The relationship between apathy and nonparametric variables of rest activity rhythm in older adults with cerebral small vessel disease.

The goal of the current study was to demonstrate if the rest-activity rhythm (RAR) was altered in apathetic older adults with cerebral small vessel disease (CSVD) and find out the relationship between apathy/depression severity and RAR features in CSVD patients. This is a cross-sectional observational investigation including 53 CSVD cases (54.74% men), aged 70.70 ± 6.18 years old. The participants were assessed by neuropsychiatric inventory (NPI) subscale of apathy (NPI-apathy) and depression (NPI-depression) in succession, according to updated diagnostic criteria for apathy (DCA). Each subject wore an actigraph device (ActiGraph GT3X) in their nondominant hand for 7 days to collect raw data. Using a non-parametric methodological analysis, this study determined RAR variables such as interdaily stability (IS), intraday variability (IV) and relative amplitude (RA). Patients in the apathy-positive group had a higher Fazekas score than those in the apathy-negative group. IS, but not IV, RA, or objective sleep variables, differed between elderly patients with varying degrees of CSVD burden. Furthermore, apathy severity was statistically correlated with RA after adjusting for age, gender and education level, whereas depression severity was not associated with RAR variables. Finally, we discovered that the severity of apathy had no significant relationship with the severity of depression. All these findings indicated that the RAR altered in apathetic older adults with CSVD, and apathy was associated with decreased RAR amplitude.

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients. Methods: Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing. Results: Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm. Conclusion: The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.

Regional cortical thinning, demyelination and iron loss in cerebral small vessel disease.

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 (ß = -0.30, Pcorrected < 0.001), lower R1 (ß = -0.26, Pcorrected = 0.001), lower R2* (ß = -0.32, Pcorrected < 0.001) and lower susceptibility values (ß = -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 (ß = 0.20, Pcorrected = 0.030), lower R1 values (ß = 0.20, Pcorrected = 0.006), lower R2* values (ß = 0.29, Pcorrected = 0.006) and lower susceptibility values (ß = 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.

Elevated Plasma Oligomeric Amyloid ß-42 Is Associated with Cognitive Impairments in Cerebral Small Vessel Disease.

Due to the heterogeneity of amyloid ß-42 (Aß42) species, the potential correlation between plasma oligomeric Aß42 (oAß42) and cognitive impairments in cerebral small vessel disease (CSVD) remains unclear. Herein, a sandwich ELISA for the specific detection of Aß42 oligomers (oAß42) and total Aß42 (tAß42) was developed based on sequence- and conformation-specific antibody pairs for the evaluation of plasma samples from a Chinese CSVD community cohort. After age and gender matching, 3-Tesla magnetic resonance imaging and multidimensional cognitive assessment were conducted in 134 CSVD patients and equal controls. The results showed that plasma tAß42 and oAß42 levels were significantly elevated in CSVD patients. By regression analysis, these elevations were correlated with the presence of CSVD and its imaging markers (i.e., white matter hyperintensities). Plasma Aß42 tests further strengthened the predictive power of vascular risk factors for the presence of CSVD. Relative to tAß42, oAß42 showed a closer correlation with memory domains evaluated by neuropsychological tests. In conclusion, this sensitive ELISA protocol facilitated the detection of plasma Aß42; Aß42, especially its oligomeric form, can serve as a biosensor for the presence of CSVD and associated cognitive impairments represented by memory domains.

Features of Cerebral Small Vessel Disease Contributes to the Differential Diagnosis of Alzheimer's Disease.

