White Matter Hyperintensity Volume Research Articles

Associations among plasma, MRI and amyloid PET biomarkers of dementia and the impact of health‐related comorbidities

AbstractBackgroundKnowledge regarding associations between plasma and neuroimaging biomarkers indexing neurodegeneration and neuropathology observed in dementia is limited. Further, it is uncertain how comorbid health complications (e.g., kidney function) may alter plasma levels and impact associations with neuroimaging biomarkers.MethodWe examined associations between plasma and neuroimaging biomarkers in cognitively normal participants (NC; N = 300) and individuals with consensus diagnosis (Dx) of mild cognitive impairment (MCI; N = 192) or dementia (DEM; N = 64) enrolled in the Wake Forest ADRC (Table 1). We examined plasma biomarkers (Quanterix SIMOA HD‐X: Aβ42/40, GFAP, NfL, p‐tau181) and neuroimaging measures of amyloid deposition (global PiB PET SUVr; Aβ‐PET), total brain volume (BVOL), global white matter hyperintensity volume (WMH), diffusion‐weighted fractional anisotropy (FA) and NODDI freewater (FW; white matter). Linear models adjusted for APOE‐ε4 carrier status, demographics (age, sex, race, education), and cardiometabolic factors (estimated glomerular filtration rate (eGFR); BMI).ResultsPlasma biomarkers were moderately correlated with each other (absolute r = .22‐.64; all p<.001) and significantly elevated (Aβ42/40 lower) in DEM and MCI (Figure 1) versus NC, and Aβ‐PET‐positive (SUVr >1.21) versus negative individuals (all p<.001). Plasma and neuroimaging markers were significantly associated in both unadjusted models and models including eGFR and BMI (all p<.05; attenuation effect <10% with and without Dx; Figure 2a & 2b). In fully adjusted models (Figure 2b: Dx and all covariates), age, sex, and race differentially impacted associations of Aβ42/40, p‐tau181, and NfL with neuroimaging biomarkers (coefficients p <.05). APOE‐ε4 status exclusively impacted associations with Aβ‐PET SUVr/status. GFAP remained significantly associated with all neuroimaging biomarkers after covariate adjustment; no Aβ42/40 associations survived adjustment. P‐tau181 remained significantly associated with Aβ‐PET and BVOL, while associations with NfL were reduced in models stratified by Dx.ConclusionAmong aging community‐dwelling participants, plasma biomarkers significantly differed between diagnostic groups (DEM>MCI>NC), were elevated in Aβ‐PET positive individuals, and associated with poorer brain health. Except for GFAP, and to an extent p‐tau181, associations between plasma and neuroimaging biomarkers were differentially impacted by inclusion of comorbidities and covariates when stratified by diagnosis. Future work will examine high‐dimensional interactions among comorbidities, demographic information, and plasma and neuroimaging biomarkers in individuals with or at‐risk of dementia.

Graph Theory Analysis of Structural Connectivity in Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC)

AbstractBackgroundThe anatomical distribution of limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) typically involves the amygdala, hippocampus, and other subcortical, temporal and frontal lobe regions. But its impact on the structural integrity of this network of regions remains unknown. In this study, we tested the hypothesis that LATE‐NC is associated with abnormalities in graph theoretic measures of structural connectivity in the network of regions known to be involved in LATE‐NC.MethodThis study included 148 deceased older adults participating in Rush Memory and Aging Project and Religious Orders Study (Fig.1A). Ex‐vivo diffusion tensor imaging (DTI) scans were acquired on 3T scanners, followed by detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1B). Fractional anisotropy (FA) maps derived from DTI scans were used to define region‐to‐region structural connectivity in a network of 19 regions known to be involved in LATE‐NC using graph theory‐based network measures (Fig.2).General linear models were used to investigate the association of global and local graph measures with LATE‐NC stages, controlling for other neuropathologies (Alzheimer’s disease, Lewy bodies, arteriolosclerosis, atherosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts), demographics (age at death, sex, education), total white matter hyperintensity volume, postmortem intervals and scanner variables. Statistical significance was set at p<0.05.ResultLinear regression revealed that greater LATE‐NC stage was associated with increased characteristic path length and with lower values of the remaining global network measures (p<0.05) (Fig.3A). LATE‐NC was also associated with lower local efficiency, increased path length, lower nodal strength, and lower clustering coefficient in 74%, 79%, 32%, and 63% of the nodes, respectively (p<0.05) (Fig.3B). Finally, LATE‐NC was associated with both greater (in 21% of nodes) and lower (in 16% of nodes) eigenvector centrality, and with both greater and lower betweenness centrality in 21% of nodes, respectively (p<0.05) (Fig.3B).ConclusionUsing graph theory and a hypothesis‐driven approach, we found significant degradation of structural integrity in white matter of the network of regions affected by LATE‐NC. These findings may shed light on the effects of LATE‐NC on brain connectivity, and in combination with other imaging and clinical information, may aid towards the development of tools for in‐vivo detection of this devastating neuropathology.

