White Matter Hyperintensities Research Articles

Association of novel lipid indices with the white matter hyperintensities in cerebral small vessel disease: a cross-sectional study

BackgroundLipids are associated with atherosclerosis, and novel lipid indices have been recently identified to be closely linked to cardiovascular diseases. This study explored the association between four novel lipid indices and the white matter hyperintensities (WMHs) in patients diagnosed with cerebral small vessel disease (CSVD).MethodsBetween January 2023 and February 2024, 219 patients were recruited, including 165 patients with CSVD WMHs and 54 healthy controls. Based on WMHs severity, patients with CSVD were categorised into mild and moderate-to-severe cohorts using the Fazekas rating scale. The plasma levels of four novel lipid indices (low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio [LDL-C/HDL-C], triglyceride/high-density lipoprotein cholesterol ratio [TG/HDL-C], total cholesterol/high-density lipoprotein cholesterol ratio [TC/HDL-C], and non-high-density lipoprotein cholesterol [Non-HDL-C]), were rigorously monitored in the enrolled patients.ResultsA total of 165 patients with CSVD WMHs were enrolled, including 94 with mild WMHs and 71 with moderate-to-severe WMHs. Multivariable logistic regression analysis revealed that LDL-C/HDL-C, TG/HDL-C, TC/HDL-C, and Non-HDL-C levels were significantly associated with WMHs (all P ≤ 0.001). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of plasma lipid levels for WMHs in patients with CSVD. The novel lipid indicators outperformed traditional lipid indicators in assessing the diagnostic capability of WMHs. The combined index of the four blood lipid indices had an optimal cutoff point (OCP) of 0.489, with 88.3% sensitivity and 60.6% specificity. The area under the curve (AUC) is 0.800 (95% confidence interval [CI], 0.731–0.869; P < 0.001). Compared with males (OR = 1.126, 95% CI = 0.779–1.628), females (OR = 2.484, 95% CI = 1.398–4.414; P for interaction = 0.023) had a higher risk of developing WMHs.ConclusionThis study demonstrates a significant association between four novel lipid indices and the cerebral WMHs in CSVD, highlighting the potential of these markers as novel plasma biomarkers and predictive indicators for assessing CSVD progression and guiding clinical management.

Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment.

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.

APOE ε4 carrier status moderates the effect of lifestyle factors on cognitive reserve.

This study examines the role of lifestyle factors in cognitive reserve among older adults, focusing on the moderating effect of apolipoprotein E (APOE) ε4 status. Data from 157 participants aged 45 and older from the Healthy Brain Initiative (HBI) were analyzed. Cognitive reserve was estimated using residual scores from Cognivue Clarity tests after accounting for brain atrophy and white matter hyperintensities (WMHs). Lifestyle factors included education, occupational attainment, physical activity, social engagement, diet, and mindfulness. Structural equation models were conducted to assess interactions. Significant interactions were found between APOE ε4 status and mindfulness and social engagement on cognitive reserve, indicating stronger associations for APOE ε4 carriers. APOE ε4 carriers may benefit more from certain lifestyle factors, potentially through stress reduction and anti-inflammatory pathways. These findings support integrating APOE ε4 genetic screening into personalized prevention strategies to enhance interventions aimed at preserving cognitive function and delaying dementia onset in at-risk populations. Mindfulness and social engagement have increased cognitive reserve in APOE ε4 carriers. Study uses residual scores from Cognivue Clarity tests to estimate cognitive reserve. APOE ε4 carriers show stronger associations with certain lifestyle factors on cognitive reserve. Personalized interventions could enhance cognitive resilience in genetically at-risk populations. Comprehensive assessment of multiple lifestyle factors highlights targeted intervention benefits.

Characteristics and temporal evolution of asymptomatic diffusion-weighted imaging lesions in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).

