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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".
Subject(s)
Neuropsychological Tests , Humans , Singapore , Male , Middle Aged , Female , Aged , Longitudinal Studies , Adult , Reference Values , Young Adult , Aged, 80 and over , AdolescentABSTRACT
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
The progression of PET-based Braak stages correlates with cognitive deterioration in aging and Alzheimer's disease. Here, we investigate the association between PET-based Braak stages and functional impairment and assess whether PET-based Braak staging predicts a longitudinal decline in the performance of activities of daily living. In this cohort study, we evaluated cognitively unimpaired individuals and individuals with mild cognitive impairment or Alzheimer's disease dementia. Participants underwent [18F]MK6240 tau-PET, were assigned a PET-based Braak stage at baseline and were followed for a mean (SD) of 1.97 (0.66) years. Functional performance was evaluated with the Functional Activities Questionnaire, Everyday Cognition and functional Clinical Dementia Rating sum of boxes. Multiple linear regressions assessed the association of PET-based Braak stages with baseline functionality and with the longitudinal rate of change in functional scores, adjusting for age, sex and amyloid-ß load. We employed voxel-based regression models to investigate the association between functionality and tau-PET signal and assessed the voxel overlap with Braak regions of interest. We included 291 individuals (181 cognitively unimpaired, 56 amyloid-ß+ mild cognitive impairment and 54 amyloid-ß+ Alzheimer's disease) aged 70.60 (7.48) years. At baseline, PET-based Braak stages III-IV (ß = 0.43, P = 0.03) and V-VI (ß = 1.20, P < 0.0001) showed associations with poorer Functional Activities Questionnaire scores. Similarly, stages III-IV (ß = 0.43, P = 0.02) and V-VI (ß = 1.15, P < 0.0001) were associated with worse Everyday Cognition scores. Only stages V-VI were associated with higher functional Clinical Dementia Rating sum of boxes (ß = 1.17, P < 0.0001) scores. Increased tau-PET signals in all Braak regions of interest were linked to worse performance in all tools. The voxelwise analysis showed widespread cortical associations between functional impairment and tau-PET and high voxel overlap with Braak regions of interest. Baseline PET-based Braak stages V-VI predicted significant longitudinal functional decline as assessed by the Functional Activities Questionnaire (ß = 1.69, P < 0.0001), the Everyday Cognition (ß = 1.05, P = 0.001) and the functional Clinical Dementia Rating sum of boxes (ß = 1.29, P < 0.0001). Our results suggest that functional impairment increases with the severity of tau accumulation. These findings also indicate that PET-based Braak staging is a good predictor of functional impairment in the Alzheimer's disease continuum. Finally, our study provides evidence for the clinical significance of the PET-based Braak staging framework.
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Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left-skewed and the results of the association analysis might not be robust. This study aims to study the distribution of the cognitive outcomes and to discuss potential solutions. Materials and Methods: In this retrospective cohort study of individuals with subjective cognitive decline or mild cognitive impairment, the inverse-transformed cognitive outcomes are modelled using different statistical distributions. The robustness of the proposed models are checked under different scenarios: with intercept-only, models with covariates, and with and without bootstrapping. Results: The main results were based on the VCAT score and validated via the MoCA score. The findings suggested that the inverse transformation method improved the modelling the cognitive scores compared to the conventional methods using the original cognitive scores. The association of the baseline characteristics (age, gender, and years of education) and the cognitive outcomes were reported as estimates and 95% confidence intervals. Bootstrap methods improved the estimate precision and the bootstrapped standard errors of the estimates were more robust. Cognitive outcomes were widely analysed using linear regression models with the default normal distribution as a conventional method. We compared the results of our suggested models with the normal distribution under various scenarios. Goodness-of-fit measurements were compared between the proposed models and conventional methods. Conclusions: The findings support the use of the inverse transformation method to model the cognitive outcomes instead of the original cognitive scores for early-stage neurocognitive disorders where the cognitive outcomes are left-skewed.