Associations among plasma, MRI and amyloid PET biomarkers of dementia and the impact of health‐related comorbidities

AbstractBackgroundKnowledge regarding associations between plasma and neuroimaging biomarkers indexing neurodegeneration and neuropathology observed in dementia is limited. Further, it is uncertain how comorbid health complications (e.g., kidney function) may alter plasma levels and impact associations with neuroimaging biomarkers.MethodWe examined associations between plasma and neuroimaging biomarkers in cognitively normal participants (NC; N = 300) and individuals with consensus diagnosis (Dx) of mild cognitive impairment (MCI; N = 192) or dementia (DEM; N = 64) enrolled in the Wake Forest ADRC (Table 1). We examined plasma biomarkers (Quanterix SIMOA HD‐X: Aß42/40, GFAP, NfL, p‐tau181) and neuroimaging measures of amyloid deposition (global PiB PET SUVr; Aß‐PET), total brain volume (BVOL), global white matter hyperintensity volume (WMH), diffusion‐weighted fractional anisotropy (FA) and NODDI freewater (FW; white matter). Linear models adjusted for APOE‐e4 carrier status, demographics (age, sex, race, education), and cardiometabolic factors (estimated glomerular filtration rate (eGFR); BMI).ResultPlasma biomarkers were moderately correlated with each other (absolute r = .22‐.64; all p<.001) and significantly elevated (Aß42/40 lower) in DEM and MCI (Figure 1) versus NC, and Aß‐PET‐positive (SUVr >1.21) versus negative individuals (all p<.001). Plasma and neuroimaging markers were significantly associated in both unadjusted models and models including eGFR and BMI (all p<.05; attenuation effect <10% with and without Dx; Figure 2a & 2b). In fully adjusted models (Figure 2b: Dx and all covariates), age, sex, and race differentially impacted associations of Aß42/40, p‐tau181, and NfL with neuroimaging biomarkers (coefficients p <.05). APOE‐e4 status exclusively impacted associations with Aß‐PET SUVr/status. GFAP remained significantly associated with all neuroimaging biomarkers after covariate adjustment; no Aß42/40 associations survived adjustment. P‐tau181 remained significantly associated with Aß‐PET and BVOL, while associations with NfL were reduced in models stratified by Dx.ConclusionAmong aging community‐dwelling participants, plasma biomarkers significantly differed between diagnostic groups (DEM>MCI>NC), were elevated in Aß‐PET positive individuals, and associated with poorer brain health. Except for GFAP, and to an extent p‐tau181, associations between plasma and neuroimaging biomarkers were differentially impacted by inclusion of comorbidities and covariates when stratified by diagnosis. Future work will examine high‐dimensional interactions among comorbidities, demographic information, and plasma and neuroimaging biomarkers in individuals with or at‐risk of dementia.

Influence of lung function on macro‐ and micro‐structural brain changes in mid‐ and late‐ life: a large population‐based cohort study in the UK Biobank

AbstractBackgroundLung function has been associated with cognitive decline and dementia, but the extent to which lung function impacts brain structural changes remains unclear. We aimed to investigate the association of lung function with structural macro‐ and micro‐ brain changes across mid‐ and late‐ life in a large population‐based cohort study.MethodThe study included a total of 37,590 neurologic disorder‐free participants aged 40‐70 years from the UK Biobank, who underwent brain magnetic resonance imaging (MRI) scans 9 years after baseline. After 2.5 years, a subsample (n = 3,941) underwent a second MRI scan. Lung function was assessed using a composite score based on forced expiratory volume in 1 second, forced vital capacity, and peak expiratory flow, and divided into tertiles (i.e., low, moderate, and high). Regional brain volumes (including total brain, gray matter, white matter, hippocampus, and white matter hyperintensities) and diffusion markers (fractional anisotropy [FA] and mean diffusivity [MD]) were assessed. Data were analyzed using linear regression and mixed‐effects models.ResultAt baseline, lung function ranged from ‐3.43 to 22.91 among all participants. In multi‐adjusted linear regression, low lung function was dose‐dependently related to smaller brain volumes and lower white matter integrity. Compared to high lung function, low lung function was associated with smaller total brain (β [95% CI]: ‐0.083 [‐0.097, ‐0.070], gray matter ‐0.145 [‐0.161, ‐0.130], white matter ‐0.017 [‐0.031, ‐0.004], and hippocampal ‐0.102 [‐0.128, ‐0.075]) volume, as well as poor white matter health (FA ‐0.165 [‐0.195, ‐0.135] for lower, WMH 0.269 [0.242, 0.295] and MD 0.168 [0.140, 0.196] for higher). Over the 2.5 years follow‐up, low PF was associated with reduced white matter (‐0.021 [‐0.041, ‐0.002]) and hippocampal (‐0.078 [‐0.110, ‐0.046]) volume, reduced FA (‐0.063 [‐0.091, ‐0.035]), and increased WMH volume (0.065 [0.016, 0.114]) and MD (0.121 [0.089, 0.154]). After stratification by age, the associations remained significant among adults aged 40‐60 years and 60+ years.ConclusionLow lung function is associated with macro‐ and micro‐ structural brain changes involving both neurodegenerative and vascular pathologies. This association is significant in both mid‐ and late‐ life.

