Higher White Matter Hyperintensities Research Articles

The influence of vascular pathology on the generalizability of machine learning models for cognitive performance estimation

AbstractBackgroundImage‐based machine learning models are promising to aid diagnosis in dementia, e.g. by diagnostic classification or estimating cognitive performance. However, the contribution of vascular pathology is often ignored, although many patients have mixed pathologies. This may hamper model generalizability from research setting to clinical practice, as the models are generally developed on populations with lower vascular burden than is encountered clinically. This study aims to evaluate whether model generalizability is influenced by differences in vascular pathology load between training and test groups, represented by white matter hyperintensities (WMHs).MethodWe developed a convolutional neural network to estimate cognitive performance through ADAS13. We included 4791 timepoints from 1632 ADNI subjects. To mimic differences in vascular burden between research and clinical populations, we split the data into a low, middle and high WMH load group using WMH ratio tertiles (WMH volume corrected for intracranial volume). The model was applied to maps derived from T1‐weighted and FLAIR brain MRI using voxel‐based morphometry: model 1 (gray matter density map (GMDM), age, sex), model 2 (GMDM, WMH density map (WMHDM), age, sex) and model 3 (GMDM, log(WMH ratio), age, sex) (Fig. 1). First, we trained all models on the low WMH load group, meaning to test on the high WMH load group to assess generalizability. Second, we trained models 1 and 2 on all data. Mean Absolute Error (MAE) served as the performance metric.ResultThe models trained on the low WMH load group (MAE = 5.08 – 5.41) performed similar to constant value prediction (MAE = 5.63) (Fig. 2, circles). Using all data, models did train successfully (model 1: MAE = 5.64, model 2: MAE = 6.31, constant value: MAE = 7.39) (Fig. 2, crosses). Because of the suboptimal model training in the low WMH load group, especially for individuals with higher ADAS13 scores which were underrepresented in the data (Fig. 3), we could not evaluate generalizability to the high WMH load group.ConclusionThis study was unable to provide new insight into the influence of vascular pathology on the generalizability of machine learning models in dementia. More clinically representative data is needed, covering the full cognitive performance spectrum and higher vascular pathology loads.

Association of self‐reported and objective sleep parameters with hippocampus and white matter hyperintensities volumes in a community‐dwelling older adults

AbstractBackgroundNumerous studies report that sleep disturbances are associated with brain alterations; yet, results still remain controversial. Our aim was thus to examine the associations between self‐reported and objective sleep parameters, and volumes of hippocampus and white matter hyperintensities (WMH).MethodThis cross‐sectional analysis used data from the French ESPRIT study. At baseline, 718 participants aged 65‐80 underwent a brain magnetic resonance imaging examination. Among them, 675 had hippocampus volume data and 712 had WMH volume data. They also completed a sleep questionnaire at baseline and 167 participants underwent an ambulatory polysomnography to assess their objective sleep. Logistic regression models were performed and minimally adjusted for age, sex, educational level, and APOE ε4 status to assess the associations between sleep parameters and volumes of hippocampus and WMH.ResultThe participants’ mean age at baseline was 71.4 years (±4.0) and 51.3% were women. We found that a short (≤6 hours) but also a long (≥9 hours) 24‐hour sleep duration, a late (>8 am) get‐up time and a low score at the Epworth Severity Scale were associated with a low hippocampal volume. However, these associations did not remain significant after false discovery rate (FDR) correction. We also observed, even after FDR correction, that an early get‐up time (≤6 am) and having difficulty in initiating sleep were associated with a high WMH volume whereas a late bedtime (≥11 pm) was associated with a low WMH volume. Regarding objective data, longer rapid eye movement sleep and slow wave sleep durations were associated with a low WMH volume, and a higher number of periodic leg movements during sleep was associated with a high WMH volume; but these associations were not significant after FDR correction. All the results remained similar after taking into account intracranial volume.ConclusionIn this population‐based study in older adults, the most robust findings concerned higher WMH volume for participants with early get‐up time, difficulties in initiating sleep or late bedtime. Overall, these results are consistent with the general view that there may be specific types of sleep parameters that can play a role in brain alterations.

