Visual Cognitive Assessment Test: Utility of the brief cognitive battery for early screening of cognitive impairment in Chongqing, China.

OBJECTIVES: Early detection of cognitive impairment is essential for timely intervention. Currently, most widely used cognitive screening tests are influenced by language and cultural differences; therefore, there is a need for the development of a language-neutral, visual-based cognitive assessment tool. The Visual Cognitive Assessment Test (VCAT), a 30-point test that assesses memory, executive function, visuospatial function, attention, and language, has demonstrated its utility in a multilingual population. In this study, we evaluated the reliability, validity, and diagnostic performance of the VCAT for screening early cognitive impairment in Chongqing, China METHODS: A total of 134 individuals (49 healthy controls (HCs), 52 with mild cognitive impairment (MCI), and 33 with mild dementia) completed the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), VCAT, and domain-specific neuropsychological assessments. The diagnostic performances of MMSE, MoCA, and VCAT were evaluated using the area under the curve (AUC), sensitivity, and specificity. Construct validity of the VCAT was assessed with well-established domain-specific cognitive assessments. Reliability was measured using Cronbach's alpha. RESULTS: The VCAT and its subdomains demonstrated both good construct validity and internal consistency (α = 0.577). The performance of VCAT was comparable to that of MoCA and MMSE in differentiating mild dementia from nondemented groups (AUC: 0.940 vs. 0.902 and 0.977, respectively; p = .098 and .053) and in distinguishing cognitive impairment (CI) from HC (AUC: 0.929 vs. 0.899 and 0.891, respectively; p = .239 and .161), adjusted for education level. The optimal score range for VCAT in determining dementia, MCI, and HC was 0-14, 15-19, and 20-30, respectively. CONCLUSION: The VCAT proves to be a reliable screening test for early cognitive impairment within our cohort. Being both language and cultural neutral, the VCAT has the potential to be utilized among a wider population within China.

Statin Therapy for Secondary Prevention in Ischemic Stroke Patients With Cerebral Microbleeds.

BACKGROUND AND OBJECTIVES: The association between statin use and the risk of intracranial hemorrhage (ICrH) following ischemic stroke (IS) or transient ischemic attack (TIA) in patients with cerebral microbleeds (CMBs) remains uncertain. This study investigated the risk of recurrent IS and ICrH in patients receiving statins based on the presence of CMBs. METHODS: We conducted a pooled analysis of individual patient data from the Microbleeds International Collaborative Network, comprising 32 hospital-based prospective studies fulfilling the following criteria: adult patients with IS or TIA, availability of appropriate baseline MRI for CMB quantification and distribution, registration of statin use after the index stroke, and collection of stroke event data during a follow-up period of ≥3 months. The primary endpoint was the occurrence of recurrent symptomatic stroke (IS or ICrH), while secondary endpoints included IS alone or ICrH alone. We calculated incidence rates and performed Cox regression analyses adjusting for age, sex, hypertension, atrial fibrillation, previous stroke, and use of antiplatelet or anticoagulant drugs to explore the association between statin use and stroke events during follow-up in patients with CMBs. RESULTS: In total, 16,373 patients were included (mean age 70.5 ± 12.8 years; 42.5% female). Among them, 10,812 received statins at discharge, and 4,668 had 1 or more CMBs. The median follow-up duration was 1.34 years (interquartile range: 0.32-2.44). In patients with CMBs, statin users were compared with nonusers. Compared with nonusers, statin therapy was associated with a reduced risk of any stroke (incidence rate [IR] 53 vs 79 per 1,000 patient-years, adjusted hazard ratio [aHR] 0.68 [95% CI 0.56-0.84]), a reduced risk of IS (IR 39 vs 65 per 1,000 patient-years, aHR 0.65 [95% CI 0.51-0.82]), and no association with the risk of ICrH (IR 11 vs 16 per 1,000 patient-years, aHR 0.73 [95% CI 0.46-1.15]). The results in aHR remained consistent when considering anatomical distribution and high burden (≥5) of CMBs. DISCUSSION: These observational data suggest that secondary stroke prevention with statins in patients with IS or TIA and CMBs is associated with a lower risk of any stroke or IS without an increased risk of ICrH. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients with IS or TIA and CMBs, statins lower the risk of any stroke or IS without increasing the risk of ICrH.

Lower serum uric acid and impairment of right cerebral hemisphere structural brain networks are related to depressive symptoms in cerebral small vessel disease: A cross-sectional study.