The role of asymptomatic diffusion-weighted imaging-positive (aDWI+) lesions in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) patients remains unclear, and their radiographic features may differ from those of symptomatic diffusion-weighted imaging-positive (sDWI+) lesions. We aimed to investigate the clinicoradiographic characteristics of aDWI+ lesions in CADASIL patients. We conducted a retrospective analysis using data from the Taiwan CADASIL Registry. aDWI+ lesions were defined as incidentally detected DWI+ lesions without corresponding acute neurological deficits. We compared the baseline clinical characteristics of patients with and without aDWI+ lesions and analyzed their radiological features and evolution in relation to sDWI+ lesions. Among 154 enrolled patients (mean age 62 ± 10 years), 17 (11%) had aDWI+ lesions. Baseline clinical characteristics were similar in the two groups, but those with aDWI+ lesions had more lacunes (median 8 vs. 2), multiple cerebral microbleeds (CMBs; 85% vs. 40%), and anterior temporal white matter hyperintensity (WMH; 47% vs. 14%). Multivariable analysis showed that aDWI+ lesions were associated with anterior temporal WMH (odds ratio 5.7, 95% confidence interval 1.5-21.0) after adjusting for multiple lacunes, multiple CMBs, and total WMH score. Compared to sDWI+ lesions, aDWI+ lesions were more often small infarcts (<1 cm; 89% vs. 23%) and less likely to involve the corticospinal tract (11% vs. 96%). Among the 11 aDWI+ lesions with follow-up magnetic resonance imaging, seven became microinfarcts, three became lacunes, and one disappeared. aDWI+ lesions in CADASIL are not uncommon and are associated with higher burdens of small vessel disease and anterior temporal WMH. Further research is needed to assess their long-term impact on CADASIL.

Uncovering mediational pathways behind racial and socioeconomic disparities in brain volumes: insights from the UK Biobank study.

Mediation pathways explaining racial/ethnic and socioeconomic (SES) disparities in structural MRI markers of brain health remain underexplored. We examined racial/ethnic and SES disparities in sMRI markers and tested total, direct, and indirect effects through lifestyle, health-related, and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70years at baseline assessment (47% men). Race (non-White vs. White) and lower SES-predicted poorer brain sMRI volumetric outcomes at follow-up, with racial/ethnic disparities in sMRI outcomes involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across outcomes, with the SES-sMRI total effect being partially mediated for all outcomes. Over 20% of the total effect (TE) of race/ethnicity on WMH was explained by the indirect effect (IE), by a combination of different pathways going through SES, lifestyle, health-related, and cognition factors. This is in contrast to < 10% for total brain, gray matter (GM), white matter (WM), and frontal GM left/right. Another significant finding is that around 57% of the total effect for SES and the normalized white matter hyperintensity (WMH) was attributed to an indirect effect. This effect encompasses many pathways that involve lifestyle, health-related, and cognitive aspects. Aside from WMH, the percent of TE of SES mediated through various pathways ranged from ~ 5% for WM to > 15% up to 36% for most of the remaining sMRI outcomes, which are composed mainly of GM phenotypes. Race and SES were important determinants of brain volumetric outcomes, with partial mediation of racial/ethnic disparities through SES, lifestyle, health-related, and cognition factors.

Decoding Brain Development and Aging

Abstract The aging process induces a variety of changes in the brain detectable by magnetic resonance imaging (MRI). These changes include alterations in brain volume, fluid-attenuated inversion recovery (FLAIR) white matter hyperintense lesions, and variations in tissue properties such as relaxivity, myelin, iron content, neurite density, and other microstructures. Each MRI technique offers unique insights into the structural and compositional changes occurring in the brain due to normal aging or neurodegenerative diseases. Age-related brain volume changes encompass a decrease in gray matter and an increase in ventricular volume, associated with cognitive decline. White matter hyperintensities, detected by FLAIR, are common and linked to cognitive impairments and increased risk of stroke and dementia. Tissue relaxometry reveals age-related changes in relaxivity, aiding the distinction between normal aging and pathological conditions. Myelin content, measurable by MRI, changes with age and is associated with cognitive and motor function alterations. Iron accumulation, detected by susceptibility-sensitive MRI, increases in certain brain regions with age, potentially contributing to neurodegenerative processes. Diffusion MRI provides detailed insights into microstructural changes such as neurite density and orientation. Neurofluid imaging, using techniques like gadolinium-based contrast agents and diffusion MRI, reveals age-related changes in cerebrospinal and interstitial fluid dynamics, crucial for brain health and waste clearance. This review offers a comprehensive overview of age-related brain changes revealed by various MRI techniques. Understanding these changes helps differentiate between normal aging and pathological conditions, aiding the development of interventions to mitigate age-related cognitive decline and other symptoms. Recent advances in machine learning and artificial intelligence have enabled novel methods for estimating brain age, offering also potential biomarkers for neurological and psychiatric disorders.

