Early Stages Of Alzheimer's Disease Research Articles

Examining iron-related off-target binding effects of 18F-AV1451 PET in the cortex of Aβ+ individuals.

The presence of neurofibrillary tangles containing hyper-phosphorylated tau is a characteristic of Alzheimer's disease (AD) pathology. The positron emission tomography (PET) radioligand sensitive to tau neurofibrillary tangles (18F-AV1451) also binds with iron. This off-target binding effect may be enhanced in older adults on the AD spectrum, particularly those with amyloid-positive biomarkers. Here, we examined group differences in 18F-AV1451 PET after controlling for iron-sensitive measures from magnetic resonance imaging (MRI) and its relationships to tissue microstructure and cognition in 40 amyloid beta positive (Aβ+) individuals, 20 amyloid beta negative (Aβ-) with MCI and 31 Aβ- control participants. After controlling for iron, increased 18F-AV1451 PET uptake was found in the temporal lobe and hippocampus of Aβ+ participants compared to Aβ- MCI and control participants. Within the Aβ+ group, significant correlations were seen between 18F-AV1451 PET uptake and tissue microstructure and these correlations remained significant after controlling for iron. These findings indicate that off-target binding of iron to the 18F-AV1451 ligand may not affect its sensitivity to Aβ status or cognition in early-stage AD.

Protein Oxidation in Aging and Alzheimer's Disease Brain.

Proteins are essential molecules that play crucial roles in maintaining cellular homeostasis and carrying out biological functions such as catalyzing biochemical reactions, structural proteins, immune response, etc. However, proteins also are highly susceptible to damage by reactive oxygen species (ROS) and reactive nitrogen species (RNS). In this review, we summarize the role of protein oxidation in normal aging and Alzheimer's disease (AD). The major emphasis of this review article is on the carbonylation and nitration of proteins in AD and mild cognitive impairment (MCI). The oxidatively modified proteins showed a strong correlation with the reported changes in brain structure, carbohydrate metabolism, synaptic transmission, cellular energetics, etc., of both MCI and AD brains compared to the controls. Some proteins were found to be common targets of oxidation and were observed during the early stages of AD, suggesting that those changes might be critical in the onset of symptoms and/or formation of the pathological hallmarks of AD. Further studies are required to fully elucidate the role of protein oxidation and nitration in the progression and pathogenesis of AD.

An early-stage Alzheimer's disease detection using various imaging modalities and techniques – A mini-review

An early-stage Alzheimer's disease detection using various imaging modalities and techniques – A mini-review

Electroacupuncture regulates Rab5a-mediating NGF transduction to improve learning and memory ability in the early stage of AD mice.

Nerve growth factor (NGF) loss is a potential factor for the degeneration of basal forebrain cholinergic neurons (BFCNs) in Alzheimer's disease (AD), and Rab5a is a key regulatory molecule of NGF signaling transduction. Here, we investigated the changes of Rab5a in 5 × FAD mice and further explored the mechanism of Electroacupuncture (EA) treatment in improving cognition in the early stage of AD. The total Rab5a and Rab5a-GTP in 5-month-old 5 × FAD mice and wild-type mice were detected using WB and IP technologies. 5 × FAD mice were treated with EA at the Bai hui (DU20) and Shen ting (DU24) acupoints for 4 weeks and CRE/LOXP technology was used to confirm the role of Rab5a in AD mediated by EA stimulation. The Novel Object Recognition and Morris water maze tests were used to evaluate the cognitive function of 5 × FAD mice. The Nissl, immunohistochemistry, and Thioflavin S staining were used to observe pathological morphological changes in the basal forebrain circuit. The Golgi staining was used to investigate the synaptic plasticity of the basal forebrain circuit and WB technology was used to detect the expression levels of cholinergic-related and NGF signal-related proteins. The total Rab5a was unaltered, but Rab5a-GTP increased and the rab5a-positive early endosomes appeared enlarged in the hippocampus of 5 × FAD mice. Notably, EA reduced Rab5a-GTP in the hippocampus in the early stage of 5 × FAD mice. EA could improve object recognition memory and spatial learning memory by reducing Rab5a activity in the early stage of 5 × FAD mice. Moreover, EA could reduce Rab5a activity to increase NGF transduction and increase the levels of phosphorylated TrkA, AKT, and ERK in the basal forebrain and hippocampus, and increase the expression of cholinergic-related proteins, such as ChAT, vAchT, ChT1, m1AchR, and m2AchR in the basal forebrain and ChAT, m1AchR, and m2AchR in the hippocampus, improving synaptic plasticity in the basal forebrain hippocampal circuit in the early stage of 5 × FAD mice. Rab5a hyperactivation is an early pathological manifestation of 5 × FAD mice. EA could suppress Rab5a-GTP to promote the transduction of NGF signaling, and enhance the synaptic plasticity of the basal forebrain hippocampal circuit improving cognitive impairment in the early stage of 5 × FAD mice.

