Early-stage Alzheimer Research Articles

A randomized clinical trial evaluating Hydralazine’s efficacy in early-stage Alzheimer’s disease: The EHSAN Study

Alzheimer’s Disease (AD), a neurodegenerative disorder escalating worldwide, remains incurable with existing interventions merely mitigating symptoms. Hydralazine, an antihypertensive agent, has displayed neuroprotective potential in AD animal models via amplification of mitochondrial functionality and stimulation of stress management and repair pathways. Nevertheless, its effectiveness and tolerability in human AD cohorts are yet to be confirmed. This study protocol describes the design of an ongoing, single-center, randomized, triple-blind, placebo-controlled trial to assess hydralazine’s effects on cognitive function in mild to moderate -stage AD patients. We will enroll 424 patients aged 50 and older, meeting NINCDS-ADRDA criteria for probable AD with Mini-Mental State Examination scores from 12–26. They’ll be randomly assigned to receive either hydralazine HCL (25 mg, thrice daily) or a placebo for 12 months. The primary outcome is the Alzheimer’s Disease Assessment Scale change from baseline to 12 months. Secondary outcomes include various measures using Lawton instrumental activities of daily living scale, neuropsychiatry inventory, and caregiver activity survey. This trial will explore the potential benefits and risks of hydralazine in mild to moderate AD treatment. It’s the first trial examining hydralazine’s impact on mild to moderate -stage AD in human and is registered at the Iranian Registry of Clinical Trials (IRCT20200711048075N1, registered 29/07/2020) and ClinicalTrials.gov (NCT 04,842,552AQ, registered 13/04/2021). Ethics approval was granted by the Research Ethics Committee of the National Institute for Medical Research Development (IR.NIMAD.REC.1398.424), following the SPIRIT Statement guidelines. Findings will be disseminated via peer-reviewed publications and conferences. This inaugural human clinical trial evaluates hydralazine’s impact on patients in the mild to moderate AD. Executed with a randomized, triple-blind, placebo-controlled methodology, this study incorporates a significant sample size and an extended monitoring duration. Multiple parameters, including cognitive capabilities, will be assessed. Potential limitations include the inherent homogeneity of the AD cohort, the lack of biomarker assays, and the unpredictable progression of the disease. Notably, the study might not elucidate the protracted effects of hydralazine beyond a 12-month period. Another limitation of our clinical trial is that patients were diagnosed with Alzheimer’s disease based solely on clinical evaluation and MRI findings, without the inclusion of specific biomarkers, which may impact the accuracy and specificity of the diagnosis. Trial registration: Iranian Registry of Clinical Trials (IRCT20200711048075N1, registered 29/07/2020) and ClinicalTrials.gov (NCT 04,842,552, registered 13/04/2021).

Large-scale proteomic analyses of incident Alzheimer's disease reveal new pathophysiological insights and potential therapeutic targets.

Pathophysiological evolutions in early-stage Alzheimer's disease (AD) are not well understood. We used data of 2923 Olink plasma proteins from 51,296 non-demented middle-aged adults. During a follow-up of 15 years, 689 incident AD cases occurred. Cox-proportional hazard models were applied to identify AD-associated proteins in different time intervals. Through linking to protein categories, changing sequences of protein z-scores can reflect pathophysiological evolutions. Mendelian randomization using blood protein quantitative loci data provided causal evidence for potentially druggable proteins. We identified 48 AD-related proteins, with CEND1, GFAP, NEFL, and SYT1 being top hits in both near-term (HR:1.15-1.77; P:9.11 × 10-65-2.78 × 10-6) and long-term AD risk (HR:1.20-1.54; P:2.43 × 10-21-3.95 × 10-6). These four proteins increased 15 years before AD diagnosis and progressively escalated, indicating early and sustained dysfunction in synapse and neurons. Proteins related to extracellular matrix organization, apoptosis, innate immunity, coagulation, and lipid homeostasis showed early disturbances, followed by malfunctions in metabolism, adaptive immunity, and final synaptic and neuronal loss. Combining CEND1, GFAP, NEFL, and SYT1 with demographics generated desirable predictions for 10-year (AUC = 0.901) and over-10-year AD (AUC = 0.864), comparable to full model. Mendelian randomization supports potential genetic link between CEND1, SYT1, and AD as outcome. Our findings highlight the importance of exploring the pathophysiological evolutions in early stages of AD, which is essential for the development of early biomarkers and precision therapeutics.