Cluster-Based White Matter Signatures and the Risk of Dementia, Stroke, and Mortality in Community-Dwelling Adults.

Markers of white matter (WM) injury on brain MRI are important indicators of brain health. Different patterns of WM atrophy, WM hyperintensities (WMHs), and microstructural integrity could reflect distinct pathologies and disease risks, but large-scale imaging studies investigating WM signatures are lacking. This study aims to identify distinct WM signatures using brain MRI in community-dwelling adults, determine underlying risk factor profiles, and assess risks of dementia, stroke, and mortality associated with each signature. Between 2005 and 2016, we measured WMH volume, WM volume, fractional anisotropy (FA), and mean diffusivity (MD) using automated pipelines on structural and diffusion MRI in community-dwelling adults aged older than 45 years of the Rotterdam study. Continuous surveillance was conducted for dementia, stroke, and mortality. We applied hierarchical clustering to identify separate WM injury clusters and Cox proportional hazard models to determine their risk of dementia, stroke, and mortality. We included 5,279 participants (mean age 65.0 years, 56.0% women) and identified 4 distinct data-driven WM signatures: (1) above-average microstructural integrity and little WM atrophy and WMH; (2) above-average microstructural integrity and little WMH, but substantial WM atrophy; (3) poor microstructural integrity and substantial WMH, but little WM atrophy; and (4) poor microstructural integrity with substantial WMH and WM atrophy. Prevalence of cardiovascular risk factors, lacunes, and cerebral microbleeds was higher in clusters 3 and 4 than in clusters 1 and 2. During a median 10.7 years of follow-up, 291 participants developed dementia, 220 had a stroke, and 910 died. Compared with cluster 1, dementia risk was increased for all clusters, notably cluster 3 (hazard ratio [HR] 3.06, 95% CI 2.12-4.42), followed by cluster 4 (HR 2.31, 95% CI 1.58-3.37) and cluster 2 (HR 1.67, 95% CI 1.17-2.38). Compared with cluster 1, risk of stroke was higher only for clusters 3 (HR 1.55, 95% CI 1.02-2.37) and 4 (HR 1.94, 95% CI 1.30-2.89), whereas mortality risk was increased in all clusters (cluster 2: HR 1.27, 95% CI 1.06-1.53, cluster 3: HR 1.65, 95% CI 1.35-2.03, cluster 4: HR 1.76, 95% CI 1.44-2.15), compared with cluster 1. Models including clusters instead of an individual imaging marker showed a superior goodness of fit for dementia and mortality, but not for stroke. Clustering can derive WM signatures that are differentially associated with dementia, stroke, and mortality risk. Future research should incorporate spatial information of imaging markers.

Plasma proteome-wide analysis of cerebral small vessel disease identifies novel biomarkers and disease pathways.

Cerebral small vessel disease (SVD), as defined by neuroimaging characteristics such as white matter hyperintensities (WMHs), cerebral microhemorrhages (CMHs), and lacunar infarcts, is highly prevalent and has been associated with dementia risk and other clinical sequelae. Although conditions such as hypertension are known to contribute to SVD, little is known about the diverse set of subclinical biological processes and molecular mediators that may also influence the development and progression of SVD. To better understand the mechanisms underlying SVD and to identify novel SVD biomarkers, we used a large-scale proteomic platform to relate 4,877 plasma proteins to MRI-defined SVD characteristics within 1,508 participants of the Atherosclerosis Risk in Communities (ARIC) Study cohort. Our proteome-wide analysis of older adults (mean age: 76) identified 13 WMH-associated plasma proteins involved in synaptic function, endothelial integrity, and angiogenesis, two of which remained associated with late-life WMH volume when measured nearly 20 years earlier, during midlife. We replicated the relationship between 9 candidate proteins and WMH volume in one or more external cohorts; we found that 11 of the 13 proteins were associated with risk for future dementia; and we leveraged publicly available proteomic data from brain tissue to demonstrate that a subset of WMH-associated proteins was differentially expressed in the context of cerebral atherosclerosis, pathologically-defined Alzheimer's disease, and cognitive decline. Bidirectional two-sample Mendelian randomization analyses examined the causal relationships between candidate proteins and WMH volume, while pathway and network analyses identified discrete biological processes (lipid/cholesterol metabolism, NF-kB signaling, hemostasis) associated with distinct forms of SVD. Finally, we synthesized these findings to identify two plasma proteins, oligodendrocyte myelin glycoprotein (OMG) and neuronal pentraxin receptor (NPTXR), as top candidate biomarkers for elevated WMH volume and its clinical manifestations.

