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

BACKGROUND: Cognitive 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. METHODS: A 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/Aß42 ratio, were used as indicators of Alzheimer pathology. RESULTS: At baseline, diabetes was associated with lower cognitive performance and higher burden of CeVD, but not p-tau181 or p-tau181/Aß42 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. CONCLUSIONS: The 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.

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.

The relative associations of aortic and carotid artery stiffness with CeVD and cognition.

We examined the relative associations of aortic and carotid artery stiffness with cerebrovascular disease (CeVD), cognition, and dementia subtypes in a memory clinic cohort of 272 participants (mean age = 75.4, SD = 6.8). We hypothesized that carotid artery stiffness would have greater effects on outcomes, given its proximate relationship to the brain. Aortic and carotid artery stiffness were assessed with applanation tonometry and carotid ultrasonography, respectively. CeVD markers included white matter hyperintensities (WMH), lacunes, cerebral microbleeds, cortical infarcts, and intracranial stenosis. Cognition was assessed by the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and a neuropsychological battery. Multivariable linear regression was conducted to determine associations of arterial stiffness with WMH and cognition, while logistic regression analysed associations with CeVD markers and dementia subtypes. Carotid artery stiffness z-score was associated with WMH, cortical infarcts, vascular cognitive impairment, and MMSE, independent of age, sex, education, vascular risk factors, and aortic stiffness z-score. Although aortic stiffness z-score was independently associated with cortical infarcts, this became non-significant after further adjusting for carotid artery stiffness z-score. We found that carotid artery stiffness had greater effects on CeVD, cognitive function and impairment in memory clinic patients compared to aortic stiffness.

Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.

OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting incident dementia remains unclear. This study aims to assess the incremental value of five predictor domains when added to a simple dementia risk prediction model (DRPM) for predicting incident dementia in older adults. DESIGN: Population-based, prospective cohort study. SETTING: UK Biobank study. PARTICIPANTS: Individuals aged 60 or older without dementia. MEASUREMENTS: Fifty-five dementia-related predictors were gathered and categorized into clinical and medical history, questionnaire, cognition, polygenetic risk, and neuroimaging domains. Incident dementia (all-cause) and the subtypes, Alzheimer's disease (AD) and vascular dementia (VaD), were determined through hospital and death registries. Ensemble machine learning (ML) DRPMs were employed for prediction. The incremental values of risk predictors were assessed using the percent change in Area Under the Curve (∆AUC%) and the net reclassification index (NRI). RESULTS: The simple DRPM which included age, body mass index, sex, education, diabetes, hyperlipidaemia, hypertension, depression, smoking, and alcohol consumption yielded an AUC of 0.711 (± 0.008 SD). The five predictor domains exhibited varying levels of incremental value over the basic model when predicting all-cause dementia and the two subtypes. Neuroimaging markers provided the highest incremental value in predicting all-cause dementia (∆AUC% +9.6%) and AD (∆AUC% +16.5%) while clinical and medical history data performed the best at predicting VaD (∆AUC% +12.2%). Combining clinical and medical history, and questionnaire data synergistically enhanced ML DRPM performance. CONCLUSION: Combining predictors from different domains generally results in better predictive performance. Selecting predictors involves trade-offs, and while neuroimaging markers can significantly enhance predictive accuracy, they may pose challenges in terms of cost or accessibility.

A cross sectional study of role of technology in health for middle-aged and older adults in Singapore.