Machine‐learning derived white matter signatures and the risk of dementia, stroke and mortality: the Rotterdam Study

AbstractBackgroundWhite matter hyperintensities (WMH), loss of white matter (WM) volume and WM microstructural integrity are important risk indicators of stroke and dementia, albeit of heterogeneous nature. Use of machine learning techniques may unravel different patterns of white matter injury, with distinct underlying pathologies and disease risk.MethodWe measured WMH volume, WM volume, global fractional anisotropy (FA) and global mean diffusivity (MD) in 5205 participants (mean age 64.9 years, 56.0% women) of the population‐based Rotterdam study with brain MRI between 2005 and 2016. We performed hierarchical clustering on age‐standardized imaging parameters to identify separate clusters of white matter injury, and compare determinants across clusters. We then determined the association between clusters and risk of dementia, stroke and mortality, using Cox proportional hazard models adjusted for sex, education, APOE‐ε4 and cardiovascular risk factors.ResultWe identified four distinct white matter signatures: (i) cluster with above‐average microstructural integrity and little WM atrophy and WMH, (ii) cluster with above‐average microstructural integrity and little WMH, yet substantial WM atrophy, (iii) cluster with poor microstructural integrity and substantial WMH, yet little WM atrophy, and (iv) cluster with poor microstructural integrity, substantial WM atrophy, and average WMH load. There were no clear differences between clusters in APOE genotype and cardiometabolic risk factors, except for higher prevalence of hypertension in cluster (iv). Cluster (iii) contained more women, and participants in clusters (iii) and (iv) had more microbleeds and lacunes. During a median 10.7 years of follow‐up, 272, 210, and 844 cases of dementia, stroke, death occurred, respectively. In fully adjusted models, dementia risk was increased for clusters (ii) (HR 1.57 [95%CI:1.04‐2.37]), (iii) (HR 2.43 [95%CI:1.68‐3.52]) and (iv) (HR 1.78 [95%CI:1.22‐2.62], compared to cluster (i). Moderate associations of clusters (iii) and (iv) with incidence stroke attenuated and were no longer statistically significant after adjustment for cardiovascular risk factors, while only cluster (iii) was associated with a small increase in mortality (HR 1.30 [95%CI:1.07‐1.58]).ConclusionMachine‐learning derived white matter signatures are differentially associated with dementia, stroke and mortality. Further research is needed to pinpoint differences in underlying pathology, and assess potential benefit of clusters for risk stratification.

Distinct effects of cholesterol profile components on amyloid and vascular burdens

AbstractBackgroundCholesterol plays important roles in β‐amyloid (Aβ) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aβ and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aβ and CSVD burdens in a large, non‐demented Korean cohort.MethodWe enrolled 1,175 non‐demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aβ PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low‐density lipoprotein cholesterol [LDL‐c], high‐density lipoprotein cholesterol [HDL‐c], and triglyceride) level as a predictor and each image marker (Aβ uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders.ResultIncreased LDL‐c levels (β = 0.014 to 0.115, p = 0.013) were associated with greater Aβ uptake, independent of the APOE e4 allele genotype and lipid‐lowering medication. Decreased HDL‐c levels (β = −0.133 to −0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL‐c levels were also associated with decreased hippocampal volume (direct effect β = −0.053, p = 0.040), which was partially mediated by Aβ uptake (indirect effect β = −0.018, p = 0.006).ConclusionOur findings highlight that increased LDL‐c and decreased HDL‐c levels are important risk factors for Aβ and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL‐c and HDL‐c levels is a potential strategy to prevent dementia.

