scholarly journals Associations of white matter hyperintensities with networks of grey matter blood flow and volume in midlife adults: a CARDIA MRI substudy

2021 ◽  
Author(s):  
William SH Kim ◽  
Nicholas J Luciw ◽  
Sarah Atwi ◽  
Zahra Shirzadi ◽  
Sudipto Dolui ◽  
...  
Keyword(s):  
Blood Flow ◽  
White Matter ◽  
Betweenness Centrality ◽  
Grey Matter ◽  
White Matter Hyperintensities ◽  
Clustering Coefficient ◽  
Group Differences ◽  
Grey Matter Volume ◽  
Local Efficiency ◽  
Midlife Adults

White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet characterization at midlife is poorly studied. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. 254 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study were selected and stratified by WMH burden yielding two groups of equal size (Lo- and Hi-WMH groups). We constructed group-level covariance networks based on cerebral blood flow (CBF) and grey matter volume (GMV) maps across 74 grey matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks were partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo- and Hi-WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no group differences in either CBF or GMV covariance networks. In contrast, we found group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence of WMH-related network alterations that were observed at midlife.

scholarly journals Cortical and Subcortical Grey Matter Abnormalities in White Matter Hyperintensities and Subsequent Cognitive Impairment

2021 ◽  
Author(s):  
Wenhao Zhu ◽  
◽  
Hao Huang ◽  
Shiqi Yang ◽  
Xiang Luo ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
White Matter ◽  
Cognitive Decline ◽  
Grey Matter ◽  
White Matter Hyperintensities ◽  
Grey Matter Volume ◽  
Independent Dataset ◽  
The Relationship ◽  
Robust Evidence ◽  
Bilateral Thalamus

AbstractGrey matter (GM) alterations may contribute to cognitive decline in individuals with white matter hyperintensities (WMH) but no consensus has yet emerged. Here, we investigated cortical thickness and grey matter volume in 23 WMH patients with mild cognitive impairment (WMH-MCI), 43 WMH patients without cognitive impairment, and 55 healthy controls. Both WMH groups showed GM atrophy in the bilateral thalamus, fronto-insular cortices, and several parietal-temporal regions, and the WMH-MCI group showed more extensive and severe GM atrophy. The GM atrophy in the thalamus and fronto-insular cortices was associated with cognitive decline in the WMH-MCI patients and may mediate the relationship between WMH and cognition in WMH patients. Furthermore, the main results were well replicated in an independent dataset from the Alzheimer's Disease Neuroimaging Initiative database and in other control analyses. These comprehensive results provide robust evidence of specific GM alterations underlying WMH and subsequent cognitive impairment.

scholarly journals White Matter Hyperintensity Load Drives Differential Grey Matter Changes in Mild Cognitive Impairment

2020 ◽  
Author(s):  
Ashwati Vipin ◽  
Benjamin Yi Xin Wong ◽  
Dilip Kumar ◽  
Audrey Low ◽  
Kok Pin Ng ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Executive Control ◽  
Grey Matter ◽  
White Matter Hyperintensities ◽  
White Matter Hyperintensity ◽  
Grey Matter Volume ◽  
Executive Control Network ◽  
Matter Volume

