Two-Year Longitudinal Outcomes of Subjective Cognitive Decline in Hispanics Compared to Non-hispanic Whites.

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.

The relationship between anxiety and levels of Alzheimer's disease plasma biomarkers.

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.

Predicting Risk of Alzheimer's Diseases and Related Dementias with AI Foundation Model on Electronic Health Records.

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.

Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline.

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.

Drivers of Memory Loss Underreport in Mild Cognitive Impairment Due to Alzheimer Versus Vascular Disease.

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.

Sensitivity of unconstrained quantitative magnetization transfer MRI to Amyloid burden in preclinical Alzheimer's disease.

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.

Feasibility of measuring blood-brain barrier permeability using ultra-short echo time radial magnetic resonance imaging.

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.

Vascular Aging in the Choroid Plexus: A 7T Ultrasmall Superparamagnetic Iron Oxide (USPIO)-MRI Study.

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.

Impact of dendritic spine loss on excitability of hippocampal CA1 pyramidal neurons: a computational study of early Alzheimer disease.

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.

Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores.

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.

Local and long-range GABAergic circuits in hippocampal area CA1 and their link to Alzheimer's disease.

GABAergic inhibitory neurons are the principal source of inhibition in the brain. Traditionally, their role in maintaining the balance of excitation-inhibition has been emphasized. Beyond homeostatic functions, recent circuit mapping and functional manipulation studies have revealed a wide range of specific roles that GABAergic circuits play in dynamically tilting excitation-inhibition coupling across spatio-temporal scales. These span from gating of compartment- and input-specific signaling, gain modulation, shaping input-output functions and synaptic plasticity, to generating signal-to-noise contrast, defining temporal windows for integration and rate codes, as well as organizing neural assemblies, and coordinating inter-regional synchrony. GABAergic circuits are thus instrumental in controlling single-neuron computations and behaviorally-linked network activity. The activity dependent modulation of sensory and mnemonic information processing by GABAergic circuits is pivotal for the formation and maintenance of episodic memories in the hippocampus. Here, we present an overview of the local and long-range GABAergic circuits that modulate the dynamics of excitation-inhibition and disinhibition in the main output area of the hippocampus CA1, which is crucial for episodic memory. Specifically, we link recent findings pertaining to GABAergic neuron molecular markers, electrophysiological properties, and synaptic wiring with their function at the circuit level. Lastly, given that area CA1 is particularly impaired during early stages of Alzheimer's disease, we emphasize how these GABAergic circuits may contribute to and be involved in the pathophysiology.

Gait dysfunction in Alzheimer disease.

Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.

Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function.

PURPOSE: In Dynamic contrast-enhanced MRI (DCE-MRI), Arterial Input Function (AIF) has been shown to be a significant contributor to uncertainty in the estimation of kinetic parameters. This study is to assess the feasibility of using a deep learning network to estimate local Capillary Input Function (CIF) to estimate blood-brain barrier (BBB) permeability, while reducing the required scan time. MATERIALS AND METHOD: A total of 13 healthy subjects (younger (<40 y/o): 8, older (> 67 y/o): 5) were recruited and underwent 25-min DCE-MRI scans. The 25 min data were retrospectively truncated to 10 min to simulate a reduced scan time of 10 min. A deep learning network was trained to predict the CIF using simulated tissue contrast dynamics with two vascular transport models. The BBB permeability (PS) was measured using 3 methods: (i) Ca-25min, using DCE-MRI data of 25 min with individually sampled AIF (Ca); (ii) Ca-10min, using truncated 10min data with AIF (Ca); and (iii) Cp-10min, using truncated 10 min data with CIF (Cp). The PS estimates from the Ca-25min method were used as reference standard values to assess the accuracy of the Ca-10min and Cp-10min methods in estimating the PS values. RESULTS: When compared to the reference method(Ca-25min), the Ca-10min and Cp-10min methods resulted in an overestimation of PS by 217 ± 241 % and 48.0 ± 30.2 %, respectively. The Bland Altman analysis showed that the mean difference from the reference was 8.85 ± 1.78 (x10-4 min-1) with the Ca-10min, while it was reduced to 1.63 ± 2.25 (x10-4 min-1) with the Cp-10min, resulting in an average reduction of 81%. The limits of agreement also reduced by up to 39.2% with the Cp-10min. We found a 75% increase of BBB permeability in the gray matter and a 35% increase in the white matter, when comparing the older group to the younger group. CONCLUSIONS: We demonstrated the feasibility of estimating the capillary-level input functions using a deep learning network. We also showed that this method can be used to estimate subtle age-related changes in BBB permeability with reduced scan time, without compromising accuracy. Moreover, the trained deep learning network can automatically select CIF, reducing the potential uncertainty resulting from manual user-intervention.