Association of Vascular Risk Factors and Cerebrovascular Pathology With Alzheimer Disease Pathologic Changes in Individuals Without Dementia.

Vascular risk factors (VRFs) and cerebral small vessel disease (cSVD) are common in patients with Alzheimer disease (AD). It remains unclear whether this coexistence reflects shared risk factors or a mechanistic relationship and whether vascular and amyloid pathologies have independent or synergistic influence on subsequent AD pathophysiology in preclinical stages. We investigated links between VRFs, cSVD, and amyloid levels (Aβ1-42) and their combined effect on downstream AD biomarkers, that is, CSF hyperphosphorylated tau (P-tau181), atrophy, and cognition. This retrospective study included nondemented participants (Clinical Dementia Rating < 1) from the European Prevention of Alzheimer's Dementia (EPAD) cohort and assessed VRFs with the Framingham risk score (FRS) and cSVD features on MRI using visual scales and white matter hyperintensity volumes. After preliminary linear analysis, we used structural equation modeling (SEM) to create a "cSVD severity" latent variable and assess the direct and indirect effects of FRS and cSVD severity on Aβ1-42, P-tau181, gray matter volume (baseline and longitudinal), and cognitive performance (baseline and longitudinal). A total cohort of 1,592 participants were evaluated (mean age = 65.5 ± 7.4 years; 56.16% F). We observed positive associations between FRS and all cSVD features (all p < 0.05) and a negative association between FRS and Aβ1-42 (β = -0.04 ± 0.01). All cSVD features were negatively associated with CSF Aβ1-42 (all p < 0.05). Using SEM, the cSVD severity fully mediated the association between FRS and CSF Aβ1-42 (indirect effect: β = -0.03 ± 0.01), also when omitting vascular amyloid-related markers. We observed a significant indirect effect of cSVD severity on P-tau181 (indirect effect: β = 0.12 ± 0.03), baseline and longitudinal gray matter volume (indirect effect: β = -0.10 ± 0.03; β = -0.12 ± 0.05), and baseline cognitive performance (indirect effect: β = -0.16 ± 0.03) through CSF Aβ1-42. In a large nondemented population, our findings suggest that cSVD is a mediator of the relationship between VRFs and CSF Aβ1-42 and affects downstream neurodegeneration and cognitive impairment. We provide evidence of VRFs indirectly affecting the pathogenesis of AD, highlighting the importance of considering cSVD burden in memory clinics for AD risk evaluation and as an early window for intervention. These results stress the role of VRFs and cerebrovascular pathology as key biomarkers for accurate design of anti-amyloid clinical trials and offer new perspectives for patient stratification.

Distinct patterns of white matter hyperintensity and cortical thickness of CSF1R-related leukoencephalopathy compared with subcortical ischemic vascular dementia.

CSF1R-related leukoencephalopathy is a type of autosomal dominant leukodystrophy caused by mutations in the colony stimulating factor 1 receptor (CSF1R) gene. Subcortical ischemic vascular dementia (SIVaD), which is caused by cerebral small vessel disease, is similar to CSF1R-related leukoencephalopathy in that it mainly affects subcortical white matter. In this study, we compared the patterns of white matter hyperintensity (WMH) and cortical thickness in CSF1R-related leukoencephalopathy with those in SIVaD. Fourteen patients with CSF1R-related leukoencephalopathy and 129 with SIVaD were retrospectively recruited from three tertiary medical centers. We extracted and visualized WMH data using voxel-based morphometry to compare the WMH distributions between the two groups. Cortical thickness was measured using a surface-based method. Statistical maps of differences in cortical thickness between the two groups were generated using a surface model, with age, sex, education, and intracranial volume as covariates. Predominant distribution of WMH in the CSF1R-related leukoencephalopathy group was in the bilateral frontal and parietal areas, whereas the SIVaD group showed diffuse WMH involvement in the bilateral frontal, parietal, and temporal areas. Compared with the SIVaD group, the CSF1R-related leukoencephalopathy group showed more severe corpus callosum atrophy (CCA) and widespread cortical thinning. To our knowledge, this is the first study using the automated MR measurement to capture WMH, cortical thinning, and CCA with signal changes in CSF1R-related leukoencephalopathy. It provides new evidence regarding differences in the patterns of WMH distribution and cortical thinning between CSF1R-related leukoencephalopathy and SIVaD.

