Search results for: Alzheimer disease

Authors: M. Klimova, O. Semyachkina-Glushkovskaya, J. Kurts, E. Zinchenko, N. Navolokin, A. Shirokov, A. Dubrovsky, A. Abdurashitov, A. Terskov, A. Mamedova, I. Agranovich, T. Antonova, I. Blokhina

Abstract:

The direction for research of Alzheimer's disease is to find an effective non-invasive and non-pharmacological way of treatment. Here we tested our hypothesis that the opening of the blood-brain barrier (BBB) induces activation of lymphatic drainage and clearing functions that can be used as a method for non-invasive stimulation of clearance of beta-amyloid and therapy of Alzheimer’s disease (AD). To test our hypothesis, in this study on healthy male mice we analyzed the interaction between BBB opening by repeated loud music (100-10000 Hz, 100 dB, duration 2 h: 60 sec – sound; 60 sec - pause) and functional changes in the meningeal lymphatic vessels (MLVs). We demonstrate clearance of dextran 70 kDa (i.v. injection), fluorescent beta-amyloid (intrahippocampal injection) and gold nanorods (intracortical injection) via MLV that significantly increased after the opening of BBB. Our studies also demonstrate that the BBB opening was associated with the improvement of neurocognitive status in mice with AD. Thus, we uncover therapeutic effects of BBB opening by loud music, such as non-invasive stimulation of lymphatic clearance of beta-amyloid in mice with AD, accompanied by improvement of their neurocognitive status. Our data are consistent with other results suggesting the therapeutic effect of BBB opening by focused ultrasound without drugs for patients with AD. This research was supported by a grant from RSF 18-75-10033

Keywords: Alzheimer's disease, beta-amyloid, blood-brain barrier, meningeal lymphatic vessels, repeated loud music

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Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Bilal Ahmad

Abstract:

Alzheimer’s disease (AD) is one of the most common neurodegenerative illnesses. However, how Gut-microbiota plays a role in the pathogenesis of AD is not well elucidated. The purpose of this literature review is to summarize and understand the current findings that may elucidate the gut microbiota's role in the development of AD. Methods: A literature review of all the relevant papers known to the author was conducted. Relevant articles, abstracts and research papers were collected from well-accepted web sources like PubMed, PMC, and Google Scholar. Results: Recent studies have shown that Gut-microbiota has an important role in the progression of AD via Gut-Microbiota-Brain Axis. The onset of AD supports the ‘Hygiene Hypothesis’, which shows that AD might begin in the Gut, causing dysbiosis, which interferes with the intestinal barrier by releasing pro-inflammatory cytokines and making its way up to the brain via the blood-brain barrier (BBB). Molecular mechanisms lipopolysaccharides and serotonin kynurenine (tryptophan) pathways have a direct association with inflammation, the immune system, neurodegeneration, and AD. Conclusion: The studies helped to analyze the molecular basis of AD, other neurological conditions like depression, autism, and Parkinson's disease and how they are linked to Gut-microbiota. Further, studies to explore the therapeutic effects of probiotics in AD and cognitive enhancement should be warranted to provide significant clinical and practical value.

Keywords: gut-microbiota, Alzheimer’s disease, second brain aging, lipopolysaccharides, short-chain fatty acids

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Authors: Ireneusz Majsterek, Dariusz Pytel, J. Alan Diehl

Abstract:

PKR-like ER kinase (PERK) is serine/threonie endoplasmic reticulum (ER) transmembrane kinase activated during ER-stress. PERK can activate signaling pathways known as unfolded protein response (UPR). Attenuation of translation is mediated by PERK via phosphorylation of eukaryotic initiation factor 2α (eIF2α), which is necessary for translation initiation. PERK activation also directly contributes to activation of Nrf2 which regulates expression of anti-oxidant enzymes. An increased phosphorylation of eIF2α has been reported in Alzheimer disease (AD) patient hippocampus, indicating that PERK is activated in this disease. Recent data have revealed activation of PERK signaling in non-Hodgkins lymphomas. Results also revealed that loss of PERK limits mammary tumor cell growth in vitro and in vivo. Consistent with these observations, activation of UPR in vitro increases levels of the amyloid precursor protein (APP), the peptide from which beta-amyloid plaques (AB) fragments are derived. Finally, proteolytic processing of APP, including the cleavages that produce AB, largely occurs in the ER, and localization coincident with PERK activity. Thus, we expect that PERK-dependent signaling is critical for progression of many types of diseases (human cancer, neurodegenerative disease and other). Therefore, modulation of PERK activity may be a useful therapeutic target in the treatment of different diseases that fail to respond to traditional chemotherapeutic strategies, including Alzheimer’s disease. Our goal will be to developed therapeutic modalities targeting PERK activity.

