The relation between APOE genotype and cerebral microbleeds in cognitively unimpaired middle- and old-aged individuals

Meta-Analysis of White Matter Hyperintensity Volume Differences Between APOE ε4 Carriers and Noncarriers

Several studies have suggested that white matter hyperintensity volume (WMHV) is increased among apolipoprotein E (APOE) ε4 carriers while others have reported contradictory findings. Although APOE ε4 carriage is associated with greater AD pathology, it remains unclear whether cerebrovascular damage is also associated with APOE ε4 carriage. The aim of this meta-analysis was to determine whether WMHV is associated with APOE ε4 carrier status. 12 studies that were included yielded a total sample size of 16,738 adult subjects (ε4 carrier n = 4,721; ε4 noncarrier n = 12,017). There were no significant differences in WMHV between ε4 carriers and noncarriers (Hedge's g = 0.07; 95% CI (-0.01 to 0.15), P = 0.09). Subgroup analysis of community-based studies (n = 8) indicated a small effect size where ε4 carriers had greater WMHV relative to noncarriers (Hedge's g = 0.09 95% CI (0.02 to 0.16), P = 0.008). Among clinic-based studies (n = 3) there was no significant difference in WMHV by APOE ε4 carrier status (Hedge's g = -0.09, 95% CI (-0.60 to 0.41), P = 0.70). Observed APOE ε4-associated WMHV differences may be context-dependent and may also be confounded by a lack of standardization for WMHV segmentation.

Genetic characterization of the ALFA study: Uncovering genetic profiles in the Alzheimer's continuum

INTRODUCTION

In 2013, the ALzheimer's and FAmilies (ALFA) project was established to investigate pathophysiological changes in preclinical Alzheimer's disease (AD), and to foster research on early detection and preventive interventions.

METHODS

We conducted a comprehensive genetic characterization of ALFA participants with respect to neurodegenerative/cerebrovascular diseases, AD biomarkers, brain endophenotypes, risk factors and aging biomarkers. We placed particular emphasis on amyloid/tau status and assessed gender differences. Multiple polygenic risk scores were computed to capture different aspects of genetic predisposition. We additionally compared AD risk in ALFA to that across the full disease spectrum from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

Results show that the ALFA project has been successful at establishing a cohort of cognitively unimpaired individuals at high genetic predisposition of AD.

DISCUSSION

It is, therefore, well-suited to study early pathophysiological changes in the preclinical AD continuum. Highlights Prevalence of ε4 carriers in ALzheimer and FAmilies (ALFA) is higher than in the general European population The ALFA study is highly enriched in Alzheimer's disease (AD) genetic risk factors beyond APOE AD genetic profiles in ALFA are similar to clinical groups along the continuum ALFA has succeeded in establishing a cohort of cognitively unimpaired individuals at high genetic AD risk ALFA is well suited to study pathogenic events/early pathophysiological changes in AD.

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level.

Association of statin use and lipid levels with cerebral microbleeds and intracranial hemorrhage in patients with atrial fibrillation: A prospective cohort study

BACKGROUND

An increased risk of intracranial hemorrhage (ICH) associated with statins has been reported, but data on the relationship between statin use and cerebral microbleeds (CMBs) in patients with atrial fibrillation (AF), a population at high bleeding and cardiovascular risk, are lacking.

AIMS

To explore the association between statin use and blood lipid levels with the prevalence and progression of CMBs in patients with AF with a particular focus on anticoagulated patients.

METHODS

Data of Swiss-AF, a prospective cohort of patients with established AF, were analyzed. Statin use was assessed during baseline and throughout follow-up. Lipid values were measured at baseline. CMBs were assessed using magnetic resonance imagining (MRI) at baseline and at 2 years follow-up. Imaging data were centrally assessed by blinded investigators. Associations of statin use and low-density lipoprotein (LDL) levels with CMB prevalence at baseline or CMB progression (at least one additional or new CMB on follow-up MRI at 2 years compared with baseline) were assessed using logistic regression models; the association with ICH was assessed using flexible parametric survival models. Models were adjusted for hypertension, smoking, body mass index, diabetes, stroke/transient ischemic attack, coronary heart disease, antiplatelet use, anticoagulant use, and education.