Association of white matter hyperintensity burden and cognitive performance in young‐aged, middle‐aged and old‐aged participants: Results of the population‐based 1000BRAINS study

AbstractBackgroundSome individuals seem less susceptible to the effect of high white matter hyperintensity (WMH) load on cognition reflecting differences in individual cognitive reserve (CR). Little is known about young‐ or middle‐aged participants. The aim of the present study was to examine (1) the effect of WMH on global cognition in three different age groups and (2) if education (as proxy for CR) moderates this association.MethodWe included 707 healthy participants (18‐85 years) without evidence of cardiovascular/neurological disease (young‐aged: 18‐44 years (Ø33.5±6.7): n = 108; middle‐aged: 45‐65 years (Ø57.9±5.5): n = 341; old‐aged: >65 years (Ø72.0±4.1): n = 258) from the population‐based 1000BRAINS study. An extensive cognitive assessment was conducted. The sum of all cognitive domain z‐scores defined the global score. Education was classified according to the International Standard Classification of Education as total years of formal education, combining school and vocational training. Magnetic resonance imaging (MRI) was carried out on a 3‐Tesla‐MR‐scanner (Tim‐TRIO, Siemens Medical Systems, Erlangen, Germany). WMH volume was determined using the Brain‐Intensity‐Abnormality‐Classification‐Algorithm. The associations of global cognition as outcome with WMH volume (in cm3) as predictor were analyzed using linear models (PROCESS v4.1 macro for SPPS) stratified by age group resulting in regression coefficient b with 95% confidence intervals (CI; adjusted for age, sex, depression, diabetes mellitus). To examine moderation effects of education, all models contained an interaction term (WMH x education).ResultHigher WMH volume was associated with lower global cognition in middle‐aged participants (b:‐0.27 (‐0.52 to ‐0.03, all reported results are fully adjusted). This effect was moderated by education (interaction term: b:‐0.07 (‐0.014 to ‐0.01)). In the young‐aged group, the association between WMH load and cognition was ‐1.27 (‐3.30 to 0.77). No association was found in the old‐aged group (b: ‐0.03 (‐0.20 to 0.14)).ConclusionHigher WMH load was associated with lower cognitive performance only in middle‐aged participants and was moderated to a small degree by education. Overall, the influence of WMH on global cognition in our cohort of healthy participants seems limited. Future analyses will focus on specific cognitive domains that might be more vulnerable to higher WMH load and will examine participants with certain cardiovascular risk profile.

Association of Cerebrovascular Imaging Biomarkers, Depression, and Anxiety, with Mild Cognitive Impairment.

The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.

1 Quantifying the Role of Social Determinants of Health in Racial Disparities

Objective:In the United States, Black individuals have suffered from 300 years of racism, bias, segregation and have been systematically and intentionally denied opportunities to accrue wealth. These disadvantages have resulted in disparities in health outcomes. Over the last decade there has been a growing interest in examining social determinants of health as upstream factors that lead to downstream health disparities. It is of vital importance to quantify the contribution of SDH factors to racial disparities in order to inform policy and social justice initiatives. This demonstration project uses years of education and white matter hyperintensities (WMH) to illustrate two methods of quantifying the role of a SDH in producing health disparities.Participants and Methods:The current study is a secondary data analysis of baseline data from a subset of the National Alzheimer's Coordinating Center database with neuroimaging data collected from 2002-2019. Participants were 997 cognitively diverse, Black and White (10.4% Black) individuals, aged 60-94 (mean=73.86, 56.5% female), mean education of 15.18 years (range= 0-23, SD=3.55). First, mediation, was conducted in the SEM framework using the R package lavaan. Black/White race was the independent variable, education was the mediator, WMH volume was the dependent variable, and age/sex were the covariates. Bootstrapped standard errors were calculated using 1000 iterations. The indirect effect was then divided by the total effect to determine the proportion of the total effect attributable to education. Second, a population attributable fraction (PAF) or the expected reduction in WMH if we eliminated low education and structural racism for which Black serves as a proxy was calculated. Two logistic regressions with dichotomous (median split) WMH as the dependent variable, first with low (less than high school) versus high education, and second with Black/White race added as predictors. Age/sex were covariates. PAF of education, and then of Black/White race controlling for education were obtained. Subsequently, a combined PAF was calculated.Results:In the lavaan model, the total effect of Black/White race on WMH was not significant (B=.040, se=.113, p=.246); however, Black/White race significantly predicted education (B= -.108, se=.390, p=.001) and education significantly predicted WMH burden (B=-.084, se=.008, p=.002). This resulted in a significant indirect effect (effect=.009, se=.014, p=.032). 22.6 % of the relationship between Black/White race and WMH was mediated by education. In the logistic models, the PAF of education was 5.3% and the additional PAF of Black/White race was 2.7%. The combined PAF of Black race and low education was 7.8%.Conclusions:From our mediation we can conclude that 22.6% of the relationship between Black/White race and WMH volume is explained by education. Our PAF analysis suggests that we could reduce 7.8% of the cases with high WMH burden if we eliminated low education and the structural racism for which Black serves as a proxy. This is an under estimation of the role that education and structural racism play in WMH burden due to our positively selected sample and crude measure of education. However, these methods can help researchers quantify the contribution of SDH to disparities in older adulthood and provide targets for policy change.

