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.

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

BACKGROUND: There are major challenges in determining the aetiology 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: 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, MRI and [11C] PiB 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 standardised 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%) were 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. CONCLUSIONS: 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.

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.

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.

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

OBJECTIVE: This study aims 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 2321 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 one time point as well as marital transition with cognitive impairment. RESULTS: Of the 2321 participants, a total of 1914 (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 those who were unmarried 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.

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.

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.

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.

Serum Brevican as a Biomarker of Cerebrovascular Disease in an Elderly Cognitively Impaired Cohort.

In the brain, the extracellular matrix (ECM) composition shapes the neuronal microenvironment and can undergo substantial changes with cerebral pathology. Brevican is integral to the formation of the ECM's neuroprotective perineuronal nets (PNNs). Decreased brevican levels were reported in vascular dementia (VaD) but not in Alzheimer's disease (AD). However, the status of brevican in clinical cohorts with high concomitance of AD pathological burden and cerebrovascular disease (CeVD) is unclear. In this study, 32 non-cognitively impaired (NCI), 97 cognitively impaired no dementia (CIND), 46 AD, and 23 VaD participants recruited from memory clinics based in Singapore underwent neuropsychological and neuroimaging assessments, together with measurements of serum brevican. Association analyses were performed between serum brevican and neuroimaging measures of CeVDs, including white matter hyperintensities (WMHs), lacunes, cortical infarcts, and cerebral microbleeds. Using an aggregated score for CeVD burden, only CIND participants showed lower brevican levels with higher CeVD compared to those with lower CeVD burden (p = 0.006). Among the CeVD subtypes assessed, only elevated WMH burden was associated with lower brevican levels (OR = 2.7; 95% CI = 1.3-5.5). Our findings suggest that brevican deficits may play a role in early cerebrovascular damage in participants at risk of developing dementia.

Association of diet quality with hand grip strength weakness and asymmetry in a multi-ethnic Asian cohort.

Hand grip strength (HGS) is an important diagnostic tool for sarcopenia and a reliable predictor for age-related chronic diseases and mortality. Interventions in nutrition have been shown as a low-cost strategy to maintain muscular strength and mass. However, there are limited data on the effect of diet on HGS in Southeast Asian populations. This study aims to investigate the association of diet quality with HGS weakness and asymmetry in a multi-ethnic population in Singapore. This cross-sectional study used data from the Singapore Multi-Ethnic Cohort (n = 1547). Dietary data were collected using a validated semi-quantitative FFQ and summarised as the Dietary Quality Index - International (DQI-I). HGS was calculated as the maximum value of six measurements from both hands. HGS weakness and asymmetry were defined using well-recognised criteria. Multivariable linear regression and logistic regression were utilised for continuous and binary outcomes, respectively, adjusting for age, sex, ethnicity, physical activity and smoking status. It was found that the highest quartile of DQI-I was significantly associated with higher HGS (ß = 1·11; 95 % CI 0·41, 1·82; Pfor trend < 0·001) and lower odds of HGS asymmetry (OR = 0·71; 95 % CI 0·53, 0·94; Pfor trend = 0·035) and both HGS weakness and asymmetry (OR = 0·50; 95 % CI 0·32, 0·76; Pfor trend = 0·004). Among the different components of DQI-I, only dietary adequacy was significantly associated with higher HGS (Pfor trend < 0·001) and lower odds for both HGS weakness and asymmetry (Pfor trend = 0·006). Our findings support that DQI-I, an indicator of overall diet quality, can be used to provide dietary guidelines for prevention and management of muscle wasting, sarcopenia and frailty.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS: We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS: CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION: These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS: Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Cerebral microinfarcts revisited: Detection, causes, and clinical relevance.