RESULTS

Of the 1693 patients with CMB data at baseline MRI (mean ± SD age 72.5 ± 8.4 years, 27.6% women, 90.1% on oral anticoagulants), 802 patients (47.4%) were statin users. The multivariable adjusted odds ratio (adjOR) for CMBs prevalence at baseline for statin users was 1.10 (95% CI = 0.83-1.45). AdjOR for 1 unit increase in LDL levels was 0.95 (95% CI = 0.82-1.10). At 2 years, 1188 patients had follow-up MRI. CMBs progression was observed in 44 (8.0%) statin users and 47 (7.4%) non-statin users. Of these patients, 64 (70.3%) developed a single new CMB, 14 (15.4%) developed 2 CMBs, and 13 developed more than 3 CMBs. The multivariable adjOR for statin users was 1.09 (95% CI = 0.66-1.80). There was no association between LDL levels and CMB progression (adjOR 1.02, 95% CI = 0.79-1.32). At follow-up 14 (1.2%) statin users had ICH versus 16 (1.3%) non-users. The age and sex adjusted hazard ratio (adjHR) was 0.75 (95% CI = 0.36-1.55). The results remained robust in sensitivity analyses excluding participants without anticoagulants.

CONCLUSIONS

In this prospective cohort of patients with AF, a population at increased hemorrhagic risk due to anticoagulation, the use of statins was not associated with an increased risk of CMBs.

The iron burden of cerebral microbleeds contributes to brain atrophy through the mediating effect of white matter hyperintensity

The goal of this work was to explore the total iron burden of cerebral microbleeds (CMBs) using a semi-automatic quantitative susceptibility mapping and to establish its effect on brain atrophy through the mediating effect of white matter hyperintensities (WMH). A total of 95 community-dwelling people were enrolled. Quantitative susceptibility mapping (QSM) combined with a dynamic programming algorithm (DPA) was used to measure the characteristics of 1309 CMBs. WMH were evaluated according to the Fazekas scale, and brain atrophy was assessed using a 2D linear measurement method. Histogram analysis was used to explore the distribution of CMBs susceptibility, volume, and total iron burden, while a correlation analysis was used to explore the relationship between volume and susceptibility. Stepwise regression analysis was used to analyze the risk factors for CMBs and their contribution to brain atrophy. Mediation analysis was used to explore the interrelationship between CMBs and brain atrophy. We found that the frequency distribution of susceptibility of the CMBs was Gaussian in nature with a mean of 201 ppb and a standard deviation of 84 ppb; however, the volume and total iron burden of CMBs were more Rician in nature. A weak but significant correlation between the susceptibility and volume of CMBs was found (r = -0.113, P < 0.001). The periventricular WMH (PVWMH) was a risk factor for the presence of CMBs (number: β = 0.251, P = 0.014; volume: β = 0.237, P = 0.042; total iron burden: β = 0.238, P = 0.020) and was a risk factor for brain atrophy (third ventricle width: β = 0.325, P = 0.001; Evans's index: β = 0.323, P = 0.001). PVWMH had a significant mediating effect on the correlation between CMBs and brain atrophy. In conclusion, QSM along with the DPA can measure the total iron burden of CMBs. PVWMH might be a risk factor for CMBs and may mediate the effect of CMBs on brain atrophy.

The use of neuroimaging techniques in the early and differential diagnosis of dementia

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA

INTRODUCTION

Little is known about the epidemiology of brain microbleeds in racially/ethnically diverse populations.

METHODS

In the Multi-Ethnic Study of Atherosclerosis, brain microbleeds were identified from 3T magnetic resonance imaging susceptibility-weighted imaging sequences using deep learning models followed by radiologist review.

RESULTS

Among 1016 participants without prior stroke (25% Black, 15% Chinese, 19% Hispanic, 41% White, mean age 72), microbleed prevalence was 20% at age 60 to 64.9 and 45% at ≥85 years. Deep microbleeds were associated with older age, hypertension, higher body mass index, and atrial fibrillation, and lobar microbleeds with male sex and atrial fibrillation. Overall, microbleeds were associated with greater white matter hyperintensity volume and lower total white matter fractional anisotropy.