Telemedicine has gained popularity due to the increasing use of technology in our lives. However, no studies have explored the demographic factors affecting acceptability, desirability and adherence (ADA) to telemedicine in Singapore. Our study aims to evaluate the level of ADA of telemedicine services within demographic factors and to explore the association of potential demographic factors with the degree of acceptability, desirability and adherence of telemedicine among older adults in Singapore. A cross-sectional study was conducted with Singapore citizens or permanent residents aged 40-99 years, who were able to provide informed consent. Interviewers conducted door-to-door surveys in 67 Blocks of Housing & Development Board flats in Singapore, offering a self-administered electronic questionnaire available in four languages. Random sampling without replacement determined the order of blocks, floors and units visited. The questionnaire utilised Qtelemediab scoring and covered sociodemographic data, usage of telemedicine, as well as ADA towards telemedicine. A total of 324 valid responses were analysed. Increased age was associated with a significant decrease across all three domains of ADA namely acceptability (ß = - 0.02, 95%CI - 0.03; - 0.02, p-value = 0.002), desirability (ß = - 0.02, 95%CI - 0.02; - 0.02, p-value < 0.001) and adherence (ß = - 0.02, 95%CI - 0.03; - 0.0.02, p-value < 0.001). Additionally, lower education was associated with a decrease in all domains of ADA. Conversely, employment and increased household income were associated with higher ADA scores across all three domains. These associations were independent of gender, chronic health conditions and smoking history. Older participants with lower income and lesser education demonstrated lower levels of acceptability, desirability and adherence towards telemedicine. Our study highlights the importance of considering these factors in the implementation and promotion of telemedicine solutions.

Housing status is protective of neuropsychiatric symptoms among dementia-free multi-ethnic Asian elderly.

BACKGROUND: Housing has been associated with dementia risk and disability, but associations of housing with differential patterns of neuropsychiatric symptoms (NPS) among dementia-free older adults remain to be explored. The present study sought to explore the contribution of housing status on NPS and subsyndromes associated with cognitive dysfunction in community-dwelling dementia-free elderly in Singapore. METHODS: A total of 839 dementia-free elderly from the Epidemiology of Dementia in Singapore (EDIS) study aged ≥ 60 were enrolled in the current study. All participants underwent clinical, cognitive, and neuropsychiatric inventory (NPI) assessments. The housing status was divided into three categories according to housing type. Cognitive function was measured by a comprehensive neuropsychological battery. The NPS were assessed using 12-term NPI and were grouped into four clinical subsyndromes: psychosis, hyperactivity, affective, and apathy. Associations of housing with composite and domain-specific Z-scores, as well as NPI scores, were assessed using generalized linear models (GLM). Binary logistic regression models analysed the association of housing with the presence of NPS and significant NPS (NPI total scores ≥ 4). RESULTS: Better housing status (5-room executive apartments, condominium, or private housing) was associated with better NPS (OR = 0.49, 95%CI = 0.24 to 0.98, P < 0.05) and significant NPS profile (OR = 0.20, 95%CI = 0.08 to 0.46, P < 0.01), after controlling for demographics, risk factors, and cognitive performance. Compared with those living in 1-2 room apartments, older adults in better housing had lower total NPI scores (ß=-0.50, 95%CI=-0.95 to -0.04, P = 0.032) and lower psychosis scores (ß=-0.36, 95%CI=-0.66 to -0.05, P = 0.025), after controlling for socioeconomic status (SES) indexes. Subgroup analysis indicated a significant correlation between housing type and NPS in females, those of Malay ethnicity, the more educated, those with lower income, and those diagnosed with cognitive impairment, no dementia (CIND). CONCLUSIONS: Our study showed a protective effect of better housing arrangements on NPS, especially psychosis in a multi-ethnic Asian geriatric population without dementia. The protective effect of housing on NPS was independent of SES and might have other pathogenic mechanisms. Improving housing could be an effective way to prevent neuropsychiatric disturbance among the elderly.

Marital History and Cognition in a Chinese Longevity Cohort.