Abstract Background: Small-vessel cerebrovascular disease often represented as white matter hyperintensities on magnetic resonance imaging, is considered an important risk factor for progression to dementia. Grey matter volume alterations in Alzheimer’s disease-specific regions comprising the default mode network and executive control network are also key features of early Alzheimer’s disease. However, the relationship between increasing white matter hyperintensity load and grey matter volume needs further examination in the cognitively normal and mild cognitive impairment. Here, we examined the load-dependent influence of white matter hyperintensities on grey matter volume and cognition in the cognitively normal and mild cognitive impairment stages.Methods: Magnetic resonance imaging data from 93 mild cognitive impairment and 90 cognitively normal subjects were studied and white matter hyperintensity load was categorized into low, medium and high terciles. We examined how differing loads of white matter hyperintensities related to whole-brain voxel-wise and regional grey matter volume in the default mode network and executive control network. We further investigated how regional grey matter volume moderated the relationship between white matter hyperintensities and cognition at differing white matter hyperintensity loads.Results: We found differential load-dependent effects of white matter hyperintensity burden on voxel-wise and regional grey matter atrophy in only mild cognitive impairment subjects. At low load, white matter hyperintensity load was positively related to grey matter volume in the executive control network but at high load, white matter hyperintensity load was negatively related to grey matter volume across both the executive control and default mode networks and no relationship was observed at medium white matter hyperintensity load. Additionally, negative associations between white matter hyperintensities and domains of memory and executive function were moderated by regional grey matter volume. Conclusions: Our results demonstrate dynamic relationships between white matter hyperintensity load, grey matter volume and cognition in the mild cognitive impairment stage. Interventions to slow the progression of white matter hyperintensities, instituted when white matter hyperintensity load is low could potentially prevent further cognitive decline.

scholarly journals Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

2021 ◽  
pp. jnnp-2020-323541
Author(s):  
Jessica L Panman ◽  
Vikram Venkatraghavan ◽  
Emma L van der Ende ◽  
Rebecca M E Steketee ◽  
Lize C Jiskoot ◽  
...  
Keyword(s):  
White Matter ◽  
Frontotemporal Dementia ◽  
Disease Severity ◽  
Grey Matter ◽  
Clinical Stage ◽  
Data Driven ◽  
Grey Matter Volume ◽  
Matter Volume ◽  
Mutation Carriers ◽  
Individual Disease

ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

scholarly journals Age differentiation within grey matter, white matter and between memory and white matter in an adult lifespan cohort

2017 ◽  
Author(s):  
Susanne M. M. de Mooij ◽  
Richard N. A. Henson ◽  
Lourens J. Waldorp ◽  
Cam-CAN ◽  
Rogier A. Kievit
Keyword(s):  
White Matter ◽  
Cognitive Functions ◽  
Structural Equation ◽  
Grey Matter ◽  
Fluid Intelligence ◽  
Cognitive Factors ◽  
Equation Modeling ◽  
Grey Matter Volume ◽  
Adult Lifespan ◽  
Age Related

AbstractIt is well-established that brain structures and cognitive functions change across the lifespan. A longstanding hypothesis called age differentiation additionally posits that the relations between cognitive functions also change with age. To date however, evidence for age-related differentiation is mixed, and no study has examined differentiation of the relationship between brain and cognition. Here we use multi-group Structural Equation Modeling and SEM Trees to study differences within and between brain and cognition across the adult lifespan (18-88 years) in a large (N>646, closely matched across sexes), population-derived sample of healthy human adults from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.org). After factor analyses of grey-matter volume (from T1- and T2-weighted MRI) and white-matter organisation (fractional anisotropy from Diffusion-weighted MRI), we found evidence for differentiation of grey and white matter, such that the covariance between brain factors decreased with age. However, we found no evidence for age differentiation between fluid intelligence, language and memory, suggesting a relatively stable covariance pattern between cognitive factors. Finally, we observed a specific pattern of age differentiation between brain and cognitive factors, such that a white matter factor, which loaded most strongly on the hippocampal cingulum, became less correlated with memory performance in later life. These patterns are compatible with reorganization of cognitive functions in the face of neural decline, and/or with the emergence of specific subpopulations in old age.Significance statementThe theory of age differentiation posits age-related changes in the relationships between cognitive domains, either weakening (differentiation) or strengthening (de-differentiation), but evidence for this hypothesis is mixed. Using age-varying covariance models in a large cross-sectional adult lifespan sample, we found age-related reductions in the covariance among both brain measures (neural differentiation), but no covariance change between cognitive factors of fluid intelligence, language and memory. We also observed evidence of uncoupling (differentiation) between a white matter factor and cognitive factors in older age, most strongly for memory. Together, our findings support age-related differentiation as a complex, multifaceted pattern that differs for brain and cognition, and discuss several mechanisms that might explain the changing relationship between brain and cognition.

