Nonlinear pattern of the emergence of white matter hyperintensity in healthy Han Chinese: an adult lifespan study

Cerebral white matter hyperintensity volumes: Normative age- and sex-specific values from 15 population-based cohorts comprising 14,876 individuals

White matter hyperintensities (WMH) increase with age, with marked interindividual variation. There is a need for normative data by age and sex, to improve individualized WMH burden assessment. In this study, we pooled cross-sectional data from 15 population-based cohorts (14,876 nondemented individuals, age 18-97 years), through the Meta VCI Map consortium. Whole brain and tract-specific MRI-assessed WMH volumes were calculated in MNI-152 space. We used quantile regression to create centile curves of WMH volume versus age, stratified by sex. Total WMH volume and interindividual variance increased exponentially with age for both sexes, with females showing higher WMH volumes. WMH volume increase with aging was not uniform across the white matter, but instead followed one of three different patterns depending on location. Age- and sex-specific normative data for total and regional WMH volumes were created. Our study provides detailed information on the normal distribution of total and regional WMH volumes across adulthood. The normative data enable a quantitative approach to interpreting total and regional WMH volumes in clinical practice and research settings.

The aging trajectories of brain functional hierarchy and its impact on cognition across the adult lifespan

Introduction

The hierarchical network architecture of the human brain, pivotal to cognition and behavior, can be explored via gradient analysis using restingstate functional MRI data. Although it has been employed to understand brain development and disorders, the impact of aging on this hierarchical architecture and its link to cognitive decline remains elusive.

Methods

This study utilized resting-state functional MRI data from 350 healthy adults (aged 20-85) to investigate the functional hierarchical network using connectome gradient analysis with a cross-age sliding window approach. Gradient-related metrics were estimated and correlated with age to evaluate trajectory of gradient changes across lifespan.

Results

The principal gradient (unimodal-to-transmodal) demonstrated a significant non-linear relationship with age, whereas the secondary gradient (visual-to-somatomotor) showed a simple linear decreasing pattern. Among the principal gradient, significant age-related changes were observed in the somatomotor, dorsal attention, limbic and default mode networks. The changes in the gradient scores of both the somatomotor and frontal-parietal networks were associated with greater working memory and visuospatial ability. Gender differences were found in global gradient metrics and gradient scores of somatomotor and default mode networks in the principal gradient, with no interaction with age effect.

Discussion

Our study delves into the aging trajectories of functional connectome gradient and its cognitive impact across the adult lifespan, providing insights for future research into the biological underpinnings of brain function and pathological models of atypical aging processes.

Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging

White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.

Multisystem physiological perspective of human frailty and its modulation by physical activity

"Frailty" is a term used to refer to a state characterized by enhanced vulnerability to, and impaired recovery from, stressors compared with a nonfrail state, which is increasingly viewed as a loss of resilience. With increasing life expectancy and the associated rise in years spent with physical frailty, there is a need to understand the clinical and physiological features of frailty and the factors driving it. We describe the clinical definitions of age-related frailty and their limitations in allowing us to understand the pathogenesis of this prevalent condition. Given that age-related frailty manifests in the form of functional declines such as poor balance, falls, and immobility, as an alternative we view frailty from a physiological viewpoint and describe what is known of the organ-based components of frailty, including adiposity, the brain, and neuromuscular, skeletal muscle, immune, and cardiovascular systems, as individual systems and as components in multisystem dysregulation. By doing so we aim to highlight current understanding of the physiological phenotype of frailty and reveal key knowledge gaps and potential mechanistic drivers of the trajectory to frailty. We also review the studies in humans that have intervened with exercise to reduce frailty. We conclude that more longitudinal and interventional clinical studies are required in older adults. Such observational studies should interrogate the progression from a nonfrail to a frail state, assessing individual elements of frailty to produce a deep physiological phenotype of the syndrome. The findings will identify mechanistic drivers of frailty and allow targeted interventions to diminish frailty progression.

Association between Serum Amyloid A Level and White Matter Hyperintensity Burden: a Cross-Sectional Analysis in Patients with Acute Ischemic Stroke

INTRODUCTION

This work aimed to determine the potential link between white matter hyperintensity (WMH) burden and serum amyloid A (SAA) level in patients with acute ischemic stroke.

