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Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder without a cure, despite the enormous number of investigations and therapeutic approaches. AD is a consequence of microglial responses to “damage signals”, such as aggregated tau oligomers, which trigger a neuro-inflammatory reaction, promoting the misfolding of cytoskeleton structure. Since AD is the most prevalent cause of dementia in the elderly (>60 years old), new treatments are essential to improve the well-being of affected subjects. The pharmaceutical industry has not developed new drugs with efficacy for controlling AD. In this context, major attention has been given to nutraceuticals and novel bioactive compounds, such as molecules from the Andean Shilajit (AnSh), obtained from the Andes of Chile. Primary cultures of rat hippocampal neurons and mouse neuroblastoma cells were evaluated to examine the functional and neuroprotective role of different AnSh fractions. Our findings show that AnSh fractions increase the number and length of neuronal processes at a differential dose. All fractions were viable in neurons. The AnSh fractions inhibit tau self-aggregation after 10 days of treatment. Finally, we identified two candidate molecules in M3 fractions assayed by UPLC/MS. Our research points to a novel AnSh-derived fraction that is helpful in AD. Intensive work toward elucidation of the molecular mechanisms is being carried out. AnSh is an alternative for AD treatment or as a coadjuvant for an effective treatment.

We have been developing a novel approach to identify cognitive impairment-related biomarkers by profiling brain-enriched and inflammation-associated microRNA (miRNA) in plasma specimens of cognitively unimpaired and cognitively impaired patients. Here, we present an analytical validation of the novel miRNA panel, CogniMIR®, using two competing quantitative PCR technologies for the expression analysis of 24 target miRNAs. Total RNA from the plasma specimens was isolated using the MagMAX mirVana Kit, and RT-qPCR was performed using stem-loop-based TaqMan and LNA-based qPCR assays. Evaluation of RNA dilution series for our target 24 miRNAs, performed by two operators on two different days, demonstrated that all CogniMIR® panel miRNAs can be reliably and consistently detected by both qPCR technologies, with sample input as low as 20 copies in a qPCR reaction. Intra-run and inter-run repeatability and reproducibility analyses using RNA specimens demonstrated that both operators generated repeatable and consistent Cts, with R2 values of 0.94 to 0.99 and 0.96 to 0.97, respectively. The study results clearly indicate the suitability of miRNA profiling of plasma specimens using either of the qPCR technologies. However, the LNA-based qPCR technology appears to be more operationally friendly and better suited for a CAP/CLIA-certified clinical laboratory.

Beyond deficits in hippocampal-dependent episodic memory, Alzheimer’s Disease (AD) features sensory impairment in visual cognition consistent with extensive neuropathology in the retina. 12A12 is a monoclonal cleavage specific antibody (mAb) that in vivo selectively neutralizes the AD-relevant, harmful N-terminal 20–22 kDa tau fragment(s) (i.e., NH2htau) without affecting the full-length normal protein. When systemically injected into the Tg2576 mouse model overexpressing a mutant form of Amyloid Precursor Protein (APP), APPK670/671L linked to early onset familial AD, this conformation-specific tau mAb successfully reduces the NH2htau accumulating both in their brain and retina and, thus, markedly alleviates the phenotype-associated signs. By means of a combined biochemical and metabolic experimental approach, we report that 12A12mAb downregulates the steady state expression levels of APP and Beta-Secretase 1 (BACE-1) and, thus, limits the Amyloid beta (Aβ) production both in the hippocampus and retina from this AD animal model. The local, antibody-mediated anti-amyloidogenic action is paralleled in vivo by coordinated modulation of the endocytic (BIN1, RIN3) and bioenergetic (glycolysis and L-Lactate) pathways. These findings indicate for the first time that similar molecular and metabolic retino-cerebral pathways are modulated in a coordinated fashion in response to 12A12mAb treatment to tackle the neurosensorial Aβ accumulation in AD neurodegeneration.

Caring for a person with Alzheimer’s disease (AD) is not only exhausting physically and emotionally, but can also have high financial costs. This problem becomes of a special importance in the presence of an aging process of individual as well as the society, and in light of a growing number of people with AD. Caring for person with AD constitutes a high risk of a decreased quality of life of the caregiviers; it is especially true with regard to family caregivers, who are emotionally connected with the patient. Therefore, the aim of the study was to recognize and present their social world on the basis of a narrative which is a subjective, namely a reconstruction of their life history. The technique of an autobiographical narrative interview was used for the research, as proposed by F. Schütz, who developed the method as a cohesive concept of biographical research. The collected empirical material (50 interviews) was analyzed, providing answers to the posed questions and allowing the formulation of conclusions, which made it possible to enrich the existing knowledge with the qualitative aspect of the analysis. Opieka nad osobą z chorobą Alzheimera jest nie tylko wyczerpująca fizycznie i emocjonalnie, ale może też wiązać się z wysokimi kosztami finansowymi. Problem ten nabiera szczególnego znaczenia w obliczu procesu starzenia się jednostki i społeczeństwa oraz rosnącej liczby osób z chorobą Alzheimera. Opieka nad osobą z alzheimerem naraża opiekunów na wysokie ryzyko obniżenia jakości życia, szczególnie dotyczy to opiekunów rodzinnych, którzy są emocjonalnie związani z pacjentem. Celem było rozpoznanie i przedstawienie ich społecznego świata na podstawie narracji będącej subiektywną rekonstrukcją ich historii życia. Do badań wykorzystano autobiograficzny wywiad narracyjny, zaproponowany przez F. Schütza, który opracował metodę jako spójną koncepcję badań biograficznych. Zebrany materiał empiryczny (50 wywiadów) został poddany analizie, umożliwiając udzielenie odpowiedzi na postawione pytania i sformułowanie wniosków, co pozwoliło na wzbogacenie posiadanej wiedzy o jakościowy aspekt analizy.

Alzheimer’s disease (AD) has no cure. Earlier, we showed that partial inhibition of mitochondrial complex I (MCI) with the small molecule CP2 induces an adaptive stress response, activating multiple neuroprotective mechanisms. Chronic treatment reduced inflammation, Aβ and pTau accumulation, improved synaptic and mitochondrial functions, and blocked neurodegeneration in symptomatic APP/PS1 mice, a translational model of AD. Here, using serial block-face scanning electron microscopy (SBFSEM) and three-dimensional (3D) EM reconstructions combined with Western blot analysis and next-generation RNA sequencing, we demonstrate that CP2 treatment also restores mitochondrial morphology and mitochondria-endoplasmic reticulum (ER) communication, reducing ER and unfolded protein response (UPR) stress in the APP/PS1 mouse brain. Using 3D EM volume reconstructions, we show that in the hippocampus of APP/PS1 mice, dendritic mitochondria primarily exist as mitochondria-on-a-string (MOAS). Compared to other morphological phenotypes, MOAS have extensive interaction with the ER membranes, forming multiple mitochondria-ER contact sites (MERCS) known to facilitate abnormal lipid and calcium homeostasis, accumulation of Aβ and pTau, abnormal mitochondrial dynamics, and apoptosis. CP2 treatment reduced MOAS formation, consistent with improved energy homeostasis in the brain, with concomitant reductions in MERCS, ER/UPR stress, and improved lipid homeostasis. These data provide novel information on the MOAS-ER interaction in AD and additional support for the further development of partial MCI inhibitors as a disease-modifying strategy for AD.

Choline acetyltransferase (ChAT), the acetylcholine synthesizing enzyme, is an important cholinergic marker whose levels/activity are reduced in aging and Alzheimer’s disease (AD). In humans, the M-transcript produces two ChAT isoforms, 69-kDa and 82-kDa ChAT, with preferential subcellular localization in the cytoplasm and nucleus, respectively. Under conditions of cellular stress, including aging and AD, 82-kDa ChAT is aberrantly mis-placed to the cytoplasm. The function of nuclear ChAT is unknown, but studies indicate a role in stress, via regulation of gene expression and hint to a role in neuronal vulnerability. In this regard, our laboratory has generated a novel transgenic mouse model expressing 82-kDa ChAT which is not endogenously expressed in rodents. The overall objective of this study is to understand the role of 82-kDa ChAT under physiological and pathological conditions. We aim to phenotype this new mouse model and elucidate any potential implications of this nuclear protein on aging and AD. Using qPCR, RNAscope and immunohistochemical analysis, we were able to demonstrate 82-kDa ChAT mRNA and protein expression in basal forebrain neurons of our mouse model with age/pathology-dependent subcellular distribution similar to human necropsy brains. The nuclear 82-kDa ChAT expression in wild type mice led to alterations in genes related to the aging process, with subtle improvements in age related cognitive deficits and inflammation. Similarly, its expression in AD mice (APPNL-G-F) altered the expression of several genes and proteins linked to amyloid-beta (Aβ) clearance and inflammation accompanied by enhanced cognitive behavior, reduced amyloidosis, and gliosis. These beneficial effects were inversely proportional to age and plaque load, two factors that seemed to impact the subcellular distribution of 82-kDa ChAT, aberrantly shifting it from the nucleus to the cytoplasm. In conclusion, this thesis characterizes a novel transgenic mouse model expressing the primate-specific nuclear ChAT isoform and provides the first application of this model in studying the impact of 82-kDa ChAT on AD highlighting its potential neuroprotective role. These mice will be valuable in understanding the function of 82-kDa ChAT and its role in the selective cholinergic susceptibility observed in aging and neurodegenerative diseases featuring cholinergic deficits.