BACKGROUND: Cerebral small vessel disease (CSVD), which comprises the typical features of white matter hyperintensity (WMH) and Vichor-Robin spaces (VRSs) in the brain, is one of the leading causes of aging-related cognitive decline and, ultimately, contributes to the occurrence of dementia, including Alzheimer's disease (AD). OBJECTIVE: To investigate whether CSVD imaging markers modify the pathological processes of AD and whether these markers improve AD diagnosis. METHODS: 208 participants were enrolled in the China Aging and Neurodegenerative Initiative (CANDI). Fluid AD biomarkers were detected using a single-molecule array, and cerebral small vessel dysfunction was determined using magnetic resonance imaging. RESULTS: WMH contributed to AD pathology only within the NC and MCI groups (CDR ≤0.5), whereas VRSs had no effect on AD pathology. The associations between AD biomarkers and cognitive mental status were consistent with the presence of CSVD pathology. That is, within individuals without CSVD pathology, the MMSE scores were correlated with AD fluid biomarkers, except for plasma Aß42 and Aß40. Increased plasma p-Tau levels were associated with worse cognitive performance in individuals with WMH (ß= -0.465, p = 0.0016) or VRSs (ß= -0.352, p = 0.0257) pathology. Plasma AD biomarkers combined with CSVD markers showed high accuracy in diagnosing dementia. CONCLUSION: Findings from this cross-sectional cohort study support the notion that CSVD is a risk factor for dementia and highlights that vascular pathology can promote AD biomarker levels, especially in the early course of the disease. Moreover, our results suggest that adding a vascular category to the ATN framework improves the diagnostic accuracy of AD.

Longitudinal Changes of White Matter Hyperintensities in Sporadic Small Vessel Disease: A Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVES: White matter hyperintensities (WMHs) are frequent imaging features of small vessel disease (SVD) and related to poor clinical outcomes. WMH progression over time is well described, but regression was also noted recently, although the frequency and associated factors are unknown. This systematic review and meta-analysis aims to assess longitudinal intraindividual WMH volume changes in sporadic SVD. METHODS: We searched EMBASE and MEDLINE for articles up to 28 January 2022 on WMH volume changes using MRI on ≥2 time points in adults with sporadic SVD. We classified populations (healthy/community-dwelling, stroke, cognitive, other vascular risk factors, and depression) based on study characteristics. We performed random-effects meta-analyses with Knapp-Hartung adjustment to determine mean WMH volume change (change in milliliters, percentage of intracranial volume [%ICV], or milliliters per year), 95% CI, and prediction intervals (PIs, limits of increase and decrease) using unadjusted data. Risk of bias assessment tool for nonrandomized studies was used to assess risk of bias. We followed Preferred Reporting in Systematic Review and Meta-Analysis guidelines. RESULTS: Forty-one articles, 12,284 participants, met the inclusion criteria. Thirteen articles had low risk of bias across all domains. Mean WMH volume increased over time by 1.74 mL (95% CI 1.23-2.26; PI -1.24 to 4.73 mL; 27 articles, N = 7,411, mean time interval 2.7 years, SD = 1.65); 0.25 %ICV (95% CI 0.14-0.36; PI -0.06 to 0.56; 6 articles, N = 1,071, mean time interval 3.5 years, SD = 1.54); or 0.58 mL/y (95% CI 0.35-0.81; PI -0.26 to 1.41; 8 articles, N = 3,802). In addition, 13 articles specifically mentioned and/or provided data on WMH regression, which occurred in asymptomatic, stroke, and cognitive disorders related to SVD. DISCUSSION: Net mean WMH volume increases over time mask wide-ranging change (e.g., mean increase of 1.75 mL ranging from 1.25 mL decrease to 4.75 mL increase), with regression documented explicitly in up to one-third of participants. More knowledge on underlying mechanisms, associated factors, and clinical correlates is needed, as WMH regression could be an important intervention target.

Comparative Study of Risk Factors and Cognitive Profile of Small- and Large-Vessel Vascular Dementia - A Clinic Based Study.