Keywords: PERK kinase, small molecule inhibitor, neurodegenerative disease, Alzheimer’s disease

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Authors: Mateen A Khan, Taj Mohammad, Md. Imtaiyaz Hassan

Abstract:

Alzheimer’s disease is characterized by the accumulation of the processing products of the amyloid beta peptide cleaved by amyloid precursor protein (APP). Iron increases the synthesis of amyloid beta peptides, which is why iron is present in Alzheimer's disease patients' amyloid plaques. Iron misregulation in the brain is linked to the overexpression of APP protein, which is directly related to amyloid-β aggregation in Alzheimer’s disease. The APP 5'-UTR region encodes a functional iron-responsive element (IRE) stem-loop that represents a potential target for modulating amyloid production. Targeted regulation of APP gene expression through the modulation of 5’-UTR sequence function represents a novel approach for the potential treatment of AD because altering APP translation can be used to improve both the protective brain iron balance and provide anti-amyloid efficacy. The molecular docking analysis of APP IRE RNA with eukaryotic translation initiation factors yields several models exhibiting substantial binding affinity. The finding revealed that the interaction involved a set of functionally active residues within the binding sites of eIF4F. Notably, APP IRE RNA and eIF4F interaction were stabilized by multiple hydrogen bonds with residues of APP IRE RNA and eIF4F. It was evident that APP IRE RNA exhibited a structural complementarity that tightly fit within binding pockets of eIF4F. The simulation studies further revealed the stability of the complexes formed between RNA and eIF4F, which is crucial for assessing the strength of these interactions and subsequent roles in the pathophysiology of Alzheimer’s disease. In addition, MD simulations would capture conformational changes in the IRE RNA and protein molecules during their interactions, illustrating the mechanism of interaction, conformational change, and unbinding events and how it may affect aggregation propensity and subsequent therapeutic implications. Our binding studies correlated well with the translation efficiency of APP mRNA. Overall, the outcome of this study suggests that the genomic modification and/or inhibiting the expression of amyloid protein by targeting APP IRE RNA can be a viable strategy to identify potential therapeutic targets for AD and subsequently be exploited for developing novel therapeutic approaches.

Keywords: Alzheimer's disease, Protein-RNA interaction analysis, molecular docking simulations, conformational dynamics, binding stability, binding kinetics, protein synthesis.

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Authors: Sofia Matoug, Amr Abdel-Dayem

Abstract:

This paper presents a comprehensive survey of recent research studies to segment and classify brain MR (magnetic resonance) images in order to detect significant changes to brain ventricles. The paper also presents a general framework for detecting regions that atrophy, which can help neurologists in detecting and staging Alzheimer. Furthermore, a prototype was implemented to segment brain MR images in order to extract the region of interest (ROI) and then, a classifier was employed to differentiate between normal and abnormal brain tissues. Experimental results show that the proposed scheme can provide a reliable second opinion that neurologists can benefit from.

Keywords: Alzheimer, brain images, classification techniques, Magnetic Resonance Images MRI

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

Abstract:

Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

Abstract:

Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Francesco Angelucci, Katerina Veverova, Alžbeta Katonová, Lydia Piendel, Martin Vyhnalek, Jakub Hort

Abstract:

Alzheimer's disease (AD) is a central nervous system (CNS) disease characterized by loss of memory, cognitive functions and neurodegeneration. Plasmin is an enzyme degrading many plasma proteins. In the CNS, plasmin may reduce the accumulation of A, and have other actions relevant to AD pathophysiology. Brain plasmin synthesis is regulated by two enzymes: one activating, the tissue plasminogen activator (tPA), and the other inhibiting, the plasminogen activator inhibitor-1 (PAI-1). We investigated whether tPA and PAI-1 serum levels in AD and amnestic mild cognitive impairment (aMCI) patients are altered compared to cognitively healthy controls. Moreover, we examined the PAI-1/tPA ratio in these patient groups. 40 AD, 40 aMCI and 10 healthy controls were recruited. Venous blood was collected and PAI-1 and tPA serum concentrations were quantified by sandwich ELISAs. The results showed that PAI-1 levels increased in AD and aMCI patients. This increase negatively correlated with cognitive deficit measured by MMSE. Similarly, the ratio between tPA and PAI-1 gradually increases in aMCI and AD patients. This study demonstrates that AD and aMCI patients have altered PAI-1 serum levels and PAI-1/tPA ratio. Since these enzymes are CNS regulators of plasmin, PAI-1 serum levels could be a marker reflecting a cognitive decline in AD.

