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Alzheimer's disease (AD) is a devastating, age-associated neurodegenerative disorder and the most common cause of dementia. The clinical continuum of AD spans from preclinical disease to subjective cognitive decline, mild cognitive impairment, and dementia stages (mild, moderate, and severe). Neuropathologically, AD is defined by the accumulation of amyloid ß (Aß) into extracellular plaques in the brain parenchyma and in the cerebral vasculature, and by abnormally phosphorylated tau that accumulates intraneuronally forming neurofibrillary tangles (NFTs). Development of treatment approaches that prevent or even reduce the cognitive decline because of AD has been slow compared to other major causes of death. Recently, the United States Food and Drug Administration gave full approval to 2 different Aß-targeting monoclonal antibodies. However, this breakthrough disease modifying approach only applies to a limited subset of patients in the AD continuum and there are stringent eligibility criteria. Furthermore, these approaches do not prevent progression of disease, because other AD-related pathologies, such as NFTs, are not directly targeted. A non-mutually exclusive alternative is to address lifestyle interventions that can help reduce the risk of AD and AD-related dementias (ADRD). It is estimated that addressing such modifiable risk factors could potentially delay up to 40% of AD/ADRD cases. In this review, we discuss some of the many modifiable risk factors that may be associated with prevention of AD/ADRD and/or increasing brain resilience, as well as other factors that may interact with these modifiable risk factors to influence AD/ADRD progression. ANN NEUROL 2024.
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BACKGROUND: The choroid plexus (ChP), a densely vascularized structure, has drawn increasing attention for its involvement in brain homeostasis and waste clearance. While the volumetric changes have been explored in many imaging studies, few studies have investigated the vascular degeneration associated with aging in the ChP. PURPOSE: To investigate the sub-structural characteristics of the ChP, particularly the vascular compartment using high-resolution 7T imaging enhanced with Ferumoxytol, an ultrasmall super-paramagnetic iron oxide, which greatly increase the susceptibility contrast for vessels. STUDY TYPE: Prospective. SUBJECTS: Forty-nine subjects without neurological disorders (age: 21-80 years; 42 ± 17 years; 20 females). FIELD STRENGTH/SEQUENCE: 7-T with 2D and 3D T2* GRE, 3D MPRAGE T1, 2D TSE T2, and 2D FLAIR. ASSESSMENT: The vascular and stromal compartments of the ChP were segmented using K-means clustering on post-contrast 2D GRE images. Visual and qualitative assessment of ChP vascular characteristics were conducted independently by three observers. Vascular density (Volvessel/VolChP ratio) and susceptibility change (Δχ) induced by Ferumoxytol were analyzed on 3D GRE-derived susceptibility-weighted imaging and quantitative susceptibility mapping, respectively. STATISTICAL TESTS: Independent t-test, Mann-Whitney U test, and Chi-square test were utilized for group comparisons. The relationship between age and ChP's vascular alterations was examined using Pearson's correlation. Intra-class coefficient was calculated for inter-observer agreement. A P value <0.05 was considered statistically significant. RESULTS: 2D GRE images demonstrated superior contrast and accurate delineation of ChP substructures (ICC = 0.86). Older subjects exhibited a significantly smaller vascular density (16.5 ± 4.34%) and lower Δχ (22.10 ± 12.82 ppb) compared to younger subjects (24.85 ± 6.84% and 34.64 ± 12.69 ppb). Vascular density and mean Δχ within the ChP negatively correlated with age (r = -0.48, and r = -0.45). DATA CONCLUSION: Ferumoxytol-enhanced 7T images can demonstrate ChP alterations in elderly with decreased vascular density and expansion of nonvascular compartment. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.
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BACKGROUND: We examined drivers of self and study partner reports of memory loss in mild cognitive impairment (MCI) from Alzheimer (AD-MCI) and vascular disease (Va-MCI). METHODS: We performed retrospective cross-sectional analyses of participants with AD-MCI (n=2874) and Va-MCI (n=376) from the National Alzheimer Coordinating Center data set. Statistical analysis utilized 2-sided t test or the Fisher exact test. RESULTS: Compared with AD-MCI, Va-MCI subjects (24.5% vs. 19.7%, P =0.031) and study partners (31.4% vs. 21.6%, P <0.0001) were more likely to deny memory loss. Black/African Americans were disproportionately represented in the group denying memory loss in AD-MCI (20.0% vs. 13.2%, P <0.0001) and Va-MCI (33.7% vs. 18.0%, P =0.0022). Study partners of participants with these features also disproportionately denied memory loss: female (AD-MCI: 60.1% vs. 51.7%, P =0.0002; Va-MCI: 70.3% vs. 52.3%, P =0.0011), Black/African American (AD-MCI: 23.5% vs. 11.98%, P <0.0001; Va-MCI: 48.8% vs. 26.5%, P =0.0002), and <16 years of education (AD-MCI only: 33.9% vs. 16.3%, P =0.0262). In AD-MCI and Va-MCI, participants with anxiety were disproportionately represented in the group endorsing memory loss (AD: 28.2% vs. 17.4%, P <0.0001; Va: 31.5% vs. 16.1%, P =0.0071), with analogous results with depression. CONCLUSION: The findings would suggest extra vigilance in interview-based MCI detection of persons at-risk for self-based or informant-based misreport.
