Structural network changes in cerebral small vessel disease

Tuladhar, Anil M.; Tay, Jonathan; Leijsen, Esther van; Lawrence, Andrew J.; Uden, Ingeborg W.M. van; Bergkamp, Mayra I.; Holst, Ellen van der; Kessels, Roy P. C.; Norris, David G.; Markus, Hugh S.; Leeuw, Frank Erik de

doi:10.1136/jnnp-2019-321767

Cited by 43 publications

(33 citation statements)

References 46 publications

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“…In line with this hypothesis, our results suggest that disconnectivity plays a role already in the preclinical stages of dementia. The findings in this study also extend results from clinical studies in patients with cerebral small vessel disease to the general population, [14][15][16][17] suggesting that measures of FA/MD may improve prognostic accuracy of existing prediction models to identify persons at high risk of dementia in the community. Furthermore, knowledge of tract-specific effects on cognition and risk of dementia may allow clinicians to better understand why specific patients with only small, but strategically located brain infarcts develop cognitive impairment, and which patients after stroke are most likely to develop dementia.…”

Section: Discussionsupporting

confidence: 73%

“…13 In 4 longitudinal studies from 2 clinical cohorts of patients with small vessel disease, network disruption was related to accelerated decline in psychomotor speed and an increased risk of dementia. [14][15][16][17] However, patients with substantial small vessel disease on MRI represent a minority of the individuals at high risk of dementia in the community, and it remains undetermined whether prior findings extend to the wider population without severe small vessel disease, prior TIA, or stroke. In addition, study in persons with and without small vessel disease may better determine the effect of disconnectivity on dementia, above and beyond the burden of, for example, WMHs.…”

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confidence: 99%

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Structural disconnectivity and the risk of dementia in the general population

et al. 2020

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Objective:The ‘disconnectivity hypothesis’ postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion-magnetic resonance imaging (MRI) to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.Methods:Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 non-demented persons (mean age: 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005-2011. We modelled the association of these diffusion measures with risk of dementia (follow-up until 2016), and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.Results:During a mean follow-up of 6.7 years, 101 participants had incident dementia, of whom 83 had clinical AD. Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval] per standard deviation increase – for MD: 1.79 [1.44-2.23], and FA: 0.65 [0.52;0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in non-demented individuals (difference in global cognition per standard deviation increase in MD (95% CI) was: -0.04 (-0.07;-0.01)). Associations were most profound in the projection, association and limbic system tracts.Conclusions:Structural disconnectivity is associated with and an increased risk of dementia and more pronounced cognitive decline in the general population.

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Section: Discussionsupporting

confidence: 73%

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confidence: 99%

Structural disconnectivity and the risk of dementia in the general population

et al. 2020

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“…Widespread white matter network damage is a known consequence of SVD (Tuladhar et al, 2020), although the etiology of this phenomenon remains incompletely understood. Research in this area largely focuses on understanding the pathophysiology underlying the radiological manifestations of SVD (Wardlaw et al, 2019).…”

