Abstract Cerebral small vessel disease (SVD) can disrupt the global brain network and lead to cognitive impairment. Conversely, cognitive reserve (CR) can improve one's cognitive ability to handle damaging effects like SVD, partly by optimizing the brain network's organization. Understanding how SVD and CR collectively influence brain networks could be instrumental in preventing cognitive impairment. Recently, brain redundancy has emerged as a critical network protective metric, providing a nuanced perspective of changes in network organization. However, it remains unclear how SVD and CR affect global redundancy and subsequently cognitive function. Here, we included 121 community‐dwelling participants who underwent neuropsychological assessments and a multimodal MRI examination. We visually examined common SVD imaging markers and assessed lifespan CR using the Cognitive Reserve Index Questionnaire. We quantified the global redundancy index (RI) based on the dynamic functional connectome. We then conducted multiple linear regressions to explore the specific cognitive domains related to RI and the associations of RI with SVD and CR. We also conducted mediation analyses to explore whether RI mediated the relationships between SVD, CR, and cognition. We found negative correlations of RI with the presence of microbleeds (MBs) and the SVD total score, and a positive correlation of RI with leisure activity‐related CR (CRI‐leisure). RI was positively correlated with memory and fully mediated the relationships between the MBs, CRI‐leisure, and memory. Our study highlights the potential benefits of promoting leisure activities and keeping brain redundancy for memory preservation in older adults, especially those with SVD.
Abstract White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD). This condition contributes to about 50% of dementias worldwide, a massive health burden in aging. Microstructural alterations in the deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in the superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In this paper, 141 patients with CSVD were studied. Processing speed was assessed by the completion time of the Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (lesion volume on T2-FLAIR) and diffusion MRI, including DTI and free-water (FW) imaging microstructure measures. The results of our study indicate that the superficial white matter may play a particularly important role in cognitive decline in CSVD. SWM imaging measures resulted in a large contribution to processing speed, despite a relatively small WMH burden in the SWM. SWM FW had the strongest association with processing speed among all imaging markers and, unlike the other diffusion MRI measures, significantly increased between two patient subgroups with the lowest WMH burdens (possibly representing early stages of disease). When comparing two patient subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Given significant effects of WMH volume and regional FW on processing speed, we performed a mediation analysis. SWM FW was found to fully mediate the association between WMH volume and processing speed, while no mediation effect of DWM FW was observed. Overall, our findings identify SWM abnormalities in CSVD and suggest that the SWM has an important contribution to processing speed. Results indicate that FW in the SWM is a sensitive marker of microstructural changes associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes in future research.
Widespread white matter injury is a hallmark feature of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) patients. However, controversies about the mechanism of white matter injury exist persistently. Excessive iron accumulation, frequently reported in CADASIL patients, might cause retrograde white matter injury. Therefore, we aim to test the association between iron accumulation and white matter injury in CADASIL patients. Thirty-five CADASIL patients confirmed via genetic analysis and 48 healthy controls were included. Iron accumulation was evaluated in deep gray matter using quantitative susceptibility mapping (QSM), and white matter injury was quantified by diffusion metrics. We compared iron deposition between groups and analyzed the correlation between white matter injury and iron deposition in CADASIL patients. Exploratory analysis was carried out to investigate whether white matter injury mediated the relationship between iron deposition and cognitive impairment. We found that compared with healthy controls, CADASIL patients had increased iron deposition in the caudate (p = 0.002) and putamen (p < 0.001). Besides, aberrant iron deposition in these two regions was related to decreased white matter fractional anisotropy (FA) (caudate, r = - 0.373, p = 0.042;putamen, r = - 0.421, p = 0.020), and increased radial diffusivity (RD) (caudate, r = 0.372, p = 0.043; putamen, r =0.386, p = 0.035). Furthermore, white matter injury mediated the relationship between iron deposition and cognitive impairment. These findings support a potential mechanism of white matter injury in CADASIL patients.Funding Information: This work was supported by the National Natural Science Foundation of China (Grant No. 81971577 & 81901706 & 81500993 & 81771820 & 82001767 & 82101987 & 82101984), the Natural Science Foundation of Zhejiang Province (Grant No. LQ21H180008), the China Postdoctoral Science Foundation (Grant No. 2019M662082 & 2019M662083). Declaration of Interests: The authors have no competing interests to declare that are relevant to the content of this article. Ethics Approval Statement: Study protocols had been approved by the local ethics committee. All clinical investigation has been conducted according to the principles expressed in the Declaration of Helsinki. All participants had informed written consent.