Cerebral small vessel disease (SVD) may be associated with an increased risk of depressive symptoms. Serum uric acid (SUA), an antioxidant, may be involved in the occurrence and development of depressive symptoms, but the mechanism remains unknown. Moreover, the relationship between structural brain networks and SUA has not been explored. This study examined the relationship between SUA and depressive symptoms in patients with SVD using graph theory analysis. We recruited 208 SVD inpatients and collected fasting blood samples upon admission. Depressive symptoms were assessed using the 24-item Hamilton Depression Rating Scale (HAMD-24). Magnetic resonance imaging was used to evaluate SVD, and diffusion tensor images were used to analyze structural brain networks using graph theory. Patients with depressive symptoms (n = 34, 25.76%) compared to those without (334.53 vs 381.28 µmol/L, p = 0.017) had lower SUA levels. Graph theoretical analyses showed a positive association of SUA with betweenness centrality, nodal efficiency, and clustering coefficients and a negative correlation with the shortest path length in SVD with depressive symptoms group. HAMD scores were significantly associated with nodal network metrics in the right cerebral hemisphere. Our findings suggested that lower SUA levels are significantly associated with disrupted structural brain networks in the right cerebral hemisphere of patients with SVD who have depressive symptoms.

Mild Behavioral Impairment and Cerebrovascular Profiles Are Associated with Early Cognitive Impairment in a Community-Based Southeast Asian Cohort.

Background: Mild behavioral impairment (MBI) is one of the earliest observable changes when a person experiences cognitive decline and could be an early manifestation of underlying Alzheimer's disease neuropathology. Limited attention has been given to investigating the clinical applicability of behavioral biomarkers for detection of prodromal dementia. Objective: This study compared the prevalence of self-reported MBI and vascular risk factors in Southeast Asian adults to identify early indicators of cognitive impairment and dementia. Methods: This cohort study utilized baseline data from the Biomarkers and Cognition Study, Singapore (BIOCIS). 607 participants were recruited and classified into three groups: cognitively normal (CN), subjective cognitive decline (SCD), and mild cognitive impairment (MCI). Group comparisons of cognitive-behavioral, neuroimaging, and blood biomarkers data were applied using univariate analyses. Multivariate logistic regression analyses were conducted to investigate the association between cerebrovascular disease, vascular profiles, and cognitive impairment. Results: SCD had significantly higher depression scores and poorer quality of life (QOL) compared to CN. MCI had significantly higher depression scores; total MBI symptoms, MBI-interest, MBI-mood, and MBI-beliefs; poorer sleep quality; and poorer QOL compared to CN. Higher Staals scores, glucose levels, and systolic blood pressure were significantly associated with MCI classification. Fasting glucose levels were significantly correlated with depression, anxiety, MBI-social, and poorer sleep quality. Conclusions: The results reflect current research that behavioral changes are among the first symptoms noticeable to the person themselves as they begin to experience cognitive decline. Self-reported questionnaires may aid in early diagnoses of prodromal dementia. Behavioral changes and diabetes could be potential targets for preventative healthcare for dementia.

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.

Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment.

BACKGROUND: Continuous assessment and remote monitoring of cognitive function in individuals with mild cognitive impairment (MCI) enables tracking therapeutic effects and modifying treatment to achieve better clinical outcomes. While standardized neuropsychological tests are inconvenient for this purpose, wearable sensor technology collecting physiological and behavioral data looks promising to provide proxy measures of cognitive function. The objective of this study was to evaluate the predictive ability of digital physiological features, based on sensor data from wrist-worn wearables, in determining neuropsychological test scores in individuals with MCI. METHODS: We used the dataset collected from a 10-week single-arm clinical trial in older adults (50-70 years old) diagnosed with amnestic MCI (N = 30) who received a digitally delivered multidomain therapeutic intervention. Cognitive performance was assessed before and after the intervention using the Neuropsychological Test Battery (NTB) from which composite scores were calculated (executive function, processing speed, immediate memory, delayed memory and global cognition). The Empatica E4, a wrist-wearable medical-grade device, was used to collect physiological data including blood volume pulse, electrodermal activity, and skin temperature. We processed sensors' data and extracted a range of physiological features. We used interpolated NTB scores for 10-day intervals to test predictability of scores over short periods and to leverage the maximum of wearable data available. In addition, we used individually centered data which represents deviations from personal baselines. Supervised machine learning was used to train models predicting NTB scores from digital physiological features and demographics. Performance was evaluated using "leave-one-subject-out" and "leave-one-interval-out" cross-validation. RESULTS: The final sample included 96 aggregated data intervals from 17 individuals. In total, 106 digital physiological features were extracted. We found that physiological features, especially measures of heart rate variability, correlated most strongly to the executive function compared to other cognitive composites. The model predicted the actual executive function scores with correlation r = 0.69 and intra-individual changes in executive function scores with r = 0.61. CONCLUSIONS: Our findings demonstrated that wearable-based physiological measures, primarily HRV, have potential to be used for the continuous assessments of cognitive function in individuals with MCI.

