Different Stages Of Alzheimer's Disease Research Articles

Ouabain Ameliorates Alzheimer’s Disease-Associated Neuropathology and Cognitive Impairment in FAD4T Mice

Background: Alzheimer’s disease (AD) is a common clinical neurodegenerative disorder, primarily characterized by progressive cognitive decline and behavioral abnormalities. The hallmark pathological changes of AD include widespread neuronal degeneration, plaques formed by the deposition of amyloid β-protein (Aβ), and neurofibrillary tangles (NFTs). With the acceleration of global aging, the incidence of AD is rising year by year, making it a major global public health concern. Due to the complex pathology of AD, finding effective interventions has become a key focus of research. Ouabain (OUA), a cardiac glycoside, is well-known for its efficacy in treating heart disease. Recent studies have also indicated its potential in AD therapy, although its exact mechanism of action remains unclear. Methods: This study integrates bioinformatics, multi-omics technologies, and in vivo and in vitro experiments to investigate the effects of OUA on the pathophysiological changes of AD and its underlying molecular mechanisms. Results: This study analyzed the expression of the triggering receptor expressed on myeloid cells 2 (TREM2) across different stages of AD using bioinformatics. Serum samples from patients were used to validate soluble TREM2 (sTREM2) levels. Using an Aβ1-42-induced microglial cell model, we confirmed that OUA enhances the PI3K/AKT signaling pathway activation by upregulating TREM2, which reduces neuroinflammation and promotes the transition of microglia from an M1 proinflammatory state to an M2 anti-inflammatory state. To evaluate the in vivo effects of OUA, we assessed the learning and memory capacity of FAD4T transgenic mice using the Morris water maze and contextual fear conditioning tests. We used real-time quantitative PCR, immunohistochemistry, and Western blotting to measure the expression of inflammation-associated cytokines and to assess microglia polarization. OUA enhances cognitive function in FAD4T mice and has been confirmed to modulate microglial M1/M2 phenotypes both in vitro and in vivo. Furthermore, through bioinformatics analysis, molecular docking, and experimental validation, TREM2 was identified as a potential target for OUA. It regulates PI3K/Akt signaling pathway activation, playing a crucial role in OUA-mediated M2 microglial polarization and its anti-inflammatory effects in models involving Aβ1-42-stimulated BV-2 cells and FAD4T mice. Conclusions: These findings indicate that OUA exerts anti-neuroinflammatory effects by regulating microglial polarization, reducing the production of inflammatory mediators, and activating the PI3K/Akt signaling pathway. Given its natural origin and dual effects on microglial polarization and neuroinflammation, OUA emerges as a promising therapeutic candidate for neuroinflammatory diseases such as AD.

Early diagnosis of Alzheimer’s disease using a group self-calibrated coordinate attention network based on multimodal MRI

Convolutional neural networks (CNNs) for extracting structural information from structural magnetic resonance imaging (sMRI), combined with functional magnetic resonance imaging (fMRI) and neuropsychological features, has emerged as a pivotal tool for early diagnosis of Alzheimer’s disease (AD). However, the fixed-size convolutional kernels in CNNs have limitations in capturing global features, reducing the effectiveness of AD diagnosis. We introduced a group self-calibrated coordinate attention network (GSCANet) designed for the precise diagnosis of AD using multimodal data, including encompassing Haralick texture features, functional connectivity, and neuropsychological scores. GSCANet utilizes a parallel group self-calibrated module to enhance original spatial features, expanding the field of view and embedding spatial data into channel information through a coordinate attention module, which ensures long-term contextual interaction. In a four-classification comparison (AD vs. early MCI (EMCI) vs. late MCI (LMCI) vs. normal control (NC)), GSCANet demonstrated an accuracy of 78.70%. For the three-classification comparison (AD vs. MCI vs. NC), it achieved an accuracy of 83.33%. Moreover, our method exhibited impressive accuracies in the AD vs. NC (92.81%) and EMCI vs. LMCI (84.67%) classifications. GSCANet improves classification performance at different stages of AD by employing group self-calibrated to expand features receptive field and integrating coordinated attention to facilitate significant interactions among channels and spaces. Providing insights into AD mechanisms and showcasing scalability for various disease predictions.

Investigation of amyloid‑β peptide production and clearance pathways in different stages of Alzheimer's disease.