Background In preclinical Alzheimer’s disease, it is unclear why some individuals with amyloid pathologic change are asymptomatic (stage 1), whereas others experience subjective cognitive decline (SCD, stage 2). Here, we examined the association of stage 1 vs. stage 2 with structural brain reserve in memory-related brain regions. Methods We tested whether the volumes of hippocampal subfields and parahippocampal regions were larger in individuals at stage 1 compared to asymptomatic amyloid-negative older adults (healthy controls, HCs). We also tested whether individuals with stage 2 would show the opposite pattern, namely smaller brain volumes than in amyloid-negative individuals with SCD. Participants with cerebrospinal fluid (CSF) biomarker data and bilateral volumetric MRI data from the observational, multi-centric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study were included. The sample comprised 95 amyloid-negative and 26 amyloid-positive asymptomatic participants as well as 104 amyloid-negative and 47 amyloid-positive individuals with SCD. Volumes were based on high-resolution T2-weighted images and automatic segmentation with manual correction according to a recently established high-resolution segmentation protocol. Results In asymptomatic individuals, brain volumes of hippocampal subfields and of the parahippocampal cortex were numerically larger in stage 1 compared to HCs, whereas the opposite was the case in individuals with SCD. MANOVAs with volumes as dependent data and age, sex, years of education, and DELCODE site as covariates showed a significant interaction between diagnosis (asymptomatic versus SCD) and amyloid status (Aß42/40 negative versus positive) for hippocampal subfields. Post hoc paired comparisons taking into account the same covariates showed that dentate gyrus and CA1 volumes in SCD were significantly smaller in amyloid-positive than negative individuals. In contrast, CA1 volumes were significantly (p = 0.014) larger in stage 1 compared with HCs. Conclusions These data indicate that HCs and stages 1 and 2 do not correspond to linear brain volume reduction. Instead, stage 1 is associated with larger than expected volumes of hippocampal subfields in the face of amyloid pathology. This indicates a brain reserve mechanism in stage 1 that enables individuals with amyloid pathologic change to be cognitively normal and asymptomatic without subjective cognitive decline.

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by cognitive and functional impairment. Recent research has focused on the deregulation of microRNAs (miRNAs) in blood as the potential biomarkers for AD. As such, a differential expression analysis of miRNAs was conducted in this study using an integrated framework that utilized the advantages of statistical and machine learning approaches. Three miRNA candidates that showed the strongest significance and correlation with each other, namely hsa-miR-6501-5p, hsa-miR-4433b-5p, and hsa-miR-143-3p, were identified. The roles and functions of the identified differentiated miRNA candidates with AD development were verified by predicting their target mRNAs, and their networks of interaction in AD pathogenesis were investigated. Pathway analysis showed that the pathways involved in contributing to the development of AD included oxidative phosphorylation, mitochondrial dysfunction, and calcium-mediated signalling. This study supports evidence that the miRNA expression changes in AD and indicates the need for further study in this area.

In recent years, finding the optimal solution for image segmentation has become more important in many applications. The whale optimization algorithm (WOA) is a metaheuristic optimization technique that has the advantage of achieving the global optimal solution while also being simple to implement and solving many real-time problems. If the complexity of the problem increases, the WOA may stick to local optima rather than global optima. This could be an issue in obtaining a better optimal solution. For this reason, this paper recommends a hybrid algorithm that is based on a mixture of the WOA and gray wolf optimization (GWO) for segmenting the brain sub regions, such as the gray matter (GM), white matter (WM), ventricle, corpus callosum (CC), and hippocampus (HC). This hybrid mixture consists of two steps, i.e., the WOA and GWO. The proposed method helps in diagnosing Alzheimer’s disease (AD) by segmenting the brain sub regions (SRs) by using a hybrid of the WOA and GWO (H-WOA-GWO, which is represented as HWGO). The segmented region was validated with different measures, and it shows better accuracy results of 92%. Following segmentation, the deep learning classifier was utilized to categorize normal and AD images. The combination of WOA and GWO yields an accuracy of 90%. As a result, it was discovered that the suggested method is a highly successful technique for identifying the ideal solution, and it is paired with a deep learning algorithm for classification.

Purpose Positron emission tomography (PET) with the first and only tau targeting radiotracer of 18F-flortaucipir approved by FDA has been increasingly used in depicting tau pathology deposition and distribution in patients with cognitive impairment. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform 18F-flortaucipir PET imaging. Method A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for 18F-flortaucipir PET imaging in Alzheimer’s disease (AD), focusing on clinical scenarios, patient preparation, and administered activities, as well as image acquisition, processing, interpretation, and reporting. Conclusion This international consensus and practice guideline will help to promote the standardized use of 18F-flortaucipir PET in patients with AD. It will become an international standard for this purpose in clinical practice.

Alzheimer’s disease (AD) is a neurodegenerative disorder that is pathologically related to oxidative stress and cellular senescence. Safinamide is one of the clinically prescribed monoamine oxidase B (MAOB) inhibitors. It has been reported to possess therapeutic potential in neurological disorders. However, the therapeutic potential of safinamide in AD is still under investigation. In this study, we explored the effect of safinamide in amyloid (Aβ)1–42 oligomers-stimulated M17 neuronal cells. We established the in vitro model with M17 cells by treating them with 1 μM Aβ1-42 oligomers with or without safinamide (100 or 200 nM). The results show that safinamide ameliorated Aβ1-42 oligomers-induced oxidative stress in M17 cells as revealed by the decreased reactive oxygen species (ROS) production and reduced glutathione (GSH) content. Safinamide treatment significantly ameliorated senescence-associated-β-galactosidase (SA-β-gal)-positive cells and telomerase activity. Further, we show that safinamide treatment resulted in decreased mRNA and protein expressions of p21 and plasminogen activator inhibitor-1 (PAI-1). Moreover, silencing of Sirtuin1 (SIRT1) abolished the effects of safinamide on the mRNA levels of p21 and PAI-1, as well as SA-β-gal-positive cells in Aβ1-42 oligomers-induced M17 cells. In conclusion, we reveal that safinamide exerted a protective function on M17 cells from Aβ1-42 oligomers induction-caused oxidative stress and cellular senescence through SIRT1 signaling. These present results provide meaningful evidence that safinamide may be medically developed for the prevention and therapy of AD.

This research revealed that 15 modules were obtained through weighted gene co-expression network analysis (WGCNA), among which the magenta and blue modules were significantly associated with Alzheimer's Disease (AD). There were 121 genes in the magenta module, and 1022 genes in the blue module. Through the differently expressed genes (DEGs) analysis, significant differences were shown in 134 genes (88 were up-regulated and 46 were down-regulated). 34 immune-key genes were obtained after 3 types of genes were crossed. Functional enrichment analysis showed that these genes were mainly enriched in cytokine receptor activity, immune receptor activity, and integrin family cell surface interactions. Through protein-protein interaction (PPI) network analysis, 10 hub genes were obtained: SERPINE1, ZBTB16, CD44, BCL6, HMOX1, SLC11A1, CEACAM8, ITGA5, SOCS3, and IL4R. Through immune-infiltration analysis, significant differences were demonstrated in 4 immune cells: CD8+ T cells, resting NK cells, M2 macrophages and activated dendritic cells, and a significant positive correlation was shown between CD8+ T cells and macrophages M2, or between resting NK cells and activated dendritic cells. CEACAM8 was positively correlated with CD8+ T cells and macrophages M2, and negatively correlated with activated dendritic cells and resting NK cells while the other 9 genes showed the opposite. Receiver operating characteristic (ROC) curve analysis demonstrated that both the differential immune cells and 10 hub genes had good diagnostic values. In GSE122063, the hub genes were verified and BCL6, CD44, HMOX1, IL4R, ITGA5 and SOCS3 were up-regulated. Meanwhile, the expression of hub genes was up-regulated in the brain tissues of AD rats. This study is of great significance for the diagnosis and therapy of AD.