METHODS

Consecutive patients with acute large artery atherosclerosis (LAA) stroke between April 2021 and May 2022 were included. WMH volumes (periventricular, deep, and total) were measured using the Fazekas score and a semiautomated volumetric analysis on fluid-attenuated inversion recovery-magnetic resonance imaging. The burdens of WMH were scored to assess the dose-dependent association between SAA and WMH volume. Multivariate regression and a two-piecewise linear regression model were used to evaluate whether SAA levels are an independent predictor of WMH, and to discover the threshold effect or saturation effect of SAA levels with respect to WMH volume.

RESULTS

The mean age of patients was 63.2 ± 11.5 years, with 65.9% men. The median SAA level was 3.93 mg/L and the total WMH volume of 6.86 cm³. In the multivariable analysis, SAA remained an independent predictor of total WMH volume [β = 0.82, 95% confidence interval (CI) = 0.49-1.07, p < 0.001], periventricular WMH volume (adjusted β = 0.76, 95% CI = 0.46-1.07, p < 0.001), and deep WMH volume (adjusted β = 0.26, 95% CI = 0.06-0.45, p = 0.011) after controlling for confounders. Furthermore, SAA levels were associated with periventricular Fazekas score, deep Fazekas score, and Fazekas grades. Threshold effect and saturation effect analyses demonstrated a nonlinear relationship between SAA levels and periventricular white matter hyperintensity (PVWMH) volumes, with SAA levels (2.12-19.89 mg/L) having significant dose-dependent relationships with periventricular WMH volumes (adjusted β = 1.98, 95% CI = 1.12-2.84, p < 0.001).

CONCLUSION

SAA level ranging from 2.12 to 19.89 mg/L is dose-dependently associated with periventricular WMH development. These findings point the way forward for future research into the pathophysiology of WMH.

Brain white matter hyperintensities-predicted age reflects neurovascular health in middle-to-old aged subjects

BACKGROUND

age-related neurovascular structural and functional impairment is a major aetiology of dementia and stroke in older people. There is no single marker representative of neurovascular biological age yet.

OBJECTIVE

this study aims to develop and validate a white matter hyperintensities (WMH)-based model for characterising individuals' neurovascular biological age.

METHODS

in this prospective single-site study, the WMH-based age-prediction model was constructed based on WMH volumes of 491 healthy participants (21-89 years). In the training dataset, the constructed linear-regression model with log-transformed WMH volumes showed well-balanced complexity and accuracy (root mean squared error, RMSE = 10.20 and mean absolute error, MAE = 7.76 years). This model of neurovascular age estimation was then applied to a middle-to-old aged testing dataset (n = 726, 50-92 years) as the testing dataset for external validation.

RESULTS

the established age estimator also had comparable generalizability with the testing dataset (RMSE = 7.76 and MAE = 6.38 years). In the testing dataset, the WMH-predicted age difference was negatively associated with visual executive function. Individuals with older predicted-age for their chronological age had greater cardiovascular burden and cardiovascular disease risks than individuals with normal or delayed predicted age. These associations were independent of chronological age.

CONCLUSIONS

our model is easy to use in clinical practice that helps to evaluate WMH severity objective to chronological age. Current findings support our WMH-based age measurement to reflect neurovascular health and have potential diagnostic and prognostic value for clinical or research purposes in age-related neurovascular disorders.

Diffusely abnormal white matter converts to T2 lesion volume in the absence of MRI-detectable acute inflammation

Diffusely abnormal white matter (DAWM), characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive MS (SPMS). However, little is known about changes of DAWM over time and their relation to focal white matter lesions (FWML).

The objectives of this work were: 1) To characterize the longitudinal evolution of FWML, DAWM, and DAWM that transforms into FWML, and 2) To determine whether gadolinium enhancement, known to be associated with the development of new FWML, is also related to DAWM voxels that transform into FWML.

Our data included 4220 MRI scans of 689 SPMS participants, followed for 156 weeks and 2677 scans of 686 RRMS participants, followed for 96 weeks. FWML and DAWM were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, DAWM voxels at each visit that transformed into FWML on the last MRI scan as well as their overlap with gadolinium enhancing lesion masks were identified.