Ambient Air Pollution Exposure and Cerebral White Matter Hyperintensities in Older Adults: A Cross-Sectional Analysis in the Three-City Montpellier Study.

Growing epidemiological evidence suggests an adverse relationship between exposure to air pollutants and cognitive health, and this could be related to the effect of air pollution on vascular health. We aim to evaluate the association between air pollution exposure and a magnetic resonance imaging (MRI) marker of cerebral vascular burden, white matter hyperintensities (WMH). This cross-sectional analysis used data from the French Three-City Montpellier study. Randomly selected participants 65-80 years of age underwent an MRI examination to estimate their total and regional cerebral WMH volumes. Exposure to fine particulate matter (), nitrogen dioxide (), and black carbon (BC) at the participants' residential address during the 5 years before the MRI examination was estimated with land use regression models. Multinomial and binomial logistic regression assessed the associations between exposure to each of the three pollutants and categories of total and lobar WMH volumes. Participants' () median age at MRI was 70.7 years [interquartile range (IQR): 6.1], and 52% () were women. Median exposure to air pollution over the 5 years before MRI acquisition was 24.3 (IQR: 1.7) for , 48.9 (14.6) for , and 2.66 (0.60) for BC. We found no significant association between exposure to the three air pollutants and total WMH volume. We found that exposure was significantly associated with higher risk of temporal lobe WMH burden [odds ratio (OR) for an (95% confidence interval: 1.41, 2.36) for the second volume tercile, 2.04 (1.59, 2.61) for the third volume tercile, reference: first volume tercile]. Associations for other regional WMH volumes were inconsistent. In this population-based study in older adults, exposure was associated with increased risk of high WMH volume in the temporal lobe, strengthening the evidence on adverse effect on the brain. Further studies looking at different markers of cerebrovascular damage are still needed to document the potential vascular effects of air pollution. https://doi.org/10.1289/EHP12231.

The Relationship of MRI-Derived Alzheimer's and Cerebrovascular-Related Signatures With Level of and Change in Health and Financial Literacy

The cortical thickness "signature" of Alzheimer's disease (AD-CT) and white matter hyperintensity (WMH) burden have each been associated with cognitive aging and incident AD and related dementias. Less is known about how these structural neuroimaging markers associate with other critical behaviors. We investigated associations of AD-CT and WMH volumes with a composite index of health and financial literacy given that the ability to access, understand, and utilize health and financial information significantly influences older adults' health outcomes. Participants were 303 adults without dementia (age∼80 years; 74% women) from the Rush Memory and Aging Project. Baseline 3T MRI T1-weighted structural and T2-weighted FLAIR data were used to assess AD-CT and WMH volumes, respectively. Literacy was measured using questions designed to assess comprehension of health and financial information and concepts, yielding a total literacy score. Multivariable linear mixed effects regression models determined the relationship of each neuroimaging marker, first separately and then combined, with the level of and change in literacy. Reduced AD-CT and higher WMH at baseline were each associated with lower levels of literacy; only AD-CT was associated with the rate of decline in literacy over time. The association of AD-CT with change in literacy persisted when both neuroimaging markers were included in the same model. The cortical thickness signature of AD predicts changes in health and financial literacy in nondemented older adults suggesting that the multidimensional construct of health and financial literacy relies on specific brain networks implicated in AD.