Section: Apathy In Cerebral Small Vessel Diseasementioning

confidence: 99%

Network neuroscience of apathy in cerebrovascular disease

Tay

Lisiecka-Ford

Hollocks

et al. 2020

Progress in Neurobiology

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Apathy is a reduction in motivated goal-directed behavior (GDB) that is prevalent in cerebrovascular disease, providing an important opportunity to study the mechanistic underpinnings of motivation in humans. Focal lesions, such as those seen in stroke, have been crucial in developing models of brain regions underlying motivated behavior, while studies of cerebral small vessel disease (SVD) have helped define the connections between brain regions supporting such behavior. However, current lesion-based models cannot fully explain the neurobiology of apathy in stroke and SVD. To address this, we propose a network-based model which conceptualizes apathy as the result of damage to GDB-related networks. A review of the current evidence suggests that cerebrovascular disease-related pathology can lead to network changes outside of initially damaged territories, which may propagate to regions that share structural or functional connections. The presentation and longitudinal trajectory of apathy in stroke and SVD may be the result of these network changes. Distinct subnetworks might support cognitive components of GDB, the disruption of which results in specific symptoms of apathy. This network-based model of apathy may open new approaches for investigating its underlying neurobiology, and presents novel opportunities for its diagnosis and treatment. Recent research on the fundamental neuroanatomical and neurocognitive mechanisms underlying apathy has broadened our understanding of apathy in cerebrovascular disease and across neurological disorders. Despite this, theoretical work has primarily focused on linking neurodegenerative pathology to apathy, such as in Alzheimer's disease or Parkinson's disease (e.g., Lanctôt et al., 2017; Pagonabarraga et al., 2015). This has left the mechanisms underlying apathy in cerebrovascular disease comparably under-explored. Given the high prevalence of comorbid vascular pathology in neurodegenerative

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“… 9 , 10 , 21 , 33–36 Regarding the non-bleeding SVDs, subjects with severe WMHs were further divided depending on whether a lacune was present. Previous studies that studied the significance or effects of SVD have only focussed on individual SVD markers, mostly the WMH, 37 , 38 and contradicted the actual circumstance that patients with SVD usually have several coexisted SVD markers in the brain. The latest proposed SVD measurement, the SVD score, includes more SVD markers.…”

Section: Discussionmentioning

confidence: 99%

Classification differentiates clinical and neuroanatomic features of cerebral small vessel disease

Chou

Lee

Peng

et al. 2021

Brain Communications

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Age-related cerebral small vessel disease involves heterogeneous pathogenesis such as arteriosclerosis/lipohyalinosis and cerebral amyloid angiopathy. MRI can visualise the brain lesions attributable to small vessel disease pathologies, including white-matter hyperintensities, lacune, and cerebral microbleeds. However, these MRI markers usually coexist in small vessel disease of different etiologies. Currently, there is no available classification integrating these neuroimaging markers for differentiating clinical and neuroanatomic features of small vessel disease yet. In the present study, we tested whether our proposed stratification scheme could characterize specific clinical, neuroanatomic and potentially pathogenesis/etiologies in classified small vessel disease subtypes. Cross-sectional analyses from a community-based non-demented non-stroke cohort consisting of ≥ 50 years-old individuals were conducted. All participants were scanned 3T brain MRI for small vessel disease detection and neuroanatomic measurements and underwent physical and cognitive assessments. Study population were classified into robust and four small vessel disease groups based on imaging markers indicating (1) bleeding or non-bleeding, (2) specific location of cerebral microbleeds, and (3) the severity and combination of white-matter hyperintensities and lacune. We used whole-brain voxel-based morphometry analyses and tract-based spatial statistics to evaluate the regional grey-matter volume and white-matter microstructure integrity for comparisons among groups. Among the 735 participants with eligible brain MRI images, quality screening qualified 670 for grey-matter volume analyses and 617 for white-matter microstructural analyses. Common and distinct patterns of the clinical and neuroimaging manifestations were found in the stratified four small vessel disease subgroups. Hierarchical clustering analysis revealed that small vessel disease type 4 had features distinct from the small vessel disease type 1, 2 and 3. Abnormal white-matter microstructures and cognitive function but preserved physical function and grey-matter volume were found in small vessel disease type 4. Among small vessel disease type 1, 2 and 3, there were similar characteristics but different severity; the clinical features showed both physical frail and cognitive impairment and the neuroanatomic features revealed frontal-subcortical white-matter microstructures and remote, diffuse cortical abnormalities. This novel stratification scheme highlights the distinct clinical and neuroanatomic features of small vessel disease and the possible underlying pathogenesis. It could have potential application in research and clinical settings.

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Structural network changes in cerebral small vessel disease

Cited by 43 publications

References 46 publications

Structural disconnectivity and the risk of dementia in the general population

Structural disconnectivity and the risk of dementia in the general population

Network neuroscience of apathy in cerebrovascular disease

Classification differentiates clinical and neuroanatomic features of cerebral small vessel disease

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