DISCUSSION

Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.

Advances in the Study of APOE and Innate Immunity in Alzheimer's Disease

Alzheimer's disease (AD) is a progressive degenerative disease of the nervous system (CNS) with an insidious onset. Clinically, it is characterized by a full range of dementia manifestations including memory impairment, aphasia, loss of speech, loss of use, loss of recognition, impairment of visuospatial skills, and impairment of executive function, as well as changes in personality and behavior. The exact cause of AD has not yet been identified. Nevertheless, modern research indicates that genetic factors contribute to 70% of human's risk of AD. Apolipoprotein (APOE) accounts for up to 90% of the genetic predisposition. APOE is a crucial gene that cannot be overstated. In addition, innate immunity plays a significant role in the etiology and treatment of AD. Understanding the different subtypes of APOE and their interconnections is of paramount importance. APOE and innate immunity, along with their relationship to AD, are primary research motivators for in-depth research and clinical trials. The exploration of novel technologies has led to an increasing trend in the study of AD at the cellular and molecular levels and continues to make more breakthroughs and progress. As of today, there is no effective treatment available for AD around the world. This paper aims to summarize and analyze the role of APOE and innate immunity, as well as development trends in recent years. It is anticipated that APOE and innate immunity will provide a breakthrough for humans to hinder AD progression in the near future.

Cerebral microbleeds is associated with dementia in Parkinson's disease

INTRODUCTION

Emerging evidence suggests that cerebral small vessel disease (CSVD) may worsen cognitive functions in Parkinson's disease (PD). However, the effect of microbleeds on cognitive function in patients with PD remains unknown. This study explored the association between the presence, number and location of microbleeds with dementia in PD patients.

METHODS

This cross-sectional study included 431 patients with PD from Beijing Tiantan Hospital from May 2016 to August 2019. Cognition assessments (MMSE, MoCA) were performed for these patients. MRI imaging sequences were obtained and reviewed independently by two well-trained readers who were blind to all clinical data. Spearman's correlation analysis and logistic regression model analysis were further used for the assessments.

RESULTS

An association between cerebral microbleeds with cognitive ability and dementia in PD patients was revealed. A significance was observed between the total number of microbleeds and two widely used scores of cognitive assessments (Spearman R = - 0.120 to MMSE with a p = 0.016, and - 0.117 to MoCA with a p = 0.020). In detail, infratentorial microbleeds were associated with the level of cognition in PD patients (Spearman R = - 0.099 to MMSE with a p = 0.049, and - 0.116 to MoCA with a p = 0.021). Furthermore, logistic regression analysis results also confirmed such correlations between the number of microbleeds and cognitive ability after adjusting for age, cholesterol level, Hamilton Anxiety Scale, Hamilton Depression Scale, and white matter hyperintensity Fazekas score (OR 3.28, p = 0.035, 95% CI 1.090-9.892).

CONCLUSIONS

The occurrence of microbleeds, especially in the infratentorial locations, may worsen the cognitive function of PD patients and result in dementia. Management of cerebral vascular disease could be beneficial to patients with PD.

Machine learning approach for hemorrhagic transformation prediction: Capturing predictors' interaction

Background and purpose

Patients with ischemic stroke frequently develop hemorrhagic transformation (HT), which could potentially worsen the prognosis. The objectives of the current study were to determine the incidence and predictors of HT, to evaluate predictor interaction, and to identify the optimal predicting models.

Methods

A prospective study included 360 patients with ischemic stroke, of whom 354 successfully continued the study. Patients were subjected to thorough general and neurological examination and T2 diffusion-weighted MRI, at admission and 1 week later to determine the incidence of HT. HT predictors were selected by a filter-based minimum redundancy maximum relevance (mRMR) algorithm independent of model performance. Several machine learning algorithms including multivariable logistic regression classifier (LRC), support vector classifier (SVC), random forest classifier (RFC), gradient boosting classifier (GBC), and multilayer perceptron classifier (MLPC) were optimized for HT prediction in a randomly selected half of the sample (training set) and tested in the other half of the sample (testing set). The model predictive performance was evaluated using receiver operator characteristic (ROC) and visualized by observing case distribution relative to the models' predicted three-dimensional (3D) hypothesis spaces within the testing dataset true feature space. The interaction between predictors was investigated using generalized additive modeling (GAM).

