Familial cerebral amyloid disorders with prominent white matter involvement.

Familial cerebral amyloid disorders are characterized by the accumulation of fibrillar protein aggregates, which deposit in the parenchyma as plaques and in the vasculature as cerebral amyloid angiopathy (CAA). Amyloid ß (Aß) is the most common of these amyloid proteins, accumulating in familial and sporadic forms of Alzheimer's disease and CAA. However, there are also a number of rare, hereditary, non-Aß cerebral amyloidosis. The clinical manifestations of these familial cerebral amyloid disorders are diverse, including cognitive or neuropsychiatric presentations, intracerebral hemorrhage, seizures, myoclonus, headache, ataxia, and spasticity. Some mutations are associated with extensive white matter hyperintensities on imaging, which may or may not be accompanied by hemorrhagic imaging markers of CAA; others are associated with occipital calcification. We describe the clinical, imaging, and pathologic features of these disorders and discuss putative disease mechanisms. Familial disorders of cerebral amyloid accumulation offer unique insights into the contributions of vascular and parenchymal amyloid to pathogenesis and the pathways underlying white matter involvement in neurodegeneration. With Aß immunotherapies now entering the clinical realm, gaining a deeper understanding of these processes and the relationships between genotype and phenotype has never been more relevant.

Predictors of white matter hyperintensities in the elderly Congolese population.

Background: White matter hyperintensities (WMHs) are strongly linked to cardiovascular risk factors and other health conditions such as Alzheimer's disease. However, there is a dearth of research on this topic in low-income countries and underserved populations, especially in the Democratic Republic of Congo (DRC) where the population is aging rapidly with increasing cardiovascular risk factors and dementia-related diseases. This study evaluates health factors associated with WMH in the elderly Sub-Saharan Africa (SSA), specifically Congolese adults. Methods: In a cross-sectional study of 77 people from the DRC, participants underwent neuroimaging to analyze WMH volume and completed clinical evaluation, laboratory-based blood exams, self-reported questionnaires, and interviews. A simple linear regression model was conducted to test the association between WMH and potential predictors (neurological status, age, sex, hypertension, diabetes, tobacco abuse, stroke, high cholesterol, cardiovascular medication, and alcohol abuse). Stepwise selection and backward elimination analyses were performed to obtain the final model. Finally, a multiple linear regression model was conducted to assess the association between WMH and variables retained in the final model (neurological status, sex, and age). Results: Of the 77 individuals, 47 (61%) had dementia, 40 (52.6%) were males, and the mean age was 73 years (± 8.0 years standard deviation). In simple linear regression models, WMH was significantly associated with dementia (expß1=1.75, 95% CI=1.14 - 2.71, p-value=0.01) though it had a weak association with age (expß1=1.03, 95% CI=1.00 - 1.05, p-value=0.05) and sex (male) (expß1=0.66, 95% CI=0.43 - 1.01, p-value=0.05). In multiple linear regression models, WMH was statistically significantly associated with dementia (expß1=1.97, 95% CI=1.31 - 2.95, p-value =0.001), male sex (expß2=0.54, 95% CI=0.36 - 0.80, p-value=0.003), and age (expß3=1.03, 95% CI=1.00 - 1.06, p-value=0.03). However, WMH was not significantly associated with common cardiovascular risk factors, such as high blood pressure, diabetes, tobacco use, obesity, and high cholesterol levels. Conclusion: WMH is significantly associated with neurological status, sex, and age in the Congolese population. Understanding these predictors may improve our ability to diagnose, assess, and develop preventative treatments for white matter disease in SSA/DRC populations, where neuroimaging is difficult to obtain.

Predicting white-matter hyperintensity progression and cognitive decline in patients with cerebral small-vessel disease: a magnetic resonance-based habitat analysis.