ASC specks as a single-molecule fluid biomarker of inflammation in neurodegenerative diseases

Immunotherapeutic strategies for Alzheimer’s and Parkinson’s disease would be facilitated by better measures of inflammation. Here we established an ultra-sensitive single-molecule pull-down immunoassay combined with direct stochastic optical reconstruction microscopy (dSTORM) to measure the number, size and shape of individual extracellular inflammasome ASC specks. We assayed human post-mortem brain, serum and cerebrospinal fluid of patients with Parkinson’s and Alzheimer’s as well as healthy elderly. The number of ASC specks increased and showed altered morphology in the blood of early-stage Parkinson’s and Alzheimer’s patients compared to controls, mimicking those found in the brain and cerebrospinal fluid. In serum samples we also measured the number of Aβ, p-tau and α-syn aggregates and formed a composite biomarker of (ASC + p-tau)/Aβ and (ASC + α-syn)/Aβ ratios that distinguished age-matched healthy controls from patients with early-stage Alzheimer’s with AUC of 92% and early-stage Parkinson’s with AUC of 97%. Our findings confirm ASC specks as a fluid candidate biomarker of inflammation for neurodegenerative diseases with blood being the main focus for further development as convenient sample for diagnostics and clinical trials.

Early-stage Alzheimer’s disease profiling in blood achieved by multiplexing aptamer-SERS biosensors

Neurological disorders are the second leading cause of death globally, with Alzheimer’s disease (AD) emerging as a significant contributor, responsible for 276 million cases in disability-adjusted life years. Conventional diagnostic methods are often invasive, costly, and place a considerable strain on global healthcare systems. In this study, we presented an innovative and efficient strategy for AD assessment through blood profiling using a multiwell glass chip integrated with aptamer-based surface-enhanced Raman scattering (SERS) biosensors. High-affinity aptamers were selected using capillary electrophoresis-based systematic evolution of ligands by exponential enrichment (CE-SELEX). A mouse brain injury model was employed to systematically investigate biomarkers indicative of physiological, vascular, and cellular damage, such as neurogranin (Nrgn), angiopoietin-2 (Angio-2), PRDX3, lactate dehydrogenase (L-LDH), and τ-441, which were quantified at atto-molar levels in blood samples. Additionally, with the aid of CT-scan imaging, an aptamer-SERS assay was developed to evaluate the dynamic regulation of AD biomarkers. The aptamer-SERS biosensor system was also applied to human samples, demonstrating its capability to multiplex AD biomarkers and establish a time-dependent correlation between percentage biomarker regulation and disease progression. The innovative design, fabrication of aptamer-SERS nanoprobes, and the bio-sensing outcomes illustrate the strong potential of this approach for selective, sensitive, and quantitative early-stage AD diagnosis in clinical applications.

Lecanemab's Path Forward: Navigating the Future of Alzheimer's Treatment in Europe Amidst the EMA's Rejection.

Lecanemab (Leqembi©, Biogen), a humanized anti-amyloid-beta monoclonal antibody, has been approved for early-stage Alzheimer's disease (AD) in several countries, including the US and Japan. However, the European Medicines Agency (EMA) recently issued a negative opinion on its marketing authorization, reflecting concerns over the clinical value and manageability of anti-amyloid treatments. This decision highlights the ongoing disconnect between research advancements and clinical practice, where the focus on biological markers over tangible clinical improvements remains contentious. Despite promising biological effects, lecanemab's clinical outcomes have been modest, raising questions about its therapeutic role. The EMA's refusal underscores the need to address doubts surrounding the real-world effectiveness and safety of such treatments, especially concerning amyloid-related imaging abnormalities (ARIAs), a common side effect observed in clinical trials. The recent approval of lecanemab by the UK's Medicines and Healthcare products Regulatory Agency, despite the National Institute for Health and Care Excellence's rejection on cost-effectiveness grounds, further fuels the debate on the feasibility of anti-amyloid therapies. This commentary emphasizes the importance of real-world data on lecanemab's impact on cognitive decline, daily functioning, and side-effect management. As the global clinical use of lecanemab increases, continuous and standardized reporting on its outcomes is crucial for guiding future regulatory decisions and for potentially bridging the gap between research and practice in AD treatment.