Alzheimer's disease (AD) is an age‑related, progressive decline in cognitive ability. Accumulation and deposition of amyloid‑β (Aβ) is still the best‑known cause of AD that worsens over time. It is unclear whether the increase in Aβ production or the inefficiency of the degradation system causes the accumulation of β‑fibrils during AD development. This research investigated Aβ‑producing and clearance pathways in different stages of AD. For this purpose, patients were categorized into four experimental groups: patients with mild cognitive impairment, patients with moderate cognitive decline, patients with very severe cognitive decline, and healthy patients as control. Levels of Aβ‑40, soluble amyloid precursor protein beta (sAPPβ), matrix metalloproteinase‑9 (MMP‑9), matrix metalloproteinase‑3 (MMP‑3), neprilysin (NEP), angiotensin‑converting enzyme (ACE), and insulin‑degrading enzyme (IDE) were determined by ELISA kits and immunoblotting in serum samples. According to the results, the levels of Aβ‑40 and sAPPβ increased in AD patients from an early stage, and levels were maintained in progressive AD stages. MMP‑9 also increased in the early stage, but its content decreased with disease development. MMP‑3 was significantly higher in the three stages of AD compared to the control patients. However, IDE, NEP, and ACE enzymes as clearing systems decreased in all studied AD samples, with their reductions more remarkable in the middle and late stages. The results showed that multiple Aβ‑degrading enzymes such as NEP and IDE in AD patients decline as AD progresses, while Aβ‑40 and sAPPβ increased from the early stage of the disease. Therefore, it could be concluded that detection of the dementia phase is a critical step for therapeutic strategies.

Computer-aided diagnosis of Alzheimer’s disease and neurocognitive disorders with multimodal Bi-Vision Transformer (BiViT)

Cognitive disorders affect various cognitive functions that can have a substantial impact on individual’s daily life. Alzheimer’s disease (AD) is one of such well-known cognitive disorders. Early detection and treatment of cognitive diseases using artificial intelligence can help contain them. However, the complex spatial relationships and long-range dependencies found in medical imaging data present challenges in achieving the objective. Moreover, for a few years, the application of transformers in imaging has emerged as a promising area of research. A reason can be transformer’s impressive capabilities of tackling spatial relationships and long-range dependency challenges in two ways, i.e., (1) using their self-attention mechanism to generate comprehensive features, and (2) capture complex patterns by incorporating global context and long-range dependencies. In this work, a Bi-Vision Transformer (BiViT) architecture is proposed for classifying different stages of AD, and multiple types of cognitive disorders from 2-dimensional MRI imaging data. More specifically, the transformer is composed of two novel modules, namely Mutual Latent Fusion (MLF) and Parallel Coupled Encoding Strategy (PCES), for effective feature learning. Two different datasets have been used to evaluate the performance of proposed BiViT-based architecture. The first dataset contain several classes such as mild or moderate demented stages of the AD. The other dataset is composed of samples from patients with AD and different cognitive disorders such as mild, early, or moderate impairments. For comprehensive comparison, a multiple transfer learning algorithm and a deep autoencoder have been each trained on both datasets. The results show that the proposed BiViT-based model achieves an accuracy of 96.38% on the AD dataset. However, when applied to cognitive disease data, the accuracy slightly decreases below 96% which can be resulted due to smaller amount of data and imbalance in data distribution. Nevertheless, given the results, it can be hypothesized that the proposed algorithm can perform better if the imbalanced distribution and limited availability problems in data can be addressed.Graphical abstract

Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer's Disease.

Alzheimer's disease (AD) is characterized by alterations of the brain's structural and functional connectivity during its progressive degenerative processes. Existing auxiliary diagnostic methods have accomplished the classification task, but few of them can accurately evaluate the changing characteristics of brain connectivity. In this work, a prior-guided adversarial learning with hypergraph (PALH) model is proposed to predict abnormal brain connections using triple-modality medical images. Concretely, a prior distribution from anatomical knowledge is estimated to guide multimodal representation learning using an adversarial strategy. Also, the pairwise collaborative discriminator structure is further utilized to narrow the difference in representation distribution. Moreover, the hypergraph perceptual network is developed to effectively fuse the learned representations while establishing high-order relations within and between multimodal images. Experimental results demonstrate that the proposed model outperforms other related methods in analyzing and predicting AD progression. More importantly, the identified abnormal connections are partly consistent with previous neuroscience discoveries. The proposed model can evaluate the characteristics of abnormal brain connections at different stages of AD, which is helpful for cognitive disease study and early treatment.

Beneficial versus Detrimental Effects of Complement-Microglial Interactions in Alzheimer's Disease.

