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Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remain unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function. Here, we investigated the potential inter-relations between cognitive impairment, apathy and gait dysfunction, with a specific focus on determining whether these clinical features are associated with damage to the meso-cortical and meso-limbic pathways in SVD. In this cross-sectional study, we included 213 participants with SVD for whom MRI and comprehensive neurobehavioural assessments were performed. These assessments comprised six clinical measures: processing speed, executive function, memory, apathy (based on the Apathy Evaluation Scale) and gait function (based on the time and steps in the Timed Up and Go Test). We reconstructed five tracts connecting the ventral tegmental area (VTA) and dorsolateral prefrontal cortex (PFC), ventral lateral PFC, medial orbitofrontal cortex, anterior cingulate cortex (ACC) and nucleus accumbens within meso-cortical and meso-limbic pathways using diffusion weighted imaging. The damage along the five tracts was quantified using the free water (FW) and FW-corrected mean diffusivity indices. Furthermore, we explored the inter-correlations among the six clinical measures and identified their common components using principal component analysis (PCA). Linear regression analyses showed that higher FW values of tracts within meso-cortical pathways were related to these clinical measures in cognition, apathy, and gait (all P-corrected values < 0.05). The PCA showed strong inter-associations among these clinical measures and identified a common component wherein all six clinical measures loaded on. Higher FW values of tracts within meso-cortical pathways were related to the PCA-derived common component (all P-corrected values < 0.05). Moreover, FW values of the VTA-ACC tract showed the strongest contribution to the PCA-derived common component over all other neuroimaging features. In conclusion, our study showed that the three clinical features (cognitive impairment, apathy, and gait dysfunction) of SVD are strongly inter-related and that the damage in meso-cortical pathway could be the common neural basis underlying the three features in SVD. These findings advance our understanding of the mechanisms behind these clinical features of SVD and have the potential to inform novel management and intervention strategies for SVD., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The link between white matter hyperintensities (WMH) and cortical thinning is thought to be an important pathway by which WMH contributes to cognitive deficits in cerebral small vessel disease (SVD). However, the mechanism behind this association and the underlying tissue composition abnormalities are unclear. The objective of this study is to determine the association between WMH and cortical thickness, and the in vivo tissue composition abnormalities in the WMH-connected cortical regions. In this cross-sectional study, we included 213 participants with SVD who underwent standardized protocol including multimodal neuroimaging scans and cognitive assessment (i.e. processing speed, executive function and memory). We identified the cortex connected to WMH using probabilistic tractography starting from the WMH and defined the WMH-connected regions at three connectivity levels (low, medium and high connectivity level). We calculated the cortical thickness, myelin and iron of the cortex based on T1-weighted, quantitative R1, R2* and susceptibility maps. We used diffusion-weighted imaging to estimate the mean diffusivity of the connecting white matter tracts. We found that cortical thickness, R1, R2* and susceptibility values in the WMH-connected regions were significantly lower than in the WMH-unconnected regions (all Pcorrected < 0.001). Linear regression analyses showed that higher mean diffusivity of the connecting white matter tracts were related to lower thickness (β = -0.30, Pcorrected < 0.001), lower R1 (β = -0.26, Pcorrected = 0.001), lower R2* (β = -0.32, Pcorrected < 0.001) and lower susceptibility values (β = -0.39, Pcorrected < 0.001) of WMH-connected cortical regions at high connectivity level. In addition, lower scores on processing speed were significantly related to lower cortical thickness (β = 0.20, Pcorrected = 0.030), lower R1 values (β = 0.20, Pcorrected = 0.006), lower R2* values (β = 0.29, Pcorrected = 0.006) and lower susceptibility values (β = 0.19, Pcorrected = 0.024) of the WMH-connected regions at high connectivity level, independent of WMH volumes and the cortical measures of WMH-unconnected regions. Together, our study demonstrated that the microstructural integrity of white matter tracts passing through WMH is related to the regional cortical abnormalities as measured by thickness, R1, R2* and susceptibility values in the connected cortical regions. These findings are indicative of cortical thinning, demyelination and iron loss in the cortex, which is most likely through the disruption of the connecting white matter tracts and may contribute to processing speed impairment in SVD, a key clinical feature of SVD. These findings may have implications for finding intervention targets for the treatment of cognitive impairment in SVD by preventing secondary degeneration., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Cysteine-altering missense variants (NOTCH3cys) in one of the 34 epidermal growth-factor-like repeat (EGFr) domains of the NOTCH3 protein are the cause of NOTCH3-associated small vessel disease (NOTCH3-SVD). NOTCH3-SVD is highly variable, ranging from cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) at the severe end of the spectrum to non-penetrance. The strongest known NOTCH3-SVD modifier is NOTCH3cys variant position: NOTCH3cys variants located in EGFr domains 1-6 are associated with a more severe phenotype than NOTCH3cys variants located in EGFr domains 7-34. The objective of this study was to further improve NOTCH3-SVD genotype-based risk prediction by using relative differences in NOTCH3cys variant frequencies between large CADASIL and population cohorts as a starting point. Scientific CADASIL literature, cohorts and population databases were queried for NOTCH3cys variants. For each EGFr domain, the relative difference in NOTCH3cys variant frequency (NVFOR) was calculated using genotypes of 2574 CADASIL patients and 1647 individuals from population databases. Based on NVFOR cut-off values, EGFr domains were classified as either low (LR-EGFr), medium (MR-EGFr) or high risk (HR-EGFr). The clinical relevance of this new three-tiered EGFr risk classification was cross-sectionally validated by comparing SVD imaging markers and clinical outcomes between EGFr risk categories using a genotype-phenotype data set of 434 CADASIL patients and 1003 NOTCH3cys positive community-dwelling individuals. CADASIL patients and community-dwelling individuals harboured 379 unique NOTCH3cys variants. Nine EGFr domains were classified as an HR-EGFr, which included EGFr domains 1-6, but additionally also EGFr domains 8, 11 and 26. Ten EGFr domains were classified as MR-EGFr and 11 as LR-EGFr. In the population genotype-phenotype data set, HR-EGFr individuals had the highest risk of stroke [odds ratio (OR) = 10.81, 95% confidence interval (CI): 5.46-21.37], followed by MR-EGFr individuals (OR = 1.81, 95% CI: 0.84-3.88) and LR-EGFr individuals (OR = 1 [reference]). MR-EGFr individuals had a significantly higher normalized white matter hyperintensity volume (nWMHv; P = 0.005) and peak width of skeletonized mean diffusivity (PSMD; P = 0.035) than LR-EGFr individuals. In the CADASIL genotype-phenotype data set, HR-EGFr domains 8, 11 and 26 patients had a significantly higher risk of stroke (P = 0.002), disability (P = 0.041), nWMHv (P = 1.8 × 10-8), PSMD (P = 2.6 × 10-8) and lacune volume (P = 0.006) than MR-EGFr patients. SVD imaging marker load and clinical outcomes were similar between HR-EGFr 1-6 patients and HR-EGFr 8, 11 and 26 patients. NVFOR was significantly associated with vascular NOTCH3 aggregation load (P = 0.006), but not with NOTCH3 signalling activity (P = 0.88). In conclusion, we identified three clinically distinct NOTCH3-SVD EGFr risk categories based on NFVOR cut-off values, and identified three additional HR-EGFr domains located outside of EGFr domains 1-6. This EGFr risk classification will provide an important key to individualized NOTCH3-SVD disease prediction., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Alzheimer's disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and coexist in most memory clinic patients. White matter damage as assessed by diffusion MRI is a key feature in both Alzheimer's and cerebral small vessel disease. However, disease-specific biomarkers of white matter alterations are missing. Recent advances in diffusion MRI operating on the fixel level (fibre population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows derivation of measures of both white matter microstructure, measured by fibre density, and macrostructure, measured by fibre-bundle cross-section. Here, we evaluated the capacity of these state-of-the-art fixel metrics to disentangle the effects of cerebral small vessel disease and Alzheimer's disease on white matter integrity. We included three independent samples (total n = 387) covering genetically defined cerebral small vessel disease and age-matched controls, the full spectrum of biomarker-confirmed Alzheimer's disease including amyloid- and tau-PET negative controls and a validation sample with presumed mixed pathology. In this cross-sectional analysis, we performed group comparisons between patients and controls and assessed associations between fixel metrics within main white matter tracts and imaging hallmarks of cerebral small vessel disease (white matter hyperintensity volume, lacune and cerebral microbleed count) and Alzheimer's disease (amyloid- and tau-PET), age and a measure of neurodegeneration (brain volume). Our results showed that (i) fibre density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks; (ii) fibre-bundle cross-section was mainly associated with brain volume; and (iii) both fibre density and fibre-bundle cross-section were reduced in the presence of amyloid, but not further exacerbated by abnormal tau deposition. Fixel metrics were only weakly associated with amyloid- and tau-PET. Taken together, our results in three independent samples suggest that fibre density captures the effect of cerebral small vessel disease, while fibre-bundle cross-section is largely determined by neurodegeneration. The ability of fixel-based imaging markers to capture distinct effects on white matter integrity can propel future applications in the context of precision medicine., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.

Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity × estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.

White matter hyperintensities and lacunes are among the most frequent abnormalities on brain magnetic resonance imaging. They are commonly related to cerebral small vessel disease and associated with both stroke and dementia. We examined the spatial relationships between incident lacunes and white matter hyperintensities and related these findings to information on vascular anatomy to study possible mechanistic links between the two lesion types. Two hundred and seventy-six patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a genetically defined small vessel disease with mutations in the NOTCH3 gene were followed with magnetic resonance imaging over a total of 633 patient years. Using difference images and Jacobian maps from registered images we identified 104 incident lacunes. The majority (n = 95; 91.3%) of lacunes developed at the edge of a white matter hyperintensity whereas few lacunes were found to develop fully within (n = 6; 5.8%) or outside (n = 3; 2.9%) white matter hyperintensities. Adding information on vascular anatomy revealed that the majority of incident lacunes developed proximal to a white matter hyperintensity along the course of perforating vessels supplying the respective brain region. We further studied the spatial relationship between prevalent lacunes and white matter hyperintensities both in 365 patients with CADASIL and in 588 elderly subjects from the Austrian Stroke Prevention Study. The results were consistent with the results for incident lacunes. Lesion prevalence maps in different disease stages showed a spread of lesions towards subcortical regions in both cohorts. Our findings suggest that the mechanisms of lacunes and white matter hyperintensities are intimately connected and identify the edge of white matter hyperintensities as a predilection site for lacunes. Our observations further support and refine the concept of the white matter hyperintensity penumbra.

Cerebral small vessel disease is the most common cause of vascular cognitive impairment. It typically manifests with lacunar infarcts and ischaemic white matter lesions. However, little is known about how these lesions relate to the cognitive symptoms. Previous studies have found a poor correlation between the burden of ischaemic lesions and cognitive symptoms, thus leaving much of the variance in cognitive performance unexplained. The objective of the current study was to investigate the relationship between the location of subcortical ischaemic lesions and cognitive symptoms in small vessel disease. We applied a voxel-based lesion-symptom mapping approach to data from 215 patients with CADASIL, a genetically defined small vessel disease with mutations in the NOTCH3 gene. All patients were examined by magnetic resonance imaging and comprehensive neuropsychological testing. Lacunar lesions and white matter lesions were segmented on three-dimensional T(1) and fluid-attenuated inversion recovery sequences, respectively. One hundred and forty-five subjects had a total of 854 lacunar lesions (range 1-13 per individual). The normalized volume of white matter hyperintensities ranged from 0.0425% to 21.5% of the intracranial cavity. Significant clusters for cognitive performance were detected for both lacunar lesions and white matter hyperintensities. The most prominent results were obtained on a compound score for processing speed, the predominantly affected cognitive domain in this group of patients. Strategic locations included the anterior parts of the thalamus, the genu and anterior limb of the internal capsule, the anterior corona radiata and the genu of the corpus callosum. By combining the lesion-symptom mapping data with information from a probabilistic white matter atlas we found that the majority of the processing speed clusters projected on the anterior thalamic radiation and the forceps minor. In multivariate models that included demographic parameters, brain atrophy and the volume of ischaemic lesions, regional volumes of lacunar lesions and white matter hyperintensities in the anterior thalamic radiation predicted performance in processing speed tasks, whereas there was no independent contribution of the global volume of ischaemic lesions. These observations emphasize the importance of lesion location for both lacunar and ischaemic white matter lesions. Our findings further highlight the anterior thalamic radiation as a major anatomical structure impacting on processing speed. Together these findings provide strong support for a central role of frontal-subcortical circuits in cerebral small vessel disease and vascular cognitive impairment.