An Efficient Machine Learning Technique for Early Detection of Alzheimer’s Disease

Abstract: This paper presents an efficient machine learning technique for the early detection of Alzheimer's disease. This approach leverages a combination of feature extraction and selection methods, coupled with advanced machine learning algorithms, to accurately identify early-stage Alzheimer's disease from neuroimaging data. The proposed technique demonstrates high sensitivity and specificity, making it a promising tool for clinicians in the early diagnosis and management of Alzheimer's disease.

Advanced Recognizing and Categorizing System for Alzheimer's and Parkinson's Syndromes using CNN Algorithm and Clinical Data

Parkinson’s Disease (PD) and Alzheimer’s Disease (AD) are advancing neurodegenerative diseases that impact a large number of individuals globally. This study provides a novel method to identify and categorize individuals in the early stages of PD and AD by analyzing online handwriting structures, leveraging the current progress in Machine Learning (ML) in the medical domain. The research explores multiple data augmentation strategies to address the limited training information available for classifying neuro-degenerative disorders based on behavioral information. The study used a Convolutional Neural Network (CNN) classification as a foundation model by identifying essential radiomics characteristics from the T1-weighted Magnetic Resonance Imaging (MRI) data. The research explores data augmentation strategies designed explicitly for time-series information, such as online handwriting patterns, instead of standard methods used for hardware-based detection. This approach, with more validation, might assist in distinguishing between difficult instances of AD and PD that have a comparable mild motor and non-motor symptoms.

The NeuroProtect Formula: A Preventive Approach to AD Targeting the HIF-1/PI3K-AKT Signaling Pathway Evaluated through In Vivo, In Vitro, and Network Pharmacology Approaches.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder with limited options for reversing its middle-to-late stages. Early intervention is crucial to slow down disease progression. This study aimed to investigate the potential of the NeuroProtect (NP) formula, a combination of geniposide and Panax notoginseng saponins, in preventing AD. We evaluated the effects of the NP formula on amyloid plaque accumulation, neuronal degeneration, and molecular signaling pathways using in vivo and in vitro models. To predict functional pathways and potential downstream targets of NP intervention, we employed network pharmacology. The preventative impact of the NP formula was assessed using APP/PS1 mice. We conducted HE staining, ELISA assay, Golgi staining, and immunohistochemistry to detect the protective effect of NP. Additionally, cell experiments were performed to assess cell activity and target protein expression. Network pharmacology analysis revealed 145 drug-disease interactions and identified 5 core active targets associated with AD. Molecular docking results demonstrated strong binding affinity between the components of the NP formula (GP, GN-Rb1, GN-Rg1, NS-R1) and target proteins (STAT3, HIF1A, TLR4, mTOR, VEGFA). Notably, the binding energy between NS-R1 and mTOR was -11.4kcal/mol. Among the top 10 enriched KEGG pathways, the HIF-1 and PI3K-AKT signaling pathways were highlighted. In vivo experiments demonstrated that the NP formula significantly ameliorated pathological changes, decreased the Aβ42/Aβ40 ratio in the hippocampus and cortex, and increased dendritic spine density in the CA1 region during the early stage of AD. In vitro experiments further illustrated the NP formula's ability to reverse the inhibitory effects of Aβ25-35 on cell viability and regulate the expression of Tlr4, Mtor, Hif1a, Stat3, and Vegfa. Our findings suggest that NP exhibits neuroprotective effects during the early stages of AD, positioning it as a potential candidate for AD prevention. The NP formula may exert its preventive effects through the HIF-1/PI3K-AKT signaling pathway, with mTOR identified as a key target.

Corydalis ternata Nakai Alleviates Cognitive Decline in Alzheimer's Disease by Reducing β-Amyloid and Neuroinflammation.