Alzheimer's disease (AD) affects the basic ability to function and has imposed an immense burden on the community and health care system. Focused ultrasound (FUS) has recently been proposed as a novel noninvasive therapeutic approach for AD. However, systematic reviews on the FUS application in AD treatment have not been forthcoming. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria to summarize the techniques associated with safety and efficacy, as well as possible underlying mechanisms of FUS effects on AD in animal and human studies. Animal studies demonstrated FUS with microbubbles (FUS-MB) induced blood-brain-barrier (BBB) opening that could facilitate various therapeutic agents entering the brain. Repeated FUS-MB and FUS stimulation can relieve AD pathology and improve cognitive and memory function. Human studies showed repeated FUS-MB are well tolerated with few adverse events and FUS stimulation could enhance local perfusion and neural function, which correlated with cognitive improvement. We conclude that FUS is a feasible and safe therapeutic and drug delivery strategy for AD. However, FUS treatment on humans is still in the early stages and requires further optimization and standardization.

Graphical abstract, The adenosine-triphosphate-(ATP)-binding cassette (ABC) transporter ABCA7 is a genetic risk factor for Alzheimer’s disease (AD). Defective ABCA7 promotes AD development and/or progression. Unfortunately, ABCA7 belongs to the group of ‘under-studied’ ABC transporters that cannot be addressed by small-molecules. However, such small-molecules would allow for the exploration of ABCA7 as pharmacological target for the development of new AD diagnostics and therapeutics. Pan-ABC transporter modulators inherit the potential to explore under-studied ABC transporters as novel pharmacological targets by potentially binding to the proposed ‘multitarget binding site’. Using the recently reported cryogenic-electron microscopy (cryo-EM) structures of ABCA1 and ABCA4, a homology model of ABCA7 has been generated. A set of novel, diverse, and potent pan-ABC transporter inhibitors has been docked to this ABCA7 homology model for the discovery of the multitarget binding site. Subsequently, application of pharmacophore modelling identified the essential pharmacophore features of these compounds that may support the rational drug design of innovative diagnostics and therapeutics against AD.

Alzheimer’s disease (AD) is a deadly cognitive condition in which people develop severe dementia symptoms. Neurologists commonly use a series of physical and mental tests to diagnose AD that may not always be effective. Damage to brain cells is the most significant physical change in AD. Proper analysis of brain images may assist in the identification of crucial bio-markers for the disease. Because the development of brain cells is so intricate, traditional image processing algorithms sometimes fail to perceive important bio-markers. The deep neural network (DNN) is a machine learning technique that helps specialists in making appropriate decisions. In this work, we used brain magnetic resonance scans to implement some commonly used DNN models for AD classification. According to the classification results, where the average of multiple metrics is observed, which includes accuracy, precision, recall, and an F1 score, it is found that the DenseNet-121 model achieved the best performance (86.55%). Since DenseNet-121 is a computationally expensive model, we proposed a hybrid technique incorporating LeNet and AlexNet that is light weight and also capable of outperforming DenseNet. To extract important features, we replaced the traditional convolution Layers with three parallel small filters (1×1,3×3, and 5×5). The model functions effectively, with an overall performance rate of 93.58%. Mathematically, it is observed that the proposed model generates significantly fewer convolutional parameters, resulting in a lightweight model that is computationally effective.

Background: The cerebrospinal fluid (CSF)/serum albumin quotient (Q-Alb) is a marker of the blood-CSF barrier (BCSFB) and possibly of the blood–brain barrier (BBB). The latter is known to be altered in Alzheimer’s disease (AD) based on neuropathological and neuroimaging studies. Following investigations performed on clinically diagnosed cohorts, we aimed at comparing Q-Alb in cognitively impaired patients with neurochemical demonstration of AD pathophysiology and neurological disease controls (NDCs). Methods: We evaluated N = 144 AD patients (MCI, N = 43; AD dementia — ADD, N = 101) and N = 132 NDCs. AD patients were all A + according to the A/T/N framework and were neurochemically classified based on T and N parameters. Results: Q-Alb did not significantly differ between AD patients and NDCs. Moreover, it was not associated with disease stage (MCI vs. ADD), MMSE score, or CSF AD biomarkers. Discussion: Our study indicates that BCSFB dysfunction is not a specific feature of AD. When interpreting Q-Alb as a marker of the BBB, the lack of difference from NDCs might be due to BBB dysfunction widely occurring in other neurological, non-degenerative, conditions or — more probably — to low sensitivity of this biochemical parameter towards subtle BBB alterations causing leakage of molecules smaller than albumin. Furthermore, Q-Alb is not associated with the degree of global cognitive deterioration in AD, nor with CSF AD neurochemical biomarkers.

Magnetic resonance imaging (MRI) has been a valuable tool in investigating the pathological cascade of Alzheimer's disease (AD) and its progression, which are still open questions. Although some MRI-derived hallmarks in terms of functional connectivity and white matter degeneration have been revealed, the temporal involvement and interplay between them as well as other hallmarks such as amyloid load and neuronal density remain poorly understood. On the other hand, brain glucose hypometabolism is gradually taking center stage as a key player in the onset of AD, which had been described as a form of "type-3 diabetes". In this context, this thesis work presents a comprehensive study to characterize longitudinal changes in functional connectivity using resting-state functional MRI and microstructure using diffusion MRI, and to correlate them to glucose hypometabolism and neuronal density in a rat model of AD. This study is mainly focused on establishing an optimized image processing pipeline dedicated for rat fMRI data, optimizing a computational model of diffusion in white matter using a novel deep learning approach, and assessing the spatiotemporal relationships between biomarkers regarding to microstructure and function in the brain by using advanced statistical methods as well as state-of-the-art machine learning approaches in order to provide a comprehensive characterization of the pathological cascade and progression of neurodegeneration resulting from brain glucose metabolism disruption.

The brain is a challenging target for antibody-based positron emission tomography (immunoPET) to image amyloid-beta (Aβ). Antibodies detect pathology with high sensitivity, but due to their size and biological half-life, they cause a high background radiation, if radiolabelled. Antibodies fused to transferrin-receptor (TfR) binders can penetrate the BBB via receptor-mediated transcytosis. In this thesis, I evaluated several methods to reduce the biological half-life for bispecific antibodies, which bind to Aβ and TfR, to reduce the time between injection and imaging. In paper I, we studied two different clearing approaches – direct clearance and induced clearance – to reduce blood concentrations of a monospecific and a bispecific, brain penetrating antibody, for enhanced contrast. The direct clearing approach was too efficient to show a benefit for brain imaging. The induced clearing strategy, based on the inverse-electron demand Diels−Alder (IEDDA) reaction of a TCO and a tetrazine, proved the concept of induced clearance for the monospecific antibody, but not for the bispecific antibody. For paper II, we changed the antibody design and compared a bispecific antibody with its corresponding monospecific variant, both with and without a mutation that attenuated binding to the neonatal Fc receptor (FcRn), to decrease antibody circulation time in vivo. The mutation reduced the blood half-life and we suggested an imaging time 12 to 24 h after injection. In paper III, we radiolabelled both FcRn mutated antibody constructs with fluorine-18, to compare their pharmacokinetic profiles in WT mice with PET imaging over 9 h. The bispecific antibody, that showed higher brain uptake, was then injected into WT and AD mice (AppNL-G-F). PET scanning 12 h after injection revealed higher antibody retention in AppNL-G-F compared to WT mice. In paper IV, we tested two novel tetrazines for their potential to be used as pre-targeting agents. Pre-targeting describes a two-step approach with the aim to achieve a high contrast PET image. First a TCO-modified antibody is injected and after a while a second substance, a radiolabelled tetrazine is injected. Successful pre-targeting requires a tetrazine which can penetrate the brain and then be efficiently cleared. We could show that both fluorine-18 labelled tetrazines entered the brain, where one of them was more efficient than the other. In conclusion we have shown that it is possible to increase the peripheral clearance of radiolabelled antibodies and get one step closer to same-day immunoPET imaging. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no 813528.

Background Brain-directed immunotherapy is a promising strategy to target amyloid-β (Aβ) deposits in Alzheimer’s disease (AD). In the present study, we compared the therapeutic efficacy of the Aβ protofibril targeting antibody RmAb158 with its bispecific variant RmAb158-scFv8D3, which enters the brain by transferrin receptor-mediated transcytosis. Methods AppNL−G−F knock-in mice received RmAb158, RmAb158-scFv8D3, or PBS in three treatment regimens. First, to assess the acute therapeutic effect, a single antibody dose was given to 5 months old AppNL−G−F mice, with evaluation after 3 days. Second, to assess the antibodies’ ability to halt the progression of Aβ pathology, 3 months old AppNL−G−F mice received three doses during a week, with evaluation after 2 months. Reduction of RmAb158-scFv8D3 immunogenicity was explored by introducing mutations in the antibody or by depletion of CD4+ T cells. Third, to study the effects of chronic treatment, 7-month-old AppNL−G−F mice were CD4+ T cell depleted and treated with weekly antibody injections for 8 weeks, including a final diagnostic dose of [125I]RmAb158-scFv8D3, to determine its brain uptake ex vivo. Soluble Aβ aggregates and total Aβ42 were quantified with ELISA and immunostaining. Results Neither RmAb158-scFv8D3 nor RmAb158 reduced soluble Aβ protofibrils or insoluble Aβ1-42 after a single injection treatment. After three successive injections, Aβ1-42 was reduced in mice treated with RmAb158, with a similar trend in RmAb158-scFv8D3-treated mice. Bispecific antibody immunogenicity was somewhat reduced by directed mutations, but CD4+ T cell depletion was used for long-term therapy. CD4+ T cell-depleted mice, chronically treated with RmAb158-scFv8D3, showed a dose-dependent increase in blood concentration of the diagnostic [125I]RmAb158-scFv8D3, while concentration was low in plasma and brain. Chronic treatment did not affect soluble Aβ aggregates, but a reduction in total Aβ42 was seen in the cortex of mice treated with both antibodies. Conclusions Both RmAb158 and its bispecific variant RmAb158-scFv8D3 achieved positive effects of long-term treatment. Despite its ability to efficiently enter the brain, the benefit of using the bispecific antibody in chronic treatment was limited by its reduced plasma exposure, which may be a result of interactions with TfR or the immune system. Future research will focus in new antibody formats to further improve Aβ immunotherapy.