Cerebral microinfarcts (CMIs) are small ischemic lesions invisible to the naked eye at brain autopsy, while the larger ones (0.5-4 mm in diameter) have been visualized in-vivo on magnetic resonance imaging (MRI). CMIs can be detected on diffusion-weighted imaging (DWI) as incidental small DWI-positive lesions (ISDPLs) and on structural MRI for those confined to the cortex and in the chronic phase. ISDPLs may evolve into old cortical-CMIs, white matter hyperintensities or disappear depending on their location and size. Novel techniques in neuropathology and neuroimaging facilitate the detection of CMIs, which promotes understanding of these lesions. CMIs have heterogeneous causes, involving both cerebral small- and large-vessel disease as well as heart diseases such as atrial fibrillation and congestive heart failure. The underlying mechanisms incorporate vascular remodeling, inflammation, blood-brain barrier leakage, penetrating venule congestion, cerebral hypoperfusion, and microembolism. CMIs lead to clinical outcomes, including cognitive decline, a higher risk of stroke and mortality, and accelerated neurobehavioral disturbances. It has been suggested that CMIs can impair brain function and connectivity beyond the microinfarct core and are also associated with perilesional and global cortical atrophy. This review aims to summarize recent progress in studies involving both cortical-CMIs and ISDPLs since 2017, including their detection, etiology, risk factors, MRI correlates, and clinical consequences.

Chromosome 10q24.32 Variants Associate With Brain Arterial Diameters in Diverse Populations: A Genome-Wide Association Study.

BACKGROUND: Brain arterial diameters (BADs) are novel imaging biomarkers of cerebrovascular disease, cognitive decline, and dementia. Traditional vascular risk factors have been associated with BADs, but whether there may be genetic determinants of BADs is unknown. METHODS AND RESULTS: The authors studied 4150 participants from 6 geographically diverse population-based cohorts (40% European, 14% African, 22% Hispanic, 24% Asian ancestries). Brain arterial diameters for 13 segments were measured and averaged to obtain a global measure of BADs as well as the posterior and anterior circulations. A genome-wide association study revealed 14 variants at one locus associated with global BAD at genome-wide significance (P<5×10-8) (top single-nucleotide polymorphism, rs7921574; ß=0.06 [P=1.54×10-8]). This locus mapped to an intron of CNNM2. A trans-ancestry genome-wide association study meta-analysis identified 2 more loci at NT5C2 (rs10748839; P=2.54×10-8) and AS3MT (rs10786721; P=4.97×10-8), associated with global BAD. In addition, 2 single-nucleotide polymorphisms colocalized with expression of CNNM2 (rs7897654; ß=0.12 [P=6.17×10-7]) and AL356608.1 (rs10786719; ß=-0.17 [P=6.60×10-6]) in brain tissue. For the posterior BAD, 2 variants at one locus mapped to an intron of TCF25 were identified (top single-nucleotide polymorphism, rs35994878; ß=0.11 [P=2.94×10-8]). For the anterior BAD, one locus at ADAP1 was identified in trans-ancestry genome-wide association analysis (rs34217249; P=3.11×10-8). CONCLUSIONS: The current study reveals 3 novel risk loci (CNNM2, NT5C2, and AS3MT) associated with BADs. These findings may help elucidate the mechanism by which BADs may influence cerebrovascular health.

Lipidomics profiling reveals distinct patterns of plasma sphingolipid alterations in Alzheimer's disease and vascular dementia.

BACKGROUND: Alzheimer's disease (AD) and vascular dementia (VaD) are two of the commonest causes of dementia in the elderly. Of the myriad biomolecules implicated in dementia pathogenesis, sphingolipids have attracted relatively scant research attention despite their known involvement in multiple pathophysiological processes. The potential utility of peripheral sphingolipids as biomarkers in dementia cohorts with high concomitance of cerebrovascular diseases is also unclear. METHODS: Using a lipidomics platform, we performed a case-control study of plasma sphingolipids in a prospectively assessed cohort of 526 participants (non-cognitively impaired, NCI = 93, cognitively impaired = 217, AD = 166, VaD = 50) using a lipidomics platform. RESULTS: Distinct patterns of sphingolipid alterations were found in AD and VaD, namely an upregulation of d18:1 species in AD compared to downregulation of d16:1 species in VaD. In particular, GM3 d18:1/16:0 and GM3 d18:1/24:1 showed the strongest positive associations with AD. Furthermore, evaluation of sphingolipids panels showed specific combinations with higher sensitivity and specificity for classification of AD (Cer d16:1/24:0. Cer d18:1/16:0, GM3 d16:1/22:0, GM3 d18:1/16:0, SM d16:1/22:0, HexCer d18:1/18:0) and VAD (Cer d16:1/24:0, Cer d18:1/16:0, Hex2Cer d16:1/16:0, HexCer d18:1/18:0, SM d16:1/16:0, SM d16:1/20:0, SM d18:2/22:0) compared to NCI. CONCLUSIONS: AD and VaD are associated with distinct changes of plasma sphingolipids, warranting further studies into underlying pathophysiological mechanisms and assessments of their potential utility as dementia biomarkers and therapeutic targets.