Impact of white matter hyperintensities on subjective cognitive decline phenotype in a diverse cohort of cognitively normal older adults.

OBJECTIVES: Subjective cognitive decline (SCD) is a preclinical stage of AD. White matter hyperintensities (WMH), an MRI marker of cerebral small vessel disease, associate with AD biomarkers and progression. The impact of WMH on SCD phenotype is unclear. METHODS/DESIGN: A retrospective, cross-sectional analysis was conducted on a diverse cohort with SCD evaluated at the NYU Alzheimer's Disease Research Center between January 2017 and November 2021 (n = 234). The cohort was dichotomized into none-to-mild (n = 202) and moderate-to-severe (n = 32) WMH. Differences in SCD and neurocognitive assessments were evaluated via Wilcoxon or Fisher exact tests, with p-values adjusted for demographics using multivariable logistic regression. RESULTS: Moderate-to-severe WMH participants reported more difficulty with decision making on the Cognitive Change Index (1.5 SD 0.7 vs. 1.2 SD 0.5, p = 0.0187) and worse short-term memory (2.2 SD 0.4 vs. 1.9 SD 0.3, p = 0.0049) and higher SCD burden (9.5 SD 1.6 vs. 8.7 SD 1.7, p = 0.0411) on the Brief Cognitive Rating Scale. Moderate-to-severe WMH participants scored lower on the Mini-Mental State Examination (28.0 SD 1.6 vs. 28.5 SD 1.9, p = 0.0491), and on delayed paragraph (7.2 SD 2.0 vs. 8.8 SD 2.9, p = 0.0222) and designs recall (4.5 SD 2.3 vs. 6.1 SD 2.5, p = 0.0373) of the Guild Memory Test. CONCLUSIONS: In SCD, WMH impact overall symptom severity, specifically in executive and memory domains, as well as objective performance on global and domain-specific tests in verbal memory and visual working/associative memory.

On gaps of clinical diagnosis of dementia subtypes: A study of Alzheimer's disease and Lewy body disease.

Introduction: Alzheimer's disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, clinical differentiation of these subtypes could be difficult. However, it is unclear how the magnitude of diagnostic uncertainty varies across dementia spectra and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these factors. Methods: We studied data of 1,920 participants recorded by the National Alzheimer's Coordinating Center from 2005 to 2019. Selection criteria included autopsy-based neuropathological assessments for AD and LBD, and the initial visit with Clinical Dementia Rating (CDR) stage of normal, mild cognitive impairment, or mild dementia. Longitudinally, we analyzed the first visit at each subsequent CDR stage. This analysis included positive predictive values, specificity, sensitivity and false negative rates of clinical diagnosis, as well as disparities by sex, race, age, and education. If autopsy-confirmed AD and/or LBD was missed in the clinic, the alternative clinical diagnosis was analyzed. Findings: In our findings, clinical diagnosis of AD+LBD had poor sensitivities. Over 61% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had a low sensitivity at the early dementia stage and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 32% had concurrent LBD neuropathology at autopsy. Among participants diagnosed as LBD, 32% to 54% revealed concurrent autopsy-confirmed AD pathology. When three subtypes were missed by clinicians, "No cognitive impairment" and "primary progressive aphasia or behavioral variant frontotemporal dementia" were the leading primary etiologic clinical diagnoses. With increasing dementia stages, the clinical diagnosis accuracy of black participants became significantly worse than other races, and diagnosis quality significantly improved for males but not females. Discussion: These findings demonstrate that clinical diagnosis of AD, LBD, and AD+LBD are inaccurate and suffer from significant disparities on race and sex. They provide important implications for clinical management, anticipatory guidance, trial enrollment and applicability of potential therapies for AD, and promote research into better biomarker-based assessment of LBD pathology.