Comparisons of late-onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age.We compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound-B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non-carriers (NON-MCs), and ACS participants with a positive (FH+) and negative (FH-) family history of LOAD.At baseline, MCs had the lowest age-adjusted level of CSF Aβ42 and the highest levels of total and phosphorylated tau-181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline.Preclinical ADAD and LOAD share many biomarker signatures, but cross-sectional and longitudinal differences may exist.

Introduction:Extracellular vesicles (EVs) may propagate and modulate Alzheimer's disease (AD) pathology. We aimed to comprehensively characterize the proteome of cerebrospinal fluid (CSF) EVs to identify proteins and pathways altered in AD.Methods:CSF EVs were isolated by ultracentrifugation (Cohort 1) or Vn96 peptide (Cohort 2) from non-neurodegenerative controls (n = 15, 16) and AD patients (n = 22, 20, respectively). EVs were subjected to untargeted quantitative mass spectrometry-based proteomics. Results were validated by enzyme-linked immunosorbent assay (ELISA) in Cohorts 3 and 4, consisting of controls (n = 16, n = 43, (Cohort3, Cohort4)), and patients with AD (n = 24, n = 100).Results:We found > 30 differentially expressed proteins in AD CSF EVs involved in immune-regulation. Increase of C1q levels in AD compared to non-demented controls was validated by ELISA (∼ 1.5 fold, p (Cohort 3) = 0.03, p (Cohort 4) = 0.005).Discussion:EVs may be utilized as a potential biomarker and may play a so far unprecedented role in immune-regulation in AD.

Hepatic encephalopathy (HE) is a chronic metabolic disease accompanied by neuropathological and neuropsychiatric features, including memory deficits, psychomotor dysfunction, depression, and anxiety. Alzheimer’s disease (AD), the most common neurodegenerative disease, is characterized by tau hyperphosphorylation, excessive amyloid beta (Aβ) accumulation, the formation of fibrillary tangles, hippocampus atrophy, and neuroinflammation. Recent studies have suggested a positive correlation between HE and AD. Some studies reported that an impaired cholesterol pathway, abnormal bile acid secretion, excessive ammonia level, impaired Aβ clearance, astrocytic dysfunction, and abnormal γ-aminobutyric acid GABAergic neuronal signaling in HE may also be involved in AD pathology. However, the mechanisms and related genes involved in AD-like pathology in the HE brain are unclear. Thus, we compared the cortical transcriptome profile between an HE mouse model, bile duct ligation (BDL), and an AD mouse model, the 5×FAD. Our study showed that the expression of many genes implicated in HE is associated with neuronal dysfunction in AD mice. We found changes in various protein-coding RNAs, implicated in synapses, neurogenesis, neuron projection, neuron differentiation, and neurite outgrowth, and non-coding RNAs possibly associated with neuropathology. Our data provide an important resource for further studies to elucidate AD-like pathophysiology in HE patients.

Heterozygous hTau mice were used for the study of tau seeding. These mice express the six human tau isoforms, with a high predominance of 3Rtau over 4Rtau. The following groups were assessed: (i) non-inoculated mice aged 9 months (n = 4); (ii) Alzheimer’s Disease (AD)-inoculated mice (n = 4); (iii) Globular Glial Tauopathy (GGT)-inoculated mice (n = 4); (iv) Pick’s disease (PiD)-inoculated mice (n = 4); (v) control-inoculated mice (n = 4); and (vi) inoculated with vehicle alone (n = 2). AD-inoculated mice showed AT8-immunoreactive neuronal pre-tangles, granular aggregates, and dots in the CA1 region of the hippocampus, dentate gyrus (DG), and hilus, and threads and dots in the ipsilateral corpus callosum. GGT-inoculated mice showed unique or multiple AT8-immunoreactive globular deposits in neurons, occasionally extended to the proximal dendrites. PiD-inoculated mice showed a few loose pre-tangles in the CA1 region, DG, and cerebral cortex near the injection site. Coiled bodies were formed in the corpus callosum in AD-inoculated mice, but GGT-inoculated mice lacked globular glial inclusions. Tau deposits in inoculated mice co-localized active kinases p38-P and SAPK/JNK-P, thus suggesting active phosphorylation of the host tau. Tau deposits were absent in hTau mice inoculated with control homogenates and vehicle alone. Deposits in AD-inoculated hTau mice contained 3Rtau and 4Rtau; those in GGT-inoculated mice were mainly stained with anti-4Rtau antibodies, but a small number of deposits contained 3Rtau. Deposits in PiD-inoculated mice were stained with anti-3Rtau antibodies, but rare neuronal, thread-like, and dot-like deposits showed 4Rtau immunoreactivity. These findings show that tau strains produce different patterns of active neuronal seeding, which also depend on the host tau. Unexpected 3Rtau and 4Rtau deposits after inoculation of homogenates from 4R and 3R tauopathies, respectively, suggests the regulation of exon 10 splicing of the host tau during the process of seeding, thus modulating the plasticity of the cytoskeleton.

Verbenalin, among the major constituents of Verbena officinalis, has been reported to exhibit sleep-promoting and antioxidant activities. This study demonstrates the effects of verbenalin on amyloid-beta (Aβ) peptide generation in Swedish mutant amyloid precursor protein (APP)-overexpressing Neuro2a cells (SweAPP/N2a) and in Alzheimer’s disease (AD) animal models. We further performed molecular biological analyses of these in vitro and in vivo models of AD. The effects of verbenalin were assessed based on the expression of factors related to Aβ peptide production using Western blotting, enzyme-linked immunosorbent assay, and immunohistochemistry (IHC). The intracellular expression and release of APP protein were both decreased by verbenalin treatment in SweAPP/N2a cells. Thus, the production of Aβ peptides was decreased. Compared to those in AD transgenic (Tg) mice, IHC revealed that verbenalin-treated animals showed decreased Aβ and tau expression levels in the hippocampus. In addition, verbenalin restored the expression of brain-derived neurotrophic factor (BDNF) in the hippocampus of AD animal models. These findings suggest that verbenalin may decrease Aβ formation both in vitro and in vivo. Verbenalin may also help improve the pathological hallmarks of AD.

Background Genetic variants within the APOE locus may modulate Alzheimer’s disease (AD) risk independently or in conjunction with APOE*2/3/4 genotypes. Identifying such variants and mechanisms would importantly advance our understanding of APOE pathophysiology and provide critical guidance for AD therapies aimed at APOE. The APOE locus however remains relatively poorly understood in AD, owing to multiple challenges that include its complex linkage structure and uncertainty in APOE*2/3/4 genotype quality. Here, we present a novel APOE*2/3/4 filtering approach and showcase its relevance on AD risk association analyses for the rs439401 variant, which is located 1801 base pairs downstream of APOE and has been associated with a potential regulatory effect on APOE. Methods We used thirty-two AD-related cohorts, with genetic data from various high-density single-nucleotide polymorphism microarrays, whole-genome sequencing, and whole-exome sequencing. Study participants were filtered to be ages 60 and older, non-Hispanic, of European ancestry, and diagnosed as cognitively normal or AD (n = 65,701). Primary analyses investigated AD risk in APOE*4/4 carriers. Additional supporting analyses were performed in APOE*3/4 and 3/3 strata. Outcomes were compared under two different APOE*2/3/4 filtering approaches. Results Using more conventional APOE*2/3/4 filtering criteria (approach 1), we showed that, when in-phase with APOE*4, rs439401 was variably associated with protective effects on AD case-control status. However, when applying a novel filter that increases the certainty of the APOE*2/3/4 genotypes by applying more stringent criteria for concordance between the provided APOE genotype and imputed APOE genotype (approach 2), we observed that all significant effects were lost. Conclusions We showed that careful consideration of APOE genotype and appropriate sample filtering were crucial to robustly interrogate the role of the APOE locus on AD risk. Our study presents a novel APOE filtering approach and provides important guidelines for research into the APOE locus, as well as for elucidating genetic interaction effects with APOE*2/3/4.