Keywords: Alzheimer disease, amnestic mild cognitive impairment, plasmin, tissue-type plasminogen activator

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Authors: Huafeng Wei

Abstract:

Failures of developing new drugs primarily based on the amyloid pathology hypothesis after decades of efforts internationally lead to changes of focus targeting alternative pathways of pathology in Alzheimer’s disease (AD). Disruption of intracellular Ca2+ homeostasis, especially the pathological and excessive Ca2+ release from the endoplasmic reticulum (ER) via ryanodine receptor (RyRs) Ca2+ channels, has been considered an upstream pathology resulting in major AD pathologies, such as amyloid and Tau pathology, mitochondria damage and inflammation, etc. Therefore, dantrolene, an inhibitor of RyRs that reduces the pathological Ca2+ release from ER and a clinically available drug for the treatment of malignant hyperthermia and muscle spasm, is expected to ameliorate AD multiple pathologies synapse and cognitive dysfunction. Our own studies indicated that dantrolene ameliorated impairment of neurogenesis and synaptogenesis in neurons developed from induced pluripotent stem cells (iPSCs) originated from skin fibroblasts of either familiar (FAD) or sporadic (SAD) AD by restoring intracellular Ca2+ homeostasis. Intranasal administration of dantrolene significantly increased its passage across the blood-brain barrier (BBB) and, therefore its brain concentrations and durations. This can render dantrolene a more effective therapeutic drug with fewer side effects for chronic AD treatment. This review summarizes the potential therapeutic and side effects of dantrolene and repurposes intranasal dantrolene as a disease-modifying drug for future AD treatment.

Keywords: Alzheimer's disease, calcium, drug development, dementia, neurodegeneration, neurogenesis

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Authors: Ali Bayram, Burak Uz, Ilhan Dolasik, Remzi Yiğiter

Abstract:

The GABARAP (GABAA-receptor-associated protein) family consists of GABARAP, GABARAPL1 (GABARAP-like 1) and GABARAPL2 (GABARAP-like 2). GABARAPL1, like GABARAP, was described to interact with both GABAA receptor and tubulin, and to be involved in intracellular GABAA receptor trafficking and promoting tubulin polymerization. In addition, GABARAPL1 is thought to be involved in various physiological (autophagosome closure, regulation of circadian rhythms) and/or pathological mechanisms (cancer, neurodegeneration). Alzheimer’s disease (AD) is a progressive neuro degenerative disorder characterized with impaired cognitive functions. Disruption of the GABAergic neuro transmission as well as cholinergic and glutamatergic interactions, may also be involved in the pathogenesis of AD. GABARAPL1 presents a regulated tissue expression and is the most expressed gene among the GABARAP family members in the central nervous system. We, herein, conducted a study to investigate the GABARAPL1 mRNA expression levels in patients with AD. 50 patients with AD and 49 control patients were enrolled to the present study. Messenger RNA expression levels of GABARAPL1 were detected by real-time polymerase chain reaction. GABARAPL1 mRNA expression in AD / control patients was 0,495 (95% confidence interval: 0,404-0,607), p= 0,00000002646. Reduced activity of GABARAPL1 gene might play a role, at least partly, in the pathophysiology of AD.

Keywords: Alzheimer’s disease, GABARAPL1, mRNA expression, RT-PCR

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

Abstract:

Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

Abstract:

Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential Cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L were in-silico screened using molecular docking, pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect towards the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interactions stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries towards the rational development of potent anti-Alzheimer agents.

