Cerebrovascular disease affects brain structural integrity long before clinically overt strokes

Prevention of dementia in an ageing world: Evidence and biological rationale

As the population ages, the number of people with dementia is expected to increase in the coming decades, with consequences at the societal and individual levels. In this narrative review, we provide a summary of the scientific evidence concerning dementia prevention, with a focus on the following three strategies: 1) Targeting the body to protect the brain, including prevention and treatment of cardiovascular morbidity; 2) Compensatory interventions to counteract brain ageing, including education and life-long engagement in cognitively and socially stimulating activities; and 3) Lifespan health promotion, such as a physically active lifestyle, smoking cessation, and a healthy and balanced diet. Next, we consider the biological mechanisms by which these strategies may act by taking into account the main pathways implicated in the development and progression of dementia: neurodegeneration, brain resilience, vascular damage, neuroinflammation, and oxidative stress. Based on the current evidence, and in line with the declining trends of dementia incidence in high-income countries, we conclude that timely multidomain preventive actions are promising strategies to reduce the dementia epidemic worldwide. There is still a considerable gap between the epidemiological evidence and its underlying biological mechanisms. Filling this gap will be crucial to move forward in dementia prevention worldwide.

Degeneration of structural brain networks is associated with cognitive decline after ischaemic stroke

Over one-third of stroke patients has long-term cognitive impairment. The likelihood of cognitive dysfunction is poorly predicted by the location or size of the infarct. The macro-scale damage caused by ischaemic stroke is relatively localized, but the effects of stroke occur across the brain. Structural covariance networks represent voxelwise correlations in cortical morphometry. Atrophy and topographical changes within such distributed brain structural networks may contribute to cognitive decline after ischaemic stroke, but this has not been thoroughly investigated. We examined longitudinal changes in structural covariance networks in stroke patients and their relationship to domain-specific cognitive decline. Seventy-three patients (mean age, 67.41 years; SD = 12.13) were scanned with high-resolution magnetic resonance imaging at sub-acute (3 months) and chronic (1 year) timepoints after ischaemic stroke. Patients underwent a number of neuropsychological tests, assessing five cognitive domains including attention, executive function, language, memory and visuospatial function at each timepoint. Individual-level structural covariance network scores were derived from the sub-acute grey-matter probabilistic maps or changes in grey-matter probability maps from sub-acute to chronic using data-driven partial least squares method seeding at major nodes in six canonical high-order cognitive brain networks (i.e. dorsal attention, executive control, salience, default mode, language-related and memory networks). We then investigated co-varying patterns between structural covariance network scores within canonical distributed brain networks and domain-specific cognitive performance after ischaemic stroke, both cross-sectionally and longitudinally, using multivariate behavioural partial least squares correlation approach. We tested our models in an independent validation data set with matched imaging and behavioural testing and using split-half validation. We found that distributed degeneration in higher-order cognitive networks was associated with attention, executive function, language, memory and visuospatial function impairment in sub-acute stroke. From the sub-acute to the chronic timepoint, longitudinal structural co-varying patterns mirrored the baseline structural covariance networks, suggesting synchronized grey-matter volume decline occurred within established networks over time. The greatest changes, in terms of extent of distributed spatial co-varying patterns, were in the default mode and dorsal attention networks, whereas the rest were more focal. Importantly, faster degradation in these major cognitive structural covariance networks was associated with greater decline in attention, memory and language domains frequently impaired after stroke. Our findings suggest that sub-acute ischaemic stroke is associated with widespread degeneration of higher-order structural brain networks and degradation of these structural brain networks may contribute to longitudinal domain-specific cognitive dysfunction.

Predicted Brain Age After Stroke

Aging is a known non-modifiable risk factor for stroke. Usually, this refers to chronological rather than biological age. Biological brain age can be estimated based on cortical and subcortical brain measures. For stroke patients, it could serve as a more sensitive marker of brain health than chronological age. In this study, we investigated whether there is a difference in brain age between stroke survivors and control participants matched on chronological age. We estimated brain age at 3 months after stroke, and then followed the longitudinal trajectory over three time-points: within 6 weeks (baseline), at 3 and at 12 months following their clinical event. We found that brain age in stroke participants was higher compared to controls, with the mean difference between the groups varying between 3.9 and 8.7 years depending on the brain measure used for prediction. This difference in brain age was observed at 6 weeks after stroke and maintained at 3 and 12 months after stroke. The presence of group differences already at baseline suggests that stroke might be an ultimate manifestation of gradual cerebrovascular burden accumulation and brain degeneration. Brain age prediction, therefore, has the potential to be a useful biomarker for quantifying stroke risk.

The Post Ischaemic Stroke Cardiovascular Exercise Study: Protocol for a randomised controlled trial of fitness training for brain health

INTRODUCTION

Compared to healthy individuals, stroke patients have five times the rate of dementia diagnosis within three years. Aerobic exercise may induce neuroprotective mechanisms that help to preserve, and even increase, brain volume and cognition. We seek to determine whether aerobic fitness training helps to protect brain volume and cognitive function after stroke compared to an active, non-aerobic control.

METHODS

In this Phase IIb, single blind, randomised controlled trial, 100 ischaemic stroke participants, recruited at two months post-stroke, will be randomly allocated to either the intervention (aerobic and strength exercise) or active control (stretching and balance training). Participants will attend one-hour, individualised exercise sessions, three days-per-week for eight weeks. Assessments at two months (baseline), four months (post-intervention), and one year (follow-up) post-stroke will measure brain volume, cognition, mood, cardiorespiratory fitness, physical activity, blood pressure and blood biomarkers.Study outcome: Our primary outcome measure is hippocampal volume at four months after stroke. We hypothesise that participants who undertake the prescribed intervention will have preserved hippocampal volume at four months compared to the control group. We also hypothesise that this group will have preserved total brain volume and cognition, better mood, fitness, and higher levels of physical activity, than those receiving stretching and balance training.

DISCUSSION

The promise of exercise training to prevent, or slow, the accelerated rates of brain atrophy and cognitive decline experienced by stroke survivors needs to be tested. Post Ischaemic Stroke Cardiovascular Exercise Study has the potential, if proven efficacious, to identify a new treatment that could be readily translated to the clinic.