Background: White-matter hyperintensity (WMH) is the key magnetic resonance imaging (MRI) marker of cerebral small-vessel disease (CSVD). This study aimed to investigate whether habitat analysis based on physiologic MRI parameters can predict the progression of WMH and cognitive decline in CSVD. Methods: Diffusion- and perfusion-weighted imaging data were obtained from 69 patients with CSVD at baseline and at 1-year of follow-up. The white-matter region was classified into constant WMH, growing WMH, shrinking WMH, and normal-appearing white matter (NAWM) according to the T2-fluid-attenuated inversion recovery (FLAIR) sequences images at the baseline and follow-up. We employed k-means clustering on a voxel-wise basis to delineate WMH habitats, integrating multiple diffusion metrics and cerebral blood flow (CBF) values derived from perfusion data. The WMH at the baseline and the predicted WMH from the habitat analysis were used as regions of avoidance (ROAs). The decreased rate of global efficiency for the whole brain structural connectivity was calculated after removal of the ROA. The association between the decreased rate of global efficiency and Montreal Cognitive Assessment (MoCA) and mini-mental state examination (MMSE) scores was evaluated using Pearson correlation coefficients. Results: We found that the physiologic MRI habitats with lower fractional anisotropy and CBF values and higher mean diffusivity, axial diffusivity, and radial diffusivity values overlapped considerably with the new WMH (growing WMH of baseline) after a 1-year follow-up; the accuracy of distinguishing growing WMH from NAWM was 88.9%±12.7% at baseline. Similar results were also found for the prediction of shrinking WMH. Moreover, after the removal of the predicted WMH, a decreased rate of global efficiency had a significantly negative correlation with the MoCA and MMSE scores at follow-up. Conclusions: This study revealed that a habitat analysis combining perfusion with diffusion parameters could predict the progression of WMH and related cognitive decline in patients with CSVD.

Cognitive function in Parkinson's disease: associations with perivascular space in basal ganglia.

BACKGROUND: Cognitive impairment is one of the most common symptoms of Parkinson's disease (PD), and may be detectable through changes in neural features visualized by magnetic resonance imaging (MRI). Mild cognitive impairment is a transitional state between normal aging and dementia, and early recognition of Parkinson's disease with mild cognitive impairment (PD-MCI) can help improve the quality of life and treatment for patients. This study investigated the association of enlarged perivascular space (EPVS) and white matter hyperintensity (WMH) with PD-MCI. AIMS: This study aimed to evaluate whether EPVS and WMH can be used as potential MRI markers for PD-MCI. METHODS: This retrospective study involved 200 patients with PD who underwent cranial MRI in our hospital from April 2021 to April 2022. Patients were divided into those with no cognitive impairment (PD-NCI) or mild cognitive impairment. Uni- and multivariate logistic regression analyzed associations of EPVS, WMH, and clinicodemographic characteristics with cognitive decline. RESULTS: Univariate regression identified severe EPVS in basal ganglia, severe WMH, older age, late-onset, male sex, low educational level, longer duration of disease, low triglycerides, low uric acid, and low scores on the Mini-mental State Exam as risk factors for PD-MCI. After adjusting for clinicodemographic risk factors in multivariate regression, low education level and EPVS in basal ganglia remained risk factors for cognitive impairment. CONCLUSIONS: Severe EPVS in basal ganglia and poor education, but not WMH, are independent risk factors of PD-MCI. Our findings suggest that non-invasive detection of EPVS in basal ganglia by MRI may be a valuable early indicator of cognitive decline in PD patients.

PLEKHG1: New Potential Candidate Gene for Periventricular White Matter Abnormalities.

Hypoxic-ischemic brain damage presents a significant neurological challenge, often manifesting during the perinatal period. Specifically, periventricular leukomalacia (PVL) is emerging as a notable contributor to cerebral palsy and intellectual disabilities. It compromises cerebral microcirculation, resulting in insufficient oxygen or blood flow to the periventricular region of the brain. As widely documented, these pathological conditions can be caused by several factors encompassing preterm birth (4-5% of the total cases), as well single cotwin abortion and genetic variants such as those associated with GTPase pathways. Whole exome sequencing (WES) analysis identified a de novo causative variant within the pleckstrin homology domain-containing family G member 1 (PLEKHG1) gene in a patient presenting with PVL. The PLEKHG1 gene is ubiquitously expressed, showing high expression patterns in brain tissues. PLEKHG1 is part of a family of Rho guanine nucleotide exchange factors, and the protein is essential for cell division control protein 42 (CDC42) activation in the GTPase pathway. CDC42 is a key small GTPase of the Rho-subfamily, regulating various cellular functions such as cell morphology, migration, endocytosis, and cell cycle progression. The molecular mechanism involving PLEKHG1 and CDC42 has an intriguing role in the reorientation of cells in the vascular endothelium, thus suggesting that disruption responses to mechanical stress in endothelial cells may be involved in the formation of white matter lesions. Significantly, CDC42 association with white matter abnormalities is underscored by its MIM phenotype number. In contrast, although PLEKHG1 has been recently associated with patients showing white matter hyperintensities, it currently lacks a MIM phenotype number. Additionally, in silico analyses classified the identified variant as pathogenic. Although the patient was born prematurely and subsequently to dichorionic gestation, during which its cotwin died, we suggest that the variant described can strongly contribute to PVL. The aim of the current study is to establish a plausible association between the PLEKHG1 gene and PVL.