Keywords: alzheimer’s disease, molecular docking, cannabis sativa l, cholinesterase inhibitors

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Authors: Ali̇ Bayram, Semih Dalkilic, Remzi Yigiter

Abstract:

N-methyl-D-aspartate (NMDA) receptor is a subtype of glutamate receptor and plays a pivotal role in learning, memory, neuronal plasticity, neurotoxicity and synaptic mechanisms. Animal experiments were suggested that glutamate-induced excitotoxic injuriy and NMDA receptor blockage lead to amnesia and other neurodegenerative diseases including Alzheimer’s disease (AD), Huntington’s disease, amyotrophic lateral sclerosis. Aim of this study is to investigate association between NMDA receptor coding gene GRIN2B expression level and Alzheimer disease. The study was approved by the local ethics committees, and it was conducted according to the principles of the Declaration of Helsinki and guidelines for the Good Clinical Practice. Peripheral blood was collected 50 patients who diagnosed AD and 49 healthy control individuals. Total RNA was isolated with RNeasy midi kit (Qiagen) according to manufacturer’s instructions. After checked RNA quality and quantity with spectrophotometer, GRIN2B expression levels were detected by quantitative real time PCR (QRT-PCR). Statistical analyses were performed, variance between two groups were compared with Mann Whitney U test in GraphpadInstat algorithm with 95 % confidence interval and p < 0.05. After statistical analyses, we have determined that GRIN2B expression levels were down regulated in AD patients group with respect to control group. But expression level of this gene in each group was showed high variability. İn this study, we have determined that NMDA receptor coding gene GRIN2B expression level was down regulated in AD patients when compared with healthy control individuals. According to our results, we have speculated that GRIN2B expression level was associated with AD. But it is necessary to validate these results with bigger sample size.

Keywords: Alzheimer’s disease, N-methyl-d-aspartate receptor, NR2B, GRIN2B, mRNA expression, RT-PCR

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

Abstract:

Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L. were in-silico screened using molecular docking and pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect on the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer's therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interaction stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries toward the rational development of potent anti-Alzheimer agents.

Keywords: Alzheimer’s disease, molecular docking, Cannabis sativa L., cholinesterase inhibitors, molecular dynamics, ADMET, MM-PBSA

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Authors: Son Nguyen, Thanh Van, Ly Le

Abstract:

Ca2+ - dependent calmodulin kinase IIa (CaMKIIa) has recently been found to associate with protein tau missorting and polymerization in Alzheimer’s Disease (AD). However, there has yet inhibitors targeting CaMKIIa to investigate the correlation between CaMKIIa activity and protein tau polymer formation. Combining virtual screening and our statistics in binding contribution scoring function (BCSF), we rationally identified potential compounds that bind to specific CaMKIIa active site and specificity-affinity distribution of the ligand within the active site. Using molecular dynamics simulation, we identified structural stability of CaMKIIa and potent inhibitors, and site-directed bonding, separating non-specific and specific molecular interaction features. Despite of variation in confirmation of simulation time, interactions of the potent inhibitors were found to be strongly associated with the unique chemical features extracted from molecular binding poses. In addition, competitive inhibitors within CaMKIIa showed an important molecular recognition pattern toward specific ligand features. Our approach combining virtual screening with BCSF may provide an universally applicable method for precise identification in the discovery of compounds.

Keywords: Alzheimer’s disease, Ca 2+ -dependent calmodulin kinase IIa, protein tau, molecular docking

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Authors: Lourdes Hanna, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan, Grace Imaguezegie

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Background: Degeneration of the central nervous system (CNS), also known as neurodegeneration, describes an age-associated progressive loss of the structure and function of neuronal materials, leading to functional and mental impairments. Main body: Neuroinflammation contributes to the continuous worsening of neurodegenerative states which are characterised by functional and mental impairments due to the progressive loss of the structure and function of neu-ronal materials. Some of the most common neurodegenerative diseases include Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). Whilst neuroinflammation is a key contributor to the progression of such disease states, it is not the single cause as there are multiple factors which contribute. Theoretically, non-steroidal anti-inflammatory drugs (NSAIDs) have potential to target neuroinflammation to reduce the severity of disease states. Whilst some animal models investigating the effects of NSAIDs on the risk of neurodegenerative diseases have shown a beneficial effect, this is not the same finding. Conclusion: Further investigation using more advanced research methods is required to better understand neuroinflammatory pathways and understand if there is still a potential window for NSAID efficacy.