Background: Vascular dementia (VaD) is a clinically heterogeneous entity. There is a dearth of studies for comparison of the cognitive profile of cerebral small-vessel disease (SVD) with large-vessel disease. Objective: We planned to evaluate and compare the cognitive profile of SVD and large-vessel VaD and evaluate various risk factors associated with them. Materials and Methods: Patients of VaD were recruited after excluding mixed and ambiguous cases. Patients were classified into SVD and large-vessel VaD and analyzed for their clinic-epidemiological and cognitive profiles. Results: Among 76 patients, 48 (62.5%) have SVD and 28 (37.5%) have large-vessel disease. Hypertension (93.4%) was the commonest risk factor, followed by smoking (34.21%), hyperlipidemia (26.31%), and diabetes mellitus (DM, 22.36%). Hypertension (P < 0.05) and DM were common in SVD, whereas smoking, hyperlipidaemia, and cardiac diseases were common in large-vessel disease. Attention (77.1% vs 25%), executive function (68.8% vs 28.6%), and calculation (58.3% vs 32.1%) were significantly more impaired in SVD compared to large-vessel disease, whereas visuoperceptual (21.4% vs 6.3%), praxis (28.6% vs 4.2%), and gnosis (14.3% vs 2.1%) were significantly more impaired in large-vessel disease than in SVD. Disruption of frontal-subcortical connection was responsible for the cognitive profile in SVD, but in large-vessel disease, it resulted from the cumulative loss of function from different lesions. Conclusions: Despite having common vascular risk factors, few are more common in SVD than in large-vessel disease. The different clinical and cognitive profile is due to the diverse anatomical lesions in these two subclasses of VaD.

Intelligent Algorithm-Based Quantitative Electroencephalography in Evaluating Cerebral Small Vessel Disease Complicated by Cognitive Impairment.

To analyze the application value of artificial intelligence model based on Visual Geometry Group- (VGG-) 16 combined with quantitative electroencephalography (QEEG) in cerebral small vessel disease (CSVD) with cognitive impairment, 72 patients with CSVD complicated by cognitive impairment were selected as the research subjects. As per Diagnostic and Statistical Manual (5th Edition), they were divided into the vascular dementia (VD) group of 34 cases and vascular cognitive impairment with no dementia (VCIND) group of 38 cases. The two groups were analyzed for the clinical information, neuropsychological test results, and monitoring results of QEEG based on intelligent algorithms for more than 2 hours. The accuracy rate of VGG was 84.27% and Kappa value was 0.7, while that of modified VGG (nVGG) was 88.76% and Kappa value was 0.78. The improved VGG algorithm obviously had higher accuracy. The test results found that the QEEG identified 8 normal, 19 mild, 10 moderate, and 0 severe cases in the VCIND group, while in the VD group, the corresponding numbers were 4, 13, 11, and 7; in the VCIND group, 7 cases had the normal QEEG, 11 cases had background changes, 9 cases had abnormal waves, and 11 cases had in both background changes and abnormal waves, and in the VD group, the corresponding numbers were 5, 2, 5, and 22, respectively; in the VCIND group, QEEG of 18 patients had no abnormal waves, QEEG of 11 patients had a few abnormal waves, and QEEG of 9 patients had many abnormal waves, and QEEG of 0 people had a large number of abnormal waves, and in the VD group, the corresponding numbers were 7, 6, 12, and 9. The above data were statistically different between the two groups (P < 0.05). Hence, QEEG based on intelligent algorithms can make a good assessment of CSVD with cognitive impairment, which had good clinical application value.

Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease.

BACKGROUND: Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH). METHODS: Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation. RESULTS: Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single-leg stance, timed up-and-go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant-evaluated IADL, but not on self-evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up-and-go performance. CONCLUSION: The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment.

Apathy in small vessel cerebrovascular disease is associated with deficits in effort-based decision making.