Effects of strategic white matter hyperintensities of cholinergic pathways on basal forebrain volume in patients with amyloid-negative neurocognitive disorders.

BACKGROUND: The cholinergic neurotransmitter system is crucial to cognitive function, with the basal forebrain (BF) being particularly susceptible to Alzheimer's disease (AD) pathology. However, the interaction of white matter hyperintensities (WMH) in cholinergic pathways and BF atrophy without amyloid pathology remains poorly understood. METHODS: We enrolled patients who underwent neuropsychological tests, magnetic resonance imaging, and 18F-florbetaben positron emission tomography due to cognitive impairment at the teaching university hospital from 2015 to 2022. Among these, we selected patients with negative amyloid scans and additionally excluded those with Parkinson's dementia that may be accompanied by BF atrophy. The WMH burden of cholinergic pathways was quantified by the Cholinergic Pathways Hyperintensities Scale (CHIPS) score, and categorized into tertile groups because the CHIPS score did not meet normal distribution. Segmentation of the BF on volumetric T1-weighted MRI was performed using FreeSurfer, then was normalized for total intracranial volume. Multivariable regression analysis was performed to investigate the association between BF volumes and CHIPS scores. RESULTS: A total of 187 patients were enrolled. The median CHIPS score was 12 [IQR 5.0; 24.0]. The BF volume of the highest CHIPS tertile group (mean ± SD, 3.51 ± 0.49, CHIPSt3) was significantly decreased than those of the lower CHIPS tertile groups (3.75 ± 0.53, CHIPSt2; 3.83 ± 0.53, CHIPSt1; P = 0.02). In the univariable regression analysis, factors showing significant associations with the BF volume were the CHIPSt3 group, age, female, education, diabetes mellitus, smoking, previous stroke history, periventricular WMH, and cerebral microbleeds. In multivariable regression analysis, the CHIPSt3 group (standardized beta [ßstd] = -0.25, P = 0.01), female (ßstd = 0.20, P = 0.04), and diabetes mellitus (ßstd = -0.22, P < 0.01) showed a significant association with the BF volume. Sensitivity analyses showed a negative correlation between CHIPS score and normalized BF volume, regardless of WMH severity. CONCLUSIONS: We identified a significant correlation between strategic WMH burden in the cholinergic pathway and BF atrophy independently of amyloid positivity and WMH severity. These results suggest a mechanism of cholinergic neuronal loss through the dying-back phenomenon and provide a rationale that strategic WMH assessment may help identify target groups that may benefit from acetylcholinesterase inhibitor treatment.

Correlation between matrix metalloproteinase-2, matrix metalloproteinase-9, and tissue inhibitor of metalloproteinases-1 and white matter hyperintensities in patients with cerebral small vessel disease based on cranial magnetic resonance 3D imaging.