(1) Background: Alzheimer’s disease (AD), an age-progressive neurodegenerative disease that affects cognitive function, causes changes in the functional connectivity of the default-mode network (DMN). However, the question of whether AD-related changes occur in the functional connectivity of the basal ganglia has rarely been specifically analyzed. This study aimed to measure the changes in basal ganglia functional connectivity among patients with AD and mild cognitive impairment (MCI) in their resting state using the functional connectivity density (FCD) value, the functional connectivity (FC) intensity, and the graph theory index, and to confirm their influence on clinical manifestations. (2) Methods: Resting-state functional MRI (rs-fMRI) and neuropsychological data from 48 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used for analyses. The 48 ADNI participants comprised 16 patients with AD, 16 patients with MCI, and 16 normal controls (NCs). The functional connectivity of basal ganglia was evaluated by FCDs, FC strength, and graph theory index. We compared voxel-based FCD values between groups to show specific regions with significant variation and significant connectivity from ROI conduction to ROI analysis. Pearson’s correlation analyses between functional connectivity and several simultaneous clinical variables were also conducted. Additionally, receiver operating characteristic (ROC) analyses associated with classification were conducted for both FCD values and graph theory indices. (3) Results: The level of FCD in patients with cognitive impairment showed obvious abnormalities (including short-range and long-range FCD). In addition to DMN-related regions, aberrant functional connectivity was also found to be present in the basal ganglia, especially in the caudate and amygdala. The FCD values of the basal ganglia (involving the caudate and amygdala) were closely related to scores from the Mini-Mental State Examination (MMSE) and the Functional Activities Questionnaire (FAQ); meanwhile, the graph theory indices (involving global efficiency and degree) of the basal ganglia (involving the caudate, amygdala, and putamen) were also found to be closely correlated with MMSE scores. In ROC analyses of both FCD and graph theory, the amygdala was of the utmost importance in the early-stage detection of MCI; additionally, the caudate nucleus was found to be crucial in the progression of cognitive decline and AD diagnosis. (4) Conclusions: It was systematically confirmed that there is a phenomenon of change in the functional connections in the basal ganglia during cognitive decline. The findings of this study could improve our understanding of AD and MCI pathology in the basal ganglia and make it possible to propose new targets for AD treatment in further studies.

Aluminum (Al) excess and hypercholesterinaemia are established risks of Alzheimer’s disease (AD). The aim of this study was to establish an AD-resembling hypercholesterinaemic animal model—with the involvement of 8 week and 48 week-old Fischer-344 rats—by Al administration for the safe and rapid verification of β-amyloid-targeted positron emission tomography (PET) radiopharmaceuticals. Measurement of lipid parameters and β-amyloid–affine [11C]C-Pittsburgh Compound B ([11C]C-PIB) PET examinations were performed. Compared with the control, the significantly elevated cholesterol and LDL levels of the rats receiving the cholesterol-rich diet support the development of hypercholesterinaemia (p ≤ 0.01). In the older cohort, a notably increased age-related radiopharmaceutical accumulation was registered compared to in the young (p ≤ 0.05; p ≤ 0.01). A monotherapy-induced slight elevation of mean standardised uptake values (SUVmean) was statistically not significant; however, adult rats administered a combined diet expressed remarkable SUVmean increment compared to the adult control (SUVmean: from 0.78 ± 0.16 to 1.99 ± 0.28). One and two months after restoration to normal diet, the cerebral [11C]C-PIB accumulation of AD-mimicking animals decreased by half and a third, respectively, to the baseline value. The proposed in vivo Al-induced AD-resembling animal system seems to be adequate for the understanding of AD neuropathology and future drug testing and radiopharmaceutical development.

BackgroundAberrant alternative splicing plays critical role in aging and age-related diseases. Heterogeneous nuclear ribonucleoproteins (hnRNPs) reportedly regulate RNA splicing process. Whether and how hnRNPs contribute to age-related neurodegenerative diseases, especially Alzheimer’s disease (AD), remain elusive.MethodsImmunoblotting and immunostaining were performed to determine expression patterns and cellular/subcellular localization of the long isoform of hnRNP D-like (L-DL), which is a hnRNP family member, in mouse hippocampus. Downregulation of L-DL in WT mice was achieved by AAV-mediated shRNA delivery, followed by memory-related behavioural tests. L-DL interactome was analysed by affinity-precipitation and mass spectrometry. Alternative RNA splicing was measured by RNA-seq and analyzed by bioinformatics-based approaches. Downregulation and upregulation of L-DL in APP/PS1 mice were performed using AAV-mediated transduction.ResultsWe show that L-DL is specifically localized to nuclear speckles. L-DL levels are decreased in the hippocampus of aged mouse brains and downregulation of L-DL impairs cognition in mice. L-DL serves as a structural component to recruit other speckle proteins, and regulates cytoskeleton- and synapse-related gene expression by altering RNA splicing. Mechanistically, these splicing changes are modulated via L-DL-mediated interaction of SF3B3, a core component of U2 snRNP, and U2AF65, a U2 spliceosome protein that guides U2 snRNP’s binding to RNA. In addition, L-DL levels are decreased in APP/PS1 mouse brains. While downregulation of L-DL deteriorates memory deficits and overexpression of L-DL improves cognitive function in AD mice, by regulating the alternative splicing and expression of synaptic geneCAMKV.ConclusionsOur findings define a molecular mechanism by which hnRNP L-DL regulates alternative RNA splicing, and establish a direct role for L-DL in AD-related synaptic dysfunction and memory decline.

Long-term, repeatable monitoring of the appearance and progress of Alzheimer’s disease (AD) in real time can be extremely beneficial to acquire highly reliable diagnostic insights, which is crucial for devising apt strategies towards effective AD treatment. Herein, we present an optimized innovative cranial window imaging method for the long-term repeatable imaging of amyloid-β (Aβ) plaques and vessels in an AD mouse model. Basically, two-photon excitation fluorescence (TPEF) microscopy was used to monitor the fluorescently labeled Aβ plaques, whereas the label-free blood vessels were studied using coherent anti-Stokes Raman scattering (CARS) microscopy in the live in vivo AD mouse model. It was possible to clearly observe the Aβ deposition and vascular structure in the target cortex localization for 31 weeks in the AD mouse model using this method. The combined TPEF/CARS imaging studies were also instrumental in realizing the relationship between the tendency of Aβ deposition and ageing. Essentially, the progression of cerebral amyloid angiopathy (CAA) in the AD mouse model was quantitatively characterized, which revealed that the proportion Aβ deposition in the unit vessel can increase from 13.63% to 28.80% upon increasing the age of mice from 8 months old to 14 months old. The proposed imaging method provided an efficient, safe, repeatable platform with simple target localization aptitude towards monitoring the brain tissues, which is an integral part of studying any brain-related physiological or disease conditions to extract crucial structural and functional information.

Aging and Alzheimer’s disease (AD) are characterized by common pathological features associated with alterations in neuronal connections. These inevitably affect the functioning of specific brain areas and their interrelations, leading to questions about neuronal plasticity and the compensatory mechanisms associated with dopaminergic (DA) mediation. In this study on twelve-month-old freely moving 5XFAD-transgenic mice, serving as a model of AD, and their wild-type (WT) littermates, we analyze electroencephalograms (EEGs) from the motor cortex (MC), putamen (Pt) and the DA-producing ventral tegmental area (VTA) and substantia nigra (SN). Baseline EEGs in the transgenic mice were characterized by delta2 activity enhancements in VTA and alpha attenuation in VTA and SN. In contrast to WT mice, which lack differences in EEG from these brain areas, 5XFAD mice showed theta–alpha attenuation and delta2 and beta2 enhancements in EEG from both VTA and SN vs. MC. In 5XFAD mice, a DA mimetic, apomorphine, lowered (vs. saline) the theta oscillations in Pt, VTA and SN and enhanced alpha in MC, Pt, VTA and beta1 in all brain areas. These results and those obtained earlier in younger (six-month-old) mice suggest that the age-related characteristics of cerebral adaptive mechanisms affected by AD might be associated with modification of dopaminergic mediation in the mechanisms of intracerebral dynamic interrelations between different brain areas.