Recently, natural herbs have gained increasing attention owing to their comparatively low toxicity levels and the abundance of historical medical documentation regarding their use. Nevertheless, owing to a lack of knowledge regarding these herbs and their compounds, attempts to find those that could be beneficial for treating diseases have often been ad hoc; thus, there is now a growing demand for an in silico method to identify beneficial herbs. In this study, we present a computational approach for identifying natural herbs specifically effective in treating cognitive decline in Alzheimer's disease (AD) sufferers, which analyzes the similarities between herbal compounds and known drugs targeting AD-related proteins. Our in silico method suggests that Corydalis ternata can improve cognitive decline in AD sufferers. Behavioral tests with an AD mouse model for the confirmation of the in silico prediction reveals that C. ternata significantly alleviated the cognitive decline (memory and motor functions) caused by neurodegeneration. Further pathology analyses reveal that C. ternata decreases the level of Aβ plaques, reduces neuroinflammation, and promotes autophagy flux, and thus C. ternata can be clinically effective for preventing mild cognitive impairment during the early stages of AD. These findings highlight the potential utility of our in silico method and the potential clinical application of the identified natural herb in treating and preventing AD.

Advancing Alzheimer's Disease Detection Harnessing Graph Convolutional Networks For Enhanced Early Identification

There is an urgent need for improved methods of early diagnosis in order to combat the devastating effects of Alzheimer's disease (AD), a major player among neurodegenerative diseases. Understanding the critical need for early detection to get the best possible therapy results, this research explores the use of the Graph Convolutional Networks (GCN) algorithm to detect early-stage Alzheimer's disease. The work captures detailed interactions between various brain areas by integrating neuro imaging data to generate brain connectivity diagrams. Improving GCN's performance in graph analysis, testing its discriminatory strength, and gauging its resilience on different datasets are the main aims of this study. We must study fresh and advanced methodologies since traditional diagnostic methods frequently fail to uncover subtle early-stage AD features. An exciting new direction for improving accuracy and enabling prompt intervention is the suggested GCN-based model, which aims to decode these subtle signals suggestive of AD. The research is in line with the overarching goal of improving the sensitivity and efficacy of AD diagnostic tools. There is a pressing need for more sophisticated methodology as traditional methods can miss small but significant changes in brain connections that occur before obvious symptoms. This study uses GCN to improve AD early detection methods, which might change the way the illness is diagnosed and treated forever.

Development of Improved Weighed Quantum Lion Optimization with Smooth Support Vector Machine for Alzheimer’s Disease

Accurate diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) was identified on an early stage is essential in the healthcare industry to stop degeneration. The Smooth Support Vector Machine (SSVM) model, Principal Component Analysis (PCA), feature extraction, and Magnetic Resonance Imaging (MRI) image prepossessing are the components for the diagnosis of AD is proposed in this research at early stage. To assist in the classifier's training, we proposed a novel Improved Weighed Quantum Lion Optimization (IWQLO). The SSVM parameters are specifically proposed to be optimized using a new Switching delayed Lion Optimization (SLO) algorithm. The IWQLO-SSVM approach was effectively used to classify AD and MCI utilizing MRI scans of the Alzheimer's disease Neuroimaging Initiative (ADNI) database and Outcome and Assessment Information Set (OASIS) database. For six example scenarios, the classification accuracy of our proposed method is acceptable. Testing show that the proposed approach improves the performance measures such as accuracy, precision, specificity, sensitivity and recall for detecting the early stage AD diagnosis.

Amyloid antibody therapy for early-stage Alzheimer's disease: a critical review of three recent trials.

Amyloid antibody therapy for early-stage Alzheimer's disease: a critical review of three recent trials.

Endothelial DR6 in blood-brain barrier malfunction in Alzheimer’s disease

The impairment of the blood-brain barrier (BBB) has been increasingly recognised as a critical element in the early pathogenesis of Alzheimer’s disease (AD), prompting a focus on brain endothelial cells (BECs), which serve as the primary constituents of the BBB. Death receptor 6 (DR6) is highly expressed in brain vasculature and acts downstream of the Wnt/β-catenin pathway to promote BBB formation during development. Here, we found that brain endothelial DR6 levels were significantly reduced in a murine model of AD (APPswe/PS1dE9 mice) at the onset of amyloid-β (Aβ) accumulation. Toxic Aβ25-35 oligomer treatment recapitulated the reduced DR6 in cultured BECs. We further showed that suppressing DR6 resulted in BBB malfunction in the presence of Aβ25-35 oligomers. In contrast, overexpressing DR6 increased the level of BBB functional proteins through the activation of the Wnt/β-catenin and JNK pathways. More importantly, DR6 overexpression in BECs was sufficient to rescue BBB dysfunction in vitro. In conclusion, our findings provide new insight into the role of endothelial DR6 in AD pathogenesis, highlighting its potential as a therapeutic target to tackle BBB dysfunction in early-stage AD progression.