OBJECTIVE: The objective of this study was to investigate the correlation between serum levels of matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9), and tissue inhibitor of metalloproteinases-1 (TIMP-1) levels and their ratios with the severity of white matter hyperintensities (WMHs) in patients with cerebral small vessel disease (CSVD). METHODS: This cross-sectional study was done on a prospective cohort of patients with CSVD. Qualitative and quantitative analyses of WMHs were performed using Fazekas grading and lesion prediction algorithm (LPA) methods. Biomarkers MMP-2, MMP-9, and TIMP-1 were measured to explore their correlation with the severity of WMHs. RESULTS: The sample consisted of 144 patients with CSVD. There were 63 male and 81 female patients, with an average age of 67.604 ± 8.727 years. Among these, 58.33% presented with white matter hyperintensities at Fazekas grading level 1, with an average total template volume of WMHs of 4.305 mL. MMP-2 (P = 0.025), MMP-9 (P = 0.008), TIMP-1 (P = 0.026), and age (P = 0.007) were identified as independent correlates of WMHs based on Fazekas grading. Independent correlates of the total template volume of WMHs included MMP-2 (P = 0.023), TIMP-1 (P = 0.046), age (P = 0.047), systolic blood pressure (P = 0.047), and homocysteine (Hcy) (P = 0.014). In addition, age (P = 0.003; P < 0.001), interleukin-6 (IL-6) (P < 0.001; P = 0.044), Hcy (P < 0.001; P < 0.001), glycated hemoglobin (HbA1c) (P = 0.016; P = 0.043), and chronic kidney disease (P < 0.001; P < 0.001) were associated with both WMHs Fazekas grading and the total template volume of WMHs. CONCLUSION: Serum levels of MMP-9, MMP-2, and TIMP-1 were independently associated with the Fazekas grading, while serum TIMP-1 and MMP-2 levels were independently related to the total template volume of WMHs. The association of TIMP-1 and MMP-2 with the severity of CSVD-related WMHs suggests their potential role as disease-related biomarkers. However, further research is required to uncover the specific mechanisms underlying these interactions.

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

BACKGROUND: White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease (AD) pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, AD imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. METHODS: We identified 1144 participants from the Mayo Clinic Study of Aging consisting of a population-based sample from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET, and tau-PET standardized uptake value ratio, automated WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). RESULTS: Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.82 and 0.74). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97) and showed poor correlation with amyloid and tau PET markers similar to the visual grading. CONCLUSION: Our study investigated risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Differential blood-based biomarkers of subcortical and deep brain small vessel disease.

Background: Cerebral small vessel disease is the most common cause of lacunar strokes (LS). Understanding LS pathogenesis is vital for predicting disease severity, prognosis, and developing therapies. Objectives: To research molecular profiles that differentiate LS in deep brain structures from those in subcortical white matter. Design: Prospective case-control study involving 120 patients with imaging-confirmed LS and a 120 control group. Methods: We examined the relationship between Alzheimer's disease biomarkers [amyloid beta (Aß1-40, Aß1-42)], serum inflammatory marker (interleukin-6, IL-6), and endothelial dysfunction markers [soluble tumor necrosis factor-like weak inducer of apoptosis, and pentraxin-3 (sTWEAK, PTX3)] with respect to LS occurring in deep brain structures and subcortical white matter. In addition, we investigated links between LS, leukoaraiosis presence (white matter hyperintensities, WMHs), and functional outcomes at 3 months. Poor outcome was defined as a modified Rankin scale >2 at 3 months. Results: Significant differences were observed in levels of IL-6, PTX3, and sTWEAK between patients with deep lacunar infarcts and those with recent small subcortical infarcts (20.8 versus 15.6 pg/mL, p < 0.001; 7221.3 versus 4624.4 pg/mL, p < 0.0001; 2528.5 versus 1660.5 pg/mL, p = 0.001). Patients with poor outcomes at 3 months displayed notably higher concentrations of these biomarkers compared to those with good outcomes. By contrast, Aß1-40 and Aß1-42 were significantly lower in patients with deep LS (p < 0.0001). Aß1-42 levels were significantly higher in patients with LS in subcortical white matter who had poor outcomes. WMH severity only showed a significant association with deep LS and correlated with sTWEAK (p < 0.0001). Conclusion: The pathophysiological mechanisms of lacunar infarcts in deep brain structures seem different from those in the subcortical white matter. As a result, specific therapeutic and preventive strategies should be explored.

Association of vulnerable plaques with white matter hyperintensities on high-resolution magnetic resonance imaging.

