Alterations in parietal and temporal white matter microstructure derived from diffusion tensor imaging occur in preclinical and clinical Alzheimer's disease. Amyloid beta (Aβ) deposition and such ...white matter alterations are two pathological hallmarks of Alzheimer's disease. However, the relationship between these pathologies is not yet understood, partly since conventional diffusion MRI methods cannot distinguish between cellular and extracellular processes. Thus, we studied Aβ‐associated longitudinal diffusion MRI changes in Aβ‐positive (N = 21) and Aβ‐negative (N = 51) cognitively normal elderly obtained from the Alzheimer's Disease Neuroimaging Initiative dataset using linear mixed models. Aβ‐positivity was based on Alzheimer's Disease Neuroimaging Initiative amyloid‐PET recommendations using a standardized uptake value ratio cut‐off of 1.11. We used free‐water imaging to distinguish cellular and extracellular changes. We found that Aβ‐positive subjects had increased baseline right uncinate fasciculus free‐water fraction (FW), associated with worse baseline Alzheimer's disease assessment scale scores. Furthermore, Aβ‐positive subjects showed faster decrease in fractional anisotropy (FW‐corrected) in the right uncinate fasciculus and faster age‐dependent right inferior longitudinal fasciculus FW increases over time. Right inferior longitudinal fasciculus FW increases were associated with greater memory decline. Importantly, these results remained significant after controlling for gray and white matter volume and hippocampal volume. This is the first study to illustrate the influence of Aβ burden on early longitudinal (in addition to baseline) white matter changes in cognitively normal elderly individuals at‐risk of Alzheimer's disease, thus underscoring the importance of longitudinal studies in assessing microstructural alterations in individuals at risk of Alzheimer's disease prior to symptoms onset.
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.
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.
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.
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.
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.
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-β1-42 (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+ (β = 1.53; p = 0.036; CI 0.15:2.92) and A- N- (β = 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 (β = - 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.
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.
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.
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).
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.
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.
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.
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.
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.
In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion ...while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.
Patients with amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) show functional and structural connectivity alterations in the default mode network (DMN) while cerebrovascular ...disease (CeVD) shows functional and structural connectivity changes in the executive control network (ECN). Such disruptions are associated with memory and executive function impairment, respectively. Concurrent AD and CeVD pathology is associated with a higher rate of cognitive decline and differential neurodegenerative patterns. Together, such findings are likely reflective of different underlying pathology in AD with and without CeVD. However, few studies have examined the effect of CeVD on network functional connectivity (task-free functional magnetic resonance imaging (fMRI)) and structural connectivity (diffusion MRI) of the DMN and ECN in aMCI and AD using a hypothesis-driven multiple seed-based approach.
We examined functional and structural connectivity network changes in 39 aMCI, 50 aMCI+CeVD, 47 AD, 47 AD+CeVD, and 65 healthy controls (HCs) and their associations with cognitive impairment in the executive/attention and memory domains.
We demonstrate divergent DMN and ECN functional connectivity changes in CeVD and non-CeVD subjects. Compared with controls, intra-DMN hippocampal functional connectivity reductions were observed in both AD and AD+CeVD, while intra-DMN parietal and medial prefrontal-parietal functional connectivity was higher in AD+CeVD and aMCI+CeVD, but lower in AD. Intra-ECN frontal functional connectivity increases and fronto-parietal functional connectivity decreases occurred in CeVD but not non-CeVD subjects. Such functional connectivity alterations were related with cognitive impairment in a dissociative manner: intra-DMN functional connectivity changes were associated with worse cognition primarily in non-CeVD groups, while intra-ECN functional connectivity changes were associated with worse cognition primarily in CeVD groups. Additionally, CeVD and non-CeVD groups showed overlapping and distinct alterations in inter-network DMN-ECN functional connectivity depending on disease severity. In contrast to functional connectivity, CeVD groups had greater network structural connectivity damage compared with non-CeVD groups in both aMCI and AD patients. Network structural connectivity damage was associated with worse cognition.
We demonstrate differential functional and structural network changes between aMCI and AD patients with and without CeVD through diverging and deleterious network-based degeneration underlying domain-specific cognitive impairment.
Southeast Asia represents 10% of the global population, yet little is known about regional clinical characteristics of dementia and risk factors for dementia progression. This study aims to describe ...the clinico-demographic profiles of dementia in Southeast Asia and investigate the association of onset-type, education, and cerebrovascular disease (CVD) on dementia progression in a real-world clinic setting.
In this longitudinal study, participants were consecutive series of 1606 patients with dementia from 2010 to 2019 from a tertiary memory clinic from Singapore. The frequency of dementia subtypes stratified into young-onset (YOD; <65 years age-at-onset) and late-onset dementia (LOD; ≥65 years age-at-onset) was studied. Association of onset-type (YOD or LOD), years of lifespan education, and CVD on the trajectory of cognition was evaluated using linear mixed models. The time to significant cognitive decline was investigated using Kaplan-Meier analysis.
Dementia of the Alzheimer's type (DAT) was the most common diagnosis (59.8%), followed by vascular dementia (14.9%) and frontotemporal dementia (11.1%). YOD patients accounted for 28.5% of all dementia patients. Patients with higher lifespan education had a steeper decline in global cognition (p<0.001), with this finding being more pronounced in YOD (p=0.0006). Older patients with a moderate-to-severe burden of CVD demonstrated a trend for a faster decline in global cognition compared to those with a mild burden.
There is a high frequency of YOD with DAT being most common in our Southeast Asian memory clinic cohort. YOD patients with higher lifespan education and LOD patients with moderate-to-severe CVD experience a steep decline in cognition.
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.
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•Uric acid, an important antioxidant, may be involved in depression.•Relationship between SUA and depressive symptoms in SVD was assessed.•HAMD-24, MRI, and graph theory analysis were used.•Patients with depressive symptoms had lower SUA levels than those without.•Lower SUA levels are associated with disrupted structural brain networks.
Variants in triggering receptor expressed on myeloid cells 2 (TREM2) are associated with increased Alzheimer's disease (AD) risk. Recent studies have reported inconsistent peripheral TREM2 mRNA ...expression levels and relationship with cognitive scores in AD and mild cognitive impairment (MCI). Additionally, no study has examined the association of peripheral TREM2 levels with neuroimaging measures in AD and MCI.
To determine peripheral TREM2 mRNA levels in AD, amnestic MCI (aMCI) and healthy controls, and the association with cognitive performance and brain structural changes.
We measured peripheral TREM2 mRNA levels in 80 AD, 30 aMCI, and 86 healthy controls using real time polymerase chain reaction. TREM2 levels were correlated with various cognitive performance and brain volumes, correcting for APOE4 status.
TREM2 mRNA levels were significantly higher in AD compared to controls and aMCI. Levels did not differ between aMCI and controls. Corrected for APOE4, higher TREM2 levels correlated with lower Mini-Mental State Examination, Montreal Cognitive Assessment (MoCA) and episodic memory scores, and lower total grey matter and right hippocampal volumes. Whole-brain voxel-based morphometry analysis found negative association between TREM2 mRNA levels and grey matter volumes in temporal, parietal and frontal regions. AD subjects with MoCA scores ≤20 had higher TREM2 levels correlating with smaller total grey matter, left hippocampal and right hippocampal volumes.
Peripheral TREM2 mRNA levels are higher in AD and are associated with AD-related cognitive deficits and hippocampal atrophy. Our findings suggest that TREM2 may be a potential non-invasive peripheral biomarker for AD diagnosis.
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