Neuroinflammation increases oxygen extraction in a mouse model of Alzheimer’s disease

BackgroundNeuroinflammation, impaired metabolism, and hypoperfusion are fundamental pathological hallmarks of early Alzheimer’s disease (AD). Numerous studies have asserted a close association between neuroinflammation and disrupted cerebral energetics. During AD progression and other neurodegenerative disorders, a persistent state of chronic neuroinflammation reportedly exacerbates cytotoxicity and potentiates neuronal death. Here, we assessed the impact of a neuroinflammatory challenge on metabolic demand and microvascular hemodynamics in the somatosensory cortex of an AD mouse model.MethodsWe utilized in vivo 2-photon microscopy and the phosphorescent oxygen sensor Oxyphor 2P to measure partial pressure of oxygen (pO2) and capillary red blood cell flux in cortical microvessels of awake mice. Intravascular pO2 and capillary RBC flux measurements were performed in 8-month-old APPswe/PS1dE9 mice and wildtype littermates on days 0, 7, and 14 of a 14-day period of lipopolysaccharide-induced neuroinflammation.ResultsBefore the induced inflammatory challenge, AD mice demonstrated reduced metabolic demand but similar capillary red blood cell flux as their wild type counterparts. Neuroinflammation provoked significant reductions in cerebral intravascular oxygen levels and elevated oxygen extraction in both animal groups, without significantly altering red blood cell flux in capillaries.ConclusionsThis study provides evidence that neuroinflammation alters cerebral oxygen demand at the early stages of AD without substantially altering vascular oxygen supply. The results will guide our understanding of neuroinflammation’s influence on neuroimaging biomarkers for early AD diagnosis.

Automatic feature extraction with Vectorial Genetic Programming for Alzheimer’s Disease prediction through handwriting analysis

Alzheimer’s Disease (AD) is an incurable neurodegenerative disease that strongly impacts the lives of the people affected. Even if, to date, there is no cure for this disease, its early diagnosis helps to manage the course of the disease better with the treatments currently available. Even more importantly, an early diagnosis will also be necessary for the new treatments available in the future. Recently, machine learning (ML) based tools have demonstrated their effectiveness in recognizing people’s handwriting in the early stages of AD. In most cases, they use features defined by using the domain knowledge provided by clinicians. In this paper, we present a novel approach based on vectorial genetic programming (VE_GP) to recognize the handwriting of AD patients. VE_GP is an enhanced version of GP that can manage time series directly. We applied VE_GP to data collected using an experimental protocol, which was defined to collect handwriting data to support the development of ML tools for the early diagnosis of AD based on handwriting analysis. The experimental results confirmed the effectiveness of the proposed approach in terms of classification performance, size, and simplicity.

Cost-Effectiveness of Lecanemab for Individuals With Early-Stage Alzheimer Disease.

Little is known regarding the cost-effectiveness of lecanemab (Leqembi), a monoclonal antibody approved by the US Food and Drug Administration in January 2023 for the treatment of mild cognitive impairment (MCI) or mild dementia due to Alzheimer disease (AD). This study aims to quantify the cost-effectiveness of lecanemab and how it varies based on the accuracy of AD testing and individuals' APOE ε4 status. Seven alternative test-treat-target strategies defined by combinations of testing approaches (PET, CSF, or plasma assay), treatment choices (standard of care [SoC] alone or lecanemab in addition to SoC), and targeting strategies (targeting APOE ε4 noncarriers or heterozygous patients or not) were compared. A hybrid decision tree-Markov cohort model was constructed with 5 states: (1) MCI (Clinical Dementia Rating-Sum of Boxes [CDR-SB] 0-4.5); (2) mild dementia (CDR-SB 4.6-9.5); (3) moderate dementia (CDR-SB 9.6-16); (4) severe dementia (CDR-SB >16); and (5) death. Effectiveness was measured by quality-adjusted life years and costs from third-party and societal perspectives were estimated in 2022 US dollars over a lifetime horizon. Among the 7 test-treat-target strategies, SoC alone was the optimal strategy from a cost-effectiveness perspective. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype was cost-effective vs SoC alone, regardless of the test used to diagnose patients with early-stage AD. However, CSF assay followed by targeted treatment would become cost-effective if lecanemab is priced below $5,100 per year. These results were robust to the accuracy of diagnostic testing and rates of lecanemab discontinuation and adverse events. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype is cost-effective vs SoC alone for patients with MCI or mild dementia due to AD. Lecanemab would be cost-effective in some settings if priced below $5,100 per year.