Elecsys Cerebrospinal Fluid Immunoassays Accurately Detect Alzheimer's Disease Regardless of Concomitant Small Vessel Disease.

Differentiating dementia due to small vessel disease (SVD) from dementia due to Alzheimer's disease (AD) with concomitant SVD is challenging in clinical practice. Accurate and early diagnosis of AD is critical to delivering stratified patient care. We characterized the results of Elecsys® cerebrospinal fluid (CSF) immunoassays (Roche Diagnostics International Ltd) in patients with early AD, diagnosed using core clinical criteria, with varying extent of SVD. Frozen CSF samples (n = 84) were measured using Elecsys β-Amyloid(1-42) (Aβ42), Phospho-Tau (181P) (pTau181), and Total-Tau (tTau) CSF immunoassays, adapted for use on the cobas® e 411 analyzer (Roche Diagnostics International Ltd), and a robust prototype β-Amyloid(1-40) (Aβ40) CSF immunoassay. SVD was assessed by extent of white matter hyperintensities (WMH) using the lesion segmentation tool. Interrelations between WMH, biomarkers, fluorodeoxyglucose F18-positron emission tomography (FDG-PET), and other parameters (including age and Mini-Mental State examinations [MMSE]) were assessed using Spearman's correlation, sensitivity/specificity, and logistic/linear regression analyses. The extent of WMH showed significant correlation with Aβ42/Aβ40 ratio (Rho=-0.250; p = 0.040), tTau (Rho = 0.292; p = 0.016), tTau/Aβ42 ratio (Rho = 0.247; p = 0.042), age (Rho = 0.373; p = 0.002), and MMSE (Rho=-0.410; p = 0.001). Sensitivity/specificity point estimates for Elecsys CSF immunoassays versus FDG-PET positivity for underlying AD pathophysiology were mostly comparable or greater in patients with high versus low WMH. WMH were not a significant predictor and did not interact with CSF biomarker positivity but modified the association between pTau181 and tTau. Elecsys CSF immunoassays detect AD pathophysiology regardless of concomitant SVD and may help to identify patients with early dementia with underlying AD pathophysiology.

Association of Polysomnographic Sleep Parameters With Neuroimaging Biomarkers of Cerebrovascular Disease in Older Adults With Sleep Apnea.

Our objective was to determine whether polysomnographic (PSG) sleep parameters are associated with neuroimaging biomarkers of cerebrovascular disease (CVD) related to white matter (WM) integrity in older adults with obstructive sleep apnea (OSA). From the population-based Mayo Clinic Study of Aging, we identified participants without dementia who underwent at least 1 brain MRI and PSG. We quantified 2 CVD biomarkers: WM hyperintensities (WMHs) from fluid-attenuated inversion recovery (FLAIR)-MRI, and fractional anisotropy of the genu of the corpus callosum (genu FA) from diffusion MRI. For this cross-sectional analysis, we fit linear models to assess associations between PSG parameters (NREM stage 1 percentage, NREM stage 3 percentage [slow-wave sleep], mean oxyhemoglobin saturation, and log of apnea-hypopnea index [AHI]) and CVD biomarkers (log of WMH and log of genu FA), respectively, while adjusting for age (at MRI), sex, APOE ε4 status, composite cardiovascular and metabolic conditions (CMC) score, REM stage percentage, sleep duration, and interval between MRI and PSG. We included 140 participants with FLAIR-MRI (of which 103 had additional diffusion MRI). The mean ± SD age was 72.7 ± 9.6 years at MRI with nearly 60% being men. The absolute median (interquartile range [IQR]) interval between MRI and PSG was 1.74 (0.9-3.2) years. 90.7% were cognitively unimpaired (CU) during both assessments. For every 10-point decrease in N3%, there was a 0.058 (95% CI 0.006-0.111, p = 0.030) increase in the log of WMH and 0.006 decrease (95% CI -0.012 to -0.0002, p = 0.042) in the log of genu FA. After matching for age, sex, and N3%, participants with severe OSA had higher WMH (median [IQR] 0.007 [0.005-0.015] vs 0.006 [0.003-0.009], p = 0.042) and lower genu FA (median [IQR] 0.57 [0.55-0.63] vs 0.63 [0.58-0.65], p = 0.007), when compared with those with mild/moderate OSA. We found that reduced slow-wave sleep and severe OSA were associated with higher burden of WM abnormalities in predominantly CU older adults, which may contribute to greater risk of cognitive impairment, dementia, and stroke. Our study supports the association between sleep depth/fragmentation and intermittent hypoxia and CVD biomarkers. Longitudinal studies are required to assess causation.

