ABSTRACT
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable devices collecting physiological and behavioral data can help in remote, passive, and continuous monitoring of moods and NPS, overcoming limitations and inconveniences of current assessment methods. In this longitudinal study, we examined the predictive ability of digital biomarkers based on sensor data from a wrist-worn wearable to determine the severity of NPS and mood disorders on a daily basis in older adults with predominant MCI. In addition to conventional physiological biomarkers, such as heart rate variability and skin conductance levels, we leveraged deep-learning features derived from physiological data using a self-supervised convolutional autoencoder. Models combining common digital biomarkers and deep features predicted depression severity scores with a correlation of r = 0.73 on average, total severity of mood disorder symptoms with r = 0.67, and mild behavioral impairment scores with r = 0.69 in the study population. Our findings demonstrated the potential of physiological biomarkers collected from wearables and deep learning methods to be used for the continuous and unobtrusive assessments of mental health symptoms in older adults, including those with MCI. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT05059353) on September 28, 2021, titled "Effectiveness and Safety of a Digitally Based Multidomain Intervention for Mild Cognitive Impairment".
ABSTRACT
Advances in biomarker-based diagnostic modalities, recent approval of anti-amyloid monoclonal antibodies for early Alzheimer's disease (AD; mild cognitive impairment or mild dementia due to AD) and late-stage clinical development of other disease-modifying therapies for AD necessitate a significant paradigm shift in the early detection, diagnosis and management of AD. Anti-amyloid monoclonal antibodies target the underlying pathophysiological mechanisms of AD and have demonstrated a significant reduction in the rate of clinical decline in cognitive and functional outcome measures in patients with early AD. With growing recognition of the benefit of early interventions in AD, an increasing number of people may seek diagnosis for their subjective cognitive problems in an already busy medical system. Various factors such as limited examination time, lack of expertise for cognitive assessment and limited access to specialized tests can impact diagnostic accuracy and timely detection of AD. To overcome these challenges, a new model of care will be required. In this paper, we provide practical guidance for institutional readiness for anti-amyloid therapies for early AD in Asia, in terms of best practices for identifying eligible patients and diagnosing them appropriately, safe administration of anti-amyloid monoclonal antibodies and monitoring of treatment, managing potential adverse events such as infusion reactions and amyloid-related imaging abnormalities, and cross-disciplinary collaboration. Education and training will be the cornerstone for the establishment of new pathways of care for the identification of patients with early AD and delivery of anti-amyloid therapies in a safe and efficient manner to eligible patients.
ABSTRACT
Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.
Brain networks identified by functional connectivity (FC) have preserved architectures from rest to task and across task demands. Higher similarity, implying more efficient network reconfiguration, was associated with better cognition and task performance in young adults. To examine how it may be influenced by aging, we compared whole-brain and network-level FC similarities between resting-state and spatial working memory fMRI in young and older adults. At whole-brain level and higher order cognitive networks, older adults evidenced less efficient network reconfiguration from rest to task than young adults. Importantly, more efficient reconfiguration was associated with better accuracy. This relationship relied more on internetwork connections in older adults. Despite reduced neural resources compared to young, maintaining efficient network updating still contributes to better cognition at older age.
Subject(s)
Neuropsychological Tests , Humans , Singapore , Male , Middle Aged , Female , Aged , Longitudinal Studies , Adult , Reference Values , Young Adult , Aged, 80 and over , AdolescentABSTRACT
Background: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD. Objective: Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD. Methods: Plasma NfL and neuroimaging data from patients with bvFTD (nâ=â16) and AD or mild cognitive impairment (nâ=â38; ADâ+âMCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients. RESULTS: We demonstrated divergent associations between NfL and functional connectivity in ADâ+âMCI and bvFTD patients. Specifically, ADâ+âMCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in ADâ+âMCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores. CONCLUSIONS: Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.
Subject(s)
Alzheimer Disease , Biomarkers , Frontotemporal Dementia , Magnetic Resonance Imaging , Neurofilament Proteins , Humans , Alzheimer Disease/blood , Alzheimer Disease/physiopathology , Alzheimer Disease/diagnostic imaging , Female , Frontotemporal Dementia/blood , Frontotemporal Dementia/physiopathology , Frontotemporal Dementia/diagnostic imaging , Male , Aged , Neurofilament Proteins/blood , Middle Aged , Biomarkers/blood , Cognitive Dysfunction/blood , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/diagnostic imaging , Brain/diagnostic imaging , Brain/physiopathology , Nerve Net/diagnostic imaging , Nerve Net/physiopathology , Default Mode Network/physiopathology , Default Mode Network/diagnostic imagingABSTRACT
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.