Early altered directionality of resting brain network state transitions in the TgF344-AD rat model of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease resulting in memory loss and cognitive decline. Synaptic dysfunction is an early hallmark of the disease whose effects on whole-brain functional architecture can be identified using resting-state functional MRI (rsfMRI). Insights into mechanisms of early, whole-brain network alterations can help our understanding of the functional impact of AD's pathophysiology. Here, we obtained rsfMRI data in the TgF344-AD rat model at the pre- and early-plaque stages. This model recapitulates the major pathological and behavioral hallmarks of AD. We used co-activation pattern (CAP) analysis to investigate if and how the dynamic organization of intrinsic brain functional networks states, undetectable by earlier methods, is altered at these early stages. We identified and characterized six intrinsic brain states as CAPs, their spatial and temporal features, and the transitions between the different states. At the pre-plaque stage, the TgF344-AD rats showed reduced co-activation of hub regions in the CAPs corresponding to the default mode-like and lateral cortical network. Default mode-like network activity segregated into two distinct brain states, with one state characterized by high co-activation of the basal forebrain. This basal forebrain co-activation was reduced in TgF344-AD animals mainly at the pre-plaque stage. Brain state transition probabilities were altered at the pre-plaque stage between states involving the default mode-like network, lateral cortical network, and basal forebrain regions. Additionally, while the directionality preference in the network-state transitions observed in the wild-type animals at the pre-plaque stage had diminished at the early-plaque stage, TgF344-AD animals continued to show directionality preference at both stages. Our study enhances the understanding of intrinsic brain state dynamics and how they are impacted at the early stages of AD, providing a nuanced characterization of the early, functional impact of the disease's neurodegenerative process.

5-HT4 receptor agonists treatment reduces tau pathology and behavioral deficit in the PS19 mouse model of tauopathy.

Accumulation of tau in synapses in the early stages of Alzheimer's disease (AD) has been shown to cause synaptic damage, synaptic loss, and the spread of tau pathology through trans-synaptically connected neurons. Moreover, synaptic loss correlates with a decline in cognitive function, providing an opportunity to investigate therapeutic strategies to target synapses and synaptic tau to rescue or prevent cognitive decline in AD. One of the promising synaptic targets is the 5-HT4 serotonergic receptor present postsynaptically in the brain structures involved in the memory processes. 5-HT4R stimulation exerts synaptogenic and pro-cognitive effects involving synapse-to-nucleus signaling essential for synaptic plasticity. However, it is not known whether 5-HT4R activation has a therapeutic effect on tau pathology. The goal of this study was to investigate the impact of chronic stimulation of 5-HT4R by two agonists, prucalopride and RS-67333, in PS19 mice, a model of tauopathy. We utilized gradient assays to isolate pre- and post-synaptic compartments, followed by biochemical analyses for tau species and ubiquitinated proteins in the synaptic compartments and total brain tissue. Next, we performed kinetic assays to test the proteasome's hydrolysis capacity in treatment conditions. Moreover, behavioral tests such as the open field and non-maternal nest-building tests were used to evaluate anxiety-like behaviors and hippocampal-related cognitive functioning in the treatment paradigm. Our results show that 5-HT4R agonism reduced tauopathy, reduced synaptic tau, increased proteasome activity, and improved cognitive functioning in PS19 mice. Our data suggest that enhanced proteasome activity by synaptic mediated signaling leads to the enhanced turnover of tau initially within synapses where the receptors are localized, and over time, the treatment attenuated the accumulation of tau aggregation and improved cognitive functioning of the PS19 mice. Therefore, stimulation of 5-HT4R offers a promising therapy to rescue synapses from the accumulation of toxic synaptic tau, evident in the early stages of AD.

Impact of PET Reconstruction on Amyloid-β Quantitation in Cross-Sectional and Longitudinal Analyses.