Results

The incidence of HT in patients with ischemic stroke was 19.8%. Infarction size, cerebral microbleeds (CMB), and the National Institute of Health stroke scale (NIHSS) were identified as the best HT predictors. RFC (AUC: 0.91, 95% CI: 0.85-0.95) and GBC (AUC: 0.91, 95% CI: 0.86-0.95) demonstrated significantly superior performance compared to LRC (AUC: 0.85, 95% CI: 0.79-0.91) and MLPC (AUC: 0.85, 95% CI: 0.78-0.92). SVC (AUC: 0.90, 95% CI: 0.85-0.94) outperformed LRC and MLPC but did not reach statistical significance. LRC and MLPC did not show significant differences. The best models' 3D hypothesis spaces demonstrated non-linear decision boundaries suggesting an interaction between predictor variables. GAM analysis demonstrated a linear and non-linear significant interaction between NIHSS and CMB and between NIHSS and infarction size, respectively.

Conclusion

Cerebral microbleeds, NIHSS, and infarction size were identified as HT predictors. The best predicting models were RFC and GBC capable of capturing nonlinear interaction between predictors. Predictor interaction suggests a dynamic, rather than, fixed cutoff risk value for any of these predictors.

CAIDE dementia risk score relates to severity and progression of cerebral small vessel disease in healthy midlife adults: the PREVENT-Dementia study

BACKGROUND

Markers of cerebrovascular disease are common in dementia, and may be present before dementia onset. However, their clinical relevance in midlife adults at risk of future dementia remains unclear. We investigated whether the Cardiovascular Risk Factors, Ageing and Dementia (CAIDE) risk score was associated with markers of cerebral small vessel disease (SVD), and if it predicted future progression of SVD. We also determined its relationship to systemic inflammation, which has been additionally implicated in dementia and SVD.

METHODS

Cognitively healthy midlife participants were assessed at baseline (n=185) and 2-year follow-up (n=158). To assess SVD, we quantified white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), microbleeds and lacunes. We derived composite scores of SVD burden, and subtypes of hypertensive arteriopathy and cerebral amyloid angiopathy. Inflammation was quantified using serum C-reactive protein (CRP) and fibrinogen.

RESULTS

At baseline, higher CAIDE scores were associated with all markers of SVD and inflammation. Longitudinally, CAIDE scores predicted greater total (p<0.001), periventricular (p<0.001) and deep (p=0.012) WMH progression, and increased CRP (p=0.017). Assessment of individual CAIDE components suggested that markers were driven by different risk factors (WMH/EPVS: age/hypertension, lacunes/deep microbleeds: hypertension/obesity). Interaction analyses demonstrated that higher CAIDE scores amplified the effect of age on SVD, and the effect of WMH on poorer memory.

CONCLUSION

Higher CAIDE scores, indicating greater risk of dementia, predicts future progression of both WMH and systemic inflammation. Findings highlight the CAIDE score's potential as both a prognostic and predictive marker in the context of cerebrovascular disease, identifying at-risk individuals who might benefit most from managing modifiable risk.

Resistance to developing brain pathology due to vascular risk factors: the role of educational attainment

Brain pathology develops at different rates between individuals with similar burden of risk factors, possibly explained by brain resistance. We examined if education contributes to brain resistance by studying its influence on the association between vascular risk factors and brain pathology. In 4111 stroke-free and dementia-free community-dwelling participants (62.9 ± 10.7 years), we explored the association between vascular risk factors (hypertension and the Framingham Stroke Risk Profile [FRSP]) and imaging markers of brain pathology (markers of cerebral small vessel disease and brain volumetry), stratified by educational attainment level. Associations of hypertension and FSRP with markers of brain pathology were not significantly different between levels of educational attainment. Certain associations appeared weaker in those with higher compared to lower educational attainment, particularly for white matter hyperintensities (WMH). Supplementary residual analyses showed significant associations between higher educational attainment and stronger resistance to WMH among others. Our results suggest a role for educational attainment in resistance to vascular brain pathology. Yet, further research is needed to better characterize determinants of brain resistance.