Background: One of the widespread manifestations of cerebral small vessel disease (CSVD) of the brain parenchyma is white matter lesion, which appears as white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI). Previous studies have illustrated that large artery atherosclerosis is related to CSVD, but the precise progress of pathogenesis remains unknown. High-resolution MRI (HR-MRI) has the ability to delineate intracranial vascular walls, enabling a thorough exploration of the structure and composition of unstable plaques. This study aimed to apply HR-MRI to characterize the wall changes and plaque characteristics of middle cerebral arteries in patients with WMHs and to investigate the correlation between plaque vulnerability parameters and different degrees of WMHs. Methods: In this study, 138 patients with acute ischemic stroke at Harbin Medical University's First Clinical Hospital (May 2021 to October 2023) were cross-sectionally reviewed and underwent conventional brain and HR-MRI using T1-weighted 3D volumetric isotropic turbo spin echo acquisition (T1W-3D-VISTA) of the unilateral middle cerebral artery (MCA). According to Fazekas grade (0-6), the patients were divided into two groups: Fazekas score 0-2, no-or-mild WMHs; and Fazekas 3-6, moderate-to-severe WMHs. The intraplaque hemorrhage, plaque distribution, plaque enhancement, plaque load, remodeling pattern, and stenosis of the two groups were measured. Binary logistic regression analysis was conducted to evaluate the relationship between vulnerable plaques and WMHs. Results: Of the participants who were initially considered for inclusion, 71 were deemed eligible, among whom 34 were placed in the no-or-mild WMH group and 37 in the moderate-to-severe WMH group. Between the two groups, there were significant differences in intraplaque hemorrhage (P=0.01), a wide distribution (P=0.02), and plaque enhancement (P=0.02). Univariate analysis showed that WMHs were associated with age [odds ratio (OR) =1.080; 95% confidence interval (CI): 1.020-1.144; P=0.008], hypertension (OR =3.500; 95% CI: 1.276-9.597; P=0.01), intraplaque hemorrhage (OR =3.955; 95% CI: 1.247-12.538; P=0.02), a wide distribution (OR =3.067; 95% CI: 1.159-8.115; P=0.02), and significant plaque enhancement (OR =4.372; 95% CI: 1.101-17.358; P=0.03); however, the multivariate results showed that the only independent factors associated with WMHs were age (OR =1.095; 95% CI: 1.019-1.176; P=0.01) and intraplaque hemorrhage (OR =5.88; 95% CI: 1.466-23.592; P=0.01). Conclusions: Our findings suggest that age and intraplaque hemorrhage may be associated with more severe WMHs in patients with acute ischemic stroke, which may be helpful for further clinical examination and intervention treatment.

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Background: White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods: We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results: Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion: Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Chronic kidney disease and its association with cerebral small vessel disease in the general older hypertensive population.

BACKGROUND: Cerebral small vessel disease can be identified using magnetic resonance imaging, and includes white matter hyperintensities, lacunar infarcts, cerebral microbleeds, and brain atrophy. Cerebral small vessel disease and chronic kidney disease share many risk factors, including hypertension. This study aims to explore an association between chronic kidney disease and cerebral small vessel disease, and also to explore the role of hypertension in this relationship. METHODS: With a cross sectional study design, data from 390 older adults was retrieved from the general population study Good Aging in Skåne. Chronic kidney disease was defined as glomerular filtration rate < 60 ml/min/1,73m2. Associations between chronic kidney disease and magnetic resonance imaging markers of cerebral small vessel disease were explored using logistic regression models adjusted for age and sex. In a secondary analysis, the same calculations were performed with the study sample stratified based on hypertension status. RESULTS: In the whole group, adjusted for age and sex, chronic kidney disease was not associated with any markers of cerebral small vessel disease. After stratification by hypertension status and adjusted for age and sex, we observed that chronic kidney disease was associated with cerebral microbleeds (OR 1.93, CI 1.04-3.59, p-value 0.037), as well as with cortical atrophy (OR 2.45, CI 1.34-4.48, p-value 0.004) only in the hypertensive group. In the non-hypertensive group, no associations were observed. CONCLUSIONS: In this exploratory cross-sectional study, we observed that chronic kidney disease was associated with markers of cerebral small vessel disease only in the hypertensive subgroup of a general population of older adults. This might indicate that hypertension is an important link between chronic kidney disease and cerebral small vessel disease. Further studies investigating the relationship between CKD, CSVD, and hypertension are warranted.