Vigorous, regular physical exercise may slow disease progression in Alzheimer's disease.

INTRODUCTION: Mild to moderate exercise may decrease Alzheimer's disease (AD) risk, but the effects of vigorous, regular physical exercise remain unclear. METHODS: Two patients with initial diagnoses of amnestic mild cognitive impairment (MCI) demonstrated positive AD biomarkers throughout 16 and 8 years of follow-up, with final diagnoses of mild AD and amnestic MCI, respectively. RESULTS: Patient 1 was diagnosed with amnestic MCI at age 64. Neuropsychological testing, magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET), amyloid imaging PET, and cerebrospinal fluid (CSF) biomarkers during follow-ups remained consistent with AD. By age 80, progression was minimal with Montreal Cognitive Assessment (MoCA) 26 of 30. Patient 2 was diagnosed with amnestic MCI at age 72. Neuropsychological testing, MRI, FDG-PET, and amyloid imaging PET during follow-ups remained consistent with AD. At age 80, MoCA was 27 of 30 with no clinical progression. Both patients regularly performed vigorous, regular exercise that increased after retirement/work reduction. DISCUSSION: Vigorous, regular exercise may slow disease progression in biomarker-positive amnestic MCI and mild AD.

Intracranial artery stenosis is associated with cortical thinning in stroke-free individuals of two longitudinal cohorts.

BACKGROUND: We examined the association between asymptomatic intracranial artery stenosis (aICAS) and cortical thickness using brain magnetic resonance morphometry in two cohorts. METHODS: This cross-sectional study included stroke-free participants from the Northern Manhattan Study (NOMAS) and the National Alzheimer's Coordinating Center (NACC). We represented the predictor aICAS in NOMAS as a continuous global stenosis score reflecting an overall burden of stenosis (possible range 0-44) assessed by magnetic resonance angiography and in NACC as a dichotomous autopsy-determined Circle of Willis (CoW) atherosclerosis (none-mild vs moderate-severe). The primary outcome of interest was total cortical thickness. We analyzed each dataset separately using multivariable linear regression. RESULTS: The analysis included 1209 NOMAS (46% had any stenosis, 5% had ≥70% stenosis of at least one vessel; stenosis score range 0-11) and 392 NACC (36% moderate-severe CoW atherosclerosis) participants. We found an inverse relationship between stenosis score and total cortical thickness (ß-estimate [95% confidence interval (CI)]: -2.98 [-5.85, -0.11]) in adjusted models. We replicated these results in NACC (ß-estimate [95% CI]: -0.06 [-0.11, -0.003]). Post-hoc, we segregated stenosis scores by location and only posterior circulation stenosis score was associated with total cortical thickness (anterior ß-estimate [95% CI]: -0.90 [-5.16, 3.36], posterior ß-estimate [95% CI]: -7.25 [-14.30, -0.20]). CONCLUSION: We found both radiographically and neuropathologically determined aICAS to be associated with global cortical thinning. Interestingly, posterior circulation stenoses appeared to drive this association with global cortical thinning, raising the possibility of pathophysiologic mechanisms for cortical thinning other than impaired hemodynamics.

Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study.

Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.