Vascular contribution to the preclinical Alzheimer’s disease pathological changes: Insights from the EPAD cohort

AbstractBackgroundThe role of cardiovascular risk factors and cerebral small vessel disease (CSVD) on the sequences of Alzheimer’s Disease (AD) pathological events remains to be determined.MethodWe included 1592 non‐demented participants from EPAD‐LCS (Table‐1). Linear models were used to study associations between the Framingham score (FRS) and CSF‐Aβ1‐42; CSVD indices (visual assessment for perivascular spaces [PVS] in the basal ganglia [BG] and centrum‐semiovale [CS], periventricular and deep white matter hyperintensities [WMHs], presence of lobar or deep cerebral microbleeds [CMBs], and lacunes, and quantification of global and lobar WMH volumes) and Aβ1‐42 and p‐Tau181, including an interaction between CSVD indices and Aβ1‐42 for the latter. Hippocampal volumes (HCV) were quantified using LEAP. Structural equation models (SEM) were used to assess the association between clinical variables as described in Figure‐1. Models were corrected for age, sex, site and multiple comparisons.ResultHigher FRS scores were associated with lower CSF Aβ1‐42 (β = ‐0.18; p<0.001) and higher P‐tau181 (β = 0.21; p<0.001). Aβ1‐42 was negatively associated with all CSVD markers (all p<0.001; Figure‐2).We found stronger association between Aβ1‐42 and P‐tau181 in participants with higher Fazekas deep and periventricular (p‐interaction<0.005) scores, and higher regional WMH (all p‐interactions<0.005) volumes.Using SEM, the CSVD‐burden latent factor fully mediated the association between FRS and Aβ1‐42 (indirect effect: β = ‐0.03; p<0.001). Aβ1‐42 did not significantly predict the CSVD‐burden latent factor. We observed a significant direct effect of Aβ1‐42 on P‐tau181 levels (β = ‐0.14; p<0.001) and HCV (β = 0.06; p<0.05), and of P‐tau181 levels onto HCV (β = ‐0.05; p<0.05). A significant indirect, but not direct, effect of the latent factor on both P‐tau181 (indirect effect: β = 0.36; p < 0.05) and HCV (indirect effect: β = ‐0.24; p < 0.05) through Aβ1‐42 was observed.ConclusionExpression of cerebrovascular pathology fully mediates the effects of vascular risk factors on amyloid and accelerates manifestation of downstream biomarkers in the preclinical phases of AD, stressing the importance of vascular‐protective treatments.

Heart rate fragmentation and brain MRI markers of small vessel disease in MESA.

Heart rate (HR) fragmentation indices quantify breakdown of HR regulation and are associated with atrial fibrillation and cognitive impairment. Their association with brain magnetic resonance imaging (MRI) markers of small vessel disease is unexplored. In 606 stroke-free participants of the Multi-Ethnic Study of Atherosclerosis (mean age 67), HR fragmentation indices including percentage of inflection points (PIP) were derived from sleep study recordings. We examined PIP in relation to white matter hyperintensity (WMH) volume, total white matter fractional anisotropy (FA), and microbleeds from 3-Tesla brain MRI completed 7 years later. In adjusted analyses, higher PIP was associated with greater WMH volume (14% per standard deviation [SD], 95% confidence interval [CI]: 2, 27%, P=0.02) and lower WM FA (-0.09 SD per SD, 95% CI: -0.16, -0.01, P=0.03). HR fragmentation was associated with small vessel disease. HR fragmentation can be measured automatically from ambulatory electrocardiogram devices and may be useful as a biomarker of vascular brain injury.

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment.

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetryincluding white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above. Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS). We stratified 1961 persons with GDS ≤9 by age and cognitive score, and randomly selected 10% from each subgroup for MRI brain volumetry. Crude volumes were standardized to reflect percentage of intracranial volume. Results MRI volumetry studies were done in 199 individuals (F/M = 90/109; 73 with body mass index (BMI) ≥25; 44 hypertensives; 29 diabetics; mean cognitive score 76.3). Both grey and white matter volumes decreased with increasing age. WMHV increased with age and hypertension. Grey matter volume (GMV) decreased with increasing WMHV. Positive predictors of cognition included standardized hippocampal volume (HCV), urban living, education, and BMI, while WMHV and age were negative predictors. Urban dwellers had higher cognitive scores than rural, and, paradoxically, smaller HCV. Conclusion In this study of MRI volumetry correlated with age, cognitive scores and VRFs, increasing age and WMHV predicted lower cognitive scores, whereas urban living and hippocampal volume predicted higher scores. Age and WMHV also correlated with decreasing GMV. Further study is warranted into sociodemographic and biological factors that mutually influence cognition and brain volumes, including nutritional and endocrine factors, especially at lower cognitive score bands. In this study, at the lower KCB score bins, the lack of laboratory data pertaining to nutritional and endocrine deficiencies is a drawback that reflects the logistical limitations of screening large populations at the community level.Our volumetric data which is age and cognition stratified, and takes into account the vascular risk factors associated, nevertheless constitutesimportant baseline data for the Indian population. Our findings couldpossibly contribute to the formulation of baseline criteria for defining VCI inIndia and could help in early diagnosis and control of cognitive decline and its key risk factors.