Individuals with subjective memory complaints (SMC) feature a higher risk of cognitive decline and clinical progression of Alzheimer's disease (AD). However, the pathological mechanism underlying SMC remains unclear. We aimed to assess the intrinsic connectivity network and its relationship with AD-related pathologies in SMC individuals.We included 44 SMC individuals and 40 normal controls who underwent both resting-state functional MRI and positron emission tomography (PET). Based on graph theory approaches, we detected local and global functional connectivity across the whole brain by using degree centrality (DC) and eigenvector centrality (EC) respectively. Additionally, we analyzed amyloid deposition and tauopathy via florbetapir-PET imaging and cerebrospinal fluid (CSF) data. The voxel-wise two-sample T-test analysis was used to examine between-group differences in the intrinsic functional network and cerebral amyloid deposition. Then, we correlated these network metrics with pathological results.The SMC individuals showed higher DC in the bilateral hippocampus (HP) and left fusiform gyrus and lower DC in the inferior parietal region than controls. Across all subjects, the DC of the bilateral HP and left fusiform gyrus was positively associated with total tau and phosphorylated tau181. However, no significant between-group difference existed in EC and cerebral amyloid deposition.We found impaired local, but not global, intrinsic connectivity networks in SMC individuals. Given the relationships between DC value and tau level, we hypothesized that functional changes in SMC individuals might relate to pathological biomarkers.
Brain connectivity alterations associated with mental disorders have been widely reported in both functional MRI (fMRI) and diffusion MRI (dMRI). However, extracting useful information from the vast amount of information afforded by brain networks remains a great challenge. Capturing network topology, graph convolutional networks (GCNs) have demonstrated to be superior in learning network representations tailored for identifying specific brain disorders. Existing graph construction techniques generally rely on a specific brain parcellation to define regions-of-interest (ROIs) to construct networks, often limiting the analysis into a single spatial scale. In addition, most methods focus on the pairwise relationships between the ROIs and ignore high-order associations between subjects. In this letter, we propose a mutual multi-scale triplet graph convolutional network (MMTGCN) to analyze functional and structural connectivity for brain disorder diagnosis. We first employ several templates with different scales of ROI parcellation to construct coarse-to-fine brain connectivity networks for each subject. Then, a triplet GCN (TGCN) module is developed to learn functional/structural representations of brain connectivity networks at each scale, with the triplet relationship among subjects explicitly incorporated into the learning process. Finally, we propose a template mutual learning strategy to train different scale TGCNs collaboratively for disease classification. Experimental results on 1,160 subjects from three datasets with fMRI or dMRI data demonstrate that our MMTGCN outperforms several state-of-the-art methods in identifying three types of brain disorders.
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Abstract Objective This study investigated cerebral small vessel disease (CSVD) damage patterns in early‐onset and late‐onset Alzheimer's disease (EOAD and LOAD) and their effects on cognitive function. Methods This study included 93 participants, 45 AD patients (14 EOAD and 31 LOAD), and 48 normal controls (13 YNC and 35 ONC) from the ADNI database. All participants had diffusion tensor imaging data; some had amyloid PET and plasma p‐tau 181 data. The study used peak width of skeletonized mean diffusivity (PSMD) to measure CSVD severity and compared PSMD between patients and age‐matched controls. The effect of age on the relationship between PSMD and cognition was also examined. The study also repeated the analysis in amyloid‐positive AD patients and amyloid‐negative controls in another independent database (31 EOAD and 38 LOAD), and the merged database. Results EOAD and LOAD showed similar cognitive function and disease severity. PSMD was validated as a reliable correlate of cognitive function. In the ADNI database, PSMD was significantly higher for LOAD and showed a tendency to increase for EOAD; in the independent and merged databases, PSMD was significantly higher for both LOAD and EOAD. The impact of PSMD on cognitive function was notably greater in the younger group (YNC and EOAD) than in the older group (ONC and LOAD), as supported by the ADNI and merged databases. Interpretation EOAD has less CSVD burden than LOAD, but has a greater impact on cognition. Proactive cerebrovascular prevention strategies may have potential clinical value for younger older adults with cognitive decline.