Alzheimer’s disease (AD) is the most common type of dementia and is a serious disruption to normal life. Monoamine oxidase-B (MAO-B) is an important target for the treatment of AD. In this study, machine learning approaches were applied to investigate the identification model of MAO-B inhibitors. The results showed that the identification model for MAO-B inhibitors with K-nearest neighbor(KNN) algorithm had a prediction accuracy of 94.1% and 88.0% for the 10-fold cross-validation test and the independent test set, respectively. Secondly, a quantitative activity prediction model for MAO-B was investigated with the Topomer CoMFA model. Two separate cutting mode approaches were used to predict the activity of MAO-B inhibitors. The results showed that the cut model with q2 = 0.612 (cross-validated correlation coefficient) and r2 = 0.824 (non-cross-validated correlation coefficient) were determined for the training and test sets, respectively. In addition, molecular docking was employed to analyze the interaction between MAO-B and inhibitors. Finally, based on our proposed prediction model, 1-(4-hydroxyphenyl)-3-(2,4,6-trimethoxyphenyl)propan-1-one (LB) was predicted as a potential MAO-B inhibitor and was validated by a multi-spectroscopic approach including fluorescence spectra and ultraviolet spectrophotometry.

INTRODUCTION: The development of valid methods to diagnose prodromal Alzheimer's disease (AD) in adults with Down syndrome (DS) is one of the many goals of the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS). METHODS: The diagnostic utility of a modified Cued Recall Test (mCRT) was evaluated in 332 adults with DS ranging from 25 to 81 years of age. Total recall was selected a priori, as the primary indicator of performance. Multiple regression and receiver-operating characteristic (ROC) analyses were used to compare diagnostic groups. RESULTS: Performance on the mCRT, as indicated by the total recall score, was highly sensitive to differences between diagnostic groups. ROC areas under the curve (AUCs) ranging from 0.843 to 0.955, were observed. DISCUSSION: The mCRT has strong empirical support for its use in clinical settings, as a valuable tool in studies targeting biomarkers of AD, and as a potential outcome measure in clinical trials targeting AD in this high-risk population.

Alzheimer's disease is the most common cause of Dementia. It accelerates the degeneration of brain cells and the progression of memory loss. Identifying and predicting Alzheimer's disease in its early stages is hard. A machine learning system that can predict the disease can solve this problem. High-dimensional data analysis is a massive problem for engineers and researchers in Machine learning. A simple and effective way to solve this problem is to use feature selection to eliminate redundant and useless data. This study aims to determine how accurate different machine learning methods are at diagnosing Alzheimer's disease with help of the feature selection method. Therefore, we utilize the Open Access Series of Imaging Studies dataset in several Machine learning models to accurately detect and predict Alzheimer's disease. We use the wrapper feature selection method in the proposed work to choose the minimal attribute set from the textual records. These approaches include Random Forest and Support vector machine as well as Decision Tree, XGBoost and Voting. We also utilize AdaBoost and Gradient Boosting on the selected data to classify Alzheimer's disease from the Alzheimer's disease vs. Normal disease dataset. As part of the analysis of the results, we found that the machine learning with feature selection methods provides better result as compared to machine learning without feature selection methods.

This review aimed to demonstrate recent research on the relationship between sleep disturbance and Alzheimer's disease (AD) due to sleep disturbance being determined as a specific modifiable risk factor for AD, but the mechanism is not well comprehended yet. The two main etiologies of AD are an accumulation of amyloid-ß (Aß) and tau protein in the brain. Several studies indicate a strong association between poor sleep and an increase of Aß in cerebrospinal fluid and plasma, signifying that sleep disturbance plays a crucial role in AD onset. Therefore, knowing this relation can help prevent AD through sleep disturbance monitoring and management. Keywords: potential intervention, Alzheimer's disease (AD), sleep disturbance monitoring. Title: Mini-Review: A potential intervention of Alzheimer disease prevention based on a sleep disturbance monitoring Author: Yeajin Choi International Journal of Healthcare Sciences ISSN 2348-5728 (Online) Vol. 10, Issue 1, April 2022 - September 2022 Page No: 230-232 Research Publish Journals Website: www.researchpublish.com Published Date: 26-August-2022 DOI: https://doi.org/10.5281/zenodo.7024644 Paper Download Link (Source) https://www.researchpublish.com/papers/mini-review-a-potential-intervention-of-alzheimer-disease-prevention-based-on-a-sleep-disturbance-monitoring, International Journal of Healthcare Sciences, ISSN 2348-5728 (Online), Research Publish Journals, Website: www.researchpublish.com, {"references":["[1]\tSerge Gauthier PR-N, Jose A. Morais, Claire Webster. World Alzhiemer's disesase Report 2021. London,England: Alzheimer's disease international; 2021.","[2]\tOrganization WH. World Health Rankings 2021 [Available from: https://www.worldlifeexpectancy.com/thailand-alzheimers-dementia.","[3]\tNedergaard M. Neuroscience. Garbage truck of the brain. Science. 2013;340(6140):1529-30.","[4]\tTarasoff-Conway JM, Carare RO, Osorio RS, Glodzik L, Butler T, Fieremans E, et al. Clearance systems in the brain-implications for Alzheimer disease. Nat Rev Neurol. 2015;11(8):457-70.","[5]\tLee H, Xie L, Yu M, Kang H, Feng T, Deane R, et al. The Effect of Body Posture on Brain Glymphatic Transport. J Neurosci. 2015;35(31):11034-44.","[6]\tXiang Y, Bu XL, Liu YH, Zhu C, Shen LL, Jiao SS, et al. Physiological amyloid-beta clearance in the periphery and its therapeutic potential for Alzheimer's disease. Acta Neuropathol. 2015;130(4):487-99.","[7]\tXie L, Kang H, Xu Q, Chen MJ, Liao Y, Thiyagarajan M, et al. Sleep drives metabolite clearance from the adult brain. Science. 2013;342(6156):373-7.","[8]\tSunkaria A, Bhardwaj S. Sleep Disturbance and Alzheimer's Disease: The Glial Connection. Neurochem Res. 2022;47(7):1799-815.","[9]\tAbeysinghe A, Deshapriya R, Udawatte C. Alzheimer's disease; a review of the pathophysiological basis and therapeutic interventions. Life Sci. 2020;256:117996.","[10]\tParoni G, Bisceglia P, Seripa D. Understanding the Amyloid Hypothesis in Alzheimer's Disease. J Alzheimers Dis. 2019;68(2):493-510.","[11]\tMullane K, Williams M. Alzheimer's disease (AD) therapeutics - 1: Repeated clinical failures continue to question the amyloid hypothesis of AD and the current understanding of AD causality. Biochem Pharmacol. 2018;158:359-75.","[12]\tEftekharzadeh B, Daigle JG, Kapinos LE, Coyne A, Schiantarelli J, Carlomagno Y, et al. Tau Protein Disrupts Nucleocytoplasmic Transport in Alzheimer's Disease. Neuron. 2019;101(2):349.","[13]\tMandelkow EM, Mandelkow E. Biochemistry and cell biology of tau protein in neurofibrillary degeneration. Cold Spring Harb Perspect Med. 2012;2(7):a006247.","[14]\tYun CH, Lee HY, Lee SK, Kim H, Seo HS, Bang SA, et al. Amyloid Burden in Obstructive Sleep Apnea. J Alzheimers Dis. 2017;59(1):21-9.","[15]\tMaestri M, Carnicelli L, Tognoni G, Di Coscio E, Giorgi FS, Volpi L, et al. Non-rapid eye movement sleep instability in mild cognitive impairment: a pilot study. Sleep Med. 2015;16(9):1139-45.","[16]\tMander BA, Marks SM, Vogel JW, Rao V, Lu B, Saletin JM, et al. beta-amyloid disrupts human NREM slow waves and related hippocampus-dependent memory consolidation. Nat Neurosci. 2015;18(7):1051-7.","[17]\tJu YE, McLeland JS, Toedebusch CD, Xiong C, Fagan AM, Duntley SP, et al. Sleep quality and preclinical Alzheimer disease. JAMA Neurol. 2013;70(5):587-93."]}

Background The deposition of β-amyloid (Aβ) in the brain is a biomarker of Alzheimer’s disease (AD). Highly sensitive Aβ positron emission tomography (PET) imaging plays an essential role in diagnosing and evaluating the therapeutic effects of AD. Aim To synthesize a new Aβ tracer [18F]DRKXH1 (5-(4-(6-(2-[18]fluoroethoxy)ethoxy)imidazo[1,2-alpha]pyridin-2-yl)phenyl) and evaluate the tracer performance by biodistribution analysis, in vivo small-animal PET-CT dynamic scan, ex vivo and in vitro autoradiography, and PET in human subjects. Methods [18F]DRKXH1 was synthesized automatically by the GE FN module. Log D (pH 7.4) and biodistribution of [18F]DRKXH1 were investigated. Small-animal-PET was used for [18F]DRKXH1 and [18F]AV45 imaging study in AD transgenic mice (APPswe/PSEN1dE9) and age-matched normal mice. The distribution volume ratios (DVR) and standardized uptake value ratios (SUVRs) were calculated with the cerebellum as the reference region. The deposition of Aβ plaques in the brain of AD transgenic mice was determined by ex vivo autoradiography and immunohistochemistry. In vitro autoradiography was performed in the postmortem brain sections of AD patients and healthy controls. Two healthy control subjects and one AD patient was subjected to in vivo PET study using [18F]DRKXH1. Results The yield of [18F]DRKXH1 was 40%, and the specific activity was 156.64 ± 11.55 GBq/μmol. [18F]DRKXH1 was mainly excreted through the liver and kidney. The small-animal PET study showed high initial brain uptake and rapid washout of [18F]DRKXH1. The concentration of [18F]DRKXH1 was detected in the cortex and hippocampus of AD transgenic mice brain. The cortex DVR of AD transgenic mice was higher than that of WT mice (P 18F]-DRKXH1 is higher than that of [18F]-AV45 (1.29 ± 0.05 vs. 1.05 ± 0.08; t = 5.33, P = 0.0003). Autoradiography of postmortem human brain sections showed [18F]DRKXH1-labeled Aβ plaques in the AD brain. The AD patients had high retention in cortical regions, while healthy control subjects had uniformly low radioactivity uptake. Conclusions [18F]DRKXH1 is an Aβ tracer with high sensitivity in preclinical study and has the potential for in vivo detection of the human brain.