Patients with small vessel cerebrovascular disease frequently suffer from apathy, a debilitating neuropsychiatric syndrome, the underlying mechanisms of which remain to be established. Here we investigated the hypothesis that apathy is associated with disrupted decision making in effort-based decision making, and that these alterations are associated with abnormalities in the white matter network connecting brain regions that underpin such decisions. Eighty-two patients with MRI evidence of small vessel disease were assessed using a behavioural paradigm as well as diffusion weighted MRI. The decision-making task involved accepting or rejecting monetary rewards in return for performing different levels of physical effort (hand grip force). Choice data and reaction times were integrated into a drift diffusion model that framed decisions to accept or reject offers as stochastic processes approaching a decision boundary with a particular drift rate. Tract-based spatial statistics were used to assess the relationship between white matter tract integrity and apathy, while accounting for depression. Overall, patients with apathy accepted significantly fewer offers on this decision-making task. Notably, while apathetic patients were less responsive to low rewards, they were also significantly averse to investing in high effort. Significant reductions in white matter integrity were observed to be specifically related to apathy, but not to depression. These included pathways connecting brain regions previously implicated in effort-based decision making in healthy people. The drift rate to decision parameter was significantly associated with both apathy and altered white matter tracts, suggesting that both brain and behavioural changes in apathy are associated with this single parameter. On the other hand, depression was associated with an increase in the decision boundary, consistent with an increase in the amount of evidence required prior to making a decision. These findings demonstrate altered effort-based decision making for reward in apathy, and also highlight dissociable mechanisms underlying apathy and depression in small vessel disease. They provide clear potential brain and behavioural targets for future therapeutic interventions, as well as modelling parameters that can be used to measure the effects of treatment at the behavioural level.

Exploring the Contribution of Myelin Content in Normal Appearing White Matter to Cognitive Outcomes in Cerebral Small Vessel Disease.

BACKGROUND: Myelin damage is a salient feature in cerebral small vessel disease (cSVD). Of note, myelin damage extends into the normal appearing white matter (NAWM). Currently, the specific role of myelin content in cognition is poorly understood. OBJECTIVE: The objective of this exploratory study was to investigate the association between NAWM myelin and cognitive function in older adults with cSVD. METHODS: This exploratory study included 55 participants with cSVD. NAWM myelin was measured using myelin water imaging and was quantified as myelin water fraction (MWF). Assessment of cognitive function included processing speed (Trail Making Test Part A), set shifting (Trail Making Test Part B minus A), working memory (Verbal Digit Span Backwards Test), and inhibition (Stroop Test). Multiple linear regression analyses assessed the contribution of NAWM MWF on cognitive outcomes controlling for age, education, and total white matter hyperintensity volume. The overall alpha was set at ≤0.05. RESULTS: After accounting for age, education, and total white matter hyperintensity volume, lower NAWM MWF was significantly associated with slower processing speed (ß â€Š= -0.29, p = 0.037) and poorer working memory (ß= 0.30, p = 0.048). NAWM MWF was not significantly associated with set shifting or inhibitory control (p > 0.132). CONCLUSION: Myelin loss in NAWM may play a role in the evolution of impaired processing speed and working memory in people with cSVD. Future studies, with a longitudinal design and larger sample sizes, are needed to fully elucidate the role of myelin as a potential biomarker for cognitive function.

Modified cerebral small vessel disease score is associated with vascular cognitive impairment after lacunar stroke.

We conducted a cross-sectional study to characterize the relationship between total and modified small vessel disease (SVD) score with vascular cognitive impairment (VCI). Patients (n = 157) between the ages of 50 and 85 years old who had suffered their first lacunar infarction were analyzed prospectively. Brain magnetic resonance imaging was performed to identify SVD manifestations, which were used to calculate total or modified SVD scores. Neuropsychological assessments measured cognitive function. Spearman correlation analysis demonstrated that the total and modified SVD scores were associated with overall cognition as well as with function in the executive and visuospatial domains. The associations remained significant in linear regression after adjusting for age, sex, education and vascular risk factors. Binary logistic regression and chi-squared trend tests revealed that VCI risk increased significantly with SVD burden based on the modified SVD score. Subsequent chi-squared testing demonstrated that the VCI rate was significantly higher in patients with a modified SVD score of 5-6 than in patients without any SVD burden. Our results suggest that both the total and modified SVD scores show a negative association with cognitive function, but the modified SVD score may be better at identifying patients at high VCI risk.