Quantifying brain health in acute ischemic stroke through effective reserve.

To quantify brain health using a measure of reserve that incorporates pre-existing pathology. We analyzed two retrospective ischemic stroke cohorts (GASROS and SALVO) with neuroimaging and 90-day modified Rankin Scores (mRS) available. White matter hyperintensity (WMHv), brain, and intracranial volumes were automatically extracted, and brain parenchymal fraction (BPF) calculated. The latent variable effective reserve (eR) was modeled using age, WMHv, and BPF or brain volume in GASROS. Models were compared using Bayes Information Criterion (BIC). The best model's eR estimates were categorized into quartiles and evaluated in SALVO. GASROS included 476 (median age: 65.8; 65.3% male) and SALVO included 43 (median age: 69.2; 62.8% male) patients. Inverse associations between eR and mRS was seen in both models, with brain volume outperforming BPF (path coefficients: -0.67, -0.48, respectively; p < 0.001; |ΔBIC| = 362). Quartile-based eR stratification in SALVO showed a similar inverse trend, with worse outcomes in the low reserve group (mRS≤2 - highest vs lowest quartile: 85/90% vs 59/45% for GASROS/SALVO). Expanding the concept of eR, highlights its clinical translational potential. The strong link between higher eR and better outcomes underscores its value as a protective brain health metric.

Stroke-like episodes in patients with adult-onset neuronal intranuclear inclusion disease and patients with late-onset MELAS: A comparative study.

To delineate the characteristics of stroke-like episodes (SLEs) in patients with adult-onset neuronal intranuclear inclusion disease (NIID) and to compare these characteristics with those of patients with MELAS. Twenty-three adult-onset NIID patients who presented with acute or subacute brain disorders and 13 late-onset MELAS patients were enrolled in the study. Patients with NIID were categorized into the SLEs group and the encephalopathy-like episodes (ELEs) group according to the associated stroke-like lesions (SLLs) findings. Clinical characteristics were compared between the SLEs group and the ELEs group among NIID patients and between NIID patients with SLEs and MELAS patients. Eleven (47.8%) NIID patients who manifested acute or subacute brain disorders had detectable associated SLLs and were categorized into SLEs group. SLEs patients were more likely to report fever, headache, and seizures instead of sleep disorders than ELEs patients. Four (36.4%) NIID patients with SLEs absence of diagnostic or suggestive NIID imaging features. The clinical manifestations, laboratory test results, and neuroimaging and muscle biopsy histological features of NIID patients with SLEs majorly overlapped with those of late-onset MELAS patients. Older age at the first SLE (OR [95% CI], 1.203 [1.045-1.384]), symptoms of movement disorders on admission (OR [95% CI], 9.625 [1.378-67.246]), and white matter hyperintensity in corpus callosum (OR [95% CI], 16.00 [1.542-166.46]) associated with the NIID diagnosis in patients with SLEs. NIID patients with SLEs exhibit evident features of mitochondrial disorders. Interventions aimed at mitochondrial dysfunction might be a promising therapeutic approach for treating this disease.