scholarly journals Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns

2020 ◽  
pp. 0271678X2095760
Author(s):  
Lene Pålhaugen ◽  
Carole H Sudre ◽  
Sandra Tecelao ◽  
Arne Nakling ◽  
Ina S Almdahl ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Framingham Risk Score ◽  
Early Stage ◽  
White Matter Hyperintensity ◽  
Group Differences ◽  
Vascular Risk ◽  
Automated Algorithm ◽  
Framingham Risk

White matter hyperintensities (WMHs) are associated with vascular risk and Alzheimer’s disease. In this study, we examined relations between WMH load and distribution, amyloid pathology and vascular risk in 339 controls and cases with either subjective (SCD) or mild cognitive impairment (MCI). Regional deep (DWMH) and periventricular (PWMH) WMH loads were determined using an automated algorithm. We stratified on Aβ1-42 pathology (Aβ+/−) and analyzed group differences, as well as associations with Framingham Risk Score for cardiovascular disease (FRS-CVD) and age. Occipital PWMH ( p = 0.001) and occipital DWMH ( p = 0.003) loads were increased in SCD-Aβ+ compared with Aβ− controls. In MCI-Aβ+ compared with Aβ− controls, there were differences in global WMH ( p = 0.003), as well as occipital DWMH ( p = 0.001) and temporal DWMH ( p = 0.002) loads. FRS-CVD was associated with frontal PWMHs ( p = 0.003) and frontal DWMHs ( p = 0.005), after adjusting for age. There were associations between global and all regional WMH loads and age. In summary, posterior WMH loads were increased in SCD-Aβ+ and MCI-Aβ+ cases, whereas frontal WMHs were associated with vascular risk. The differences in WMH topography support the use of regional WMH load as an early-stage marker of etiology.

Adverse effects of pre-existing cerebral small vessel disease on cognitive improvement after carotid endarterectomy

2019 ◽  
Vol 15 (6) ◽  
pp. 657-665 ◽  
Author(s):  
Jun Yoshida ◽  
Fumio Yamashita ◽  
Makoto Sasaki ◽  
Kunihiro Yoshioka ◽  
Shunrou Fujiwara ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
White Matter ◽  
Carotid Endarterectomy ◽  
White Matter Hyperintensities ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Cognitive Improvement ◽  
Vessel Disease

Background Although patients with improved cognition after carotid endarterectomy usually exhibit postoperative restoration of cerebral blood flow, less than half of patients with such cerebral blood flow change have postoperatively improved cognition. Cerebral small vessel disease on magnetic resonance imaging is associated with irreversible cognitive impairment. Aims The purpose of the present prospective study was to determine whether pre-existing cerebral small vessel disease affects cognitive improvement after carotid endarterectomy. Methods Brain MR imaging was performed preoperatively, and the number or grade of each cerebral small vessel disease was determined in 80 patients undergoing carotid endarterectomy for ipsilateral internal carotid artery stenosis (≥70%). The volume of white matter hyperintensities relative to the intracranial volume was also calculated. Brain perfusion single-photon emission computed tomography and neuropsychological testing were performed preoperatively and two months postoperatively. Based on these data, a postoperative increase in cerebral blood flow and postoperative improved cognition, respectively, were determined. Results Logistic regression analysis using the sequential backward elimination approach revealed that a postoperative increase in cerebral blood flow (95% confidence interval [CI], 10.74–3730.00; P = 0.0004) and the relative volume of white matter hyperintensities (95% CI, 0.01–0.63; P = 0.0314) were significantly associated with postoperative improved cognition. Although eight of nine patients with postoperative improved cognition exhibited both a relative volume of white matter hyperintensities <0.65% and a postoperative increase in cerebral blood flow, none of patients with a relative volume of white matter hyperintensities ≥0.65% had postoperative improved cognition regardless of any postoperative change in cerebral blood flow. Conclusion Pre-existing cerebral white matter hyperintensities on magnetic resonance imaging adversely affect cognitive improvement after carotid endarterectomy.