Research indicates that brain-region-specific synapse loss and dysfunction are early hallmarks and stronger neurobiological correlates of cognitive decline in Alzheimer's disease (AD) than amyloid plaque and neurofibrillary tangle counts or neuronal loss. Even though the precise mechanisms underlying increased synaptic pruning in AD are still unknown, it has been confirmed that dysregulation of the balance between complement activation and inhibition is a crucial driver of its pathology. The complement includes three distinct activation mechanisms, with the activation products C3a and C5a, potent inflammatory effectors, and a membrane attack complex (MAC) leading to cell lysis. Besides pro-inflammatory cytokines, the dysregulated complement proteins released by activated microglia bind to amyloid β at the synaptic regions and cause the microglia to engulf the synapses. Additionally, research indicating that microglia-removed synapses are not always degenerating and that suppression of synaptic engulfment can repair cognitive deficits points to an essential opportunity for intervention that can prevent the loss of intact synapses. In this study, we focus on the latest research on the role and mechanisms of complement-mediated microglial synaptic pruning at different stages of AD to find the right targets that could interfere with complement dysregulation and be relevant for therapeutic intervention at the early stages of the disease.

Selenotranscriptome network in Alzheimer’s disease

The interplay between selenoproteins, oxidative stress, and cell death pathways holds promise in unravelling novel therapeutic targets for Alzheimer’s disease (AD) in the future. Nonetheless, further comprehensive investigations are warranted to fully comprehend the precise contributions of selenoproteins in the aetiology and potential therapeutic strategies for Alzheimer’s disease. Previous work into gene expression networks in AD has included analysis of the entire transcriptome and, as of yet, has not yielded consistent insight into pathological pathways.1 Despite the comprehensive assessment of the transcriptome enabled by current technologies, one drawback of the whole transcriptome analysis is the risk of overlooking subtle yet significant variations in metabolic pathways.2 Thus, we aimed to assess gene expression of known selenoprotein and selenium-containing pathways in two different brain regions (dorsolateral prefrontal cortex (DPC) and posterior cingulate cortex (PCC)) across the AD spectrum. We used RNA sequencing data from The Rush University’s Religious Orders Study and Memory and Aging Project (ROSMAP) cohort available in the AD Knowledge Portal (https://www.synapse.org/).3 This study included data available for a total of 889 DPC and 647 PCC samples. Four pathological phenotypes were determined based on pathology (CERAD) and clinical (CDR) status: AD ([(+) pathology, (+) clinical], prodromal disease, corresponding to donors that have not received a clinical diagnosis despite the presence of pathological alterations ([(+) pathology, (−) clinical], controls ([(−) pathology, (−) clinical] and non-AD dementia [(+) pathology, (+) clinical]. This last group was excluded from the analysis as it is assumed they may have been misdiagnosed or presented with non-AD dementia. Six selenium or AD-related pathways were assessed, accounting for 421 unique genes. Group comparisons were performed using linear mixed modelling adjusted for age, sex, APOEe4 status and batch via DESeq2 package with Benjamini-Hochberg adjustment for multiple testing. A total of 18 genes significantly differed between AD and controls in both brain areas (same direction in both brain areas; P < 0.05), including eight selenoprotein genes or genes directly associated with selenoprotein synthesis. Fifteen of them were also different (same direction) in PCC (seven selenoprotein/selenoprotein synthesis genes), and four were different in DPC (four selenoprotein/selenoprotein synthesis genes) between AD and prodromal. Only three genes significantly differed between prodromal and control samples (DPC), including the selenoprotein DIO3 and the transcription factor SP3. Our findings indicate a progressive change in gene expression across the different stages of AD. These findings shed light on critical genes involved in selenoprotein synthesis that play a role in AD pathogenesis. Restricting the analysis to a subset of pathways enabled the detection of smaller alterations between groups, which is particularly appropriate in trace element homeostasis, where small alterations may have significant downstream effects.

236 Association Between Gait Limitation and Alzheimer’s Disease: Comparison among Elderly in Puerto Rico and Mainland U.S.