Keywords: intervention, central nervous system, neurodegeneration, neuroinflammation

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Authors: Nikhil Agrawal, Adam A. Skelton

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Alzheimer’s disease (AD) is one of the most common forms of dementia, which is caused by misfolding and aggregation of amyloid beta (Aβ) peptides into amyloid-β fibrils (Aβ fibrils). To disrupt the remodeling of Aβ fibrils, a number of candidate molecules have been proposed. To study the molecular mechanisms of Aβ fibrils remodeling we performed a series of all-atom molecular dynamics simulations, a total time of 3µs, in explicit solvent. Several previously undiscovered candidate molecule-Aβ fibrils binding modes are unraveled; one of which shows the direct conformational change of the Aβ fibril by understanding the physicochemical factors responsible for binding and subsequent remodeling of Aβ fibrils by the candidate molecule, open avenues into structure-based drug design for AD can be opened.

Keywords: alzheimer’s disease, amyloid, MD simulations, misfolded protein

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Authors: Huafeng Wei

Abstract:

Dementia in Alzheimer’s Disease (AD) is the number one cause of dementia internationally, without effective treatments. Increasing evidence suggest that disruption of intracellular calcium homeostasis, primarily pathological elevation of cytosol and mitochondria but reduction of endoplasmic reticulum (ER) calcium concentrations, play critical upstream roles on multiple pathologies and associated neurodegeneration, impaired neurogenesis, synapse, and cognitive dysfunction in various AD preclinical studies. The last federal drug agency (FDA) approved drug for AD dementia treatment, memantine, exert its therapeutic effects by ameliorating N-methyl-D-aspartate (NMDA) glutamate receptor overactivation and subsequent calcium dysregulation. More research works are needed to develop other drugs targeting calcium dysregulation at multiple pharmacological acting sites for future effective AD dementia treatment. Particularly, calcium channel blockers for the treatment of hypertension and dantrolene for the treatment of muscle spasm and malignant hyperthermia can be repurposed for this purpose. In our own research work, intranasal administration of dantrolene significantly increased its brain concentrations and durations, rendering it a more effective therapeutic drug with less side effects for chronic AD dementia treatment. This review summarizesthe progress of various studies repurposing drugs targeting calcium dysregulation for future effective AD dementia treatment as potentially disease-modifying drugs.

Keywords: alzheimer, calcium, cognitive dysfunction, dementia, neurodegeneration, neurogenesis

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Authors: Siamak Shahidi, Nasrin Hashemi-Firouzi, Sara Soleimani-Asl, Alireza Komaki

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Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory and cognitive performance. Recently, an involvement of the serotonergic system and their receptors are suspected in the AD progression. In the present behavioral study, the effects of BIMU (selective 5-HT4 receptor agonist) on cognition and memory in the rat model of AD was investigated. Material and Methods: The animal model of the AD was induced by intracerebroventricular (Icv) injection of amyloid beta (Aβ) in adult male Wistar rats. Animals were divided into experimental groups included control, sham, Aβ, Aβ +BIMU groups. The treatment substances were icv injected (1 μg/μL) for thirty consecutive days. Then, novel object recognition (NOR) and passive avoidance learning (PAL) tests were applied to investigate memory and cognitive performance. Results: Aβ decrease the discrimination index of NOR test. Also, it increases the time spent in the dark compartment during PAL test, as compared with sham and control groups. In addition, compared to Aβ groups, BIMU significantly increased the discrimination index of NOR test and decreased the time spent in the dark compartment of PAL test. Conclusion: These findings suggest that 5-HT4 receptor activation prevents progression of memory and cognitive impairment in a rat model of AD.

Keywords: Alzheimer disease, cognition, memory, serotonin receptors

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Authors: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

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Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

Abstract:

Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Yaiprae Chatree, Tawan Chaiwon, Rodjana Chunhabundit, Kritsana Piriyawatcharakon, Waralai Ratwiset, Sasiwimol Chaiya

Abstract:

The world is facing a serious situation of aging society. Elderly may have many physical health problems due to degenerative diseases including Alzheimer’s disease. Riceberry rice relatively contain high levels of carbohydrate, vitamin E, -oryzanol, and also abundant of bioactive compound of anthocyanin. This study aimed to determine the inhibitory effect of Riceberry rice crude extract on acetylcholinesterase activity. The active compound was extracted by using 70% ethanol (v/v). The inhibitory effect of Riceberry rice on acetylcholinesterase was evaluated by using slightly modified method of Ellman’s method. The 120 seconds time interval of kinetics measurement showed that Riceberry rice extract at concentrations of 2.5-12.5 mg/ml presented the acetylcholinesterase inhibitory activity at the statistically significant difference at p  0.05 compared to control group over 60 -120 seconds. At the concentrations of 10 and 12.5 mg/ml of Riceberry rice extract expressed the high percentage of inhibitory activity of 50.86 and 71.22%, respectively. The half maximal inhibitory concentration (IC50) of acetylcholinesterase inhibitory activity of Riceberry rice extract; considered to the end point, was found at concentration of 9.34 mg/ml. The physostigmine (positive control); however, showed a higher inhibitory capacity than that of Riceberry rice extract. The inhibitory activity of the positive control group was around at 80.40 – 90.41%. In conclusion, the results of this study indicated that Riceberry rice extract possessed the inhibitory capacity of acetylcholinesterase activity. Moreover, at the concentrations of 12.5 mg/ml it showed the identical inhibitory effect with physostigmine group. The Riceberry rice extract might be able to alleviate the clinical manifestations of Alzheimer’s disease.

Keywords: acetylcholine, acetylcholinesterase, Alzheimer's disease, riceberry rice

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Authors: Hanan Khojah, RuAngelie Edrada-Ebel

Abstract:

Neurodegenerative disease including Alzheimer’s disease is a major cause of long-term disability. Oxidative stress is frequently implicated as one of the key contributing factors to neurodegenerative diseases. Protection against neuronal damage remains a great challenge for researchers. Ficus carica (commonly known as fig) is a species of great antioxidant nutritional value comprising a protective mechanism against innumerable health disorders related to oxidative stress as well as Alzheimer’s disease. The purpose of this work was to characterize the non-polar active metabolites in Ficus carica endocarp, mesocarp, and exocarp. Crude extracts were prepared using several extraction solvents, which included 1:1 water: ethylacetate, acetone and methanol. The dried extracts were then solvent partitioned between equivalent amounts of water and ethylacetate. Purification and fractionation were accomplished by high-throughput chromatography. The isolated metabolites were tested on their effect on human neuroblastoma cell line by cell viability test and cell cytotoxicity assay with acrolein. Molecular weights of the active metabolites were determined via LC–HRESIMS and GC-EIMS. Metabolomic profiling was performed to identify the active metabolites by using differential expression analysis software (Mzmine) and SIMCA for multivariate analysis. Structural elucidation and identification of the interested active metabolites were studied by 1-D and 2-D NMR. Significant differences in bioactivity against a concentration-dependent assay on acrolein radicals were observed between the three fruit parts. However, metabolites obtained from mesocarp and the endocarp demonstrated bioactivity to scavenge ROS radical. NMR profiling demonstrated that aliphatic compounds such as γ-sitosterol tend to induce neuronal bioactivity and exhibited bioactivity on the cell viability assay. γ-Sitosterol was found in higher concentrations in the mesocarp and was considered as one of the major phytosterol in Ficus carica.

Keywords: alzheimer, Ficus carica, γ-Sitosterol, metabolomics

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Authors: Ozlem Temiz-Arpaci, Meryem Tasci, Fatma Sezer Senol, İlkay Erdogan Orhan

Abstract:

Alzheimer’s disease (AD), a neurodegenerative disorder characterized by a progressive deterioration of memory and cognition, occurs more frequently in elderly people. Current treatment approaches in this disease with the major therapeutic strategy are based on the AChE and BChE inhibition. On the other hand, tyrosinase inhibition has become a target for the treatment of Parkinson’s disease (PD) since this enzyme may play a role in neuromelanin formation in the human brain and could be critical in the formation of dopamine neurotoxicity associated with neurodegeneration linked to PD. Also benzoxazoles are structural isosteres of natural nucleotides that can interact with biopolymers so that benzoxazoles showed a lot of different biological activities. In this study, a series of 2,5-disubstituted-benzoxazole derivatives were synthesized and were evaluated as possible inhibitors of acetylcholinesterase (AChE) / butyrylcholinesterase (BChE) and tyrosinase. The results demonstrated that the compounds exhibited a weak spectrum of AChE / BChE inhibitory activity ranging between 3.92% - 54.32% except compound 8 which showed no activity against AChE and compound 4 which showed no activity against BChE at the specified molar concentrations. Also, the compounds indicated lower than tyrosinase inhibitory activity of ranging between 8.14% - 22.90% to that of reference (kojic acid).