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Doença de Alzheimer , Disfunção Cognitiva , Transtornos da Memória , Doenças Vasculares , Humanos , Feminino , Masculino , Idoso , Estudos Transversais , Transtornos da Memória/diagnóstico , Estudos Retrospectivos , Doenças Vasculares/complicações , Idoso de 80 Anos ou maisRESUMO
BACKGROUND: Subjective cognitive decline (SCD), considered a preclinical dementia stage, is less understood in Hispanics, a high-risk group for dementia. We investigated SCD to mild cognitive impairment (MCI) progression risk, as well as baseline and longitudinal features of depressive symptoms, SCD complaints, and objective cognitive performance among Hispanics compared to non-Hispanic Whites (NHW). METHODS: Hispanic (n = 23) and NHW (n = 165) SCD participants were evaluated at baseline and 2-year follow-up. Evaluations assessed function, depressive symptoms, SCD, and objective cognitive performance. RESULTS: Hispanics were at increased risk of progression to MCI (OR: 6.10, 95% CI 1.09-34.20, P = .040). Hispanic participants endorsed more depressive symptoms at baseline (P = .048) that worsened more longitudinally (OR: 3.16, 95% CI 1.18-8.51, P = .023). Hispanic participants had increased SCD complaints on the Brief Cognitive Rating Scale (BCRS) (ß = .40 SE: .17, P = .023), and in specific BCRS domains: concentration (ß = .13, SE: .07, P = .047), past memory (ß = .13, SE: .06, P = .039) and functional abilities (ß = .10, SE: .05, P = .037). In objective cognitive performance, Hispanic ethnicity associated with decline in MMSE (ß = -.27, SE: .13, P = .039), MoCA (ß = -.80 SE: .34, P = .032), Trails A (ß = 2.75, SE: .89, P = .002), Trails B (ß = 9.18, SE: 2.71, P = .001) and Guild Paragraph Recall Delayed (ß = -.80 SE: .28, P = .005). Conclusions: Hispanic ethnicity associated with a significantly increased risk of 2-year progression of SCD to MCI compared to NHW. This increased risk associated with increased depressive symptoms, distinctive SCD features, and elevated amnestic and non-amnestic objective cognitive decline. This supports further research to refine the assessment of preclinical dementia in this high-risk group.
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Synaptic spine loss is an early pathophysiologic hallmark of Alzheimer disease (AD) that precedes overt loss of dendritic architecture and frank neurodegeneration. While spine loss signifies a decreased engagement of postsynaptic neurons by presynaptic targets, the degree to which loss of spines and their passive components impacts the excitability of postsynaptic neurons and responses to surviving synaptic inputs is unclear. Using passive multicompartmental models of CA1 pyramidal neurons (PNs), implicated in early AD, we find that spine loss alone drives a boosting of remaining inputs to their proximal and distal dendrites, targeted by CA3 and entorhinal cortex (EC), respectively. This boosting effect is higher in distal versus proximal dendrites and can be mediated by spine loss restricted to the distal compartment, enough to impact synaptic input integration and somatodendritic backpropagation. This has particular relevance to very early stages of AD in which pathophysiology extends from EC to CA1.
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Introduction: Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. Methods: To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. Results: SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. Discussion: The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.
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Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has previously been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we fit an unconstrained 2-pool quantitative MT (qMT) model, i.e., without constraints on the longitudinal relaxation rate R 1 s of semi-solids, and investigate the sensitivity of the estimated parameters to amyloid accumulation in preclinical subjects. We scanned 15 cognitively normal volunteers, of which 9 were amyloid positive by [18F]Florbetaben PET. A 12 min hybrid-state qMT scan with an effective resolution of 1.24 mm isotropic and whole-brain coverage was acquired to estimate the unconstrained 2-pool qMT parameters. Group comparisons and correlations with Florbetaben PET standardized uptake value ratios were analyzed at the lobar level. We find that the exchange rate and semi-solid pool's R 1 s were sensitive to the amyloid concentration, while morphometric measures of cortical thickness derived from structural MRI were not. Changes in the exchange rate are consistent with previous reports in clinical AD, while changes in R 1 s have not been reported previously as its value is typically constrained in the literature. Our results demonstrate that qMT MRI may be a promising surrogate marker of amyloid beta without the need for contrast agents or radiotracers.