Comparing three neuropsychological subgrouping approaches in subjective and mild cognitive impairment from a naturalistic multicenter study

Subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are two clinical groups with an increased risk to develop dementia, but they are highly heterogeneous. This study compared three different approaches to subgroup SCI and MCI patients and investigated their capacity to disentangle cognitive and biomarker heterogeneity. We included 792 patients from the MemClin-cohort (142 SCI and 650 MCI). Biomarkers included cerebrospinal fluid measures of beta-amyloid-42 and phosphorylated tau, as well as visual ratings of medial temporal lobe atrophy and white matter hyperintensities on magnetic resonance imaging. We found that a more inclusive approach identified individuals with a positive beta-amyloid-42 biomarker; a less inclusive approach captured individuals with higher medial temporal lobe atrophy; and a data-driven approach captured individuals with high white matter hyperintensities burden. The three approaches also captured some neuropsychological differences. We conclude that choice of approach may differ depending on the purpose. This study helps to advance our current understanding of the clinical and biological heterogeneity within SCI and MCI, particularly in the unselected memory clinic setting.

In vivo biomarkers of arteriolosclerosis are associated with ADRD biomarkers

AbstractBackgroundBrain arteriolosclerosis, which involves thickening of the vessel wall and stenosis of arterioles, is one of the main pathologies of cerebral small vessel disease, and often co‐occurs with other pathology indicative of Alzheimer’s disease and related disorders (ADRD). A novel classifier of arteriolosclerosis, ARTS, was recently developed by the MarkVCID consortium for in vivo studies of arteriolosclerosis. We hypothesized that higher levels of arteriolosclerosis are associated with worse ADRD biomarker levels.Method109 participants from the Wake Forest Alzheimer’s Disease Research Center’s Clinical Core underwent clinical and cognitive evaluation, 3T brain MRI, and PiB (amyloid) PET (n=92). Participants were adjudicated by NIA‐AA criteria as having normal cognition (n=69), mild cognitive impairment (n=25), or dementia (n=15). Raw T1, FLAIR, and TOPUP and Eddy Current Corrected DTI images along with age and sex were inputs to a machine learning based classifier generating ARTS scores; higher ARTS indicates higher likelihood of arteriolosclerosis. For variables of interest, T1 MRI were processed (FreeSurfer v5.3) to calculate cortical gray matter (GM), hippocampal, and intracranial (ICV) volumes, and temporal meta‐ROI cortical thickness. White matter hyperintensity (WMH) volumes were calculated on FLAIR with LST in SPM12. NODDI were processed using AMICO to generate mean Free Water (FW) in hippocampus and global GM and white matter (WM). A set of AD‐sensitive cortical ROIs were used to extract mean PET SUVr signal. Separate multivariable general linear models (GLM) examined relationships between ARTS and variables of interest adjusted initially for age and total ICV (Table 1), and then again after adjusting for additional covariates (sex, race, education, APOE‐e4 carrier status, and clinical diagnosis).ResultAmong 109 participants (71±7 years, 60% women), ARTS ranged from ‐.80 to .29 (mean±SD = ‐.37±.20), suggesting a low overall likelihood of arteriolosclerosis in our sample. Higher ARTS was significantly associated with lower cortical thickness, higher WMH, higher WM FW, and greater amyloid deposition (Table 1). When adjusting for additional covariates, only amyloid no longer significantly associated with ARTS (p=0.19).ConclusionHigher ARTS scores are cross‐sectionally associated with other abnormalities in ADRD biomarkers. Future directions will examine the relationship between ARTS and Flortaucipir (tau) uptake.

