = 69.6 (SD 5.2) years, N (male) = 281 (80.5%), mean follow-up before scan = 21.4 (SD 0.82) years). Higher levels of all three markers were significantly associated with lower grey matter density. Only higher Framingham stroke risk was significantly associated with lower white matter integrity (low fractional anisotropy and high mean diffusivity). Our findings provide some empirical support for the concept of allostatic load, linking the effect of everyday stress on the body with features of the ageing human brain.

Healthy cognitive ageing in the Lothian Birth Cohort studies: marginal gains not magic bullet

In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.