Enhanced image quality and lesion detection in FLAIR MRI of white matter hyperintensity through deep learning-based reconstruction

ObjectiveTo delve deeper into the study of degenerative diseases, it becomes imperative to investigate whether deep-learning reconstruction (DLR) can improve the evaluation of white matter hyperintensity (WMH) on 3.0T scanners, and compare its lesion detection capabilities with conventional reconstruction (CR). MethodsA total of 131 participants (mean age, 46 years ±17; 46 men) were included in the study. The images of these participants were evaluated by readers blinded to clinical data. Two readers independently assessed subjective image indicators on a 4-point scale. The severity of WMH was assessed by four raters using the Fazekas scale. To evaluate the relative detection capabilities of each method, we employed the Wilcoxon signed rank test to compare scores between the DLR and the CR group. Additionally, we assessed interrater reliability using weighted k statistics and intraclass correlation coefficient to test consistency among the raters. ResultsIn terms of subjective image scoring, the DLR group exhibited significantly better scores compared to the CR group (P < 0.001). Regarding the severity of WMH, the DL group demonstrated superior performance in detecting lesions. Majority readers agreed that the DL group provided clearer visualization of the lesions compared to the conventional group. ConclusionDLR exhibits notable advantages over CR, including subjective image quality, lesion detection sensitivity, and inter reader reliability.

Interactive effect of diabetes mellitus and subclinical MRI markers of cerebrovascular disease on cognitive decline and incident dementia: a memory-clinic study

BackgroundCognitive impairment is an increasingly recognized comorbidity of diabetes, yet the mechanisms underlying this association remain poorly understood. This knowledge gap has contributed to conflicting findings regarding the impact of diabetes on long-term cognitive outcomes in older adults. The presence of cerebrovascular disease (CeVD) may potentially modify this relationship. However, interactive effect between diabetes and subclinical MRI markers of CeVD on cognitive trajectories and incident dementia remains unexplored.MethodsA total of 654 participants underwent brain MRI at baseline, from whom 614 with at least one follow-up were selected for longitudinal analysis. Cognitive tests were performed annually up to 5 years. CeVD markers of interest were lacunes, white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), cortical microinfarcts (CMIs), intracranial stenosis (ICS), and cortical infarcts. Blood-based Alzheimer biomarkers, including p-tau181 and p-tau181/Aβ42 ratio, were used as indicators of Alzheimer pathology.ResultsAt baseline, diabetes was associated with lower cognitive performance and higher burden of CeVD, but not p-tau181 or p-tau181/Aβ42 ratio. Longitudinally, we found an interactive effect of diabetes and WMHs, rather than an independent effect of diabetes, on cognitive decline and dementia risk. Subgroup analyses showed association of diabetes with cognitive outcomes was stronger in participants with high WMHs load but non-significant in those with low WMHs load. Moreover, these associations remained unchanged after adjusting for blood-based Alzheimer biomarkers.ConclusionsThe effect of diabetes on cognitive decline is contingent upon the presence of WMHs and independent of Alzheimer’s pathology. This finding raises the possibility of utilizing WMHs as an imaging biomarker to identify diabetic subgroup at greater risk of developing cognitive impairment. Furthermore, therapeutic interventions targeting WMHs may prevent cognitive deterioration in older adults with diabetes.

Systolic blood pressure variability in late-life predicts cognitive trajectory and risk of Alzheimer's disease.

The relationship of systolic blood pressure variability (SBPV) with Alzheimer's disease (AD) remains controversial. We aimed to explore the roles of SBPV in predicting AD incidence and to test the pathways that mediated the relationship of SBPV with cognitive functions. Longitudinal data across 96 months (T0 to T4) were derived from the Alzheimer's disease Neuroimaging Initiative cohort. SBPV for each participant was calculated based on the four measurements of SBP across 24 months (T0 to T3). At T3, logistic regression models were used to test the SBPV difference between 86 new-onset AD and 743 controls. Linear regression models were used to test the associations of SBPV with cognition and AD imaging endophenotypes for 743 non-demented participants (median age = 77.0, female = 42%). Causal mediation analyses were conducted to explore the effects of imaging endophenotypes in mediating the relationships of SBPV with cognitive function. Finally, Cox proportional hazard model was utilized to explore the association of SBPV with incident risk of AD (T3 to T4, mean follow-up = 3.5 years). Participants with new-onset AD at T3 had significantly higher SBPV compared to their controls (p = 0.018). Higher SBPV was associated with lower scores of cognitive function (p = 0.005 for general cognition, p = 0.029 for memory, and p = 0.016 for executive function), higher cerebral burden of amyloid deposition by AV45 PET (p = 0.044), lower brain metabolism by FDG PET (p = 0.052), and higher burden of white matter hyperintensities (WMH) (p = 0.012). Amyloid pathology, brain metabolism, and WMH partially (ranging from 17.44% to 36.10%) mediated the associations of SBPV with cognition. Higher SBPV was significantly associated with elevated risk of developing AD (hazard ratio = 1.29, 95% confidence interval = 1.07 to 1.57, p = 0.008). These findings supported that maintaining stable SBP in late life helped lower the risk of AD, partially by modulating amyloid pathology, cerebral metabolism, and cerebrovascular health.