Subject(s)
Cognitive Dysfunction , Dementia , Humans , Reproducibility of Results , Cognitive Dysfunction/psychology , Dementia/diagnosis , Dementia/epidemiology , Neuropsychological Tests , CognitionABSTRACT
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.
ABSTRACT
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.
Subject(s)
Hydroxymethylglutaryl-CoA Reductase Inhibitors , Ischemic Attack, Transient , Ischemic Stroke , Stroke , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Cerebral Hemorrhage/epidemiology , Cerebral Infarction/complications , Hydroxymethylglutaryl-CoA Reductase Inhibitors/adverse effects , Intracranial Hemorrhages/complications , Ischemic Attack, Transient/epidemiology , Ischemic Stroke/complications , Magnetic Resonance Imaging , Neoplasm Recurrence, Local/complications , Prospective Studies , Risk Factors , Secondary Prevention , Stroke/epidemiologyABSTRACT
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.
Subject(s)
Cognitive Dysfunction , Dementia , Humans , Dementia/epidemiology , Quality of Life , Cohort Studies , Southeast Asian People , Cognitive Dysfunction/diagnosis , Cognitive Dysfunction/epidemiology , Cognitive Dysfunction/psychology , Biomarkers , Glucose , Neuropsychological TestsABSTRACT
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.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Dementia , Humans , Female , Middle Aged , Male , Gray Matter/diagnostic imaging , Cohort Studies , Cross-Sectional Studies , Cognitive Dysfunction/diagnosis , Brain/diagnostic imaging , Cognition , Magnetic Resonance Imaging/methods , Biomarkers , Perfusion/adverse effects , Dementia/complications , Phenotype , Alzheimer Disease/diagnosisABSTRACT
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.
Subject(s)
Cognitive Dysfunction , Wearable Electronic Devices , Aged , Humans , Middle Aged , Cognition , Cognitive Dysfunction/diagnosis , Machine Learning , Neuropsychological Tests , Clinical Trials as TopicSubject(s)
Cognitive Dysfunction , Stroke , Humans , Magnetic Resonance Imaging , Brain , Stroke/complications , Neuropsychological Tests , CognitionABSTRACT
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.
ABSTRACT
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.
Subject(s)
Alzheimer Disease , Dementia , Leukoencephalopathies , White Matter , Humans , Gray Matter/diagnostic imaging , Gray Matter/pathology , Apolipoprotein E4/genetics , Magnetic Resonance Imaging/methods , Dementia/diagnostic imaging , Dementia/genetics , Dementia/pathology , Leukoencephalopathies/diagnostic imaging , Leukoencephalopathies/genetics , Leukoencephalopathies/pathology , Apolipoproteins , Atrophy/pathology , White Matter/diagnostic imaging , White Matter/pathology , Alzheimer Disease/pathology , Brain/diagnostic imaging , Brain/pathologyABSTRACT
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, SDâ=â9.38, mean education years was 13.59, SDâ=â3.70 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 =â-0.265, pâ=â0.001). CONCLUSIONS: The VCAT is useful in detecting MCI in the community in Singapore and may be an effective measure of neurodegeneration.
Subject(s)
Cognitive Dysfunction , Humans , Male , Female , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/epidemiology , ROC Curve , Mental Status and Dementia Tests , Neuropsychological Tests , CognitionABSTRACT
[This corrects the article DOI: 10.3389/fneur.2022.1005406.].
ABSTRACT
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 â¼3.6 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.
Subject(s)
Cognition Disorders , Cognitive Dysfunction , Stroke , Humans , Male , Aged , Female , Cognition , Cognition Disorders/complications , Risk Factors , Cognitive Dysfunction/psychologyABSTRACT
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.
Subject(s)
Frontotemporal Dementia , Pick Disease of the Brain , Humans , Frontotemporal Dementia/genetics , Frontotemporal Dementia/pathology , C9orf72 Protein/genetics , Southeast Asian People , MutationABSTRACT
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.
Subject(s)
Alzheimer Disease , Frontotemporal Dementia , Parkinson Disease , Humans , Interleukin-33/metabolism , Interleukin-1 Receptor-Like 1 Protein/metabolism , Frontotemporal Dementia/cerebrospinal fluid , Cross-Sectional Studies , Alzheimer Disease/psychology , Biomarkers/cerebrospinal fluid , CognitionABSTRACT
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.