Our results showed that the average yearly rate of conversion of DAWM-to-FWML was 1.27 cc for SPMS and 0.80 cc for RRMS. FWML in SPMS participants significantly increased (t = 3.9; p = 0.0001) while DAWM significantly decreased (t = −4.3 p &lt; 0.0001) and the ratio FWML:DAWM increased (t = 12.7; p &lt; 0.00001). RRMS participants also showed an increase in the FWML:DAWM Ratio (t = 6.9; p &lt; 0.00001) but without a significant change of the individual volumes. Gadolinium enhancement was associated with 7.3% and 18.7% of focal New T2 lesion formation in the infrequent scans of the RRMS and SPMS cohorts, respectively. In comparison, only 0.1% and 0.0% of DAWM-to-FWML voxels overlapped with gadolinium enhancement.

We conclude that DAWM transforms into FWML over time, in both RRMS and SPMS. DAWM appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

The Resilience and Vulnerability of Human Brain Networks Across the Lifespan

Resilience, the ability for a system to maintain its basic functionality when suffering from lesions, is a critical property for human brain, especially in the brain aging process. This study adopted a novel metric of network resilience, the Resilience Index (RI), to assess human brain resilience with three different lifespan datasets. Based on the structural brain networks constructed from diffusion tensor imaging (DTI), we observed an inverted-U relationship between RI and age, that is, RI increased during development and early adulthood, reached a peak at about 35 years old, and then decreased during aging, which suggested that brain resilience could be quantified by RI. Furthermore, we studied brain network vulnerability by the decreases in RI when virtual lesions occurred to nodes (i.e., brain regions) or edges (i.e., structural brain connectivity). We found that the strong edges were markedly vulnerable, and the homotopic edges were the most prominent representatives of vulnerable edges. In other words, an arbitrary attack on homotopic edges would have a high probability to degrade brain network resilience. These findings suggest the change of human brain resilience across the lifespan and provide a new perspective for exploring human brain vulnerability.

Age Moderates Associations of Hypertension, White Matter Hyperintensities, and Cognition

BACKGROUND

Hypertension and white matter hyperintensities (WMH) are mutually associated risk factors for cognitive impairment. However, age may modify the associations between hypertension and WMH, and their links to cognitive impairment.

OBJECTIVE

We evaluated the interaction between age and hypertension on WMH, and the age-stratified associations of hypertension and WMH with cognition.

METHODS

Key measures include systolic blood pressure (SBP), WMH (modified Fazekas visual ratings of cranial MRI), and the Montreal Cognitive Assessment (MoCA). Participants (N = 488) with prodromal and mild dementia were age-stratified (≤49, 50-59, 60-69,≥70), and considered hypertensive if their SBP≥140 mmHg. The interaction between age strata and hypertension on WMH, and age-stratified associations of hypertension and WMH with cognition, were evaluated using multiple linear regression analyses. Analyses controlled for other risk factors for WMH and cognitive impairment.

RESULTS

Age moderated the association between SBP and WMH. Hypertension was associated with higher WMH only in those aged 60-69, and WMH trends across age bands differed between those with and without hypertension. Finally, WMH and SBP≥140 were independently associated with lower MoCA scores within the 50-59 age band, while WMH alone was associated with poorer MoCA scores in the≥70 age band.

CONCLUSION

In adults with prodromal or mild dementia, hypertension was associated with WMH specifically in the 60-69 age strata. Associations between hypertension and WMH with poorer cognition also differed across age bands. Future studies will be needed to investigate whether blood pressure management to slow cognitive decline by targeting WMH may be age dependent.

Prevalence and risk factors for brain white matter changes in young and middle-aged participants with Brain Dock (brain screening): a registry database study and literature review

This study aimed to determine the prevalence and risk factors for brain white matter changes in normal young and middle-aged participants who underwent Brain Dock (brain screening). We analyzed 5,000 consecutive healthy participants from the Brain Dock registry between August to December 2018. Age, sex, body mass index (BMI), medical history, deep subcortical white matter high intensity (DSWMH), periventricular high intensity (PVH), and enlargement of perivascular space (EPVS) were investigated in relation to age. The prevalence of DSWMH, PVH, and EPVS were 35.3%, 14.0%, and 17.8%, respectively. Multivariate logistic regression analyses for brain white matter changes were conducted. The significant risk factors in participants aged < 50 years were: age (OR:1.09, 95% CI:1.07-1.12), the female sex (1.29, 1.03-1.60), BMI obesity (1.86, 1.12-3.08), and hypertension (1.67, 1.18-2.35) for DSWMH; age (1.08, 1.04-1.13) and the female sex (1.56, 1.03-2.36) for PVH; and age (1.07, 1.05-1.10) and the female sex (0.77, 0.60-1.00) for EPVS. In conclusion, age was consistently identified as a significant risk factor in young and middle-aged participants. Some risk factors for brain white matter changes were identified even in young and middle-aged participants in this study. Further longitudinal studies should be done in the future.