Xanthohumol Protects Against Neuronal Excitotoxicity and Mitochondrial Dysfunction in APP/PS1 Mice: An Omics-Based Study.

Background: Neuronal excitotoxicity and metabolic decline, which begin in the early stages of Alzheimer's disease (AD), pose challenges for effective amelioration. Our previous work suggested that the natural compound xanthohumol, the most abundant prenylated flavonoid in hops, prevents memory deficits in APP/PS1 mice; however, the underlying mechanisms remain unclear. Methods: This study utilized APP/PS1 mice and cutting-edge omics techniques to investigate the effects of xanthohumol on hippocampal proteome, serum metabolome, and microbiome. Results: Our findings revealed that xanthohumol reduces the postsynaptic overexpression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid, N-methyl-D-aspartate, and metabotropic glutamate receptors, but enhances ATP synthesis and mitophagy in the young AD hippocampus. Further mechanistic analyses suggested systemic regulatory effects, particularly on the decreasing glutamate synthesis in the blood and intestines of AD mice following xanthohumol administration. Conclusions: These results underscore the potential of xanthohumol in mitigating AD pathology through multifaceted mechanisms, sparking interest and curiosity in its preventive and therapeutic potential in AD.

Chemogenetic neuronal silencing decouples c-Jun activation from cell death in the temporal cortex.

Initial symptoms of neurodegenerative diseases are often defined by the loss of the most vulnerable neural populations specific to each disorder. In the early stages of Alzheimer's disease, vulnerable circuits in the temporal lobe exhibit diminished activity prior to overt degeneration. It remains unclear whether these functional changes contribute to regional vulnerability or are simply a consequence of pathology. We previously found that entorhinal neurons in the temporal cortex undergo cell death following transient suppression of electrical activity, suggesting a causal role for activity disruption in neurodegeneration. Here we demonstrate that electrical arrest of this circuit stimulates the injury-response transcription factor c-Jun. Entorhinal silencing induces transcriptional changes consistent with c-Jun activation that share characteristics of gene signatures in other neuronal populations vulnerable to Alzheimer's disease. Despite its established role in the neuronal injury response, inhibiting c-Jun failed to ameliorate entorhinal degeneration following activity disruption. Finally, we present preliminary evidence of integrated stress response activity that may serve as an alternative hypothesis to what drives entorhinal degeneration after silencing. Our data demonstrate that c-Jun is activated in response to neuronal silencing in the entorhinal cortex but is decoupled from subsequent neurodegeneration.

A timeline study on vascular co-morbidity induced cerebral endothelial dysfunction assessed by perfusion MRI

Endothelial dysfunction is considered a key element in the early pathogenesis of neurodegenerative disorders. Dysfunction of the cerebral endothelial cells can result in dysregulation of cerebral perfusion and disruption of the Blood Brain Barrier (BBB), leading to brain damage, neurodegeneration and cognitive decline. It has been shown that the presence of modifiable risk factors exacerbates endothelial dysfunction. This study primarily aimed to identify which among various perfusion MRI methodologies could be effectively utilized to non-invasively identify early pathological alterations as a result of endothelial dysfunction. We compared these perfusion MRI measurements to invasive immunohistochemistry to detect early pathological alterations in the cerebral vasculature of a rat model of multiple cardiovascular co-morbidities (the ZSF1 Obese rat) at several stages of the cerebrovascular pathology. We observed cerebral hyperperfusion, expressed by increased Cerebral Blood Flow (CBF) and increased BBB permeability in the ZSF1 Obese rats, at an early stage of disease development. The increase in CBF observed with Arterial Spin Labeling (ASL) was lost during later stages of disease progression. These findings are in line with recent clinical findings in early stages of Alzheimer's disease (AD), that also show early increases in CBF.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease.

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau positron emission tomography (PET) in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16), logopenic variant Primary Progressive Aphasia (n = 15), and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent magnetic resonance imaging (MRI), tau PET, and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = .10), tau in other functional networks (R2 = .11-.26), and the magnitude of cortical atrophy (R2 = .20) and amyloid burden (R2 = .09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients one year later. This simple measure could aid the development of a personalized prognostic, monitoring, and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

The Effect of Segmentation Method on Medial Temporal Lobe Subregion Volumes in Aging.