Association of brain arterial diameters with demographic and anatomical factors in a multi-national pooled analysis of cohort studies.

BACKGROUND AND PURPOSE: Brain arterial diameters are markers of cerebrovascular disease. Demographic and anatomical factors may influence arterial diameters. We hypothesize that age, sex, height, total cranial volume (TCV), and persistent fetal posterior cerebral artery (fPCA) correlate with brain arterial diameters across populations. METHODS: Participants had a time-of-flight MRA from nine international cohorts. Arterial diameters of the cavernous internal carotid arteries (ICA), middle cerebral arteries (MCA), and basilar artery (BA) were measured using LAVA software. Regression models assessed the association between exposures and brain arterial diameters. RESULTS: We included 6,518 participants (mean age: 70 ± 9 years; 41% men). Unilateral fPCA was present in 13.2% and bilateral in 3.2%. Larger ICA, MCA, and BA diameters correlated with older age (Weighted average [WA] per 10 years: 0.18 mm, 0.11 mm, and 0.12 mm), male sex (WA: 0.24 mm, 0.13 mm, and 0.21 mm), and TCV (WA: for one TCV standard deviation: 0.24 mm, 0.29 mm, and 0.18 mm). Unilateral and bilateral fPCAs showed a positive correlation with ICA diameters (WA: 0.39 mm and 0.73 mm) and negative correlation with BA diameters (WA: -0.88 mm and -1.73 mm). Regression models including age, sex, TCV, and fPCA explained on average 15%, 13%, and 25% of the ICA, MCA, and BA diameter interindividual variation, respectively. Using height instead of TCV as a surrogate of head size decreased the R-squared by 3% on average. CONCLUSION: Brain arterial diameters correlated with age, sex, TCV, and fPCA. These factors should be considered when defining abnormal diameter cutoffs across populations.

Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts.

INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Cost-benefit and discriminant validity of a stepwise dementia case-finding approach in an Asian older adult community.

Background: Case-finding is a recommended approach for dementia early detection in the community. Aims: To investigate the discriminant validity and cost-effectiveness of a stepwise dementia case-finding approach in a Singaporean older adult community. Methods: The two-phase study was conducted in the community from 2009 to 2015 in Singapore. A total of 3780 participants (age ≥60 years) completed phase I (a brief cognitive screening); 918 completed phase II and were included in the final analysis. In phase I, all participants were administered the Abbreviated Mental Test (AMT) and the Progressive Forgetfulness Question (PFQ). Those who screened positive on either test were invited to phase II, whereby the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and a formal neuropsychological battery were administered, followed by the research diagnosis of no cognitive impairment, cognitive impairment no dementia (CIND)-Mild (≤2 impaired cognitive domains), CIND-Moderate (>2 impaired domains) or dementia. Receiver operating characteristic curve analyses were conducted for the different cognitive instruments. All discriminant indices were calculated, including sensitivity, specificity, positive and negative predictive values (NPV) and accuracy. Cost-effectiveness analysis was conducted by estimating the amount of screening time needed and the number of older adults requiring re-evaluation in two case-finding scenarios, ie, with or without preselection by the PFQ. Results: The stepwise case-finding approach (preselection by the PFQ, then MMSE or MoCA or AMT) showed an excellent NPV (>99%) and accuracy (>86%) for excluding dementia-free cases. Without preselection by the PFQ, screening time for the three cognitive tools were 317.5, 317.5 and 254 hours, with 159, 302 and 175 screen-positive older adults involved in further evaluation. By adopting the stepwise case-finding approach, total screening time were 156.5, 156.5 and 126.2 hours, which decreased by 50.7%, 50.7% and 50.3% as compared with those without preselection. Furthermore, after preselection, only 98, 167 and 145 screen-positive older adults required further evaluation, corresponding to a reduction of 38.4%, 44.7% and 17.1% in the numbers compared with those without preselection. Conclusions: A stepwise approach for dementia case-finding should be implemented in the community to minimise the time and resources needed for large-scale early detection of dementia.