White Matter Hyperintensities Quantification in Healthy Adults: A Systematic Review and Meta-Analysis

BACKGROUND

Although white matter hyperintensities (WMH) volumetric assessment is now customary in research studies, inconsistent WMH measures among homogenous populations may prevent the clinical usability of this biomarker.

PURPOSE

To determine whether a point estimate and reference standard for WMH volume in the healthy aging population could be determined.

STUDY TYPE

Systematic review and meta-analysis.

POPULATION

In all, 9716 adult subjects from 38 studies reporting WMH volume were retrieved following a systematic search on EMBASE.

FIELD STRENGTH/SEQUENCE

1.0T, 1.5T, or 3.0T/fluid-attenuated inversion recovery (FLAIR) and/or proton density/T₂ -weighted fast spin echo sequences or gradient echo T₁ -weighted sequences.

ASSESSMENT

After a literature search, sample size, demographics, magnetic field strength, MRI sequences, level of automation in WMH assessment, study population, and WMH volume were extracted.

STATISTICAL TESTS

The pooled WMH volume with 95% confidence interval (CI) was calculated using the random-effect model. The I² statistic was calculated as a measure of heterogeneity across studies. Meta-regression analysis of WMH volume on age was performed.

RESULTS

Of the 38 studies analyzed, 17 reported WMH volume as the mean and standard deviation (SD) and were included in the meta-analysis. Mean and SD of age was 66.11 ± 10.92 years (percentage of men 50.45% ± 21.48%). Heterogeneity was very high (I²  = 99%). The pooled WMH volume was 4.70 cm³ (95% CI: 3.88-5.53 cm³ ). At meta-regression analysis, WMH volume was positively associated with subjects' age (β = 0.358 cm³ per year, P < 0.05, R²  = 0.27).

DATA CONCLUSION

The lack of standardization in the definition of WMH together with the high technical variability in assessment may explain a large component of the observed heterogeneity. Currently, volumes of WMH in healthy subjects are not comparable between studies and an estimate and reference interval could not be determined.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 1.

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker

The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing individual brain health and for identifying neurodegenerative and neuropsychiatric diseases. Using a large-scale structural covariance network (SCN)-based framework with machine learning algorithms, we demonstrate this framework's ability to predict individual brain age in a large sample of middle-to-late age adults, and highlight its clinical specificity for several disease populations from a network perspective. A proposed estimator with 40 SCNs could predict individual brain age, balancing between model complexity and prediction accuracy. Notably, we found that the most significant SCN for predicting brain age included the caudate nucleus, putamen, hippocampus, amygdala, and cerebellar regions. Furthermore, our data indicate a larger brain age disparity in patients with schizophrenia and Alzheimer's disease than in healthy controls, while this metric did not differ significantly in patients with major depressive disorder. These findings provide empirical evidence supporting the estimation of brain age from a brain network perspective, and demonstrate the clinical feasibility of evaluating neurological diseases hypothesized to be associated with accelerated brain aging.

Cognitive Reserve Moderates Effects of White Matter Hyperintensity on Depressive Symptoms and Cognitive Function in Late-Life Depression

INTRODUCTION

White matter hyperintensity (WMH) has been regarded as one of the major contributor of the vascular hypothesis of late-life depression (LLD) and cognitive decline in the elderly. On the other hand, cognitive reserve (CR) has long been hypothesized to provide resilience and adaptability against age- and disease-related insults. This study examined the role of CR, using proxy of education, in moderating the association between WMH and clinical LLD expression.

METHODS

A total of 54 elderly diagnosed with major depressive disorder and 38 matched healthy controls participated in this study. They received MRI scanning and a battery of neuropsychological tests. WMH was quantified by an automated segmentation algorithm. Linear regression analyses were conducted separately in the LLD and control groups to examine the effects of WMH, education and their interaction in depression severity and various cognitive domains.