Background: Marital factor has been associated with dementia and Alzheimer's disease, but there is limited evidence on the impact of holistic marital history over time. Objective: This study aimed to examine association of marital history with cognition. Methods: The study included 24,596 dementia-free participants from the Chinese Longitudinal Healthy Longevity Study (CLHLS). Holistic marital history was collected at baseline, categorizing participants into five groups: widow-single, widow-remarried, divorce-single, divorce-remarried and married based on the first two marriages. Dementia was collected at follow-up through self-report or from a delegate if the participant was deceased. For 15,355 participants, the Chinese Mini-Mental Status Examination (CMMSE) was administered at both baseline and follow-ups. Cognitive impairment was defined as a follow-up CMMSE score below 18, and rate of cognitive change was calculated as the change in CMMSE score between consecutive visits divided by the duration. Results: Compared with married older adults, widow-single group had significantly higher risk of dementia (HR 1.28, 95% CI 1.05, 1.54), cognitive impairment (HR 1.31, 95% CI 1.17, 1.47) and significantly faster decline of MMSE score (ß -0.09, 95% CI -0.17, -0.01). Meanwhile, widow-remarried group had significantly lower risk of dementia, cognitive impairment and slower MMSE score decline than widow-single group, although the differences were only significant among female but not male. Conclusions: In this prospective cohort, married older adults and those widowed but with a second marriage had significantly better cognition than widowed individuals who did not remarry.

Association of a healthy ageing index with health-related outcomes in a multi-ethnic cohort from Singapore.

BACKGROUND: The global population is ageing rapidly and it is important to promote healthy ageing. The Healthy Ageing Index (HAI) is a comprehensive measure of health, but there is limited research on its association with other age-related outcomes. The management of an aging population necessitates considerations even among generally healthy adults, as age-related diseases often remain unaccounted for until later stages of life. This study explores the association of risk factors with HAI and its association with peripheral artery disease (PAD), muscle strength, health-related quality of life (HRQoL), and psychological distress in the Singapore Multi-Ethnic Cohort study. METHODS: This cross-sectional study involved 1909 participants (median (Q1, Q3) age: 53 (48, 60) years and 59.3% females) from Singapore Multi-Ethnic Cohort study. The risk factors of HAI included age, gender, ethnicity, education level, smoking, alcohol consumption, employment, BMI and past medical histories. PAD was assessed using ankle-brachial index (ABI), handgrip strength (HGS), HRQoL with the EQ-5D-5 L questionnaire and psychological distress via the Kessler Psychological Distress Scale (K10). HAI components were assessed using relevant marker tests. RESULTS: Older age, Malay and Indian ethnicities, unemployment, high BMI and histories of CHD, hypercholesterolaemia, tumours and TIA/stroke were associated with lower HAI scores indicative of poorer health. Higher HAI scores were associated with females and higher education levels. Lower HAI scores were significantly associated with low ABI, high K10 scores, mobility and anxiety/depression dimensions of EQ-5D-5 L. CONCLUSION: The most important factors associated with HAI were age, sex, ethnicity, education, unemployment, BMI and a history of health conditions. Lower HAI scores were significantly associated with PAD, lower HRQoL and psychological distress. Thus, the HAI demonstrates promise as an evaluation method for assessing PAD, overall muscle strength and HRQoL in a population-based setting.

Extracellular Vesicle-Enriched miRNA-Biomarkers Show Improved Utility for Detecting Alzheimer's Disease Dementia and Medial Temporal Atrophy.

Background: Emerging diagnostic modalities suggest that miRNA profiles within extracellular vesicles (EVs) isolated from peripheral blood specimens may provide a non-invasive diagnostic alternative for dementia and neurodegenerative disorders. Given that EVs confer a protective environment against miRNA enzymatic degradation, the miRNAs enriched in the EV fraction of blood samples could serve as more stable and clinically relevant biomarkers compared to those obtained from serum. Objective: To compare miRNAs isolated from EVs versus serum in blood taken from Alzheimer's disease (AD) dementia patients and control cohorts. Methods: We compared 25 AD patients to 34 individuals who exhibited no cognitive impairments (NCI). Subjects were Singapore residents with Chinese heritage. miRNAs purified from serum versus blood-derived EVs were analyzed for associations with AD dementia and medial temporal atrophy detected by magnetic resonance imaging. Results: Compared to serum-miRNAs, we identified almost twice as many EV-miRNAs associated with AD dementia, and they also correlated more significantly with medial temporal atrophy, a neuroimaging marker of AD-brain pathology. We further developed combination panels of serum-miRNAs and EV-miRNAs with improved performance in identifying AD dementia. Dominant in both panels was miRNA-1290. Conclusions: This data indicates that miRNA profiling from EVs offers diagnostic superiority. This underscores the role of EVs as vectors harboring prognostic biomarkers for neurodegenerative disorders and suggests their potential in yielding novel biomarkers for AD diagnosis.