Association of physical activity with dementia and cognitive decline in UK Biobank.

INTRODUCTION: There is a lack of studies on the association between specific physical activity (PA) types and dementia. We examined the association of leisure time physical activity (LTPA), occupational physical activity (OPA), and sedentary lifestyle with dementia risk and cognitive decline using the UK-Biobank study. METHODS: Baseline PA was collected using questionnaires. A total of 502,481 dementia-free participants were recruited in 2006-2010 and followed for 10 years until the end of 2020 for the ascertainment of dementia. Associations of PA with incident dementia and cognitive decline were examined. RESULTS: Higher levels of LTPA and OPA and lower levels of sedentary hours were associated with lower dementia risk. The fifth quintiles of LTPA (hazard ratio [HR] = 0.53, 95% confidence interval [CI]: 0.43-0.67) and OPA (HR = 0.68, 95% CI:0.51-0.90) had lower dementia risk, whereas the fifth quintile of sedentary lifestyle had higher dementia risk (HR = 1.23, 95% CI:1.08-1.41). DISCUSSION: Our findings suggest the promotion of an active lifestyle suggested to be preventive of dementia risk. This research has been conducted using the UK Biobank Resource under Application Number 71022.

APOE4 carrier status determines association between white matter disease and grey matter atrophy in early-stage dementia.

BACKGROUND: White matter hyperintensities, a neuroimaging marker of small-vessel cerebrovascular disease and apolipoprotein ε4 (APOE4) allele, are important dementia risk factors. However, APOE4 as a key effect modifier in the relationship between white matter hyperintensities and grey matter volume needs further exploration. METHODS: One hundred ninety-two early-stage dementia (including mild cognitive impairment and mild dementia) and 259 cognitively unimpaired participants from a neurocognitive research cohort with neuroimaging data, APOE genotyping, and neuropsychological assessments were studied. We investigated independent and interactive effects of white matter hyperintensities and APOE4 on whole-brain voxel-wise grey matter volume using voxel-based morphometry (uncorrected p < 0.001; minimum cluster size = 100 voxels). We further assessed interactive effects between APOE4 and white matter hyperintensities on global cognition, memory, and executive function in early-stage dementia and cognitively unimpaired participants. RESULTS: Independent of APOE4 status, higher white matter hyperintensity load was associated with greater grey matter atrophy across frontal, parietal, temporal, and occipital lobes in cognitively unimpaired and early-stage dementia subjects. However, interaction analyses and independent sample analyses revealed that APOE4 non-carriers demonstrated greater white matter hyperintensity-associated grey matter atrophy compared to APOE4 carriers in both cognitively unimpaired and early-stage dementia groups. Additional confirmatory analyses among APOE4 non-carriers demonstrated that white matter hyperintensities resulted in widespread grey matter loss. Analyses of cognitive function demonstrated that higher white matter hyperintensity load was associated with worse global (Mini-Mental State Examination, Montreal Cognitive Assessment) and executive function (Color Trails 2) in APOE4 non-carriers compared to APOE4 carriers in early-stage dementia but not cognitively unimpaired participants. CONCLUSIONS: The association between white matter hyperintensities and grey matter loss is more pronounced in APOE4 non-carriers than APOE4 carriers in the cognitively unimpaired and early-stage dementia stages. Furthermore, white matter hyperintensity presence results in poorer executive function in APOE4 non-carriers compared to APOE4 carriers. This finding may have significant impact on the design of clinical trials with disease modifying therapies.

Short-term Trajectories of Poststroke Cognitive Function: A STROKOG Collaboration Study.