OBJECTIVES/GOALS: In 2022, 116,000 Puerto Ricans were estimated to be affected by Alzheimer’s disease (AD). Gait limitation (GL) has been associated with different stages of AD. We study the GL-AD association in two elderly populations: Hispanics residing in PR and Americans in the mainland U.S., and identify the effects, and social determinants of health. METHODS/STUDY POPULATION: We propose a cross-sectional study involving data analysis from elderly (>65 years) Hispanics in PR and Americans in the U.S. Data will come from the National Alzheimer Coordinating Center (NACC) and a cohort of AD in PR. Our analysis will consider gait parameters, cognitive performance assessments, and AD stage (mild, moderate, and severe) as determined by the Alzheimer’s Association. We will examine social determinants of health and their association with GL and cognitive performance by AD. RESULTS/ANTICIPATED RESULTS: Our analysis will evaluate data about GL and AD stages to 1) investigate the association between GL and the distinct stages of AD and 2) evaluate the effects of social determinants of health in the association between GL and AD. We seek to profoundly understand how these factors interact within elderly populations. This exploration encompasses a diverse demographic, including elderly individuals in the U.S. and PR. We seek to identify disparities in social determinants among elderly individuals experiencing GL and AD by comparing PR and US populations. Through this association analysis, our study aspires to offer insight into the connections between GL and AD while considering the effects of social determinants of health in diverse populations. DISCUSSION/SIGNIFICANCE: The prevalence of AD is higher among Hispanic populations (e.g., Puerto Ricans) in the USA when compared to other ethnic groups. Experiencing GL may affect their daily lives, leading to exacerbating AD stages. The findings from this study will contribute to possible interventions to improve their GL and AD progression.

Plasma oligomer beta-amyloid is associated with disease severity and cerebral amyloid deposition in Alzheimer’s disease spectrum

BackgroundMultimer detection system-oligomeric amyloid-β (MDS-OAβ) is a measure of plasma OAβ, which is associated with Alzheimer’s disease (AD) pathology. However, the relationship between MDS-OAβ and disease severity of AD is not clear. We aimed to investigate MDS-OAβ levels in different stages of AD and analyze the association between MDS-OAβ and cerebral Aβ deposition, cognitive function, and cortical thickness in subjects within the AD continuum.MethodsIn this cross-sectional study, we analyzed a total 126 participants who underwent plasma MDS-OAβ, structural magnetic resonance image of brain, and neurocognitive measures using Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease, and cerebral Aβ deposition or amyloid positron emission tomography (A-PET) assessed by [18F] flutemetamol PET. Subjects were divided into 4 groups: N = 39 for normal control (NC), N = 31 for A-PET-negative mild cognitive impairment (MCI) patients, N = 30 for A-PET-positive MCI patients, and N = 22 for AD dementia patients. The severity of cerebral Aβ deposition was expressed as standard uptake value ratio (SUVR).ResultsCompared to the NC (0.803 ± 0.27), MDS-OAβ level was higher in the A-PET-negative MCI group (0.946 ± 0.137) and highest in the A-PET-positive MCI group (1.07 ± 0.17). MDS-OAβ level in the AD dementia group was higher than in the NC, but it fell to that of the A-PET-negative MCI group level (0.958 ± 0.103). There were negative associations between MDS-OAβ and cognitive function and both global and regional cerebral Aβ deposition (SUVR). Cortical thickness of the left fusiform gyrus showed a negative association with MDS-OAβ when we excluded the AD dementia group.ConclusionsThese findings suggest that MDS-OAβ is not only associated with neurocognitive staging, but also with cerebral Aβ burden in patients along the AD continuum.

Altered white matter functional pathways in Alzheimer's disease.

Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.

Sex differences in functional connectivity and the predictive role of the connectome-based predictive model in Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level.

Mental states in caregivers toward people with Alzheimer's disease at different stages.

Caring for people with Alzheimer's disease (AD) is burdensome, especially when family members act as caregivers. This multicenter survey first aimed to investigate caregivers' mental states as well as its influencing factors in caring for people with different severities of AD in China. People with AD and their caregivers from 30 provincial regions in mainland China were enrolled from October 2020 to December 2020 to be surveyed for caregivers' mental states and living conditions, as well as caregivers' attitudes toward treatment and caring. Logistic regression was used to explore the factors that influence the positive and negative states of caregivers who care for people with different stages of AD. A total of 1,966 valid questionnaires were analyzed (mild AD: 795, moderate AD: 521, severe AD: 650). A total of 73.6% of caregivers maintained normal states (mild group: 71.9%, moderate group: 73.9%, severe group: 75.2%; X2 = 2.023, p = 0.364), and the proportions of caregivers with positive and negative states were 26.3% (mild group: 38.4%, moderate group: 24.6%, severe group: 13.1%; X2 = 119.000, p < 0.001) and 36.5% (mild group: 25.2%, moderate group: 36.9%, severe group: 50.2%; X2 = 96.417, p < 0.001), respectively. The major factors that both influenced caregivers' positive and negative states were the severity of AD, perceived efficacy of treatment, safety issues after AD dementia diagnosis and perceived social support (p < 0.005), while neuropsychiatric symptoms causing stress in caregivers (p < 0.001) only affected the negative states of caregivers. The results of further analysis according to disease severity showed that safety issues after AD dementia diagnosis (p < 0.005) only made significant differences in the mild-to-moderate group. To reduce negative states and promote positive states among caregivers, flexible and sensitive caregiving support could be built on caregivers' demands in caring for people with different stages of AD. The support of emotion, social functioning and nursing skills is one of the significant ways for health workers to enhance caregivers' competency.