The COVID 19 pandemic has led to an increase in the number of patients in need of ventilation. Limitations in the number of respirators may cause an ethical problem for the medical and nursing staff in deciding who should be connected to the available respirators. We conducted a cross-sectional survey among a convenience sample of 278 healthcare professionals at one medical center. They were asked to rank their preference in respirator allocation to three COVID-19 patients, one 80 years old with no cognitive illness, one 50 years old with Alzheimer's disease (AD), and one 80 years old with AD. Most respondents (75%) chose the 80-year-old AD patient as last preference, but were evenly divided on how to rank the other two patients. Medical staff have difficulty deciding whether age or cognitive status should be the deciding factor ventilator allocation. Determination of a set policy would help professionals with these decisions.

Dysregulation of transcriptome expression has been reported to play an increasingly significant role in AD. In this study, we firstly identified a vital gene module associated with the accumulation of β-amyloid (Aβ) and phosphorylated tau (p-tau) using the WGCNA method. The vital module, named target module, was then employed for the identification of key transcriptome biomarkers. For coding RNA, GNA13 and GJA1 were identified as key biomarkers based on ROC analysis. As for non-coding RNA, MEG3, miR-106a-3p, and miR-24-3p were determined as key biomarkers based on analysis of a ceRNA network and ROC analysis. Experimental analyses firstly confirmed that GNA13, GJA1, and ROCK2, a downstream effector of GNA13, were all increased in 5XFAD mice, compared to littermate mice. Moreover, their expression was increased with aging in 5XFAD mice, as Aβ and p-tau pathology developed. Besides, the expression of key ncRNA biomarkers was verified to be decreased in 5XFAD mice. GSEA results indicated that GNA13 and GJA1 were respectively involved in ribosome and spliceosome dysfunction. MEG3, miR-106a-3p, and miR-24-3p were identified to be involved in MAPK pathway and PI3K-Akt pathway based on enrichment analysis. In summary, we identified several key transcriptome biomarkers, which promoted the prediction and diagnosis of AD.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory decline and cognitive impairment. Research on biomarkers can aid in early diagnosis, monitoring disease progression, evaluating treatment efficacy, and advancing fundamental research. We conducted a cross-sectional longitudinal study to see if there is an association between AD patients and age-matched healthy controls for their physiologic skin characteristics, such as pH, hydration, transepidermal water loss (TEWL), elasticity, microcirculation, and ApoE genotyping. The study used the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating-Sum of the Boxes (CDR-SB) scales as references to quantify the presence of disease, if any. Our findings demonstrate that AD patients have a dominantly neutral pH, greater skin hydration, and less elasticity compared to the control subjects. At baseline, the tortuous capillary percentage negatively correlated with MMSE scores in AD patients. However, AD patients who carry the ApoE E4 allele and exhibit a high percentage of tortuous capillaries and capillary tortuous numbers have shown better treatment outcomes at six months. Therefore, we believe that physiologic skin testing is a rapid and effective way to screen, monitor progression, and ultimately guide the most appropriate treatment for AD patients.

The vegetative state (VS) and minimally conscious state (MCS) are two major types of chronic disorders of consciousness (DoC). The assessment of these two consciousness states generally relies on the Coma Recovery Scale-Revised (CRS-R) score, but a high misdiagnosis rate limits the generalized use of this score. To identify metabolites in human plasma that can accurately distinguish VS from MCS patients, comprehensive plasma metabolic profiles were obtained with targeted metabolomics analysis and untargeted and targeted lipidomics analysis. Univariate and multivariate analyses were used to assess the significance of differences. Compared with healthy controls (HCs), the DoC groups, Emerged from Minimally Conscious State (EMCS) group and Alzheimer's disease (AD) group had significantly different metabolic profiles. Purine metabolism pathway differed the most between the DoC (MCS and VS) and HC groups. In this pathway, adenosine, ADP, and AMP, which are the derived products of ATP degradation, were decreased in the MCS and VS groups compared to healthy controls. More importantly, we identified certain lipids for which the levels were enriched in the VS or MCS groups. Specifically, phosphatidylcholine, (38:5)-H (PC(38:5)-H), and arachidonic acid (AA) differed substantially between the VS and MCS groups and may be used to distinguish these two groups of patients. Together, our findings suggest that metabolic profiling is significantly altered in patients with chronic DoC.

Objectives:To perform a meta-analysis of clinical studies on the differences in treatment or research decision-making capacity among patients with Mild Cognitive Impairment (MCI), Alzheimer’s disease (AD), and healthy comparisons (HCs).Design:A systematic search was conducted on Medline/Pubmed, CINAHL, PsycINFO, Web of Science, and Scopus. Standardized mean differences and random-effects model were used in all cases.Setting:The United States, France, Japan, and China.Participants:Four hundred and ten patients with MCI, 149 with AD, and 368 HCs were included.Measurements:The studies we included in the analysis assessed decisional capacity to consent by the MacArthur Competence Assessment Tool for Treatment (MAcCAT-T), MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR), Capacity to Consent to Treatment Instrument (CCTI), and University of California Brief Assessment of Capacity to Consent (UBACC).Results:We identified 109 potentially eligible studies from 1672 records, and 7 papers were included in the meta-analysis. The meta-analysis showed that there was significant impairment in a decision-making capacity in MCI patients compared to the HCs group in terms of Understanding (SMD = −1.04, 95% CI: −1.31 to −0.77, P < 0.001; I2 = 52%, P = 0.07), Appreciation (SMD = −0.51, 95% CI: −0.66 to −0.36, P < 0.001; I2 = 0%, P = 0.97), and Reasoning (SMD = −0.62, 95% CI: −0.77, −0.47, P < 0.001; I2=0%, P =0.46). MCI patients scored significantly higher in Understanding (SMD = 1.50, 95% CI: 0.91, 2.09, P = 0.01, I2 = 78%, P = 0.00001) compared to patients affected by AD.Conclusions:Patients affected by MCI are at higher risk of impaired capacity to consent to treatment and research compared to HCs, despite being at lower risk compared to patients affected by AD. Clinicians and researchers need to carefully evaluate decisional capacity in MCI patients providing informed consent.

Background In recent years, excellent results have suggested an association between the “brain-gut” axis and Alzheimer’s disease (AD) progression, yet the role of the “brain-gut” axis in AD pathogenesis still remains obscure. Herein, we provided a potential link between the central and peripheral neuroinflammatory disorders in AD progression. Methods The Morris water maze (MWM) test, immunohistochemistry, ELISA, ProcartaPlex Multiplex immunoassay, multiple LC-MS/MS methods, and the V3-V4 regions of 16S rRNA genes were applied to explore potential biomarkers. Results In Tg-APP/PS1 mice, gut dysbiosis and lipid metabolism were highly associated with AD-like neuroinflammation. The combination of inflammatory factors (IL-6 and INF-γ), phosphatidylcholines (PCs) and SCFA-producing bacteria were expected to be early diagnostic biomarkers for AD. Huanglian Jiedu decoction (HLJDD) suppressed gut dysbiosis and the associated Aβ accumulation, harnessed neuroinflammation and reversed cognitive impairment. Conclusion Together, our findings highlighted the roles of neuroinflammation induced by gut dysbiosis and lipid metabolism disorder in AD progression. This integrated metabolomics approach showed its potential to understand the complex mechanisms of HLJDD in the treatment of AD.