Leukoaraiosis is associated with increased risk of cognitive impairment, but its pathophysiological pathway is unclear. The aim of the present study was to determine whether brain structural damage or cerebral blood supply better correlated with the global cognitive outcome in subjects with leukoaraiosis. Seventy-five subjects with leukoaraiosis were included in present study, with age ranged from 43 to 85 years, with mean white matter hyperintensities (WMH) volume 30.69 ± 24.35 mL. Among them, 19(25.33%) subjects presented with cerebral microbleeds (CMB) and 40 (53.33%) subjects presented with lacunes. These participants received arterial spin labeling perfusion MRI, diffusion-tensor imaging (DTI) and diffusion Kurtosis imaging. We analyzed the cerebral blood flow (CBF) by dividing the brain tissue into three regions: WMH, normal appearing white matter (NAWM) and cortex. After adjusting for age and gender, the CBF of NAWM was significantly correlated with fractional anisotropy (FA) (r = 0.336, p = 0.004) and mean diffusion (MD) (r = -0.271, p = 0.020) of NAWM, while there lacked of association between CBF of cortex and mean kurtosis (MK) of cortex (r = -0.015, p = 0.912). Meanwhile, both NAWM-FA (r = -0.443, p < 0.001) and NAWM-MD (r = 0.293, p = 0.012), as well as cortex-MK (r = -0.341, p = 0.012) was significantly correlated with WMH volume. Univariate regression analysis demonstrated that global cognitive function was significantly associated with mean FA or MD of both WMH and NAWM, and cortex-CBF, but neither with the cortex-MK, nor the presences of CMB or lacunes. Finally, multiple linear regression analysis revealed that global cognitive function was independently associated with NAWM-FA (standardized β = 0.403, p < 0.001) and WMH-FA (Standardized β = 0.211, p = 0.017), but not with the cortex-CBF. A model that contained NAWM-FA, WMH-FA and years of education explained 49% of the variance of global cognitive function. Cerebral perfusion status might have a significant impact on the maintenance of white matter integrity in subjects with leukoaraiosis. Global cognitive function was more strongly associated with white matter integrity than with blood supply. DTI parameters, especially FA could serve as a potent imaging indicator for detecting the invisible alteration of white matter integrity and implying its potential cognitive relevance.
Cerebral venous collagenosis played a role in the pathogenesis of white matter hyperintensities (WMHs) through venous ischemia. Since pathological changes of veins from intramural stenosis to luminal occlusion is a dynamic process, we aimed to create a deep medullary veins (DMVs) visual grade on susceptibility-weighted images (SWI) and explore the relationship of DMVs and WMHs based on venous drainage regions. We reviewed clinical, laboratory and imaging data from 268 consecutive WMHs patients and 20 controls. SWI images were used to observe characteristics of DMVs and a brain region-based DMVs visual score was given by two experienced neuroradiologists. Fluid attenuated inversion recovery (FLAIR) images were used to calculate WMHs volume. Logistic-regression analysis and partial Pearson's correlation analysis were used to examine the association between the DMVs score and WMHs volume. We found that the DMVs score was significantly higher in WMHs patients than in controls (p < 0.001). Increased DMVs score was independently associated with higher WMHs volume after adjusting for total cholesterol level and number of lacunes (p < 0.001). Particularly, DMVs scores were correlated with regional PVHs volumes in the same brain region most. The newly proposed DMVs grading method allows the clinician to monitor the course of DMVs disruption. Our findings of cerebral venous insufficiency in WMHs patients may help to elucidate the pathogenic mechanisms and progression of WMHs.
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