RESULTS

WMH was significantly and negatively associated with executive function only in the healthy controls. In patients with LLD, we observed a significant interactive effect in education on the association between WMH and depression severity and language domain (category fluency task). Specifically, those with high education showed less depressive symptoms and cognitive decline as WMH increased.

CONCLUSION

WMH is associated with lower cognitive function. However, in patients with LLD, high education attenuates the deleterious effect of WMH on mood and cognition. Therefore, CR appears to exert a protective effect on neurocognitive functioning in people with LLD.

The relationship between white matter hyperintensities and cognitive reference abilities across the life span

We examined the relationship between white matter hyperintensities (WMH) burden and performance on 4 reference abilities: episodic memory, perceptual speed, fluid reasoning, and vocabulary. Cross-sectional data of 486 healthy adults from 20 to 80 years old enrolled in an ongoing longitudinal study were analyzed. A piecewise regression across age identified an inflection point at 43 years old, where WMH total volume began to increase with age. Subsequent analyses focused on participants above that age (N = 351). WMH total volume had significant inverse correlations with perceptual speed and memory. Regional measures of WMH showed inverse correlations with all reference abilities. We performed principal component analysis of the regional WMH data to create a model of principal components regression. Parietal WMH regional volume burden mediated the relationship between age and perceptual speed in simple and multiple mediation models. The principal components regression pattern associated with perceptual speed also mediated the relationship between age and perceptual speed performance. These results across the extended adult life span help clarify the influence of WMH on cognitive aging.

White matter in different regions evolves differently during progression to dementia

White matter hyperintensities (WMHs) are common in individuals with mild cognitive impairment (MCI) and Alzheimer's disease. Patients with MCI with high WMH volumes are known to have an increased chance of conversion to Alzheimer's disease compared with those without WMHs. In this article, we assess the differences between patients with MCI that remain stable (N = 413) and those that progress to dementia (N = 178) in terms of WMH volume (as a surrogate of amount of tissue damage) and T1-weighted (T1w) image hypointensity (as a surrogate of severity of tissue damage) in periventricular, deep, and juxtacortical brain regions. Together, lesion volume and T1w hypointensity are used as a surrogate of vascular disease burden. Our results show a significantly greater increase of all regional WMH volumes in the MCI population that converts to dementia (p < 0.001). T1w hypointensity for the juxtacortical WMHs was significantly lower in the converter group (p < 0.0001) and was not affected by age. Conversely, T1w hypointensity in other regions showed a significant decrease with age (p < 0.0001). Within the converters, Time2Conversion was associated with both WMH volume and T1w hypointensity (p < 0.0001), and conversion to dementia was significantly associated with decreased intensity (and not volume) of periventricular and juxtacortical WMHs (p < 0.001). These changes differ according to the WM region, suggesting that different mechanisms affect the juxtacortical area in comparison to deep and periventricular regions in the process of conversion to dementia.

White matter hyperintensities are linked to future cognitive decline in de novo Parkinson's disease patients

White Matter Hyperintensities (WMHs) are associated with cognitive decline in aging and Alzheimer's disease. However, the pathogenesis of cognitive decline in Parkinson's disease (PD) is not as clearly related to vascular causes, and therefore the role of WMHs as a marker of small-vessel disease (SVD) in PD is less clear. Currently, SVD in PD is assessed and treated independently of the disease. However, if WMH as the major MRI sign of SVD has a higher impact on cognitive decline in PD patients than in healthy controls, vascular pathology needs to be assessed and treated with a higher priority in this population. Here we investigate whether the presence of WMHs leads to increased cognitive decline in de novo PD, and if these effects relate to cortical atrophy. WMHs and cortical thickness were measured in de novo PD patients and age-matched controls (N_PD = 365, N_Control = 174) from Parkinson's Progression Markers Initiative (PPMI) to study the relationship between baseline WMHs, future cognitive decline (follow-up: 4.09 ± 1.14 years) and cortical atrophy (follow-up: 1.05 ± 0.10 years). PD subjects with high baseline WMH loads had significantly greater cognitive decline than i) PD subjects with low WMH load, and ii) control subjects with high WMH load. Furthermore, in PD subjects, high WMH load resulted in more cortical thinning in the right frontal lobe. Theses results show that the presence of WMHs in de novo PD patients predicts greater future cognitive decline and cortical atrophy than in normal aging.