The Association between Cerebral Small Vessel Disease and the Gut Microbiome: A Cross-Sectional Analysis.

BACKGROUND: Recent studies have demonstrated an association between the gut microbiome and cognitive function. However, the associations between the gut microbiome and brain parenchyma damage, and their underlying mechanisms, remain unclear. MATERIALS AND METHODS: We performed a cross-sectional sub-analysis using data from our prospective cohort study to determine the association between the gut microbiome and cerebral small vessel disease (SVD). We assessed patient demographics, risk factors, cognitive function, brain imaging, voxel-based specific regional analysis system for Alzheimer's Disease (VSRAD, indicating brain atrophy), and the gut microbiome as indicated by enterotypes and faecal microbiome metabolites. We then analysed the associations between total SVD scores, cognitive function, and the gut microbiome. RESULTS: We analysed data from 87 patients without dementia or a history of stroke, 64 of whom exhibited mild cognitive impairment. Higher total SVD scores were associated with cognitive decline and behavioural and psychological symptoms. Compared with all other patients, patients with enterotype I (Bacteroides >30%) were more likely to have cognitive decline (median scores: Mini-Mental State Examination, 25 vs. 27, P = 0.047; Clinical Dementia Rating-Sum of Boxes, 1.5 vs. 0.5, P = 0.002) and present with cerebral SVD and high VSRAD scores (1.01 vs. 0.57, P = 0.012). Furthermore, faecal metabolites were significantly higher in patients with higher total SVD scores compared with those with lower scores. Multivariable logistic regression analyses indicated that certain gut microbiomes may double the risk of white matter hyperintensity. CONCLUSIONS: The gut microbiome is associated with cerebral SVD.

Association of Cerebral Small Vessel Disease and Cognitive Decline After Intracerebral Hemorrhage.

OBJECTIVE: To determine whether MRI-based cerebral small vessel disease (CSVD) burden assessment, in addition to clinical and CT data, improved prediction of cognitive impairment after spontaneous intracerebral hemorrhage (ICH). METHODS: We analyzed data from ICH survivors enrolled in a single-center prospective study. We employed 3 validated CSVD burden scores: global, cerebral amyloid angiopathy (CAA)-specific, and hypertensive arteriopathy (HTNA)-specific. We quantified cognitive performance by administering the modified Telephone Interview for Cognitive Status test. We utilized linear mixed models to model cognitive decline rates, and survival models for new-onset dementia. We calculated CSVD scores' cutoffs to maximize predictive performance for dementia diagnosis. RESULTS: We enrolled 612 ICH survivors, and followed them for a median of 46.3 months (interquartile range 35.5-58.7). A total of 214/612 (35%) participants developed dementia. Higher global CSVD scores at baseline were associated with faster cognitive decline (coefficient -0.25, standard error [SE] 0.02) and dementia risk (sub-hazard ratio 1.35, 95% confidence interval 1.10-1.65). The global score outperformed the CAA and HTNA scores in predicting post-ICH dementia (all p < 0.05). Compared to a model including readily available clinical and CT data, inclusion of the global CSVD score resulted in improved prediction of post-ICH dementia (area under the curve [AUC] 0.89, SE 0.02 vs AUC 0.81, SE 0.03, p = 0.008 for comparison). Global CSVD scores ≥2 had highest sensitivity (83%) and specificity (91%) for dementia diagnosis. CONCLUSIONS: A validated MRI-based CSVD score is associated with cognitive performance after ICH and improved diagnostic accuracy for predicting new onset of dementia.