Larger deep white matter hyperintensity volume correlates with more severe social behavioral changes in patients with subacute ischemic stroke

Larger deep white matter hyperintensity volume correlates with more severe social behavioral changes in patients with subacute ischemic stroke

Correlation between migraine and cerebral small vessel disease: A case-control study.

Microcirculatory pathology is one of the pathophysiological theories of migraine, which may present as visually subclinical lesions. Image markers of cerebral small vessel disease (CSVD) have been investigated in elderly migraineurs. However, past studies looked at only part of image features, and the conclusions may have been hindered by confounding factors. The relationship between migraine and CSVD signs needs reliable demonstrations. We conducted a case-control study by recruiting episodic young migraineurs from a tertiary headache centre, with tension-type headache (TTH) and healthy controls. Distinct image features of microvascular damage and baseline characteristics across groups were assessed, and multivariate linear regression was performed to evaluate the risk factors for image abnormalities in migraineurs. Forty-eight migraineurs, 32 TTHs and 49 healthy controls were included. The median age was 32 year-old. 58.7% of the participants were female. The Scheltens score and volume of white matter hyperintensities (WMHs) in migraineurs, and the number of Virchow-Robin spaces (VRSs) in both migraineurs and TTHs were different from those in normal controls. No lacunar infarct-like lesions (ILLs) or cerebral microbleeds (CMBs) were found. Age, education level (high level: β = -2.23, lobar WMHs), attack duration (long duration: β = 3.81, lobar WMHs) and attack frequency were independent risk factors for Scheltens score and volume of WMH in migraineurs. Migraine aura (β = -2.389), attack frequency and education level were correlated with the number of VRSs. Migraine was associated with WMHs and VRSs. Aura, attack duration, attack frequency, age and education level were risk factors for image abnormalities of CVSD in migraineurs. This study provides a novel and comprehensive landscape of CSVD MRI features in young migraineurs, and it fills the blank of CMBs and VRSs which received less attention, with more persuasive, more reliable and stronger evidence of the association between CSVD and migraine. Our results also imply some new feature of TTH and the possible pathophysiology of the migraine course as well as new clues for the early management of migraine in terms of visual brain damage.

Associations between white matter hyperintensities, lacunes, entorhinal cortex thickness, declarative memory and leisure activity in cognitively healthy older adults: A 7-year study

IntroductionCerebral small vessel disease (cSVD) is a growing epidemic that affects brain health and cognition. Therefore, a more profound understanding of the interplay between cSVD, brain atrophy, and cognition in healthy aging is of great importance. In this study, we examined the association between white matter hyperintensities (WMH) volume, number of lacunes, entorhinal cortex (EC) thickness, and declarative memory in cognitively healthy older adults over a seven-year period, controlling for possible confounding factors. Because there is no cure for cSVD to date, the neuroprotective potential of an active lifestyle has been suggested. Supporting evidence, however, is scarce. Therefore, a second objective of this study is to examine the relationship between leisure activities, cSVD, EC thickness, and declarative memory. MethodsWe used a longitudinal dataset, which consisted of five measurement time points of structural MRI and psychometric cognitive ability and survey data, collected from a sample of healthy older adults (baseline N = 231, age range: 64–87 years, age M = 70.8 years), to investigate associations between cSVD MRI markers, EC thickness and verbal and figural memory performance. Further, we computed physical, social, and cognitive leisure activity scores from survey-based assessments and examined their associations with brain structure and declarative memory. To provide more accurate estimates of the trajectories and cross-domain correlations, we applied latent growth curve models controlling for potential confounders. ResultsLess age-related thinning of the right (β = 0.92, p<.05) and left EC (β = 0.82, p<.05) was related to less declarative memory decline; and a thicker EC at baseline predicted less declarative memory loss (β = 0.54, p<.05). Higher baseline levels of physical (β = 0.24, p<.05), and social leisure activity (β = 0.27, p<.01) predicted less thinning of right EC. No relation was found between WMH or lacunes and declarative memory or between leisure activity and declarative memory. Higher education was initially related to more physical activity (β = 0.16, p<.05) and better declarative memory (β = 0.23, p<.001), which, however, declined steeper in participants with higher education (β = –.35, p<.05). Obese participants were less physically (β = –.18, p<.01) and socially active (β = –.13, p<.05) and had thinner left EC (β = –.14, p<.05) at baseline. Antihypertensive medication use (β = –.26, p<.05), and light-to-moderate alcohol consumption (β = –.40, p<.001) were associated with a smaller increase in the number of lacunes whereas a larger increase in the number of lacunes was observed in current smokers (β = 0.30, p<.05). ConclusionsOur results suggest complex relationships between cSVD MRI markers (total WMH, number of lacunes, right and left EC thickness), declarative memory, and confounding factors such as antihypertensive medication, obesity, and leisure activitiy. Thus, leisure activities and having good cognitive reserve counteracting this neurodegeneration. Several confounding factors seem to contribute to the extent or progression/decline of cSVD, which needs further investigation in the future. Since there is still no cure for cSVD, modifiable confounding factors should be studied more intensively in the future to maintain or promote brain health and thus cognitive abilities in older adults.