BACKGROUND AND OBJECTIVES: Past studies on poststroke cognitive function have focused on the average performance or change over time, but few have investigated patterns of cognitive trajectories after stroke. This project used latent class growth analysis (LCGA) to identify clusters of patients with similar patterns of cognition scores over the first-year poststroke and the extent to which long-term cognitive outcome is predicted by the clusters ("trajectory groups"). METHODS: Data were sought from the Stroke and Cognition consortium. LCGA was used to identify clusters of trajectories based on standardized global cognition scores at baseline (T1) and at the 1-year follow-up (T2). One-step individual participant data meta-analysis was used to examine risk factors for trajectory groups and association of trajectory groups with cognition at the long-term follow-up (T3). RESULTS: Nine hospital-based stroke cohorts with 1,149 patients (63% male; mean age 66.4 years [SD 11.0]) were included. The median time assessed at T1 was 3.6 months poststroke, 1.0 year at T2, and 3.2 years at T3. LCGA identified 3 trajectory groups, which were characterized by different mean levels of cognition scores at T1 (low-performance, -3.27 SD [0.94], 17%; medium-performance, -1.23 SD [0.68], 48%; and high-performance, 0.71 SD [0.77], 35%). There was significant improvement in cognition for the high-performance group (0.22 SD per year, 95% CI 0.07-0.36), but changes for the low-performance and medium-performance groups were not significant (-0.10 SD per year, 95% CI -0.33 to 0.13; 0.11 SD per year, 95% CI -0.08 to 0.24, respectively). Factors associated with the low- (vs high-) performance group include age (relative risk ratio [RRR] 1.18, 95% CI 1.14-1.23), years of education (RRR 0.61, 95% CI 0.56-0.67), diabetes (RRR 3.78, 95% CI 2.08-6.88), large artery vs small vessel strokes (RRR 2.77, 95% CI 1.32-5.83), and moderate/severe strokes (RRR 3.17, 95% CI 1.42-7.08). Trajectory groups were predictive of global cognition at T3, but its predictive power was comparable with scores at T1. DISCUSSION: The trajectory of cognitive function over the first-year poststroke is heterogenous. Baseline cognitive function ∼3.6 months poststroke is a good predictor of long-term cognitive outcome. Older age, lower levels of education, diabetes, large artery strokes, and greater stroke severity are risk factors for lower cognitive performance over the first year.

Usefulness of the Visual Cognitive Assessment Test in Detecting Mild Cognitive Impairment in the Community.

BACKGROUND: A delay in the detection of mild cognitive impairment (MCI) in the community delays the opportunity for early intervention. Accurate tools to detect MCI in the community are lacking. The Visual Cognitive Assessment Test (VCAT) is a visual based cognitive test useful for multilingual populations without the need for translation. OBJECTIVE: Here, we evaluate the usefulness of VCAT in detecting MCI in a community population in Singapore. METHODS: We recruited 301 participants from the community who completed a detailed neuropsychological assessment and 170 of them completed a 3T magnetic resonance imaging (MRI) brain scan. We performed a receiver operating characteristics analysis to test the diagnostic performance of VCAT compared to Montreal Cognitive Assessment (MoCA) in distinguishing MCI from cognitively normal (CN) by measuring area under the curve (AUC). To test for the association of VCAT with structural MRI, we performed a Pearson's correlation analysis for VCAT and MRI variables. RESULTS: We recruited 39 CN and 262 MCI participants from Dementia Research Centre (Singapore). Mean age of the cohort was 63.64, SD = 9.38, mean education years was 13.59, SD = 3.70 and majority were women (55.8%). VCAT was effective in detecting MCI from CN with an AUC of 0.794 (95% CI 0.723-0.865) which was slightly higher than MoCA 0.699 (95% CI 0.621-0.777). Among subjects with MCI, VCAT was associated with medial temporal lobe atrophy (ρ = -0.265, p = 0.001). CONCLUSIONS: The VCAT is useful in detecting MCI in the community in Singapore and may be an effective measure of neurodegeneration.

Corrigendum: Topology of diffusion changes in corpus callosum in Alzheimer's disease: An exploratory case-control study.

[This corrects the article DOI: 10.3389/fneur.2022.1005406.].

C9orf72 expansions are the most common cause of genetic frontotemporal dementia in a Southeast Asian cohort.