DHA intake relates to better cerebrovascular and neurodegeneration neuroimaging phenotypes in middle-aged adults at increased genetic risk of Alzheimer disease

BACKGROUND

The number of APOE-ε4 alleles is a major nonmodifiable risk factor for sporadic Alzheimer disease (AD). There is increasing evidence on the benefits of dietary DHA (22:6n-3) before the onset of AD symptoms, particularly in APOE-ε4 carriers. Brain alterations in the preclinical stage can be detected by structural MRI.

OBJECTIVES

We aimed, in middle-aged cognitively unimpaired individuals at increased risk of AD, to cross-sectionally investigate whether dietary DHA intake relates to cognitive performance and to MRI-based markers of cerebral small vessel disease and AD-related neurodegeneration, exploring the effect modification by APOE-ε4 status.

METHODS

In 340 participants of the ALFA (ALzheimer and FAmilies) study, which is enriched for APOE-ε4 carriership (n = 122, noncarriers; n = 157, 1 allele; n = 61, 2 alleles), we assessed self-reported DHA intake through an FFQ. We measured cognitive performance by administering episodic memory and executive function tests. We performed high-resolution structural MRI to assess cerebral small vessel disease [white matter hyperintensities (WMHs) and cerebral microbleeds (CMBs)] and AD-related brain atrophy (cortical thickness in an AD signature). We constructed regression models adjusted for potential confounders, exploring the interaction DHA × APOE-ε4.

RESULTS

We observed no significant associations between DHA and cognitive performance or WMH burden. We observed a nonsignificant inverse association between DHA and prevalence of lobar CMBs (OR: 0.446; 95% CI: 0.195, 1.018; P = 0.055). DHA was found to be significantly related to greater cortical thickness in the AD signature in homozygotes but not in nonhomozygotes (P-interaction = 0.045). The association strengthened when analyzing homozygotes and nonhomozygotes matched for risk factors.

CONCLUSIONS

In cognitively unimpaired APOE-ε4 homozygotes, dietary DHA intake related to structural patterns that may result in greater resilience to AD pathology. This is consistent with the current hypothesis that those subjects at highest risk would obtain the largest benefits from DHA supplementation in the preclinical stage.This trial was registered at clinicaltrials.gov as NCT01835717.

The sequence of structural, functional and cognitive changes in multiple sclerosis

BACKGROUND

As disease progression remains poorly understood in multiple sclerosis (MS), we aim to investigate the sequence in which different disease milestones occur using a novel data-driven approach.

METHODS

We analysed a cohort of 295 relapse-onset MS patients and 96 healthy controls, and considered 28 features, capturing information on T2-lesion load, regional brain and spinal cord volumes, resting-state functional centrality ("hubness"), microstructural tissue integrity of major white matter (WM) tracts and performance on multiple cognitive tests. We used a discriminative event-based model to estimate the sequence of biomarker abnormality in MS progression in general, as well as specific models for worsening physical disability and cognitive impairment.

RESULTS

We demonstrated that grey matter (GM) atrophy of the cerebellum, thalamus, and changes in corticospinal tracts are early events in MS pathology, whereas other WM tracts as well as the cognitive domains of working memory, attention, and executive function are consistently late events. The models for disability and cognition show early functional changes of the default-mode network and earlier changes in spinal cord volume compared to the general MS population. Overall, GM atrophy seems crucial due to its early involvement in the disease course, whereas WM tract integrity appears to be affected relatively late despite the early onset of WM lesions.

CONCLUSION

Data-driven modelling revealed the relative occurrence of both imaging and non-imaging events as MS progresses, providing insights into disease propagation mechanisms, and allowing fine-grained staging of patients for monitoring purposes.