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA2/CA3/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas.

A comparative study of early stage Alzheimer’s disease classification using various transfer learning CNN frameworks

ABSTRACT The current research explores the improvements in predictive performance and computational efficiency that machine learning and deep learning methods have made over time. Specifically, the application of transfer learning concepts within Convolutional Neural Networks (CNNs) has proved useful for diagnosing and classifying the various stages of Alzheimer’s disease. Using base architectures such as Xception, InceptionResNetV2, DenseNet201, InceptionV3, ResNet50, and MobileNetV2, this study extends these models by adding batch normalization (BN), dropout, and dense layers. These enhancements improve the model’s effectiveness and precision in addressing the specified medical issue. The proposed model is rigorously validated and evaluated using publicly available Kaggle MRI Alzheimer’s data consisting of 1280 testing images and 5120 patient training images. For comprehensive performance evaluation, precision, recall, F1-score, and accuracy metrics are utilized. The findings indicate that the Xception method is the most promising of those considered. Without employing five K-fold techniques, this model obtains a 99% accuracy and 0.135 loss score. In addition, integrating five K-fold methods enhances the accuracy to 99.68% while decreasing the loss score to 0.120. The research further included the evaluation of the Receiver Operating Characteristic Area Under the Curve (ROC-AUC) for various classes and models. As a result, our model may detect and diagnose Alzheimer’s disease quickly and accurately.

B-236 New real-time PCR test for APOE genotyping in patients with Alzheimer’s disease before anti-amyloid therapy

Abstract Background In 2023, the US Food and Drug Administration approved LEQEMBI, a monoclonal antibody therapy targeting beta-amyloid plaques, for patients with early-stage Alzheimer’s disease (AD). However, anti-amyloid drug trials demonstrated an elevated risk for amyloid-related imaging abnormalities with cerebral edema (ARIA-E) in carriers of the AD risk allele apolipoprotein E epsilon 4 (APOE-ɛ4), especially in ɛ4/ɛ4 homozygous individuals [1-3]. Here, we report on the evaluation of a new real-time polymerase chain reaction (PCR) test for APOE genotyping. Methods The EURORealTime APOE (EUROIMMUN), which enables simultaneous testing for all six APOE genotypes (ɛ2/ɛ2, ɛ2/ɛ3, ɛ2/ɛ4, ɛ3/ɛ3, ɛ3/ɛ4, and ɛ4/ɛ4) by real-time PCR, was performed using genomic DNA (gDNA) isolated from EDTA blood samples. The PCR amplification results were evaluated using the EURORealTime Analysis Software (EUROIMMUN). Samples from healthy blood donors (HBD) were used to assess intra-assay, inter-assay and between-lot precision (n=6) as well as analytical sensitivity (n=21), with each APOE genotype represented by at least one sample. Assay accuracy was analyzed by comparing genotype assignments to the results of the CE-IVD-marked EUROArray APOE (EUROIMMUN) and bidirectional Sanger sequencing using 110 samples (100 AD, 10 HBD). APOE genotype frequencies were compared between patients (100 AD) and controls (250 HBD). Results Precision testing of the EURORealTime APOE resulted in 100% correct genotype calls. Assessment of the analytical sensitivity revealed valid and correct genotype assignment in all 21 samples, confirming 1 ng/µl as the recommended minimum gDNA concentration. The analytical accuracy amounted to 100% based on agreement with the two reference methods in 110/110 cases. Comparison of the APOE genotype distribution showed a higher proportion of ɛ4 allele carriers (i.e., ɛ2/ɛ4, ɛ3/ɛ4, and ɛ4/ɛ4) in AD patients than in HBD (50.0% vs. 25.2%). The prevalence of the ɛ4/ɛ4 genotype in these cohorts was 25.0% for AD patients compared with 2.8% for HBD. Conclusions The well-established high prevalence of the APOE-ɛ4/ɛ4 genotype in AD patients, together with the increased risk of ARIA-E in these homozygous carriers, substantiates the relevance of APOE genotyping prior to anti-amyloid treatment. The EURORealTime APOE test provides sensitive and reliable determination of APOE alleles, thus presenting a suitable tool to improve risk stratification for potential LEQEMBI recipients.

Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis

Alzheimer's is one of the brain syndromes that steadily affects the brain memory. The early stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the growth of Alzheimer's is not certain in patients with MCI. The premature detection of Alzheimer's is crucial for maintaining healthy brain function and avoiding memory loss. Different multi-neural network architectures have been proposed by researchers for efficient and accurate AD detection. The absence of improved feature extraction mechanisms and unexplored efficient optimizers in complex benchmark architectures lead to an inefficient and inaccurate AD classification. Moreover, the standard convolutional neural network (CNN)-based architectures for Alzheimer's diagnosis lack interpretability in their predictions. An interpretable, simplified, yet effective deep learning model is required for the accurate classification of AD. In this study, a generalized fractional order-based CNN classifier with explainable artificial intelligence (XAI) capabilities is proposed for accurate, efficient, and interpretable classification of AD diagnosis. The proposed study (a) classifies AD accurately by incorporating unexplored pooling technique with enhanced feature extraction mechanism, (b) provides fractional order-based optimization approach for adaptive learning and fast convergence speed, and (c) suggests an interpretable method for proving the transparency of the model. The proposed model outperforms complex benchmark architectures with regard to accuracy using standard ADNI dataset. The proposed fractional order-based CNN classifier achieves an improved accuracy of 99 % as compared to the state-of-the-art models.

Biomarker Profiles in Serum and CSF for Early Diagnosis of Selected Neurodegenerative Diseases

Biomarker research and justification for neurodegenerative illnesses have seen enormous efforts over the last ten years. Bio-fluid-based biomarkers have been believed to provide a better and easier approach to detecting biomarkers for diagnosing nervous system pathologies. Objectives: To evaluate the diagnostic potential of certain biomarkers in serum and cerebrospinal fluid to diagnose Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease at an initial stage. Methods: 280 participants were taken and distributed into four groups, comprising, 70 patients with early-stage Alzheimer’s disease, 70 with early-stage Parkinson’s disease, 70 with early-stage Huntington’s disease, and 70 age-matched healthy controls. Blood and cerebrospinal fluid samples were drawn and medical history was taken from the patients. Serum and cerebrospinal fluid levels of amyloid-beta (Aβ42), total tau (t-tau), phosphorylated tau (p-tau), alpha-synuclein, huntingtin protein, and neuro-filament light chain were evaluated using enzyme-linked immunosorbent assays. Results: Alzheimer’s disease patients showed reduced serum Aβ42 (80.4 ± 15.6 pg/mL) and elevated t-tau (140.5 ± 18.2 pg/mL). Parkinson’s disease patients had raised serum alpha-synuclein (12.5 ± 2.3 ng/mL) and neuro-filament light chain. Huntington’s disease patients showed significant increases in serum huntingtin protein (8.2 ± 2.0 ng/mL). These profiles indicate efficacy in early diagnosis. Conclusions: It was concluded that Aβ42 and tau effectively detect Alzheimer’s disease, while Parkinson’s disease patients can be effectively diagnosed with Serum and cerebrospinal fluid levels of the neuro-filament light chain. Similarly, huntingtin protein and neuro-filament light chain are sensitive enough to detect Huntington’s disease at its early stages.

Detection of sex-specific glutamate changes in subregions of hippocampus in an early-stage Alzheimer's disease mouse model using GluCEST MRI.

Regional glucose hypometabolism resulting in glutamate loss has been shown as one of the characteristics of Alzheimer's disease (AD). Because the impact of AD varies between the sexes, we utilized glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) for high-resolution spatial mapping of cerebral glutamate and investigated subregional changes in a sex-specific manner. Eight-month-old male and female AD mice harboring mutant amyloid precursor protein (APPNL-F/NL-F: n = 36) and wild-type (WT: n = 39) mice underwent GluCEST MRI, followed by proton magnetic resonance spectroscopy (1H-MRS) in hippocampus and thalamus/hypothalamus using 9.4T preclinical MR scanner. GluCEST measurements revealed significant (p≤0.02) glutamate loss in the entorhinal cortex (% change ± standard error: 8.73±2.12%), hippocampus (11.29±2.41%), and hippocampal fimbriae (19.15±2.95%) of male AD mice. A similar loss of hippocampal glutamate in male AD mice (11.22±2.33%; p = 0.01) was also observed in 1H-MRS. GluCEST MRI detected glutamate reductions in the fimbria and entorhinal cortex of male AD mice, which was not reported previously. Resilience in female AD mice against these changes indicates an intact status of cerebral energy metabolism. Glutamate levels were monitored in different brain regions of early-stage Alzheimer's disease (AD) and wild-type male and female mice using glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI). Male AD mice exhibited significant glutamate loss in the hippocampus, entorhinal cortex, and the fimbriae of the hippocampus. Interestingly, female AD mice did not have any glutamate loss in any brain region and should be investigated further to find the probable cause. These findings demonstrate previously unreported sex-specific glutamate changes in hippocampal sub-regions using high-resolution GluCEST MRI.