OBJECTIVE: Frontotemporal dementia (FTD) encompasses a spectrum of neurodegenerative disorders, including behavioural variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA) and non-fluent variant PPA (nfvPPA). While a strong genetic component is implicated in FTD, genetic FTD in Asia is less frequently reported. We aimed to investigate the frequency of Southeast Asian FTD patients harbouring known genetic FTD variants. METHODS: A total of 60 FTD-spectrum patients (25 familial and 35 sporadic) from Singapore and the Philippines were included. All underwent next-generation sequencing and repeat-primed PCR for C9orf72 expansion testing. Neurofilament light chain (NfL) levels were measured in a subset of patients. RESULTS: Overall, 26.6% (16/60 cases) carried pathogenic or likely pathogenic variants in a FTD-related gene, including: MAPT Gln351Arg (n = 1); GRN Cys92Ter (n = 1), Ser301Ter (n = 2), c.462 + 1G > C (n = 1); C9orf72 expansion (35-70 repeats; n = 8); TREM2 Arg47Cys (n = 1); and OPTN frameshift insertion (n = 2). Genetic mutations accounted for 48% (12/25) of patients with familial FTD, and 11.4% (4/35) of patients with sporadic FTD. C9orf72 repeat expansions were the most common genetic mutation (13.3%, 8/60), followed by GRN (6.7%, 4/60) variants. Within mutation carriers, plasma NfL was highest in a C9orf72 expansion carrier, and CSF NfL was highest in a GRN splice variant carrier. INTERPRETATION: In our cohort, genetic mutations are present in one-quarter of FTD-spectrum cases, and up to half of those with family history. Our findings highlight the importance of wider implementation of genetic testing in FTD patients from Southeast Asia.

Plasma Soluble ST2 Levels Are Higher in Neurodegenerative Disorders and Associated with Poorer Cognition.

BACKGROUND: Suppressor of tumorgenicity 2 (ST2) is highly expressed in brain tissue and is a receptor for interleukin 33 (IL-33). ST2 exists in two forms, a transmembrane receptor (ST2L) and a soluble decoy receptor (sST2). IL-33 binds to ST2L, triggering downstream signaling pathways involved in amyloid plaque clearance. Conversely, sST2 binds competitively to IL-33, attenuating its neuroprotective effects. High sST2 levels have been reported in mild cognitive impairment (MCI) and Alzheimer's disease (AD), suggesting that the IL-33/ST2 signaling pathway may be implicated in neurodegenerative diseases. OBJECTIVE: To investigate plasma sST2 levels in controls and patients with MCI, AD, frontotemporal dementia (FTD), and Parkinson's disease (PD). METHODS: Plasma sST2 levels were measured using ELISA in 397 subjects (91 HC, 46 MCI, 38 AD, 28 FTD, and 194 PD). Cerebrospinal fluid (CSF) levels of sST2 were measured in 22 subjects. Relationship between sST2 and clinical outcomes were analyzed. RESULTS: Plasma sST2 levels were increased across all disease groups compared to controls, with highest levels seen in FTD followed by AD and PD. Dementia patients with higher sST2 had lower cross-sectional cognitive scores in Frontal Assessment Battery and Digit Span Backward. At baseline, PD-MCI patients had higher sST2, associated with worse attention. In the longitudinal PD cohort, higher sST2 significantly associated with decline in global cognition and visuospatial domains. Plasma sST2 levels correlated with CSF sST2 levels. CONCLUSION: Plasma sST2 is raised across neurodegenerative diseases and is associated with poorer cognition. Higher baseline sST2 is a potential biomarker of disease severity in neurodegeneration.

BACE2: A Promising Neuroprotective Candidate for Alzheimer's Disease.

Alzheimer's disease (AD) is the most common cause of dementia that affects millions of predominantly elderly individuals worldwide. Despite intensive research over several decades, controversies still surround the etiology of AD and the disease remains incurable. Meanwhile, new molecular players of the central amyloid cascade hypothesis have emerged and among these is a protease known as ß-site APP cleavage enzyme 2 (BACE2). Unlike BACE1, BACE2 cleaves the amyloid-ß protein precursor within the Aß domain that accordingly prevents the generation of Aß42 peptides, the aggregation of which is commonly regarded as the toxic entity that drives neurodegeneration in AD. Given this non-amyloidogenic role of BACE2, it is attractive to position BACE2 as a therapeutic target for AD. Indeed, several groups including ours have demonstrated a neuroprotective role for BACE2 in AD. In this review, we discuss emerging evidence supporting the ability of BACE2 in mitigating AD-associated pathology in various experimental systems including human pluripotent stem cell-derived cerebral organoid disease models. Alongside this, we also provide an update on the identification of single nucleotide polymorphisms occurring in the BACE2 gene that are linked to increased risk and earlier disease onset in the general population. In particular, we highlight a recently identified point mutation on BACE2 that apparently leads to sporadic early-onset AD. We believe that a better understanding of the role of BACE2 in AD would provide new insights for the development of viable therapeutic strategies for individuals with dementia.