The clinical and neuropsychological profiles of Alzheimer's disease with white matter hyperintensity in North China.

Patients with Alzheimer's disease (AD) often exhibit characteristic clinical manifestations, particularly neuropsychiatric symptoms. Previous studies have shown that white matter hyperintensity (WMH) is strongly associated with AD progression, as well as neuropsychiatric symptoms. The purpose of this study was to investigate the clinical and neuropsychological characteristics of AD patients with WMH. This retrospective study involved 104 18-fluorodeoxyglucose-positron emission computed tomography (18FDG-PET-CT)-defined AD patients treated at Tianjin Huanhu Hospital from January 2010 to December 2022. Cranial magnetic resonance imaging (MRI) provided semi-quantitative data on brain structure and WMH. Collect and analyze patient clinical data. Neuropsychological assessments were used to evaluate cognitive function and psychobehavioral traits. Among the 104 patients, 66 were in the WMH group (63.5%) and 38 in the non-white matter hyperintensity (non-WMH) group (36.5%). There were no significant differences in gender, age, age of onset, education, BMI, smoking, drinking, diabetes, coronary heart disease, dementia family history, fasting blood glucose, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) between the two groups. The WMH group showed higher rates of hypertension, homocysteine (Hcy) levels, NPI, and CDR scores as compared to the non-WMH group (p < 0.05). MMSE and MoCA scores were significantly lower in the WMH group (p < 0.05). In the MMSE subitem analysis, patients in the WMH group showed a decrease in attention, recall, and language scores. In the MOCA subitem analysis, WMH patients had lower scores in executive function, naming, attention, language, abstraction, and orientation (p < 0.05). Furthermore, subgroup analysis of NPI showed a higher incidence of delusions, depression, and apathy in the WMH group (p < 0.05). According to the hierarchical analysis of mild, moderate and severe dementia groups, the hypertension, leukoencephalopathy, Hcy level, Fazekas total score, PWMH and DWMH scores in the severe dementia group were significantly higher than those in the mild and moderate dementia groups (p < 0.05). As the disease progresses, more and more patients show increased white matter hyperintensity. White matter lesions are closely correlated with cognitive decline and psychobehavioral symptoms in AD patients, and may be used as an indicator of disease progression. Priority should be given to early screening and prevention of WMH-related risk factors.

Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1-Year Risk for Ischemic Stroke Recurrence.

This study evaluates the role of quantitative characteristics of white matter hyperintensities (WMHs) in predicting the 1-year recurrence risk of ischemic stroke. We conducted a retrospective analysis of 1061 patients with ischemic stroke from January 2018 to April 2021. WMHs were automatically segmented using a cluster-based method to quantify their volume and number of clusters (NoC). Additionally, two radiologists independently rated periventricular and deep WMHs using the Fazekas scale. The cohort was divided into a training set (70%) and a testing set (30%). We employed Cox proportional hazards models to develop predictors based on quantitative WMH characteristics, Fazekas scores, and clinical factors, and compared their performance using the concordance index (C-index). A total of 180 quantitative variables related to WMHs were extracted. A higher NoC in deep white matter and brainstem, advanced age (>90years old), specific stroke subtypes, and absence of discharge antiplatelets showed stronger associations with the risk of ischemic stroke recurrence within 1year. The nomogram incorporating quantitative WMHs data showed superior discrimination compared to those based on the Fazekas scale or clinical factors alone, with C-index values of 0.709 versus 0.647 and 0.648, respectively, in the testing set. Notably, a combined model including both WMHs and clinical factors achieved the highest predictive accuracy, with a C-index of 0.735 in the testing set. Quantitative assessment of WMHs provides a valuable neuro-imaging tool for enhancing the prediction of ischemic stroke recurrence risk.