Choroid plexus calcifications are not associated with putative markers of glymphatic dysfunction: A population study in middle-aged and older adults.

BACKGROUND AND PURPOSE: Recent studies have suggested an association between dysfunction of the choroid plexus and the glymphatic system. However, information is inconclusive. Following a population-based study design, we aimed to assess the association between choroid plexus calcifications (CPCs)-as a surrogate of choroid plexus dysfunction-and severity and progression of putative markers of glymphatic dysfunction, including white matter hyperintensities (WMH) of presumed vascular origin and abnormally enlarged basal ganglia perivascular spaces (BG-PVS). METHODS: This study recruited community-dwellers aged ≥40 years living in neighboring Ecuadorian villages. Participants who had baseline head CTs and brain MRIs were included in cross-sectional analyses and those who additional had follow-up MRIs (after a mean of 6.4 ± 1.5 years) were included in longitudinal analyses. Logistic and Poisson regression models, adjusted for demographics and cardiovascular risk factors, were fitted to assess associations between CPCs and WMH and enlarged BG-PVS severity and progression. RESULTS: A total of 590 individuals were included in the cross-sectional component of the study, and 215 in the longitudinal component. At baseline, 25% of participants had moderate-to-severe WMH and 27% had abnormally enlarged BG-PVS. At follow-up, 36% and 20% of participants had WMH and enlarged BG-PVS progression, respectively. Logistic regression models showed no significant differences between CPCs volumes stratified in quartiles and severity of WMH and enlarged BG-PVS. Poisson regression models showed no association between the exposure and WMH and enlarged BG-PVS progression. Baseline age remained significant in these models. CONCLUSIONS: Choroid plexus calcifications are not associated with putative markers of glymphatic system dysfunction.

Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: The COSMIC consortium.

INTRODUCTION: White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions. METHODS: We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains. RESULTS: Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing. CONCLUSION: The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.

Cerebral arterial stiffness is linked to white matter hyperintensities and perivascular spaces in older adults - A 4D flow MRI study.

White matter hyperintensities (WMH), perivascular spaces (PVS) and lacunes are common MRI features of small vessel disease (SVD). However, no shared underlying pathological mechanism has been identified. We investigated whether SVD burden, in terms of WMH, PVS and lacune status, was related to changes in the cerebral arterial wall by applying global cerebral pulse wave velocity (gcPWV) measurements, a newly described marker of cerebral vascular stiffness. In a population-based cohort of 190 individuals, 66-85 years old, SVD features were estimated from T1-weighted and FLAIR images while gcPWV was estimated from 4D flow MRI data. Additionally, the gcPWV's stability to variations in field-of-view was analyzed. The gcPWV was 10.82 (3.94) m/s and displayed a significant correlation to WMH and white matter PVS volume (r = 0.29, p < 0.001; r = 0.21, p = 0.004 respectively from nonparametric tests) that persisted after adjusting for age, blood pressure variables, body mass index, ApoB/A1 ratio, smoking as well as cerebral pulsatility index, a previously suggested early marker of SVD. The gcPWV displayed satisfactory stability to field-of-view variations. Our results suggest that SVD is accompanied by changes in the cerebral arterial wall that can be captured by considering the velocity of the pulse wave transmission through the cerebral arterial network.

Identifying Leukoaraiosis with Mild Cognitive Impairment by Fusing Multiple MRI Morphological Metrics and Ensemble Machine Learning.