In vivo biomarkers of arteriolosclerosis are associated with ADRD biomarkers

AbstractBackgroundBrain arteriolosclerosis, which involves thickening of the vessel wall and stenosis of arterioles, is one of the main pathologies of cerebral small vessel disease, and often co‐occurs with other pathology indicative of Alzheimer’s disease and related disorders (ADRD). A novel classifier of arteriolosclerosis, ARTS, was recently developed by the MarkVCID consortium for in vivo studies of arteriolosclerosis. We hypothesized that higher levels of arteriolosclerosis are associated with worse ADRD biomarker levels.Method109 participants from the Wake Forest Alzheimer’s Disease Research Center’s Clinical Core underwent clinical and cognitive evaluation, 3T brain MRI, and PiB (amyloid) PET (n=92). Participants were adjudicated by NIA‐AA criteria as having normal cognition (n=69), mild cognitive impairment (n=25), or dementia (n=15). Raw T1, FLAIR, and TOPUP and Eddy Current Corrected DTI images along with age and sex were inputs to a machine learning based classifier generating ARTS scores; higher ARTS indicates higher likelihood of arteriolosclerosis. For variables of interest, T1 MRI were processed (FreeSurfer v5.3) to calculate cortical gray matter (GM), hippocampal, and intracranial (ICV) volumes, and temporal meta‐ROI cortical thickness. White matter hyperintensity (WMH) volumes were calculated on FLAIR with LST in SPM12. NODDI were processed using AMICO to generate mean Free Water (FW) in hippocampus and global GM and white matter (WM). A set of AD‐sensitive cortical ROIs were used to extract mean PET SUVr signal. Separate multivariable general linear models (GLM) examined relationships between ARTS and variables of interest adjusted initially for age and total ICV (Table 1), and then again after adjusting for additional covariates (sex, race, education, APOE‐e4 carrier status, and clinical diagnosis).ResultAmong 109 participants (71±7 years, 60% women), ARTS ranged from ‐.80 to .29 (mean±SD = ‐.37±.20), suggesting a low overall likelihood of arteriolosclerosis in our sample. Higher ARTS was significantly associated with lower cortical thickness, higher WMH, higher WM FW, and greater amyloid deposition (Table 1). When adjusting for additional covariates, only amyloid no longer significantly associated with ARTS (p=0.19).ConclusionHigher ARTS scores are cross‐sectionally associated with other abnormalities in ADRD biomarkers. Future directions will examine the relationship between ARTS and Flortaucipir (tau) uptake.

Lower white matter hyperintensity is associated with lower mild behavioral impairment severity among pre‐dementia people with higher education attainment

AbstractBackgroundMild behavioral impairment (MBI) describes the emergence of neurobehavioral symptoms in later life as harbingers of neurodegeneration. Emerging evidence suggests that white matter hyperintensity (WMH), a known risk factor for cognitive impairment, is associated with MBI. Furthermore, education level which reflects cognitive reserve, influences the risk of dementia. However, the role of education levels on the relationship between WMH and MBI is unknown. Here, we aim to evaluate the effects of education levels on WMH and MBI among a pre‐dementia cohort from a memory clinic in Singapore.MethodIn this retrospective cross‐sectional study, 210 pre‐dementia participants (mean age 64.31, mean MMSE 27.77, mean education level 12.60, 37.6% males), underwent cognitive assessment, Magnetic Resonance Imaging (MRI) and completed the MBI‐checklist (MBI‐C) self‐report in National Neuroscience Institute Singapore from 2017 to 2021. Multiple linear regression models evaluated the main effects of WMH total ratings and years of education on MBI, while moderation analysis evaluated the effects of years of education with WMH on MBI. All analyses were controlled for age and sex.ResultWhile education levels and WMH were not associated with MBI‐C total scores independently (p>0.05), we found that education levels moderated the effects of WMH on MBI‐C total score (β=0.269 , p=0.038). Specifically, higher education attainment is associated with lower MBI‐C total scores among individuals with lower burden of WMH; while higher MBI‐C total score is observed with higher education among people with high WMH burden (Figure 1).ConclusionHigher education attainment is associated with a lower risk of MBI when the WMH load is lower. Our findings support interventions to reduce WMH load in pre‐dementia people with higher education attainment to reduce MBI severity.