A prediction model of dementia conversion for mild cognitive impairment by combining plasma pTau181 and structural imaging features.

The early stages of Alzheimer's disease (AD) are no longer insurmountable. Therefore, identifying at-risk individuals is of great importance for precise treatment. We developed a model to predict cognitive deterioration in patients with mild cognitive impairment (MCI). Based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we constructed models in a derivation cohort of 761 participants with MCI (138 of whom developed dementia at the 36th month) and verified them in a validation cohort of 353 cognitively normal controls (54 developed MCI and 19 developed dementia at the 36th month). In addition, 1303 participants with available AD cerebrospinal fluid core biomarkers were selected to clarify the ability of the model to predict AD core features. We assessed 32 parameters as candidate predictors, including clinical information, blood biomarkers, and structural imaging features, and used multivariable logistic regression analysis to develop our prediction model. Six independent variables of MCI deterioration were identified: apolipoprotein E ε4 allele status, lower Mini-Mental State Examination scores, higher levels of plasma pTau181, smaller volumes of the left hippocampus and right amygdala, and a thinner right inferior temporal cortex. We established an easy-to-use risk heat map and risk score based on these risk factors. The area under the curve (AUC) for both internal and external validations was close to 0.850. Furthermore, the AUC was above 0.800 in identifying participants with high brain amyloid-β loads. Calibration plots demonstrated good agreement between the predicted probability and actual observations in the internal and external validations. We developed and validated an accurate prediction model for dementia conversion in patients with MCI. Simultaneously, the model predicts AD-specific pathological changes. We hope that this model will contribute to more precise clinical treatment and better healthcare resource allocation.

Serial Cerebrospinal Fluid Sampling Reveals Trajectories of Potential Synaptic Biomarkers in Early Stages of Alzheimer's Disease.

Synaptic dysfunction is closely associated with cognitive function in Alzheimer's disease (AD), and is present already in an early stage of the disease. Using serial cerebrospinal fluid (CSF) sampling, we aimed to investigate slopes of CSF synaptic proteins, and their relation with cognition along the AD continuum. We included subjects with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) (n = 50 amyloid-β+ [A +], n = 50 A-) and 50 patients with AD dementia from the Amsterdam dementia cohort, with CSF at two time points (median[IQR] 2.1[1.4-2.7] years). We analyzed 17 synaptic proteins and neurofilament light (NfL). Using linear mixed models we assessed trajectories of protein levels, and associations with cognitive decline (repeated Mini-Mental State Examination). We used Cox regression models to assess predictive value of protein levels for progression to AD dementia. At baseline most proteins showed increased levels in AD dementia compared to the other groups. In contrast NPTX2 levels were lower in AD dementia. Higher baseline levels of SNAP25, β-syn, and 14-3-3 proteins were associated with faster cognitive decline (St.B[SE] -0.27[0.12] to -0.61[0.12]). Longitudinal analyses showed that SYT1 and NPTX levels decreased over time in AD dementia (st.B[SE] -0.10[0.04] to -0.15[0.05]) and SCD/MCI-A+ (St.B[SE] -0.07[0.03] to -0.12[0.03]), but not in SCD/MCI-A- (pinteraction < 0.05). Increase over time in NfL levels was associated with faster cognitive decline in AD dementia (St.B[SE] -1.75[0.58]), but not in the other groups (pinteraction < 0.05). CSF synaptic proteins showed different slopes over time, suggesting complex synaptic dynamics. High levels of especially SNAP-25 may have value for prediction of cognitive decline in early AD stages, while increase in NfL over time correlates better with cognitive decline in later stages.

Regional Variability in MRI Scans with Different Magnetic Field Strengths in Japan: Implications for Healthcare Preparedness for Alzheimer's Disease Treatment.