Multivariate pattern analysis of medical imaging-based Alzheimer's disease.

Alzheimer's disease (AD) is a devastating brain disorder that steadily worsens over time. It is marked by a relentless decline in memory and cognitive abilities. As the disease progresses, it leads to a significant loss of mental function. Early detection of AD is essential to starting treatments that can mitigate the progression of this disease and enhance patients' quality of life. This study aims to observe AD's brain functional connectivity pattern to extract essential patterns through multivariate pattern analysis (MVPA) and analyze activity patterns across multiple brain voxels. The optimized feature extraction techniques are used to obtain the important features for performing the training on the models using several hybrid machine learning classifiers for performing binary classification and multi-class classification. The proposed approach using hybrid machine learning classification has been applied to two public datasets named the Open Access Series of Imaging Studies (OASIS) and the AD Neuroimaging Initiative (ADNI). The results are evaluated using performance metrics, and comparisons have been made to differentiate between different stages of AD using visualization tools.

PET imagining in Alzheimer’s disease

Purpose. The purpose of this article is to explore the potential of positron emission tomography (PET) in early diagnosis of Alzheimer's disease (AD), monitoring of disease progression and assessment of treatment effectiveness. And also, to become familiar with advantages and disadvantages of application of various radiopharmaceuticals.&#x0D; Materials and methods. The material for the study was the scientific results of publications in professional scientific journals of the leading countries of the world of scientific and clinical activity over the past 10 years on the clinical significance of hybrid radiation imaging methods in the diagnosis and treatment of patients with AD. The study involved the use of PET radiation imaging methods in Alzheimer's disease.&#x0D; Results. The efficacy of PET at different stages of AD has been demonstrated. The advantages and disadvantages of using different PET techniques and different radiopharmaceuticals are discussed. PET, unlike other biomarkers, is able to assess the prevalence of lesions, evaluate progression and make a prediction of the further course of the disease.&#x0D; Conclusions. Positron emission tomography in patients with AD is an effective diagnostic technique that can be used at different stages from the prodromal period in the form of mild cognitive impairment to assessing the progression or effectiveness of treatment in numerous clinical trials.

The rat brain transcriptome: from infancy to aging and sporadic Alzheimer’s disease-like pathology

Functional traits of the adult brain, which are established early in life, may impact susceptibility to Alzheimer’s disease (AD). Results from prior research conducted on senescence-accelerated OXYS rats, a prominent model for sporadic AD, provide evidence in favor of this hypothesis. The present study examined the transcriptomes of the prefrontal cortex (PFC) and hippocampus in OXYS and Wistar rats (control) during the early postnatal period (at age P3 and P10; P: postnatal day of life) to identify the signaling pathways and processes that contribute to delayed brain maturation in OXYS rats and assess their potential role in the development of AD traits later in life. Next, we compared the differentially expressed genes (DEGs) in the rat PFC and hippocampus throughout the five stages of AD-like pathology, from infancy to the progressive stage. Additionally, we noted conspicuous variations between the strains in the number of DEGs throughout all five ages. Significant differences were found in the number of DEGs between OXYS rats and Wistar rats in both brain structures at both P3 and P10. Notably, changes in gene expression patterns in the PFC and hippocampus of OXYS rats at 3 and 10 days of age are broadly associated with all basic mechanisms involved in Alzheimer’s pathogenesis, which are modified in OXYS rats at different stages of AD. Gene expression changes at P3 and P10 are associated with molecular processes including neuronal plasticity, immune responses, cerebrovascular function, and mitochondrial function. Remarkably, changes in the expression of genes associated with Aβ function were detected. The expression profile of genes linked to APP processing in the brain of OXYS rats is reduced during the early postnatal period. An intriguing finding, with potential significance for the development of AD pathology, is the decreased expression of the Abca7 gene, an important genetic factor of late-onset AD, in both brain regions of OXYS rats during the early postnatal period. The data demonstrated a decrease in Abca7 expression in the brains of OXYS rats at P20 and at 5 and 18 months (p 0.05). Additionally, three genes (Thoc3, Exosc8, and Smpd4) demonstrated overexpression in both brain regions of OXYS rats throughout their lifetimes. In conclusion, we have conducted a comparative analysis of changes in the rat brain transcriptomes from infancy to the advanced stage of AD-like pathology for the first time. The significant and comparable distinctions in gene expression and related processes were noteworthy during the early postnatal timeframe and in the severe stage of the pathology. Our findings indicate that a reduction in the effectiveness of neural network formation in the brain of OXYS rats at an early age is a clear contributor to AD symptomatology. The cause of this phenomenon remains unclear. However, we can identify shortened gestational age, low birth weight, and delayed brain development in infancy as major risk factors for the emergence of a disease-like pathology later in life, as these conditions are typically found in affected rats. Further investigation is needed to determine the causal relation between delayed brain development in infancy and neurodegeneration.