scholarly journals Reduction in cerebral blood flow in areas appearing as white matter hyperintensities on magnetic resonance imaging

2009 ◽  
Vol 172 (2) ◽  
pp. 117-120 ◽  
Author(s):  
Adam M. Brickman ◽  
Amir Zahra ◽  
Jordan Muraskin ◽  
Jason Steffener ◽  
Christopher M. Holland ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Blood Flow ◽  
Cerebral Blood Flow ◽  
White Matter ◽  
Magnetic Resonance ◽  
White Matter Hyperintensities ◽  
Resonance Imaging

scholarly journals Causal effect of atrial fibrillation on brain white or grey matter volume: A Mendelian randomization study

2020 ◽  
Author(s):  
Sehoon Park ◽  
Soojin Lee ◽  
Yaerim Kim ◽  
Semin Cho ◽  
Kwangsoo Kim ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
White Matter ◽  
Grey Matter ◽  
Mendelian Randomization ◽  
Brain Volume ◽  
Causal Effect ◽  
Grey Matter Volume ◽  
Volume Loss ◽  
White Matter Volume ◽  
Matter Volume

AbstractBackgroundAtrial fibrillation (AF) and brain volume loss are prevalent in older individuals. Further study investigating the causal effect of AF on brain volume is warranted.MethodsThis study was a Mendelian randomization (MR) analysis. The genetic instrument for AF was constructed from a previous genome-wide association study (GWAS) meta-analysis and included 537,409 individuals of European ancestry. The outcome summary statistics for quantile-normalized white or grey matter volume measured by magnetic resonance imaging were provided by the previous GWAS of 8426 white British UK Biobank participants. The main MR method was the inverse variance weighted method, supported by sensitivity MR analysis including MR-Egger regression and the weighted median method. The causal estimates from AF to white or grey matter volume were further adjusted for effects of any stroke or ischemic stroke by multivariable MR analysis.ResultsA higher genetic predisposition for AF (one standard deviation increase) was significantly associated with lower white matter volume [beta −0.128 (−0.208, −0.048)] but not grey matter volume [beta −0.041 (−0.101, 0.018)], supported by all utilized sensitivity MR analyses. The multivariable MR analysis indicated that AF is causally linked to lower white matter volume independent of the stroke effect.ConclusionsAF is a causative factor for white matter volume loss. The effect of AF on grey matter volume was inapparent in this study. A future trial is necessary to confirm whether appropriate AF management can be helpful in preventing cerebral white matter volume loss or related brain disorders in AF patients.

scholarly journals Age-specific adult rat brain MRI templates and tissue probability maps

2021 ◽  
Author(s):  
Eilidh MacNicol ◽  
Paul Wright ◽  
Eugene Kim ◽  
Irene Brusini ◽  
Oscar Esteban ◽  
...  
Keyword(s):  
White Matter ◽  
Rat Brain ◽  
Grey Matter ◽  
Brain Volume ◽  
Grey Matter Volume ◽  
Total Brain Volume ◽  
Adult Rat ◽  
Matter Volume ◽  
Probability Maps ◽  
Total Brain

Age-specific resources mitigate biases in human MRI processing arising from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue’s relative contribution to total brain volume would change with age in the adult rat. However, the currently available tissue probability maps, which provide a priori information for tissue volume estimation, provide inaccurate grey matter probabilities in subcortical structures, particularly the thalamus. Consequently, age-specific templates and tissue probability maps were generated from a longitudinal study that scanned a cohort of rats at 3, 5, 11, and 17 months old. Mixed-effects models assessed the effect of age on brain, grey matter, white matter, and CSF volumes, and the relative tissue proportions. Grey and white matter volume increased with age, and the tissue proportions relative to total brain volume varied throughout adulthood. Furthermore, we present evidence of a systematic underestimation of thalamic grey matter volume with existing resources, which is mitigated with the use of age-specific tissue probability maps since the derived estimates better matched histological evidence. To reduce age-related biases in image pre-processing, a set of rat brain resources from across the adult lifespan is consequently released to expand the preclinical MRI community’s fundamental resources.

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