Cerebrovascular Function is Altered in Hemodialysis Patients.

Hemodialysis (HD) patients have declines in cerebral blood flow (CBF) and cerebral oxygenation during HD that may lead to ischemic brain injury. Cerebrovascular reactivity (CVR) may indicate which individuals are more susceptible to intradialytic hypoperfusion and ischemia. We hypothesized that HD patients would have decreased CVR and increased CBF relative to controls and deficits in CVR would be related to brain structural deficits. We measured cortical thickness and white matter hyperintensity (WMH) volume from T1 and T2 FLAIR images respectively, CVR from a breath hold BOLD CVR fMRI and arterial transit time (ATT) and CBF from ASL. Cerebrovascular and structural deficits in gray and white matter (GM and WM) were tested by averaging across the tissue and with a pothole analysis. Finally, we correlated cortical thickness and WMH volume with GM and WM cerebrovascular variables to assess the relationship between brain structure and cerebrovascular health. In ten HD patients, cortical thickness was found to be decreased (p= 0.002), WMH volume increased (p=0.004), and WM CBF increased (p=0.02) relative to ten controls. Pothole analysis indicated a higher number of increased GM and WM CBF voxels (p=0.03, p=0.02) and a higher number of decreased GM and WM CVR voxels (p=0.02, p=0.01). This pilot study demonstrates that HD patients have decreased CVR and increased CBF relative to controls, along with reduced brain integrity. Further investigation is required to fully understand if these cerebrovascular deficits may lead to structural changes.

Predicting progression of white matter hyperintensity using coronary artery calcium score based on coronary CT angiography-feasibility and accuracy.

Coronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions. We evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to <100, 100 to 400, and > 400) to compare their WMH changes in nine brain regions. Alcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (p < 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p < 0.05). This study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD.

Distinct effects of cholesterol profile components on amyloid and vascular burdens

BackgroundCholesterol plays important roles in β-amyloid (Aβ) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aβ and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aβ and CSVD burdens in a large, non-demented Korean cohort.MethodsWe enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aβ PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aβ uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders.ResultsIncreased LDL-c levels (β = 0.014 to 0.115, p = 0.013) were associated with greater Aβ uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (β = − 0.133 to − 0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect β = − 0.053, p = 0.040), which was partially mediated by Aβ uptake (indirect effect β = − 0.018, p = 0.006).ConclusionsOur findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aβ and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.

Abstract 13410: Severe Brain White Matter Hyperintensity is Associated With Local Brain Atrophy of Parahippocampal Gyrus and Predicts Prognosis in Heart Failure Patients Without Dementia