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BACKGROUND AND PURPOSE: The purpose of this study is to evaluate the feasibility of using 3-dimensional (3D) ultra-short echo time (UTE) radial imaging method for measurement of the permeability of the blood-brain barrier (BBB) to gadolinium-based contrast agent. In this study, we propose to use the golden-angle radial sparse parallel (GRASP) method with 3D center-out trajectories for UTE, hence named as 3D UTE-GRASP. We first examined the feasibility of using 3D UTE-GRASP dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) for differentiating subtle BBB disruptions induced by focused ultrasound (FUS). Then, we examined the BBB permeability changes in Alzheimer's disease (AD) pathology using Alzheimer's disease transgenic mice (5xFAD) at different ages. METHODS: For FUS experiments, we used four Sprague Dawley rats at similar ages where we compared BBB permeability of each rat receiving the FUS sonication with different acoustic power (0.4-1.0 MPa). For AD transgenic mice experiments, we included three 5xFAD mice (6, 12, and 16 months old) and three wild-type mice (4, 8, and 12 months old). RESULTS: The result from FUS experiments showed a progressive increase in BBB permeability with increase of acoustic power (p < .05), demonstrating the sensitivity of DCE-MRI method for detecting subtle changes in BBB disruption. Our AD transgenic mice experiments suggest an early BBB disruption in 5xFAD mice, which is further impaired with aging. CONCLUSION: The results in this study substantiate the feasibility of using the proposed 3D UTE-GRASP method for detecting subtle BBB permeability changes expected in neurodegenerative diseases, such as AD.
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Doença de Alzheimer , Barreira Hematoencefálica , Meios de Contraste , Estudos de Viabilidade , Imageamento por Ressonância Magnética , Camundongos Transgênicos , Ratos Sprague-Dawley , Barreira Hematoencefálica/diagnóstico por imagem , Animais , Camundongos , Imageamento por Ressonância Magnética/métodos , Ratos , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/metabolismo , Permeabilidade Capilar/fisiologia , Imageamento Tridimensional/métodosRESUMO
Early identification of Alzheimer's disease (AD) and AD-related dementias (ADRD) has high clinical significance, both because of the potential to slow decline through initiating FDA-approved therapies and managing modifiable risk factors, and to help persons living with dementia and their families to plan before cognitive loss makes doing so challenging. However, substantial racial and ethnic disparities in early diagnosis currently lead to additional inequities in care, urging accurate and inclusive risk assessment programs. In this study, we trained an artificial intelligence foundation model to represent the electronic health records (EHR) data with a vast cohort of 1.2 million patients within a large health system. Building upon this foundation EHR model, we developed a predictive Transformer model, named TRADE, capable of identifying risks for AD/ADRD and mild cognitive impairment (MCI), by analyzing the past sequential visit records. Amongst individuals 65 and older, our model was able to generate risk predictions for various future timeframes. On the held-out validation set, our model achieved an area under the receiver operating characteristic (AUROC) of 0.772 (95% CI: 0.770, 0.773) for identifying the AD/ADRD/MCI risks in 1 year, and AUROC of 0.735 (95% CI: 0.734, 0.736) in 5 years. The positive predictive values (PPV) in 5 years among individuals with top 1% and 5% highest estimated risks were 39.2% and 27.8%, respectively. These results demonstrate significant improvements upon the current EHR-based AD/ADRD/MCI risk assessment models, paving the way for better prognosis and management of AD/ADRD/MCI at scale.
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Anxiety is highly prevalent in Alzheimer's disease (AD), correlating with CSF/PET biomarkers and disease progression. Relationships to plasma biomarkers are unclear. Herein, we compare levels of plasma biomarkers in research participants with and without anxiety at cognitively normal, mild cognitive impairment, and AD dementia stages. We observed significantly higher plasma tau/Aß42 ratio in AD participants with anxiety versus those without, but did not observe differences at other stages or plasma biomarkers. No such relationships were evident with depression. These results support a unique pathophysiological relationship between anxiety and AD that can be reflected in plasma biomarkers, suggestive of heightened neurodegeneration.
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Importance: Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Objective: Evaluate ChatGPT and LlaMA-2 performance in extracting MMSE and CDR scores, including their associated dates. Methods: Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. Results: For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT's errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. Conclusions: In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.