Amyloid-β (Aβ) accumulation in Alzheimer disease (AD) is typically measured using SUV ratio and the centiloid (CL) scale. The low spatial resolution of PET images is known to degrade quantitative metrics because of the partial-volume effect. This article examines the impact of spatial resolution, as determined by the reconstruction configuration, on the Aβ PET quantitation in both cross-sectional and longitudinal data. Methods: The cross-sectional study involved 89 subjects with 20-min [18F]florbetapir scans generated on an mCT (44 Aβ-negative [Aβ-], 45 Aβ-positive [Aβ+]) using 69 reconstruction configurations, which varied in number of iteration updates, point-spread function, time-of-flight, and postreconstruction smoothing. The subjects were classified as Aβ- or Aβ+ visually. For each reconstruction, Aβ CL was calculated using CapAIBL, and the spatial resolution was calculated as full width at half maximum (FWHM) using the barrel phantom method. The change in CLs and the effect size of the difference in CLs between Aβ- and Aβ+ groups with FWHM were examined. The longitudinal study involved 79 subjects (46 Aβ-, 33 Aβ+) with three 20-min [18F]flutemetamol scans generated on an mCT. The subjects were classified as Aβ- or Aβ+ using a cutoff CL of 20. All scans were reconstructed using low-, medium-, and high-resolution configurations, and Aβ CLs were calculated using CapAIBL. Since linear Aβ accumulation was assumed over a 10-y interval, for each reconstruction configuration, Aβ accumulation rate differences (ARDs) between the second and first periods were calculated for all subjects. Zero ARD was used as a consistency metric. The number of Aβ accumulators was also used to compare the sensitivity of CL across reconstruction configurations. Results: In the cross-sectional study, CLs in both the Aβ- and the Aβ+ groups were impacted by the FWHM of the reconstruction method. Without postreconstruction smoothing, Aβ- CLs increased for a FWHM of 4.5 mm or more, whereas Aβ+ CLs decreased across the FWHM range. High-resolution reconstructions provided the best statistical separation between groups. In the longitudinal study, the median ARD of low-resolution reconstructed data for the Aβ- group was greater than zero whereas the ARDs of higher-resolution reconstructions were not significantly different from zero, indicating more consistent rate estimates in the higher-resolution reconstructions. Higher-resolution reconstructions identified 10 additional Aβ accumulators in the Aβ- group, resulting in a 22% increased group size compared with the low-resolution reconstructions. Higher-resolution reconstructions reduced the average CLs of the negative group by 12 points. Conclusion: High-resolution PET reconstructions, inherently less impacted by partial-volume effect, may improve Aβ PET quantitation in both cross-sectional and longitudinal data. In the cross-sectional analysis, separation of CLs between Aβ- and Aβ+ cohorts increased with spatial resolution. Higher-resolution reconstructions also exhibited both improved consistency and improved sensitivity in measures of Aβ accumulation. These features suggest that higher-resolution reconstructions may be advantageous in early-stage AD therapies.

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease.

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aβ-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aβ-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

Corinthian Currants Promote the Expression of Paraoxonase-1 and Enhance the Antioxidant Status in Serum and Brain of 5xFAD Mouse Model of Alzheimer's Disease.

Paraoxonase-1 (PON1), a serum antioxidant enzyme, has been implicated in Alzheimer's disease (AD) pathogenesis that involves early oxidative damage. Corinthian currants and their components have been shown to display antioxidant and other neuroprotective effects in AD. We evaluated the effect of a Corinthian currant paste-supplemented diet (CurD), provided to 1-month-old 5xFAD mice for 1, 3, and 6 months, on PON1 activity and levels of oxidation markers in serum and the brain of mice as compared to a control diet (ConD) or glucose/fructose-matched diet (GFD). Administration of CurD for 1 month increased PON1 activity and decreased oxidized lipid levels in serum compared to ConD and GFD. Longer-term administration of CurD did not, however, affect serum PON1 activity and oxidized lipid levels. Furthermore, CurD administered for 1 and 3 months, but not for 6 months, increased PON1 activity and decreased free radical levels in the cortex of mice compared to ConD and GFD. To probe the mechanism for the increased PON1 activity in mice, we studied the effect of Corinthian currant polar phenolic extract on PON1 activity secreted by Huh-7 hepatocytes or HEK293 cells transfected with a PON1-expressing plasmid. Incubation of cells with the extract led to a dose-dependent increase of secreted PON1 activity, which was attributed to increased cellular PON1 expression. Collectively, our findings suggest that phenolics in Corinthian currants can increase the hepatic expression and activity of antioxidant enzyme PON1 and that a Corinthian currant-supplemented diet during the early stages of AD in mice reduces brain oxidative stress.