Introduction: Aged heart failure (HF) patients without dementia may have a risk of cognitive impairment (CI) that attenuates the effect of treatment for HF. White Matter Hyperintensity (WMH) is a potential risk of CI through a disconnection of subcortical brain network. On the other hand, patients with CI have severe brain atrophy in parahippocampal gyrus (PHG). However, it is not clear whether WMH is associated with atrophy in PHG and predicts prognosis of HF patients. Hypothesis: In HF patients without dementia, WMH is associated with brain atrophy of PHG, a potential risk of CI, and predicts prognosis. Methods: Sixty-five HF patients (age 76±11 years, NYHA class II, EF47±17 %) were enrolled. We excluded patients with dementia using mini-mental state examination. We took 3D-T1 weighted images and Fluid Attenuated Inversion Recovery (FLAIR) images of whole brain using 1.5T magnetic resonance imaging. Image analysis was performed to evaluate the severity of atrophy of PHG and volume of WMH using 2mm voxel-based morphometry by the statistical parametric mapping software. The Z-score value was calculated to evaluate the severity of atrophy in PHG. A Kaplan-Meier Curve adjusted with age, sex, presence of atrial fibrillation, and blood pressure was constructed using inverse probability weighting method. Results: We determined the cut-off point of the volume of WMH for estimating cardiac death using a receiver operating characteristic curve. Patients were divided into High-WMH group (n=37, volume of WMH 30±13 mL) and Low-WMH group (n=28, volume of WMH 8±5 mL) according to the cut-off value (15mL). As shown in representative cases (Figure1), the Z-score value in PHG (pink circle) was higher in High-WMH group (1.45±0.78, white arrow) compared to Low-WMH group (0.94±0.57, P=0.006). Adjusted Kaplan-Meier curves showed poor prognosis of High-WMH group (Figure 2). Conclusions: In HF patients without dementia, severe WMH is a potential risk of CI and predicts poor prognosis.

Abstract 14266: Is the Association Between Coronary Artery Disease and Adverse Brain Health Causal? A Combined Observational and Mendelian Randomisation Study

Introduction: Although coronary artery disease (CAD) is associated with worse brain health in observational studies, whether this is causal remains elusive. Aim: To examine observational associations between CAD and brain health, and use Mendelian randomisation (MR) to test for causal relationships. Methods: 472,120 UK Biobank participants were included. Outcomes were divided into brain morphology (white matter hyperintensity volumes [WMHVs] and hippocampal volumes [HVs]) and cognitive outcomes (reaction times [RTs] and visual memory [VM]). Generalized linear models were employed to explore the association between CAD and these brain health outcomes after adjusting for demographics, cardiometabolic risk factors and medications. To determine whether the observed associations were causal, we fitted MR inverse-variance weighted models, alongside sensitivity analyses for horizontal pleiotropy. Results: Observational analyses showed that CAD participants had 1.8% (95% confidence interval [CI] =[1.5, 2.0]) longer (worse) RTs but this was attenuated to 1% after adjusting for antihypertensives, diabetes or lipid-lowering drugs; 15.9% [7.0, 25.8] greater WMHVs but this was attenuated to the null after controlling for cardiometabolic risk factors; and 1.7% [1.0, 2.5] lower HVs (1% after adjusting for antihypertensives). There was no association between CAD and VM. MR analyses showed that individuals with greater CAD genetic liability made 1.01% [1.00, 1.01] more errors on VM tests but there was no evidence of causal associations with RTs, WMHVs and HVs. Conclusion: Observational analyses showed that CAD was associated with worse brain health, and addressing cardiometabolic risk factors was beneficial. However, MR analyses suggested a causal association only between genetic liability to CAD and worse VM. Future research should explore non-cardiometabolic factors (e.g., glutamate toxicity) to reduce cognitive impairment risk in individuals with CAD.

Abstract 18846: A Noninvasive Smartphone Assessment of Aortic Arch Pulse Wave Velocity and Total Arterial Compliance

Introduction: Several clinical studies including a large multiethnic population (Dallas Heart Study) have shown that total arterial compliance (TAC) and aortic arch pulse wave velocity (PWV aa ) are predictors of cardiovascular disease (CVD) events. Dallas Heart Study also showed that PWV aa predicts brain white matter hyperintensity volume independent of cardiovascular risk factors. Recently, Intrinsic Frequency (IF) analysis of carotid pressure waveform from the Framingham Heart Study was used to predict heart failure (HF) events and CVD (Hypertension, 2021 PMID: 33390053). Aim: Our goal was to show the IF method can determine PWV aa and TAC when applied on carotid pulse waveforms obtained from a standard iPhone camera. Methods: The clinical cohort consisted of 120 individuals (40% women) with ages from 20-92 yrs (mean 53 ± 18), including 54 healthy and 66 patients with CVD (22 HF). Phase-contrast magnetic resonance imaging (PC-MRI) and carotid pressure tonometry data were used to compute TAC. PWV aa values were obtained using PC-MRI flow in ascending and descending aorta (not achieved in 1 patients). A custom Apple iPhone 5S application was used to obtain carotid pulse waves by holding the camera against the neck. IF parameters of iPhone waveforms (calibrated by cuff brachial pressures) were used in machine learning algorithms (IF-iPhone). The models of TAC and PWV aa were developed using 100 participants (99 for PWV aa ) and blindly tested on an additional 20 individuals. Results: In blind tests, iPhone-IF models showed Pearson correlations of r=0.89 and r=0.84 with the measured values of TAC and PWV aa , respectively (Fig.1). Conclusions: Assessment of PWV aa and TAC can be accurately achieved using an unmodified smartphone (iPhone). PWV aa evaluation with an iPhone can be used to identify, predict, and quantify risk of vascular brain damage. A Noninvasive iPhone-based method can be used in a clinical or home setting to routinely assess TAC in the general population or in HF.