Association between G‐Protein Coupled Receptor 55 (GPR55) Single Nucleotide Polymorphisms and Alzheimer’s Disease

AbstractBackgroundG‐protein‐coupled receptor 55 (GPR55) is a lysophosphatidylinositol and novel cannabinoid receptor. GPR55 signalling and single nucleotide polymorphisms (SNPs) have been implicated as a potential therapeutic target for neurodegenerative diseases such as Alzheimer’s Disease (AD); however, foundational knowledge on the role of GPR55 in AD progression remains lacking. We hypothesised GPR55 SNP minor allele carriers would have greater brain atrophy, cognitive decline, and AD‐related biomarker changes.MethodThis retrospective, longitudinal, observational study used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We selected participants with clinically normal cognition, mild cognitive impairment (MCI) or mild AD from ADNI2 and ADNIGO phases as a discovery sample. Exploratory screening of GPR55 SNPs identified rs2969126G/C associated with brain volume. Cerebrospinal fluid amyloid beta‐42 (CSF‐Aβ42), total and phosphorylated‐tau (t/p‐tau) were considered. Mini‐Mental State Exam and the Logical Memory Delayed Recall Test were also selected to evaluate overall cognitive status, executive function, and memory. ANCOVA models evaluated baseline differences between SNP carriers and major allele homozygotes (dominant model), controlling for sex, age, baseline cognitive status and APOE e4 across AD biomarkers, brain volumetrics and cognitive measures. Longitudinal associations were assessed as interactions between SNP and visit (baseline, 12 and 24 months) in mixed models.ResultIn ADNI2/GO (n = 755), minor allele carriers represented 15% of the sample. Significantly greater decline in CSF‐Aβ42 levels was observed in Aβ42‐positive clinically normal minor allele carriers (F(1,45.2) = 6.35, p = 0.015). Carriers with MCI had significantly higher t‐tau (F(1,126) = 4.303, p = 0.04) and p‐tau concentrations (F(1,129) = 6.98, p = 0.009) longitudinally. Significantly smaller hippocampal volumes over time were seen in minor allele carriers in the whole group (F(1,444) = 5.74, p = 0.017), with a trend in the AD/MCI subgroup (F(1,325) = 3.364, p = 0.06). Clinically normal minor allele carriers had significantly poorer baseline logical memory scores (F(1,285) = 6.92, p = 0.009). These results did not replicate in the ADNI3 cohort.ConclusionCarriers of the GPR55 SNP rs2969126G/C minor allele had greater Aβ42 and tau biomarker abnormalities, smaller brain volumes and poorer memory scores over time in different stages of AD. This preliminary study prompts replication studies in different stages of AD progression to implicate GPR55 as a potential therapeutic target for AD.