The influence of white matter hyperintensities severity on functional brain activity in cerebral small vessel disease: An rs-fMRI study.

To investigate relationships between the severity of white matter hyperintensities (WMH), functional brain activity, and cognition in cerebral small vessel disease (CSVD) based on resting-state functional magnetic resonance imaging (rs-fMRI) data. A total of 103 subjects with CSVD were included. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), functional connectivity (FC) and their graph properties were applied to explore the influence of WMH burden on functional brain activity. We also investigated whether there are correlations between different functional brain characteristics and cognitive assessments. Finally, we selected disease-related rs-fMRI features in combination with ensemble learning to classify CSVD patients with low WMH load and with high WMH load. The high WMH load group demonstrated significantly abnormal functional brain activity based on rs-MRI data, relative to the low WMH load group. ALFF and graph properties in specific brain regions were significantly correlated with patients' cognitive assessments in CSVD. Moreover, altered rs-fMRI signal can help predict the severity of WMH in CSVD patients with an overall accuracy of 92.23%. This study provided a comprehensive analysis and evidence for a pattern of altered functional brain activity under different WMH load in CSVD based on rs-fMRI data, enabling accurately individual prediction of status of WMH.

Association of impaired lung function with dementia, and brain magnetic resonance imaging indices: a large population-based longitudinal study.

to examine the association between different patterns of impaired lung function with the incident risk of dementia and magnetic resonance imaging (MRI)-based brain structural features. in UK Biobank, a total of 308,534 dementia-free participants with valid lung function measures (forced expiratory volume in 1 s [FEV1] and forced vital capacity [FVC]) were included. Association was assessed using Cox proportional hazards regression model. Furthermore, the association between impaired lung function and brain MRI biomarkers related to cognitive function was analysed among 30,159 participants. during a median follow-up of 12.6years, 3,607 incident all-cause dementia cases were recorded. Restrictive impairment (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.27-1.60) and obstructive impairment (HR, 1.28; 95% CI, 1.15-1.42) were associated with higher risk of all-cause dementia. The restricted cubic splines indicated FEV1% predicted and FVC % predicted had reversed J-shaped associations with dementia. Participants with impaired lung function have higher risks of all-cause dementia across all apolipoprotein E (APOE) risk categories, whereas associations were stronger among those of low APOE risk (P for interaction = 0.034). In addition, restrictive and obstructive impairment were linked to lower total (β: -0.075, SE: 0.021, Pfdr = 0.002; β: -0.033, SE: 0.017, Pfdr = 0.069) and frontoparietal grey matter volumes, higher white matter hyperintensity, poorer white matter integrity, lower hippocampus (β: -0.066, SE: 0.024, Pfdr = 0.017; β: -0.051, SE: 0.019, Pfdr = 0.019) and other subcortical volumes. participants with restrictive and obstructive impairments had a higher risk of dementia. Brain MRI indices further supported adverse effects and provided insight into potential pathophysiology biomarkers.

Vascular burden and cognition: Mediating roles of neurodegeneration and amyloid PET.