Associations of the Mediterranean-DASH Intervention for Neurodegenerative Delay diet with brain structural markers and their changes.

The associations of the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet with brain structural changes are unclear. Among 26,466 UK Biobank participants, a 15-point MIND score was calculated from 24-hour diet recalls from2009 to 2012. We assessed its associations with 17 magnetic-resonance-derived brain volumetric markers and their longitudinal changes and explored whether genetic factors modify the associations. Higher MIND adherence was associated with larger volumes of thalamus, putamen, pallidum, hippocampus, and accumbens (beta per 3-unit increment ranging from 0.024 to 0.033) and lower white matter hyperintensities (P-trends<0.05), regardless of genetic predispositions of Alzheimer's disease. MIND score was not associated with their longitudinal changes (P>0.05) over a median of 2.2 years among participants with repeated imaging assessments (N = 2963), but was associated with slower atrophy in putamen (beta: 0.026, P-trend=0.044) and pallidum (beta: 0.030, P-trend=0.033) among APOEε4 non-carriers (N = 654). The MIND diet showed beneficial associations with certain brain imaging markers, and its associations with long-term brain structural changes warrants future investigation. Adherence to the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet was significantly associated with higher volumes and larger gray matter volumes in certain brain regions in UK adults, and the associations were not modified by genetic factors. No significant associations were observed between MIND diet and longitudinal changes in the investigated brain structural markers over a median of 2.2 years. Higher MIND score was significantly associated with slower atrophy in the putamen and pallidum among APOEε4 non-carriers.

Different types of screen time, physical activity, and incident dementia, Parkinson’s disease, depression and multimorbidity status

BackgroundSeveral previous studies have shown that excessive screen time is associated with an increased prevalence of dementia, Parkinson’s disease (PD), and depression. However, the results have been inconsistent. This study aimed to prospectively investigate the association between different types of screen time and brain structure, as well as the incidence of dementia, Parkinson’s disease, depression, and their multimorbidity status.MethodsWe included 473,184 participants initially free of dementia, PD, and depression from UK Biobank, as well as 39,652 participants who had magnetic resonance imaging (MRI) data. Screen time exposure variables including TV viewing and computer using were self-reported by participants. Cox proportional hazards regression models were used to estimate the association between different types of screen time and the incidence of dementia, Parkinson’s disease, depression, and their multimorbidity status. Multiple linear regression models were used to assess the linear relationship between different types of screen time and MRI biomarkers in a subgroup of participants.ResultsDuring the follow up, 6,096, 3,061, and 23,700 participants first incident cases of dementia, PD, and depression respectively. For moderate versus the lowest computer uses, the adjusted HRs (95% CIs) were 0.68 (0.64, 0.72) for dementia, 0.86 (0.79, 0.93) for PD, 0.85 (0.83, 0.88) for depression, 0.64 (0.55, 0.74) for dementia and depression multimorbidity, and 0.59 (0.47, 0.74) for PD and depression multimorbidity. The multivariable HRs (95% CIs) for the highest versus the lowest group of TV viewing time were 1.28 (1.17, 1.39) for dementia, 1.16 (1.03, 1.29) for PD, 1.35 (1.29, 1.40) for depression, 1.49 (1.21, 1.84) for dementia and depression multimorbidity, and 1.44 (1.05, 1.97) for PD and depression multimorbidity. Moderate computer using time was negatively associated with white matter hyperintensity volume (β = -0.042; 95% CI -0.067, -0.017), and positively associated with hippocampal volume (β = 0.059; 95% CI 0.034, 0.084). Participants with the highest TV viewing time were negatively associated with hippocampal volume (β = -0.067; 95% CI -0.094, -0.041). In isotemporal substitution analyses, substitution of TV viewing or computer using by equal time of different types of PA was associated with a lower risk of all three diseases, with strenuous sports showing the strongest benefit.ConclusionWe found that moderate computer use was associated with a reduced risk of dementia, PD, depression and their multimorbidity status, while increased TV watching was associated with a higher risk of these disease. Notably, different screen time may affect the risk of developing diseases by influencing brain structures. Replacing different types of screen time with daily-life PA or structured exercise is associated with lower dementia, PD, and depression risk.