Loss of white matter integrity mediates the association between cortical cerebral microinfarcts and cognitive dysfunction: A longitudinal study.

Cortical cerebral microinfarcts (CMIs) are associated with loss of white matter (WM) integrity and cognitive impairment in cross-sectional studies, while further investigation using longitudinal datasets is required. This study aims to establish the association between cortical CMIs and WM integrity assessed by diffusion-tensor imaging (DTI) measures and to investigate whether DTI measures mediate the relationship between cortical CMIs and cognitive decline. Cortical CMIs were graded on 3T MRI. DTI measures were derived from histogram analysis of mean diffusivity (MD) and fractional anisotropy (FA). Cognitive function was assessed using a neuropsychological test battery. Linear mixed-effect models were employed to examine associations of cortical CMIs with longitudinal changes in DTI measures and cognitive function. Final analysis included 231 patients (71.14 ± 7.60 years). Presence of cortical CMIs at baseline was associated with longitudinal changes in MD median and peak height and FA median and peak height, as well as global cognition (ß = -0.50, 95%CI: -0.91, -0.09) and executive function (ß = -0.77, 95%CI: -1.25, -0.28). MD median mediated the cross-sectional association between cortical CMIs and global cognition. Further studies are required to investigate whether cortical CMIs and loss of WM integrity are causally related or if they are parallel mechanisms that contribute to cognitive decline.

The AHA/ASA and DSM-V diagnostic criteria for vascular cognitive impairment identify cases with predominant vascular pathology.

BACKGROUND: There are major challenges in determining the etiology of vascular cognitive impairment (VCI) clinically, especially in the presence of mixed pathologies, such as vascular and amyloid. Most recently, two criteria (American Heart Association/American Stroke Association (AHA/ASA) and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V)) have been proposed for the clinical diagnosis of VCI but have not as yet been validated using neuroimaging. AIMS: This study aims to determine whether the AHA/ASA and DSM-V criteria for VCI can distinguish between cases with predominantly vascular pathology and cases with mixed pathology. METHODS: A total of 186 subjects were recruited from a cross-sectional memory clinic-based study at the National University Hospital, Singapore. All subjects underwent clinical and neuropsychological assessment, magnetic resonance imaging (MRI) and carbon 11-labeled Pittsburgh Compound B ([11C] PiB) positron emission tomography (PET) scans. Diagnosis of the etiological subtypes of VCI (probable vascular mild cognitive impairment (VaMCI), possible VaMCI, non-VaMCI, probable vascular dementia (VaD), possible VaD, non-VaD) were performed following AHA/ASA and DSM-V criteria. Brain amyloid burden was determined for each subject with standardized uptake value ratio (SUVR) values ⩾1.5 classified as amyloid positive. RESULTS: Using κ statistics, both criteria had excellent agreement for probable VaMCI, probable VaD, and possible VaD (κ = 1.00), and good for possible VaMCI (κ = 0.71). Using the AHA/ASA criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.7%), non-VaMCI (33.3%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). Similarly, using the DSM-V criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.3%), non-VaMCI (32.1%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). In both criteria, there was good agreement in differentiating individuals with non-VaD and possible VaD, with significantly higher (p < 0.001) global [11C]-PiB SUVR, from individuals with probable VaMCI and probable VaD, who had predominant vascular pathology. CONCLUSION: The AHA/ASA and DSM-V criteria for VCI can identify VCI cases with little to no concomitant amyloid pathology, hence supporting the utility of AHA/ASA and DSM-V criteria in diagnosing patients with predominant vascular pathology. DATA ACCESS STATEMENT: Data supporting this study are available from the Memory Aging and Cognition Center, National University of Singapore. Access to the data is subject to approval and a data sharing agreement due to University policy.

Association of plasma GFAP with elevated brain amyloid is dependent on severity of white matter lesions in an Asian cognitively impaired cohort.