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects). METHODS: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD. RESULTS: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aß) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD. DISCUSSION: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.

Associations Between the Dietary Inflammatory Index, Brain Volume, Small Vessel Disease, and Global Cognitive Function.

BACKGROUND: An inflammatory diet is related to poorer cognition, but the underlying brain pathways are unknown. OBJECTIVE: The aim of this study was to examine associations between the Energy-Adjusted Dietary Inflammatory Index (E-DII) and brain volume, small vessel disease, and cognition in people with and without type 2 diabetes mellitus (T2DM). DESIGN: This is a secondary cross-sectional analysis of data from the Cognition and Diabetes in Older Tasmanians study. PARTICIPANTS/SETTINGS: This study included 641 participants (n = 326 with T2DM) enrolled between 2005 and 2011 from Tasmania, Australia. MAIN OUTCOME MEASURES: The E-DII was computed from the 80-item Dietary Questionnaire for Epidemiological Studies, version 2. Brain volumes (gray matter, white matter, and white matter hyperintensities), infarcts, and microbleeds were obtained from magnetic resonance imaging. Global cognition was derived from a comprehensive battery of neuropsychological tests. STATISTICAL ANALYSIS: Logistic and linear regressions were performed to examine associations between E-DII and brain measures and a global cognitive score, adjusting for demographics, energy, T2DM, mood, ambulatory activity, and cardiovascular risk factors. An E-DII × T2DM interaction term was tested in each model. RESULTS: The mean (standard deviation) age of participants was 69.8 (7.4) years. There were no associations between the E-DII and any of the brain structural measures or global cognitive function in fully adjusted models. There was a modification effect for T2DM on the association between E-DII and gray matter volume (T2DM: ß = 1.38, 95% CI -3.03 to 5.79; without T2DM: ß = -4.34, 95% CI, -8.52 to -0.16), but not with any of the other outcome measures. CONCLUSIONS: In this cross-sectional study, E-DII was not associated with brain structure or global cognition. In 1 of the 7 outcomes, a significant modification effect for T2DM was found for the associations between E-DII and gray matter. Future prospective studies are needed to clarify the associations between diet-related inflammation and brain health.

Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease.

OBJECTIVE: To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change, and reproducibility of diffusion metrics. METHODS: We included 50 patients with sporadic and 59 patients with genetically defined SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 patients with sporadic SVD with longitudinal high-frequency imaging (in total 459 MRIs). Intersite reproducibility was determined in 10 patients with CADASIL scanned back-to-back on 2 different 3T MRI scanners. RESULTS: Metrics from DKI showed the strongest associations with processing speed performance (R 2 up to 21%) and the largest added benefit on top of conventional SVD imaging markers in patients with sporadic SVD and patients with CADASIL with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible. CONCLUSION: Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available intersite dataset facilitates future studies. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.

Cerebral Small Vessel Disease MRI Features Do Not Improve the Prediction of Stroke Outcome.

OBJECTIVE: To determine whether the total small vessel disease (SVD) score adds information to the prediction of stroke outcome compared to validated predictors, we tested different predictive models of outcome in patients with stroke. METHODS: White matter hyperintensity, lacunes, perivascular spaces, microbleeds, and atrophy were quantified in 2 prospective datasets of 428 and 197 patients with first-ever stroke, using MRI collected 24 to 72 hours after stroke onset. Functional, cognitive, and psychological status were assessed at the 3- to 6-month follow-up. The predictive accuracy (in terms of calibration and discrimination) of age, baseline NIH Stroke Scale score (NIHSS), and infarct volume was quantified (model 1) on dataset 1, the total SVD score was added (model 2), and the improvement in predictive accuracy was evaluated. These 2 models were also developed in dataset 2 for replication. Finally, in model 3, the MRI features of cerebral SVD were included rather than the total SVD score. RESULTS: Model 1 showed excellent performance for discriminating poor vs good functional outcomes (area under the curve [AUC] 0.915), and fair performance for identifying cognitively impaired and depressed patients (AUCs 0.750 and 0.688, respectively). A higher SVD score was associated with a poorer outcome (odds ratio 1.30 [1.07-1.58], p = 0.0090 at best for functional outcome). However, adding the total SVD score (model 2) or individual MRI features (model 3) did not improve the prediction over model 1. Results for dataset 2 were similar. CONCLUSIONS: Cerebral SVD was independently associated with functional, cognitive, and psychological outcomes, but had no clinically relevant added value to predict the individual outcomes of patients when compared to the usual predictors, such as age and baseline NIHSS.