It remains unclear to what extent cerebrovascular burden relates to amyloid beta (Aβ) deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with small vessel disease and Alzheimer's disease (AD) pathology. In 120 subjects, we investigated the association of vascular burden (white matter hyperintensity [WMH] volumes) with cognition. Using mediation analyses, we tested the indirect effects of WMH on cognition via Aβ deposition (18 F-AV45 positron emission tomography [PET]) and neurodegeneration (cortical thickness or 18 F fluorodeoxyglucose PET) in AD signature regions. We observed that increased total WMH volume was associated with poorer performance in all tested cognitive domains, with the strongest effects observed for semantic fluency. These relationships were mediated mainly via cortical thinning, particularly of the temporal lobe, and to a lesser extent serially mediated via Aβ and cortical thinning of AD signature regions. WMH volumes differentially impacted cognition depending on lobar location and Aβ status. In summary, our study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive function via localized neurodegeneration. HIGHLIGHTS: Alzheimer's disease often co-exists with vascular pathology. We studied a unique cohort enriched for high white matter hyperintensities (WMH). High WMH related to cognitive impairment of semantic fluency and executive function. This relationship was mediated via temporo-parietal atrophy rather than metabolism. This relationship was, to lesser extent, serially mediated via amyloid beta and atrophy.

Inflammatory profile and white matter hyperintensity burden in acute ischemic stroke patients

Inflammation is involved in small vessel disease (SVD). We aim to clarify whether inflammation related to white matter hyperintensities (WMH), a key component of SVD, may affect the inflammatory response in acute ischemic stroke (AIS) patients. For this, we sequentially measured 10 circulating inflammatory markers and assessed WMH burden on admission MRI in AIS patients treated with thrombectomy. Of 149 patients, 57 (38.3%) had a high WMH burden (Fazekas≥3). A high WMH burden was associated with 4 markers levels but this association did not remain following multivariable analyses. WMH burden is not associated with a specific inflammatory profile in AIS.

Association of white matter hyperintensities with migraine phenotypes and response to treatment.

White matter hyperintensities (WMHs) are frequently found in migraineurs. However, their clinical significance and correlation to different migraine phenotypes and treatment responses are not well defined. The study aimed to examine the association of WMHs with migraine clinical patterns and treatment response. We aimed to evaluate the association between WMHs and migraine phenotypes and explore the relationship of WMHs to treatment response. Our cross-sectional study formed of 500 migraineurs who sought treatment in Kafr el-sheik university hospital and underwent (3T) MRI to evaluate WMHs. Different migraine phenotypes were compared between patients with and without WMHs. According to reduced headache pain intensity and frequency, these patients were divided into treatment responder and non-responder groups. A total of 145 patients (29%) had WMHs. Patients with WMHs were significantly older, had a longer disease duration, and higher attack frequency. Patients who did not respond to acute and maintenance medications had a higher frequency of WMHs and high WMHs Scheltens score. Migraine with Aura and the presence of vomiting and dizziness were predictors for the development of WMHs. WMHs are more common in migraine with aura. It is more frequent in migraine associated with vomiting and dizziness. WMHs increased with advancing age and more severe disease burden. Poorer response to acute and prophylactic medications was found in patients with WMHs.

Spouse bereavement and brain pathologies: A propensity score matching study.

Spouse bereavement is one of life's greatest stresses and has been suggested to trigger or accelerate cognitive decline and dementia. However, little information is available about the potential brain pathologies underlying the association between spouse bereavement and cognitive decline. We aimed to investigate that lifetime spouse bereavement is associated with in vivo human brain pathologies underlying cognitive decline. A total of 319 ever-married older adults between the ages of 61 and 90 years underwent comprehensive clinical assessments and multimodal brain imaging including [11 C] Pittsburgh compound B-positron emission tomography (PET), AV-1451 PET, [18 F] fluorodeoxyglucose-PET, and magnetic resonance imaging. Participants were classified as experiencing no spouse bereavement or spouse bereavement, and comparisons using propensity score matching (59 cases and 59 controls) were performed. Spouse bereavement was significantly associated with higher cerebral white matter hyperintensity (WMH) volume compared with no spouse bereavement. Interaction and subsequent subgroup analyses showed that spouse bereavement was significantly associated with higher WMH in the older (>75 years) subgroup and among those with no- or low-skill occupations. In addition, spouse bereavement at 60 years or older affects WMH volume compared with no spouse bereavement, whereas spouse bereavement at younger than 60 years did not. No group differences were observed in other brain pathologies between spouse bereavement categories. The findings suggest that the spouse bereavement may contribute to dementia or cognitive decline by increasing cerebrovascular injury, particularly in older individuals and those with no- or low-skill occupations.

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome.

To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways. MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts. A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location. Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.