Voxel‐level of abnormal β‐amyloid accumulation and spatiotemporal distribution patterns in Alzheimer’s Disease

AbstractBackgroundThe spatial patterns of β‐amyloid (Aβ) accumulation are critical for early diagnosis and clinical trials of Alzheimer’s Disease (AD). In this study, we explored a new voxel‐level Aβ index and investigated spatial patterns of voxels with abnormal Aβ deposition in different stages of AD.MethodWe identified 944 ADNI participants with Aβ 18F‐florbetapir positron emission tomography (PET) image. All Aβ PET images were co‐registered with their corresponding magnetic resonance imaging (MRI) scans, intensity‐normalized to the whole cerebellum, and spatial‐normalized to the Montreal Neurological Institute (MNI) space. We defined the threshold of each voxel as the mean+2SD of 18F‐florbetapir PET images of 51 participants who were Aβ PET negative (A‐), CSF p‐Tau181 negative (T‐), hippocampal atrophy negative (N‐), and cognitively unimpaired (CU) at both baseline and follow‐up. The positive voxel number (NoVoxel+) was counted based on the threshold of each voxel. The cross‐sectional and longitudinal correlations between NoVoxel+ and cortical summary Aβ standard uptake value ratio (SUVR) were determined in A‐ and Aβ‐positive (A+) separately. We compared baseline NoVoxel+ among different stages of AD, as well as how it related to longitudinal changes of Aβ SUVR, CSF p‐Tau181, residual hippocampal volume (rHCV), temporal meta‐ROI cortical thickness, and preclinical Alzheimer cognitive composite (PACC) score, and follow‐up tau PET levels, controlling for age, sex and APOE4. Finally, we investigated the spatial patterns of NoVoxel+ in different stages of AD.ResultThe new Aβ index NoVoxel+ was strongly correlated with the cortical summary Aβ SUVR cross‐sectionally and longitudinally regardless of Aβ positivity (Figure 1). Cognitively impaired (MCI and dementia) individuals showed larger (p&lt;0.001) NoVoxel+ than the CU individuals, A+ group had greater NoVoxel+ than the A‐ group (Figure 2). NoVoxel+ was related to faster rates of increases in Aβ SUVR and CSF p‐Tau, decreases in rHCV, temporal meta‐ROI cortical thickness, and PACC. Abnormal Aβ voxels were primarily located in precuneus, medial orbital frontal and anterior/posterior cingulate regions in A‐/CU group (Figure 3).ConclusionThe proposed voxel‐level Aβ deposition NoVoxel+ may be useful to investigate the spatial and temporal patterns of Aβ accumulation in AD, particularly in early amyloidosis stage.

Transcriptomic and proteomic characterization of the locus coeruleus in a rat model of Alzheimer’s disease

AbstractBackgroundThe noradrenergic locus coeruleus (LC) is the first region to accumulate hyperphosphorylated tau pathology (p‐tau) in Alzheimer’s disease (AD). Using TgF344‐AD transgenic rats, which develop endogenous p‐tau in the LC prior to pathology in forebrain regions, we have recently demonstrated age‐dependent effects of p‐tau on LC firing rates. Specifically, LC neurons exhibit early hyperactivity followed by late hypoactivity. These changes in LC firing rates are coincident with the emergence of behavioral phenotypes that characterize different stages of AD (neuropsychiatric symptoms followed by cognitive deficits). Here, we sought to identify molecular mechanisms that could contribute to these changes using RNAscope and proteomics in TgF344‐AD rats.Methods32 male and female TgF344‐AD rats and wild‐type (WT) littermates aged 6 and 15 months were used for this study. Brains were flash‐frozen in isopentane on dry ice and stored at ‐80°C until being sectioned. At the level of the LC, the left hemisphere LC was collected with a 1 mm tissue punch. Punches of the cerebellum were taken as a control to verify LC enrichment in the brainstem punches. The right LC hemisphere was sectioned at 16 µm for processing with fluorescent in situ hybridization using the RNAscope Multiplex Fluorescent V2 Assay according to the manufacturer’s protocol. Probes included noradrenergic markers (tyrosine hydroxylase, norepinephrine transporter) and those that influence LC activity (α2‐adrenergic receptors, GRIA2, GRIN, ADCYAP1R1). Separately, tissue punches were submitted to the Emory Integrated Proteomics Core for label‐free quantification of proteins.ResultsRNAscope revealed no differences in transcript levels of noradrenergic markers at either age. Similarly, there were no differences in transcript levels of α2‐adrenergic receptors, GRIA, or ADCYAP1R1 at either age, or GRIN in 6‐month animals. We observed an increase of GRIN mRNA in 15‐month TgF344‐AD animals, suggesting an upregulation of excitatory neurotransmission.ConclusionsNoradrenergic neuronal identity remains in‐tact up to 15 months of age, a timepoint when there is no LC cell death in these rats. We have also uncovered a potential compensatory mechanism to maintain LC activity in late stages of disease. Proteomics and RNAscope analysis of other markers that may affect LC activity are ongoing.