Leukoaraiosis (LA) is strongly associated with impaired cognition and increased dementia risk. Determining effective and robust methods of identifying LA patients with mild cognitive impairment (LA-MCI) is important for clinical intervention and disease monitoring. In this study, an ensemble learning method that combines multiple magnetic resonance imaging (MRI) morphological features is proposed to distinguish LA-MCI patients from LA patients lacking cognitive impairment (LA-nCI). Multiple comprehensive morphological measures (including gray matter volume (GMV), cortical thickness (CT), surface area (SA), cortical volume (CV), sulcus depth (SD), fractal dimension (FD), and gyrification index (GI)) are extracted from MRI to enrich model training on disease characterization information. Then, based on the general extreme gradient boosting (XGBoost) classifier, we leverage a weighted soft-voting ensemble framework to ensemble a data-level resampling method (Fusion + XGBoost) and an algorithm-level focal loss (FL)-improved XGBoost model (FL-XGBoost) to overcome class-imbalance learning problems and provide superior classification performance and stability. The baseline XGBoost model trained on an original imbalanced dataset had a balanced accuracy (Bacc) of 78.20%. The separate Fusion + XGBoost and FL-XGBoost models achieved Bacc scores of 80.53 and 81.25%, respectively, which are clear improvements (i.e., 2.33% and 3.05%, respectively). The fused model distinguishes LA-MCI from LA-nCI with an overall accuracy of 84.82%. Sensitivity and specificity were also well improved (85.50 and 84.14%, respectively). This improved model has the potential to facilitate the clinical diagnosis of LA-MCI.

Occupational and domestic exposure associations with cerebral small vessel disease and vascular dementia: A systematic review and meta-analysis.

INTRODUCTION: The prevalence of cerebral smallvessel disease (SVD) and vascular dementia according to workplace or domestic exposure to hazardous substances is unclear. METHODS: We included studies assessing occupational and domestic hazards/at-risk occupations and SVD features. We pooled prevalence estimates using random-effects models where possible, or presented a narrative synthesis. RESULTS: We included 85 studies (n = 47,743, mean age = 44·5 years). 52/85 reported poolable estimates. SVD prevalence in populations exposed to carbon monoxide was 81%(95% CI = 60-93%; n = 1373; results unchanged in meta-regression), carbon disulfide73% (95% CI = 54-87%; n = 131), 1,2-dichloroethane 88% (95% CI = 4-100%, n = 40), toluene 82% (95% CI = 3-100%, n = 64), high altitude 49% (95% CI = 38-60%; n = 164),and diving 24% (95% CI = 5-67%, n = 172). We narratively reviewed vascular dementia studies and contact sport, lead, military, pesticide, and solvent exposures as estimates were too few/varied to pool. DISCUSSION: SVD and vascular dementia may be associated with occupational/domestic exposure to hazardous substances. CRD42021297800.

Serum Placental Growth Factor as a Marker of Cerebrovascular Disease Burden in Alzheimer's Disease.

BACKGROUND: Concomitant cerebrovascular diseases (CeVD) have been identified as an important determinant of Alzheimer's disease (AD) progression. Development of robust blood-based biomarkers will provide critical tools to evaluate prognosis and potential interventional strategies for AD with CeVD. OBJECTIVE: This study investigated circulating placental growth factor (PlGF), a potent pro-angiogenic factor related to endothelial dysfunction and vascular inflammation, in an Asian memory clinic cohort of non-demented individuals as well as AD, including its associations with neuroimaging markers of CeVD. METHODS: 109 patients with AD, 76 cognitively impaired with no dementia (CIND), and 56 non-cognitively impaired (NCI) were included in this cross-sectional study. All subjects underwent 3T brain magnetic resonance imaging to assess white matter hyperintensities (WMH), lacunes, cortical infarcts, and cerebral microbleeds (CMBs). Serum PlGF concentrations were measured by electrochemiluminescence immunoassays. RESULTS: Serum PlGF was elevated in AD, but not CIND, compared to the NCI controls. Adjusted concentrations of PlGF were associated with AD only in the presence of significant CeVD. Elevated PlGF was significantly associated with higher burden of WMH and with CMBs in AD patients. CONCLUSIONS: Serum PlGF has potential utility as a biomarker for the presence of CeVD, specifically WMH and CMBs, in AD. Further studies are needed to elucidate the underlying pathophysiological mechanisms linking PlGF to CeVD, as well as to further assess PlGF's clinical utility.

U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities.