INTRODUCTION: While elevated blood glial fibrillary acidic protein (GFAP) has been associated with brain amyloid pathology, whether this association occurs in populations with high cerebral small vessel disease (CSVD) concomitance remains unclear. METHODS: Using a Singapore-based cohort of cognitively impaired subjects, we assessed associations between plasma GFAP and neuroimaging measures of brain amyloid and CSVD, including white matter hyperintensities (WMH). We also examined the diagnostic performance of plasma GFAP in detecting brain amyloid beta positivity (Aß+). RESULTS: When stratified by WMH status, elevated brain amyloid was associated with higher plasma GFAP only in the WMH- group (ß = 0.383; P < 0.001). The diagnostic performance of plasma GFAP in identifying Aß+ was significantly higher in the WMH- group (area under the curve [AUC] = 0.896) than in the WMH+ group (AUC = 0.712, P = 0.008). DISCUSSION: The biomarker utility of plasma GFAP in detecting brain amyloid pathology is dependent on the severity of concomitant WMH. Highlight: Glial fibrillary acidic protein (GFAP)'s association with brain amyloid is unclear in populations with high cerebral small vessel disease (CSVD).Plasma GFAP was measured in a cohort with CSVD and brain amyloid.Plasma GFAP was better in detecting amyloid in patients with low CSVD versus high CSVD.Biomarker utility of GFAP in detecting brain amyloid depends on the severity of CSVD.

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients.

Introduction: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive 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. We propose that 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 this approach 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. Methods & results: 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 across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and 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 disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Conclusion: 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 effects, particularly in attentionrelated 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.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients.

INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-ß1-42 (Aß42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aß42 status in 11 memory clinic cohorts. Aß42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Association between Marital Status and Cognitive Impairment in a Multi-Ethnic Asian Population.

OBJECTIVE: This study aimed to examine the potential factors associated with marital status and determine the association between marital status and cognitive impairment in a multi-ethnic Asian population. METHOD: This study included 2,321 participants from Singapore Multi-Ethnic Cohort revisit study (aged 40-89). Participants were classified into married and unmarried group at baseline and follow-up according to self-reported marital status. Mini-Mental Status Examination (MMSE) was administered, and cognitive impairment was defined as a MMSE <26. We conducted both cross-sectional and longitudinal analyses to examine the association of marital status at 1 timepoint as well as marital transition with cognitive impairment. RESULTS: Of the 2,321 participants, a total of 1,914 (82.5%) were married. The factors associated with marital status included younger age, male sex, higher household income, higher education, and higher physical activity levels. Additionally, married participants also had higher alternative healthy eating index (AHEI-2010) scores and a lower burden of hypertension and diabetes. Among those who were married, the median (Q1, Q3) MMSE score was 29 (28, 30) while among those who were unmarried it was 29 (27, 30) (p < 0.01). Participants who had never been married had the highest odds of cognitive impairment compared to their married counterparts (model III: OR = 1.48, 95% CI: 1.03, 2.14). Older age (p interaction value = 0.003) and Indian ethnicity (p interaction value = 0.028) further strengthened these associations. CONCLUSION: Marriage was associated with lower odds of cognitive impairment. Marriage provides social support, companionship, and engagement in mentally stimulating activities contributing to better cognitive health. By identifying risk factors such as marital status, interventions and support systems can be developed to promote healthy cognitive aging.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Pathology-based brain arterial disease phenotypes and their radiographic correlates.