Glial fibrillary acidic protein (GFAP) is an intermediate filament structural protein involved in cytoskeleton assembly and integrity, expressed in high abundance in activated glial cells. GFAP is neuroprotective, as knockout mice are hypersensitive to traumatic brain injury. GFAP in cerebrospinal fluid is a biomarker of Alzheimer’s disease (AD), dementia with Lewy bodies, and frontotemporal dementia (FTD). Here, we present novel evidence that GFAP is markedly overexpressed and differentially phosphorylated in AD hippocampus, especially in AD with the apolipoprotein E [ε4, ε4] genotype, relative to age-matched controls (AMCs). Kinases that phosphorylate GFAP are upregulated in AD relative to AMC. A knockdown of these kinases in SH-SY5Y-APPSw human neuroblastoma cells reduced amyloid accrual and lowered protein aggregation and associated behavioral traits in C. elegans models of polyglutamine aggregation (as observed in Huntington’s disease) and of Alzheimer’s-like amyloid formation. In silico screening of the ChemBridge structural library identified a small molecule, MSR1, with stable and specific binding to GFAP. Both MSR1 exposure and GF AP-specific RNAi knockdown reduce aggregation with remarkably high concordance of aggregate proteins depleted. These data imply that GFAP and its phosphorylation play key roles in neuropathic aggregate accrual and provide valuable new biomarkers, as well as novel therapeutic targets to alleviate, delay, or prevent AD.

Acetylcholinesterase (AChE) is one of the classical targets in the treatment of Alzheimer’s disease (AD). Inhibition of AChE slows down the hydrolysis of acetycholine and increases choline levels, improving the cognitive function. The achieved success of plant-based natural drugs acting as AChE inhibitors, such as galantamine (GAL) from Galanthus genus and huperzine A from Huperzia serrate (approved drug in China), in the treatment of AD, and the fact that natural compounds (NCs) are considered as safer and less toxic compared to synthetic drugs, led us to screen the available NCs (almost 150,000) in the ZINC12 database for AChE inhibitory activity. The compounds were screened virtually by molecular docking, filtered for suitable ADME properties, and 32 ligands from 23 structural groups were selected. The stability of the complexes was estimated via 1 μs molecular dynamics simulation. Ten compounds formed stable complexes with the enzyme and had a vendor and a reasonable price per mg. They were tested for AChE inhibitory and antioxidant activity. Five compounds showed weak AChE inhibition and three of them exhibited high antioxidant activity.

Alzheimer's Disease (AD) represents the most frequent type of dementia in elderly people. There are two major forms of the disease: sporadic (SAD) - whose causes are not completely understood - and familial (FAD) - with clear autosomal dominant inheritance. The two main hallmarks of AD are extracellular deposits of amyloid-beta (Ab) peptide and intracellular deposits of the hyperphosphorylated form of the tau protein (P-tau). An ever-growing body of research supports the infectious hypothesis of sporadic forms of AD. Indeed, it has been documented that some pathogens, such as herpesviruses and certain bacterial species, are commonly present in AD patients, prompting recent clinical research to focus on the characterization of Antimicrobial Peptides (AMPs) in this pathology. Literature also demonstrates that Ab can be considered itself as an AMP thus representing a type of innate immune defense peptide that protect the host against a variety of pathogens. Beyond Ab, other proteins with antimicrobial activity, such as lactoferrin, defensins, cystatins, thymosin β4, LL37, histatin 1 and statherin have been shown to be involved in AD. Here we have summarized and discussed these findings and explored the diagnostic and therapeutic potential of AMPs in AD.

Purpose End-of-life studies have validated the binary visual reads of 18F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM)-based classifier will be tested against pathological ground truths and its performance determined in cognitively healthy older adults. Methods We applied SVM with a linear kernel to an 18F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological ground truths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest amplitudes of feature weights for each of the two neuropathological ground truths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological ground truths. A receiver operating characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK. Results The classifiers yielded adequate specificity and sensitivity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was −0.66 for the classifier trained with neuritic amyloid plaque density, and −0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48–51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%), which closely matched the CL threshold for discriminating phases 0–2 from 3–5 based on the end-of-life dataset and the neuropathological ground truth. Discussion Among a set of neuropathologically validated classifiers trained with end-of-life cases, transfer to a cognitively normal population works best for a classifier trained with amyloid phases and using only voxels with the highest amplitudes of feature weights.

Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer’s disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer’s Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer’s, Parkinson’s (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4–7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8–12 Hz) and beta (13–30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias. European Committee (H2020-EU.1.3.1.H2020-MSCA-ITN-ETN-2016 project)

Imaging genetics research based on Sparse Canonical Correlation Analysis (SCCA) helps to discover the correlation between pathological features reflected by neuroimaging and genotypic variation. Multi-Task SCCA (MTSCCA) method is to identify bi-multivariate associations between SNPs and multi-modal imaging QTs. However, the MTSCCA method is unsupervised and cannot identify diagnosis-guided genotype-phenotype associations. In order to improve the performance and interpretability of MTSCCA, we propose an improved MTSCCA algorithm, which is a supervised sparse bivariate learning model fused with a linear regression model, in which the regression part plays a guiding role in imaging QT selection. To jointly understand the relationship between genotypes and phenotypes of multiple tasks, in this study, gene expression data and single nucleotide polymorphisms (SNPs) as genetic data are considered in the algorithm. The focus of each task is to determine the genotype-phenotype pattern guided by the diagnostic team to discover the association with SNP/gene and brain region changes. Besides, the Laplacian matrices of three kinds of data are added as prior knowledge to the algorithm penalty item so that the algorithm can analyze the correlation between different features. Compared with other SCCA methods, our algorithm has improved noise resistance and stability, and found some diagnostic-specific SNP/gene-ROI specific to the two diagnostic groups of MCI and AD. Significance: This method provides a way to further study the association of multi-modal biological data and identify the complex association patterns of diseases.

Alzheimer’s disease (AD) is one of the most serious neurological disorders for elderly people. AD affected patient experiences severe memory loss. One of the main reasons for memory loss in AD patients is atrophy in the hippocampus, amygdala, etc. Due to the enormous growth of AD patients and the paucity of proper diagnostic tools, detection and classification of AD are considered as a challenging research area. Before a Cognitively normal (CN) person develops symptoms of AD, he may pass through an intermediate stage, commonly known as Mild Cognitive Impairment (MCI). MCI is having two stages, namely StableMCI (SMCI) and Progressive MCI (PMCI). In SMCI, a patient remains stable, whereas, in the case of PMCI, a person gradually develops few symptoms of AD. Several research works are in progress on the detection and classification of AD based on changes in the brain. In this paper, we have analyzed few existing state-of-art works for AD detection and classification, based on different feature extraction approaches. We have summarized the existing research articles with detailed observations. We have also compared the performance and research issues in each of the feature extraction mechanisms and observed that the AD classification using the wavelet transform-based feature extraction approaches might achieve convincing results.

Alzheimer’s Disease (AD) is a psychological disorder in elderly people which causes severe intellectual disabilities. Proper processing of neuro-images can provide differences in brain tissues which may help in diagnosing the disease more effectively. But, due to the complex structures, this is a challenge in differentiating the brain tissues and classifying AD using traditional classification mechanisms. Deep Neural Network (DNN) is a machine learning technique that has the ability to absorb the most important information for classifying an object accurately. LeNet is a popular DNN based model with a simple and effective architecture that also consumes very less implementation time. As like most of the DNN models, LeNet also uses MaxPooling layer for dimensionality reduction by eliminating the information of minimum valued elements. In brain images low intensity valued pixels also may contain very important features. To keep the minimum valued elements too in the network, we have created a separate layer that performs Min-Pooling operation. MinPooling and MaxPooling layers are then concatenated together. Finally, we have replaced all MaxPooling Layers in LeNet by the concatenated layers. We have analysed and compared the performances of modified LeNet model with 20 other most commonly used DNN models, and some of the related works. It is observed that, the modified LeNet model achieved the highest performances. It is also observed that, original LeNet model can classify AD with a performance rate of 80%, whereas, the proposed modified LeNet model achieved an average performance rate of 96.64%.

Objective This retrospective and exploratory study tested the accuracy of artificial neural networks (ANNs) at detecting Alzheimer’s disease patients with dementia (ADD) based on input variables extracted from resting-state electroencephalogram (rsEEG), structural magnetic resonance imaging (sMRI) or both. Methods For the classification exercise, the ANNs had two architectures that included stacked (autoencoding) hidden layers recreating input data in the output. The classification was based on LORETA source estimates from rsEEG activity recorded with 10–20 montage system (19 electrodes) and standard sMRI variables in 89 ADD and 45 healthy control participants taken from a national database. Results The ANN with stacked autoencoders and a deep leaning model representing both ADD and control participants showed classification accuracies in discriminating them of 80%, 85%, and 89% using rsEEG, sMRI, and rsEEG + sMRI features, respectively. The two ANNs with stacked autoencoders and a deep leaning model specialized for either ADD or control participants showed classification accuracies of 77%, 83%, and 86% using the same input features. Conclusions The two architectures of ANNs using stacked (autoencoding) hidden layers consistently reached moderate to high accuracy in the discrimination between ADD and healthy control participants as a function of the rsEEG and sMRI features employed. Significance The present results encourage future multi-centric, prospective and longitudinal cross-validation studies using high resolution EEG techniques and harmonized clinical procedures towards clinical applications of the present ANNs.