Topology of diffusion changes in corpus callosum in Alzheimer's disease: An exploratory case-control study.

Aim: This study aims to assess the integrity of white matter in various segments of the corpus callosum in Alzheimer's disease (AD) by using metrics derived from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI) and white matter tract integrity model (WMTI) and compare these findings to healthy controls (HC). Methods: The study was approved by the institutional ethics board. 12 AD patients and 12 HC formed the study population. All AD patients were recruited from a tertiary neurology memory clinic. A standardized battery of neuropsychological assessments was administered to the study participants by a trained rater. MRI scans were performed with a Philips Ingenia 3.0T scanner equipped with a 32-channel head coil. The protocol included a T1-weighted sequence, FLAIR and a dMRI acquisition. The dMRI scan included a total of 71 volumes, 8 at b = 0 s/mm2, 15 at b = 1,000 s/mm2 and 48 at b = 2,000 s/mm2. Diffusion data fit was performed using DKI REKINDLE and WMTI models. Results and discussion: We detected changes suggesting demyelination and axonal degeneration throughout the corpus callosum of patients with AD, most prominent in the mid-anterior and mid-posterior segments of CC. Axial kurtosis was the most significantly altered metric, being reduced in AD patients in almost all segments of corpus callosum. Reduced axial kurtosis in the CC segments correlated with poor cognition scores in AD patients in the visuospatial, language and attention domains.

Amyloid-Tau-Neurodegeneration Profiles and Longitudinal Cognition in Sporadic Young-Onset Dementia.

We examined amyloid-tau-neurodegeneration biomarker effects on cognition in a Southeast-Asian cohort of 84 sporadic young-onset dementia (YOD; age-at-onset <65 years) patients. They were stratified into A+N+, A- N+, and A- N- profiles via cerebrospinal fluid amyloid-ß1-42 (A), phosphorylated-tau (T), MRI medial temporal atrophy (neurodegeneration- N), and confluent white matter hyperintensities cerebrovascular disease (CVD). A, T, and CVD effects on longitudinal Mini-Mental State Examination (MMSE) were evaluated. A+N+ patients demonstrated steeper MMSE decline than A- N+ (ß = 1.53; p = 0.036; CI 0.15:2.92) and A- N- (ß = 4.68; p = 0.001; CI 1.98:7.38) over a mean follow-up of 1.24 years. Within A- N+, T- CVD+ patients showed greater MMSE decline compared to T+CVD- patients (ß = - 2.37; p = 0.030; CI - 4.41:- 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A- sub-group.

Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum.

Background: Large-scale neuronal network breakdown underlies memory impairment in Alzheimer's disease (AD). However, the differential trajectories of the relationships between network organisation and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods: Seven hundred and eight participants from the Alzheimer's Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F] fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. Results: We showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode metabolic network on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. Conclusions: Our findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage. Funding: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). We also acknowledge the funding support from the Duke NUS/Khoo Bridge Funding Award (KBrFA/2019-0020) and NMRC Open Fund Large Collaborative Grant (OFLCG09May0035).

Correlation Between Plasma Oligomeric Amyloid-ß and Performance on the Language Neutral Visual Cognitive Assessment Test in a Southeast Asian Population.

Oligomeric amyloid-ß (OAß), an upstream driver of Alzheimer's disease (AD) neuropathology, correlates with poor cognitive performance and brain volume reduction. Its effect on cognitive performance measured by the language neutral Visual Cognitive Assessment Test (VCAT) remains to be evaluated. We studied the correlation of plasma OAß with VCAT scores and grey matter volume (GMV) in a Southeast Asian cohort with mild cognitive impairment. Higher plasma OAß significantly correlated with lower; cognitive scores (VCAT, Mini-Mental State Examination) and GMV/intracranial volume ratio. Such findings reveal the clinical utility of plasma OAß as a promising biomarker and support validation through longitudinal studies.