(1) Background: The 2023 approval of lecanemab for early-stage Alzheimer's disease (AD) highlighted the need for routine 1.5T or 3.0T MRI scans to monitor amyloid-related imaging abnormalities (ARIAs). Regional disparities in MRI scan frequency, MRI scanner availability, and scanner magnetic field strengths could affect readiness for anti-amyloid therapy and lead to inconsistencies in ARIA detection nationwide. (2) Methods: We assessed regional variance in MRI scan frequency and field strength across Japan using the National Database (NDB) Open Data website, which summarizes Japanese public health insurance claims from the fiscal years (FYs) 2015 to 2021. We employed a mixed-effects model with prefecture-level random intercepts and slopes over time, subsequently categorizing prefectures into clusters based on MRI usage. (3) Results: 1.5T MRI was the most common magnetic field strength, remaining stable from FY2015 to FY2021. 3.0T MRI usage slightly increased, although the COVID-19 pandemic in FY2020 led to a maximum reduction of 5%. Prefecture-level variance was higher for 3.0T MRIs, with more frequent usage in western Japan. (4) Conclusions: This study highlights prefecture-level variance in MRI usage across Japan. The insights gained could be instrumental in improving healthcare preparedness for anti-amyloid treatment and patient management.

Tau pathology in the dorsal raphe may be a prodromal indicator of Alzheimer's disease.

Protein aggregation in brainstem nuclei is thought to occur in the early stages of Alzheimer's disease (AD), but its specific role in driving prodromal symptoms and disease progression is largely unknown. The dorsal raphe nucleus (DRN) contains a large population of serotonin (5-hydroxytryptamine; 5-HT) neurons that regulate mood, reward-related behavior, and sleep, which are all disrupted in AD. We report here that tau pathology is present in the DRN of individuals 25-80 years old without a known history of dementia, and its prevalence was comparable to the locus coeruleus (LC). By comparison, fewer cases were positive for other pathological proteins including α-synuclein, β-amyloid, and TDP-43. To evaluate how early tau pathology impacts behavior, we overexpressed human P301L-tau in the DRN of mice and observed depressive-like behaviors and hyperactivity without deficits in spatial memory. Tau pathology was predominantly found in neurons relative to glia and colocalized with a significant proportion of Tph2-expressing neurons in the DRN. 5-HT neurons were also hyperexcitable in P301L-tauDRN mice, and there was an increase in the amplitude of excitatory post-synaptic currents (EPSCs). Moreover, astrocytic density was elevated in the DRN and accompanied by an increase in IL-1α and Frk expression, which suggests increased inflammatory signaling. Additionally, tau pathology was detected in axonal processes in the thalamus, hypothalamus, amygdala, and caudate putamen. A significant proportion of this tau pathology colocalized with the serotonin reuptake transporter (SERT), suggesting that tau may spread in an anterograde manner to regions outside the DRN. Together these results indicate that tau pathology accumulates in the DRN in a subset of individuals over 50 years and may lead to behavioral dysregulation, 5-HT neuronal dysfunction, and activation of local astrocytes which may be prodromal indicators of AD.

Common and proper nouns in mild Alzheimer’s disease

Introduction Disturbance in naming accuracy and reaction time (RT) is one of the early symptoms of Alzheimer’s disease. Naming performance can be considered a diagnostic key in the early stages of Alzheimer’s disease (AD), which has remained diagnostically challenging. Although most of the studies in this field have been conducted on the naming accuracy of common nouns, others have shown that proper nouns are more sensitive for detecting the onset of AD. This study aims to compare the naming of common and proper nouns. Method Eighty pictures of common and proper nouns (40 items each) were presented to 18 healthy older adults and 18 people with mild Alzheimer’s disease using DMDX software on a laptop computer. The patients’ responses were transcribed into a pre-designed form, and their reaction times were captured by DMDX. Results Study results indicated a significant difference in the number of errors and RTs between proper and common nouns in patients with mild Alzheimer’s disease (p-value=), implying that proper nouns may be more sensitive to mild AD. Moreover, patients with mild Alzheimer’s had more problems in common and proper nouns than healthy older adults. Conclusion This study demonstrated that individuals with mild AD experienced greater difficulty recalling proper nouns, which were found to be more susceptible to the effects of AD.