Keywords: AChE and BChE inhibition, Alzheimer’s disease, benzoxazoles, tyrosinase inhibition

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

Abstract:

In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: J. DeBoard, R. Dietrich, J. Hughes, K. Yurko, G. Harms

Abstract:

Alzheimer’s disease (AD) is a predominant type of dementia and is likely a major cause of neural network impairment. The pathogenesis of this neurodegenerative disorder has yet to be fully elucidated. There are currently no known cures for the disease, and the best hope is to be able to detect it early enough to impede its progress. Beyond age and genetics, another prevalent risk factor for AD might be traumatic brain injury (TBI), which has similar neurodegenerative hallmarks. Our research focuses on obtaining information and methods to be able to predict when neurodegenerative effects might occur at a clinical level by observation of events at a cellular and molecular level in model mice. First, we wish to introduce our evidence that brain damage can be observed via brain imaging prior to the noticeable loss of neuromuscular control in model mice of AD. We then show our evidence that some blood biomarkers might be able to be early predictors of AD in the same model mice. Thus, we were interested to see if we might be able to predict which mice might show long-term neurodegenerative effects due to differing degrees of TBI and what level of TBI causes further damage and earlier death to the AD model mice. Upon application of TBIs via an apparatus to effectively induce extremely mild to mild TBIs, wild-type (WT) mice and AD mouse models were tested for cognition, neuromuscular control, olfactory ability, blood biomarkers, and brain imaging. Experiments are currently still in process, and more results are therefore forthcoming. Preliminary data suggest that neuromotor control diminishes as well as olfactory function for both AD and WT mice after the administration of five consecutive mild TBIs. Also, seizure activity increases significantly for both AD and WT after the administration of the five TBI treatment. If future data supports these findings, important implications about the effect of TBI on those at risk for AD might be possible.

Keywords: Alzheimer's disease, blood biomarker, neurodegeneration, neuromuscular control, olfaction, traumatic brain injury

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Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

Abstract:

The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

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Authors: Netasha Shaikh, Bryony Wood, Demitra Tsivos, Michael Knight, Risto Kauppinen, Elizabeth Coulthard

Abstract:

Background: Effective treatment of dementia will require early diagnosis, before significant brain damage has accumulated. Memory loss is an early symptom of Alzheimer’s disease (AD). The hippocampus, a brain area critical for memory, degenerates early in the course of AD. The hippocampus comprises several subfields. In contrast to healthy aging where CA3 and dentate gyrus are the hippocampal subfields with most prominent atrophy, in AD the CA1 and subiculum are thought to be affected early. Conventional clinical structural neuroimaging is not sufficiently sensitive to identify preferential atrophy in individual subfields. Here, we will explore the sensitivity of new magnetic resonance imaging (MRI) sequences designed to interrogate medial temporal regions as an early marker of Alzheimer’s. As it is likely a combination of tests may predict early Alzheimer’s disease (AD) better than any single test, we look at the potential efficacy of such imaging alone and in combination with standard and novel cognitive tasks of hippocampal dependent memory. Methods: 20 patients with mild cognitive impairment (MCI), 20 with mild-moderate AD and 20 age-matched healthy elderly controls (HC) are being recruited to undergo 3T MRI (with sequences designed to allow volumetric analysis of hippocampal subfields) and a battery of cognitive tasks (including Paired Associative Learning from CANTAB, Hopkins Verbal Learning Test and a novel hippocampal-dependent abstract word memory task). AD participants and healthy controls are being tested just once whereas patients with MCI will be tested twice a year apart. We will compare subfield size between groups and correlate subfield size with cognitive performance on our tasks. In the MCI group, we will explore the relationship between subfield volume, cognitive test performance and deterioration in clinical condition over a year. Results: Preliminary data (currently on 16 participants: 2 AD; 4 MCI; 9 HC) have revealed subfield size differences between subject groups. Patients with AD perform with less accuracy on tasks of hippocampal-dependent memory, and MCI patient performance and reaction times also differ from healthy controls. With further testing, we hope to delineate how subfield-specific atrophy corresponds with changes in cognitive function, and characterise how this progresses over the time course of the disease. Conclusion: Novel sequences on a MRI scanner such as those in route in clinical use can be used to delineate hippocampal subfields in patients with and without dementia. Preliminary data suggest that such subfield analysis, perhaps in combination with cognitive tasks, may be an early marker of AD.

Keywords: Alzheimer's disease, dementia, memory, cognition, hippocampus

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