Quantification of white matter hyperintensities in type 1 diabetes and its relation to neuropathy and clinical characteristics

AimsThe aims were to quantify periventricular and deep white matter hyperintensities (WMHs) in adults with type 1 diabetes with different neuropathic phenotypes and to correlate WMH measurements to explanatory factors in diabetes. MethodsWMH measurements were obtained from brain magnetic resonance imaging of 56 adults with type 1 diabetes in subgroups including painful diabetic peripheral neuropathy (DPN), painless DPN, without DPN and 20 healthy controls using Fazekas scale and automatic segmentation analysis. ResultsNo differences in Fazekas assessed WMHs were found (individuals with periventricular lesions: diabetes 66 % vs. controls 40 %,p = 0.063, deep lesions: diabetes 52 % vs. controls 50 %,p = 1.0). Using automatic detection, there were no significant differences in count of periventricular (p = 0.30) or deep (p = 0.31) WMHs. Higher periventricular lesion burden was present in diabetes compared with controls (0.21 % vs. 0.06 %,p = 0.048), which was associated with more severe DPN, increased age, decreased cognitive function, and reduced volumetric and metabolic brain measures (all p < 0.05). ConclusionsOur findings indicate increased burden of periventricular WMHs in diabetes which were associated to DPN severity and measures reflecting neurodegeneration. Deep WMHs, often considered as chronic ischemic, were not significantly different. Mechanisms reflecting neurodegeneration and accelerated brain aging could be an overlooked aspect of peripheral and central neuropathy.

White matter hyperintensity on MRI and plasma Aβ42/40 ratio additively increase the risk of cognitive impairment in hypertensive adults.

Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study. We analyzed the Systolic Blood Pressure Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aβ)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aβ risk, (3) WMH risk, and (4) combined high risk. In the cohort of 467 participants (mean age 69.7±7.1, 41.8% female, 31.9% nonwhite or Hispanic) during 4.8 years of follow-up and across the four exposure categories the rates of cognitive impairment were 5.3%, 7.8%, 11.8%, and 22.6%. Compared to the combined low-risk category, the adjusted hazard ratio for cognitive impairment was 4.12 (95% confidence interval, 1.71 to 9.94) in the combined high-risk category. This study emphasizes the potential impact of therapeutic approaches to dementia prevention that target both vascular and amyloid pathology. White matter hyperintensity (WMH) and plasma amyloid (Aβ42/40) are additive risk factors for the development of cognitive impairment in the SPRINT MIND trial. Individuals in the high-risk categories of both WMH and Aβ42/40 had a near fivefold increase in risk of cognitive impairment during 4.8 years of follow-up on average. These findings suggest that treatment strategies targeting both vascular health and amyloid burden warrant further research.

Utility of cerebrovascular imaging biomarkers to detect cerebral amyloidosis.

The relationship between cerebrovascular disease (CVD) and amyloid beta (Aβ) in Alzheimer's disease (AD) is understudied. We hypothesized that magnetic resonance imaging (MRI)-based CVD biomarkers-including cerebral microbleeds (CMBs), lacunar infarction, and white matter hyperintensities (WMHs)-would correlate with Aβ positivity on positron emission tomography (Aβ-PET). We cross-sectionally analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, N=1352). Logistic regression was used to calculate odds ratios (ORs), with Aβ-PET positivity as the standard-of-truth. Following adjustment, WMHs (OR=1.25) and superficial CMBs (OR=1.45) remained positively associated with Aβ-PET positivity (p<0.001). Deep CMBs and lacunes exhibited a varied relationship with Aβ-PET in cognitive subgroups. The combined diagnostic model, which included CVD biomarkers and other accessible measures, significantly predicted Aβ-PET (pseudo-R2=0.41). The study highlights the translational value of CVD biomarkers in diagnosing AD, and underscores the need for more research on their inclusion in diagnostic criteria. gov: ADNI-2 (NCT01231971), ADNI-3 (NCT02854033). Cerebrovascular biomarkers linked to amyloid beta (Aβ) in Alzheimer's disease (AD). White matter hyperintensities and cerebral microbleeds reliably predict Aβ-PET positivity. Relationships with Aβ-PET vary by cognitive stage. Novel accessible model predicts Aβ-PET status. Study supports multimodal diagnostic approaches.