Mechanisms of Cerebral Microvascular Disease in Chronic Kidney Disease.

Numerous studies report linkage between chronic kidney disease (CKD) and cerebrovascular disease. This association has been particularly strong for cerebral small vessel disease. Significant findings have emerged from studies ranging from case reports, small case series, and larger cohort investigations. The latter show a relationship between declining renal function, microvascular disease, and cognitive impairment. One troubling aspect has been the relative paucity of mechanistic investigations addressing the CKD-cerebrovascular disease linkage. Nevertheless, mechanistic observations have begun to emerge, showing cerebral microhemorrhage development in animal models of CKD independent of hypertension, an important co-morbidity in clinical studies. Initial cell culture studies show endothelial monolayer disruption by CKD serum, consistent with blood-brain barrier injury. It is noteworthy that CKD serum is known to contain multiple plausible mediators of microvascular injury. Further studies are on the horizon to address the critical question of potential linkage of renal dysfunction with vascular cognitive impairment.

White Matter Injury Is Associated with Reduced Manual Dexterity and Elevated Serum Ceramides in Subjects with Cerebral Small Vessel Disease.

INTRODUCTION: We have demonstrated that asymptomatic cerebral small vessel disease (cSVD) measured by white matter hyperintensity volume is associated with reduced manipulative manual dexterity on the Grooved Peg Board Test (GPBT) in middle-aged healthy individuals with a family history of early coronary artery disease. In this current study, we aim to identify the association of subcortical white matter microstructural impairment measured by diffusion tensor imaging, manual dexterity measured by GPBT and circulating serums ceramide, another marker for white matter injury. We hypothesize that lower regional fractional anisotropy (rFA) is associated with worse performance on GPBT and elevated serum ceramides in the same study population. METHODS: rFA of 48 regions representing the subcortical white matters were analyzed in GeneSTAR participants in addition to serum ceramides and GPBT scores. Unadjusted univariable analyses with Bonferroni correction for multiple comparisons were completed using Spearman correlation for testing the associations between ceramides, rFA of subcortical white matter, and GPBT performance. Subsequently, sensitivity analyses were performed after excluding the participants that had any physical limitation that may influence their performance on GPBT. Finally, in the adjusted analysis using generalized estimating equation, linear regression models were performed for the areas that met significance threshold in the unadjusted analyses. RESULTS: 112 subjects (age [49 ± 11], 51% female, 39.3% African American) were included. Adjusted analyses for the significant correlations that met the Bonferroni correction threshold in the unadjusted univariable analyses identified significant negative associations between rFA of the right fornix (RF) and log-GPBT score (ß = -0.497, p = 0.037). In addition, rFA of RF negatively correlated with log serum ceramide levels (C18: ß = -0.03, p = 0.003, C20: ß = -0.0002, p = 0.004) and rFA of left genu of corpus callosum negatively correlated with log C18 level (ß = -0.0103, p = 0.027). CONCLUSIONS: These results demonstrate that subcortical microstructural white matter disruption is associated with elevated serum ceramides and reduced manual dexterity in a population with cSVD. These findings suggest that injury to white matter tracts undermines neural networks, with functional consequences in a middle-aged population with cardiovascular risk factors.