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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: 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 TopicABSTRACT
INTRODUCTION: Misdiagnosis rate of Dementia with Lewy Bodies (DLB) remains high despite being second most common cause of neurodegenerative dementia. To date, understanding of clinical profile of pathologically confirmed prodromal DLB remains limited. The main objective of this study was to describe and compare it with pathologically confirmed Alzheimer's disease (AD). METHODS: We accessed the National Alzheimer's Coordinating Center database from 2005 to December 2022 data freeze and included 111 and 501 prodromal DLB and AD patients respectively. First visit data was analyzed. RESULTS: Clinician-determined memory impairment is common in prodromal DLB (>70%) but associated with higher risk for AD diagnosis (OR 0.355, p = 0.0003). DLB had a higher proportion of non-amnestic mild cognitive impairment (MCI) diagnoses but statistically insignificance in differentiating the two. Inattention (OR 2.273, p = 0.0015), and neuropsychiatric features, such as visual hallucinations (OR 11.98, p < 0.0001), depressed mood (OR1.709, p = 0.0292), apathy (1.824, p = 0.0345), and night/REM sleep behaviors, are associated with DLB diagnosis. Hallucinations are infrequent (7-11%). Motor symptoms, particularly gait disorders (OR 4.570, p < 0.001), falls (OR3.939, p = 0.0003), tremors (OR2.237, p = 0.0154), slowness (OR3.573, p < 0.0001), and parkinsonism signs (OR2.443, p < 0.0001), are common. 32% showed no parkinsonism during initial presentation. Neuropsychological examination revealed less impaired memory and language but impaired executive function in DLB. CONCLUSION: In clinical practice, it is important to note that memory symptoms although being higher risk associated with AD diagnosis, are prominent in prodromal DLB. Psychosis is infrequent, and non-amnestic MCI is not necessarily associated with higher risk of DLB diagnosis. A careful clinical approach is key to improve the diagnosis of prodromal DLB.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Lewy Body Disease , Parkinsonian Disorders , Humans , Lewy Body Disease/diagnosis , Lewy Body Disease/complications , Alzheimer Disease/complications , Lewy Bodies , Cognitive Dysfunction/etiology , Cognitive Dysfunction/complications , Parkinsonian Disorders/diagnosis , Hallucinations , Prodromal SymptomsABSTRACT
Amyloid-ß plaques and neurofibrillary tangles (NFTs) are the 2 histopathologic hallmarks of Alzheimer disease (AD). On the basis of the pattern of NFT distribution in the brain, Braak and Braak proposed a histopathologic staging system for AD. Braak staging provides a compelling framework for staging and monitoring of NFT progression in vivo using PET imaging. Because AD staging remains based on clinical features, there is an unmet need to translate neuropathologic staging to a biologic clinical staging system. Such a biomarker staging system might play a role in staging preclinical AD or in improving recruitment strategies for clinical trials. Here, we review the literature regarding AD staging with the Braak framework using tau PET imaging, here called PET-based Braak staging. Our aim is to summarize the efforts of implementing Braak staging using PET and assess correspondence with the Braak histopathologic descriptions and with AD biomarkers. Methods: We conducted a systematic literature search in May 2022 on PubMed and Scopus combining the terms "Alzheimer" AND "Braak" AND ("positron emission tomography" OR "PET"). Results: The database search returned 262 results, and after assessment for eligibility, 21 studies were selected. Overall, most studies indicate that PET-based Braak staging may be an efficient method to stage AD since it presents an adequate ability to discriminate between phases of the AD continuum and correlates with clinical, fluid, and imaging biomarkers of AD. However, the translation of the original Braak descriptions to tau PET was done taking into account the limitations of this imaging technique. This led to important interstudy variability in the anatomic definitions of Braak stage regions of interest. Conclusion: Refinements in this staging system are necessary to incorporate atypical variants and Braak-nonconformant cases. Further studies are needed to understand the possible applications of PET-based Braak staging to clinical practice and research. Furthermore, there is a need for standardization in the topographic definitions of Braak stage regions of interest to guarantee reproducibility and methodologic homogeneity across studies.
Subject(s)
Alzheimer Disease , Humans , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/pathology , Reproducibility of Results , tau Proteins , Neurofibrillary Tangles , Amyloid beta-Peptides , Positron-Emission Tomography , Plaque, AmyloidABSTRACT
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
[This corrects the article DOI: 10.3389/fneur.2022.1005406.].
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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
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.
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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).
Subject(s)
Alzheimer Disease , Alzheimer Disease/metabolism , Amyloid/metabolism , Amyloid beta-Peptides/metabolism , Brain/metabolism , Humans , Magnetic Resonance Imaging , Neuroimaging/methods , Positron-Emission TomographyABSTRACT
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+ (ßâ=â1.53; pâ=â0.036; CI 0.15:2.92) and A- N- (ßâ=â4.68; pâ=â0.001; 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 (ßâ=â- 2.37; pâ=â0.030; CI - 4.41:- 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A- sub-group.