Fluid and imaging amyloid‐beta biomarkers discordant individuals present different blood transcriptomic phenotypes

AbstractBackgroundCerebrospinal fluid (CSF) and Positron emission tomography (PET) amyloid‐β biomarkers are commonly used interchangeably to measure amyloid‐β deposition, an early event in the development of Alzheimer’s disease (AD). However, it is not uncommon to find individuals with discordant measurements of amyloid‐β CSF and PET. It has been hypothesized that this discordance may be an intermediate step between the CSF and brain amyloid deposition, and that discordant individuals might be in different disease stages or have different disease phenotypes. Here, we applied blood transcriptomic analysis to evaluate differences in amyloid‐β CSF and PET discordant and concordant individuals.MethodWe analyzed the blood transcriptome of 200 individuals from the ADNI cohort who had measurements of both CSF amyloid‐β42 and [18F]Florbetapir PET at baseline and at 2‐year follow‐up. The demographic characteristics of the sample are presented in table 1. Our analysis yielded four groups: CSF+/PET‐ (n = 18), CSF‐/PET+ (n = 19), CSF+/PET+ (n = 76), and CSF‐/PET‐ (n = 87). The latter was the control group for all analyses. Differentially expressed genes (DEGs, uncorrected p‐value &lt; 0.01) were used for gene set enrichment analysis (GSEA) to identify group‐specific altered biological pathways.ResultCSF+/PET‐, CSF‐/PET+ and CSF+/PET+ individuals showed a great proportion of unshared DEGs (Figure 1). The CSF+/PET‐ group, which is thought to represent a very early stage in the disease, presented the highest number of unshared DEGs (273) with upregulated GO terms involved mainly in metabolic processes. The CSF‐/PET+ group possessed 113 unique DEGs, while the CSF+/PET+ possessed 47. Interestingly, these groups presented similar alterations in biological processes, representing mainly alterations in immune response and inflammation.ConclusionOur results highlight the differences in the blood transcriptomic phenotype between CSF and PET amyloid‐β concordant and discordant individuals. Importantly, individuals very early in the AD continuum (CSF+/PET‐) presented the most distinct phenotype. Our results suggest that blood transcriptomics are able to capture subtle changes in brain amyloid‐β and might help identify individuals in different stages of AD.

A short‐hybrid scale for detecting anosognosia from the prodromal stage of Alzheimer’s disease

AbstractBackgroundWhile not originally developed for this purpose, evidence suggests that the Healthy Aging Brain Care Monitor questionnaire (HABC‐M; Monahan et al, 2012, 2014) may be a valuable instrument for assessing unawareness of cognitive decline (i.e., anosognosia) from preclinical stages of Alzheimer’s disease (AD) (Cacciamani et al, 2017). This is relevant because anosognosia may delay AD diagnosis and therapeutic interventions, with adverse consequences for patients and caregivers. However, several open questions remain: What is the actual effectiveness of this instrument across the AD spectrum? How do the cognitive, functional, and psychological subscales of the HABC‐M differ in their sensitivity to anosognosia in AD? Does the caregiver burden subscale provide additional information about AD patient’s anosognosia? The present study aimed to address these specific questions.MethodsThe HABC‐M was administered to 60 participants (30 AD patients and 30 healthy controls) and their partners (caregivers/informants). A measure of self‐awareness was then estimated by computing the discrepancy scores between the participants and their partners for the different subscales of HABC‐M (with the exception of the caregiver burden subscale, which is a caregiver‐exclusive questionnaire). To evaluate whether these measures can discriminate between patients at different stages of AD and controls, we fit linear models adjusted for age, sex, and education, and computed receiver operating characteristic curves.ResultsAll HABC‐M discrepancy scores, as well as the caregiver burden score, were able to discriminate controls from patients in distinct AD stages. For best performance, the area‐under‐curve for the HABC‐M cognitive subscale discriminated prodromal AD versus controls with a value 0.88 [95% CI: 0.78;0.97]. Adding the caregiver burden score raised it to 0.94 [0.86;0.99].ConclusionThe HABC‐M cognitive subscale (six items) can detect anosognosia from the earliest stages of AD. Separately, the caregiver burden subscale (four items) may corroborate the suspicion of anosognosia. A short‐hybrid scale combining these 10 items, instead of the 31 items of the total HABC‐M questionnaire, could provide a practical and efficient instrument for detection of anosognosia in the clinical setting. Importantly, such an instrument could further contribute to a timely AD diagnosis.