INTRODUCTION: Brain arterial diseases, including atherosclerosis, vasculitis, and dissections, are major contributors to cerebrovascular morbidity and mortality worldwide. These diseases not only increase the risk of stroke but also play a significant role in neurodegeneration and dementia. Clear and unambiguous terminology and classification of brain arterial disease phenotypes is crucial for research and clinical practice. MATERIAL AND METHODS: This review aims to summarize and harmonize the terminology used for brain large and small arterial phenotypes based on pathology studies and relate them to imaging phenotypes used in medical research and clinical practice. CONCLUSIONS AND RESULTS: Arteriosclerosis refers to hardening of the arteries but does not specify the underlying etiology. Specific terms such as atherosclerosis, calcification, or non-atherosclerotic fibroplasia are preferred. Atherosclerosis is defined pathologically by an atheroma. Other brain arterial pathologies occur and should be distinguished from atherosclerosis given therapeutic implications. On brain imaging, intracranial arterial luminal stenosis is usually attributed to atherosclerosis in the presence of atherosclerotic risk factors but advanced high-resolution arterial wall imaging has the potential to more accurately identify the underlying pathology. Regarding small vessel disease, arteriosclerosis is ambiguous and arteriolosclerosis is often used to denote the involvement of arterioles rather than arteries. Lipohyalinosis is sometimes used synonymously with arteriolosclerosis, but less accurately describes this common small vessel thickening which uncommonly shows lipid. Specific measures of small vessel wall thickness, the relationship to the lumen as well as changes in the layer composition might convey objective, measurable data regarding the status of brain small vessels.

The role of perfusion, grey matter volume and behavioural phenotypes in the data-driven classification of cognitive syndromes.

BACKGROUND: The use of structural and perfusion brain imaging in combination with behavioural information in the prediction of cognitive syndromes using a data-driven approach remains to be explored. Here, we thus examined the contribution of brain structural and perfusion imaging and behavioural features to the existing classification of cognitive syndromes using a data-driven approach. METHODS: Study participants belonged to the community-based Biomarker and Cognition Cohort Study in Singapore who underwent neuropsychological assessments, structural-functional MRI and blood biomarkers. Participants had a diagnosis of cognitively normal (CN), subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and dementia. Cross-sectional structural and cerebral perfusion imaging, behavioural scale data including mild behaviour impairment checklist, Pittsburgh Sleep Quality Index and Depression, Anxiety and Stress scale data were obtained. RESULTS: Three hundred seventy-three participants (mean age 60.7 years; 56% female sex) with complete data were included. Principal component analyses demonstrated that no single modality was informative for the classification of cognitive syndromes. However, multivariate glmnet analyses revealed a specific combination of frontal perfusion and temporo-frontal grey matter volume were key protective factors while the severity of mild behaviour impairment interest sub-domain and poor sleep quality were key at-risk factors contributing to the classification of CN, SCI, MCI and dementia (p < 0.0001). Moreover, the glmnet model showed best classification accuracy in differentiating between CN and MCI cognitive syndromes (AUC = 0.704; sensitivity = 0.698; specificity = 0.637). CONCLUSIONS: Brain structure, perfusion and behavioural features are important in the classification of cognitive syndromes and should be incorporated by clinicians and researchers. These findings illustrate the value of using multimodal data when examining syndrome severity and provide new insights into how cerebral perfusion and behavioural impairment influence classification of cognitive syndromes.

Blood-based biomarkers of cerebral small vessel disease.

Age-associated cerebral small vessel disease (CSVD) represents a clinically heterogenous condition, arising from diverse microvascular mechanisms. These lead to chronic cerebrovascular dysfunction and carry a substantial risk of subsequent stroke and vascular cognitive impairment in aging populations. Owing to advances in neuroimaging, in vivo visualization of cerebral vasculature abnormities and detection of CSVD, including lacunes, microinfarcts, microbleeds and white matter lesions, is now possible, but remains a resource-, skills- and time-intensive approach. As a result, there has been a recent proliferation of blood-based biomarker studies for CSVD aimed at developing accessible screening tools for early detection and risk stratification. However, a good understanding of the pathophysiological processes underpinning CSVD is needed to identify and assess clinically useful biomarkers. Here, we provide an overview of processes associated with CSVD pathogenesis, including endothelial injury and dysfunction, neuroinflammation, oxidative stress, perivascular neuronal damage as well as cardiovascular dysfunction. Then, we review clinical studies of the key biomolecules involved in the aforementioned processes. Lastly, we outline future trends and directions for CSVD biomarker discovery and clinical validation.