Background: Whether white matter hyperintensities (WMHs) involve U-fibers is of great value in understanding the different etiologies of cerebral white matter (WM) lesions. However, clinical practice currently relies only on the naked eye to determine whether WMHs are in the vicinity of U-fibers, and there is a lack of good neuroimaging tools to quantify WMHs and U-fibers. Methods: Here, we developed a multimodal neuroimaging toolbox named U-fiber analysis (UFA) that can automatically extract WMHs and quantitatively characterize the volume and number of WMHs in different brain regions. In addition, we proposed an anatomically constrained U-fiber tracking scheme and quantitatively characterized the microstructure diffusion properties, fiber length, and number of U-fibers in different brain regions to help clinicians to quantitatively determine whether WMHs in the proximal cortex disrupt the microstructure of U-fibers. To validate the utility of the UFA toolbox, we analyzed the neuroimaging data from 246 patients with cerebral small vessel disease (cSVD) enrolled at Zhongshan Hospital between March 2018 and November 2019 in a cross-sectional study. Results: According to the manual judgment of the clinician, the patients with cSVD were divided into a WMHs involved U-fiber group (U-fiber-involved group, 51 cases) and WMHs not involved U-fiber group (U-fiber-spared group, 163 cases). There were no significant differences between the U-fiber-spared group and the U-fiber-involved group in terms of age (P=0.143), gender (P=0.462), education (P=0.151), Mini-Mental State Examination (MMSE) scores (P=0.151), and Montreal Cognitive Assessment (MoCA) scores (P=0.411). However, patients in the U-fiber-involved group had higher Fazekas scores (P<0.001) and significantly higher whole brain WMHs (P=0.046) and deep WMH volumes (P<0.001) compared to patients in the U-fiber-spared group. Moreover, the U-fiber-involved group had higher WMH volumes in the bilateral frontal [P(left) <0.001, P(right) <0.001] and parietal lobes [P(left) <0.001, P(right) <0.001]. On the other hand, patients in the U-fiber-involved group had higher mean diffusivity (MD) and axial diffusivity (AD) in the bilateral parietal [P(left, MD) =0.048, P(right, MD) =0.045, P(left, AD) =0.015, P(right, AD) =0.015] and right frontal-parietal regions [P(MD) =0.048, P(AD) =0.027], and had significantly reduced mean fiber length and number in the right parietal [P(length) =0.013, P(number) =0.028] and right frontal-parietal regions [P(length) =0.048] compared to patients in the U-fiber-spared group. Conclusions: Our results suggest that WMHs in the proximal cortex may disrupt the microstructure of U-fibers. Our tool may provide new insights into the understanding of WM lesions of different etiologies in the brain.

Association of white matter hyperintensities with long-term EGFR-TKI treatment and prediction of progression risk.

PURPOSE: The purpose of this study was to test the hypothesis that brain white matter hyperintensities (WMH) are more common in patients receiving epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) and identify clinical risk factors associated with WMH. EXPERIMENTAL DESIGN: This multiple-center, prospective cohort study was conducted from March 2017 to July 2020. Two groups of patients with non-small cell lung cancer (NSCLC) who received or did not receive EGFR-TKI were included and followed up for more than 24 months. The progression of WMH was defined as an increase of ≥1 point on the Fazekas visual rating scale between the baseline and at the 2-year follow-up. A modified Poisson regression model was performed to evaluate risk factors on increased WMH load. RESULTS: Among 286 patients with NSCLC, 194 (68%) patients with NSCLC who received EGFR-TKI and 92 (32%) patients with NSCLC without EGFR-TKI treatment were analyzed. Modified Poisson regression analysis showed that EGFR-TKI treatment was independently associated with the WMH progression (EGFR-TKI: aRR 2.72, 95% confidence interval [CI] 1.46-5.06, p = .002). Interleukin (IL)-2, IL-4, and IL-10 were associated with increased WMH in the adjusted model (IL-2: aRR 1.55 [95% CI 1.06-2.25], p = .023; IL-4: aRR 1.66 [95% CI 1.13-2.43], p = .010; IL-10: aRR 1.48 [95% CI 1.06-2.06], p = .020). CONCLUSION: Patients with NSCLC who received EGFR-TKI may be at higher risk of developing WMH or worsening of WMH burden. The impact of increased WMH lesions in these patients is to be further assessed. IL-2, IL-4, and IL-10 may be used as potential biomarkers to monitor the risk of increased WMH burden.