Subject(s)
Alzheimer Disease , Amyloidosis , Cardiovascular Diseases , Cognitive Dysfunction , Dementia , Humans , Alzheimer Disease/psychology , Amyloid , Amyloid beta-Peptides , Biomarkers , Cognition , Cognitive Dysfunction/diagnostic imaging , Dementia/diagnostic imaging , tau Proteins , Middle Aged , Age of OnsetABSTRACT
Alzheimer's disease (AD) is characterized by the brain accumulation of amyloid-ß and tau proteins. A growing body of literature suggests that epigenetic dysregulations play a role in the interplay of hallmark proteinopathies with neurodegeneration and cognitive impairment. Here, we aim to characterize an epigenetic dysregulation associated with the brain deposition of amyloid-ß and tau proteins. Using positron emission tomography (PET) tracers selective for amyloid-ß, tau, and class I histone deacetylase (HDAC I isoforms 1-3), we find that HDAC I levels are reduced in patients with AD. HDAC I PET reduction is associated with elevated amyloid-ß PET and tau PET concentrations. Notably, HDAC I reduction mediates the deleterious effects of amyloid-ß and tau on brain atrophy and cognitive impairment. HDAC I PET reduction is associated with 2-year longitudinal neurodegeneration and cognitive decline. We also find HDAC I reduction in the postmortem brain tissue of patients with AD and in a transgenic rat model expressing human amyloid-ß plus tau pathology in the same brain regions identified in vivo using PET. These observations highlight HDAC I reduction as an element associated with AD pathophysiology.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Histone Deacetylase 1 , Adamantane/analogs & derivatives , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/genetics , Alzheimer Disease/metabolism , Amyloid beta-Peptides/metabolism , Animals , Brain/metabolism , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/genetics , Cognitive Dysfunction/metabolism , Histone Deacetylase 1/metabolism , Histone Deacetylases/genetics , Histone Deacetylases/metabolism , Humans , Hydroxamic Acids , Positron-Emission Tomography/methods , Rats , tau Proteins/metabolismABSTRACT
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.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Alzheimer Disease/diagnostic imaging , Amyloid beta-Peptides , Biomarkers , Cognition , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/pathology , Humans , Language , Neuropsychological TestsABSTRACT
The definitive diagnosis of Alzheimer's Disease (AD) without the need for neuropathological confirmation remains a challenge in AD research today, despite efforts to uncover the molecular and biological underpinnings of the disease process. Furthermore, the potential for therapeutic intervention is limited upon the onset of symptoms, providing motivation for studying and treating the AD precursor mild cognitive impairment (MCI), the prodromal stage of AD instead. Applying machine learning classification to transcriptomic data of MCI, AD, and cognitively normal (CN) control patients, we identified differentially expressed genes that serve as biomarkers for the characterization and classification of subjects into MCI or AD groups. Predictive models employing these biomarker genes exhibited good classification performances for CN, MCI, and AD, significantly above random chance. The PI3K-Akt, IL-17, JAK-STAT, TNF, and Ras signaling pathways were also enriched in these biomarker genes, indicating their diagnostic potential and pathophysiological roles in MCI and AD. These findings could aid in the recognition of MCI and AD risk in clinical settings, allow for the tracking of disease progression over time in individuals as part of a therapeutic approach, and provide possible personalized drug targets for early intervention of MCI and AD.
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BACKGROUND: There is an urgent need for noninvasive, cost-effective biomarkers for Alzheimer's disease (AD), such as blood-based biomarkers. They will not only support the clinical diagnosis of dementia but also allow for timely pharmacological and nonpharmacological interventions and evaluations. OBJECTIVE: To identify and validate a novel blood-based microRNA biomarker for dementia of the Alzheimer's type (DAT). METHODS: We conducted microRNA sequencing using peripheral blood mononuclear cells isolated from a discovery cohort and validated the identified miRNAs in an independent cohort and AD postmortem tissues. miRNA correlations with AD pathology and AD clinical-radiological imaging were conducted. We also performed bioinformatics and cell-based assay to identify miRNA target genes. RESULTS: We found that miR-150-5p expression was significantly upregulated in DAT compared to mild cognitive impairment and healthy subjects. Upregulation of miR-150-5p was observed in AD hippocampus. We further found that higher miR-150-5p levels were correlated with the clinical measures of DAT, including lower global cognitive scores, lower CSF Aß42, and higher CSF total tau. Interestingly, we observed that higher miR-150-5p levels were associated with MRI brain volumes within the default mode and executive control networks, two key networks implicated in AD. Furthermore, pathway analysis identified the targets of miR-150-5p to be enriched in the Wnt signaling pathway, including programmed cell death 4 (PDCD4). We found that PDCD4 was downregulated in DAT blood and was downregulated by miR-150-5p at both the transcriptional and protein levelsConclusion:Our findings demonstrated that miR-150-5p is a promising clinical blood-based biomarker for DAT.