Peri-Infarct Upregulation of the Oxytocin Receptor in Vascular Dementia

Identification of toll-like receptor 2 as a key regulator of neuronal apoptosis in vascular dementia by bioinformatics analysis and experimental validation

BACKGROUND

Vascular dementia (VaD), the second most prevalent type of dementia, lacks a well-defined cause and effective treatment. Our objective was to utilize bioinformatics analysis to discover the fundamental disease-causing genes and pathological mechanisms in individuals diagnosed with VaD.

METHODS

To identify potential pathogenic genes associated with VaD, we conducted weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction (PPI) analysis. The exploration of potential biological mechanisms involved the utilization of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Moreover, a bilateral common carotid artery stenosis (BCAS) mouse model of VaD was established, and the expression of the hub gene, its relationship with cognitive function and its potential pathogenic mechanism were verified by cognitive behavior tests, cerebral blood flow measurement, Western blotting, and immunofluorescence experiments.

RESULTS

This study identified 293 DEGs from the brain cortex of VaD patients and healthy controls, among these genes, the Toll-like receptor 2 (TLR2) gene was identified as hub gene, and it was associated with the apoptosis-related pathway PI3K/AKT.The BCAS model demonstrated that the use of TLR2 inhibitors greatly enhanced the cognitive function of the mice (p < 0.05). Additionally, there was a notable decrease in the number of apoptotic cells in the brain cortex of the mice (p < 0.01). Moreover, significant alterations in the levels of proteins related to the PI3K/AKT pathway and cleaved-caspase3 proteins were detected (p < 0.05).

CONCLUSIONS

TLR2 plays a role in the pathophysiology of VaD by enhancing the neuronal apoptotic pathway, suggesting it could be a promising therapeutic target.

Potential role of oxytocin in the regulation of memories and treatment of memory disorders

Oxytocin (OXT) is an "affiliative" hormone or neurohormone or neuropeptide consists of nine amino acids, synthesized in magnocellular neurons of paraventricular (PVN) and supraoptic nuclei (SON) of hypothalamus. OXT receptors are widely distributed in various region of brain and OXT has been shown to regulate various social and nonsocial behavior. Hippocampus is the main region which regulates the learning and memory. Hippocampus particularly regulates the acquisition of new memories and retention of acquired memories. OXT has been shown to regulate the synaptic plasticity, neurogenesis, and consolidation of memories. Further, findings from both preclinical and clinical studies have suggested that the OXT treatment improves performance in memory related task. Various trials have suggested the positive impact of intranasal OXT in the dementia patients. However, these studies are limited in number. In the present study authors have highlighted the role of OXT in the formation and retrieval of memories. Further, the study demonstrated the outcome of OXT treatment in various memory and related disorders.

Network pharmacology and experimental verification to explore the effect of Hedyotis diffusa on Alzheimer's disease

This study aimed to explore the active components and the effect of Hedyotis diffusa (HD) against Alzheimer's disease (AD) via network pharmacology, molecular docking, and experimental evaluations. We conducted a comprehensive screening process using the TCMSP, Swiss Target Prediction, and PharmMapper databases to identify the active components and their related targets in HD. In addition, we collected potential therapeutic targets of AD from the Gene Cards, Drugbank, and OMIM databases. Afterward, we utilized Cytoscape to establish both protein-protein interaction (PPI) networks and compound-target (C-T) networks. To gain further insights into the functional aspect, we performed GO and KEGG pathway analyses using the David database. Next, we employed Autodock vina to estimate the binding force between the components and the hub genes. To validate our network pharmacology findings, we conducted relevant experiments on Caenorhabditis elegans, further confirming the reliability of our results. Then a total of six active compounds and 149 therapeutic targets were detected. Through the analysis of the association between active compounds, therapeutic targets, and signaling pathways, it was observed that the therapeutic effect of HD primarily encompassed the inhibition of Aβ, suppression of AChE activity, and mitigating oxidative stress. Additionally, our investigation revealed that the key active compounds in HD primarily consisted of iridoids, which exhibited resistance against AD by acting on the Alzheimer's disease pathway and the AGE-RAGE signaling pathway in diabetic complications.

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

A disease similarity approach identifies short-lived Niemann-Pick type C disease mice with accelerated brain aging as a novel mouse model for Alzheimer's disease and aging research

Since its first description in 1906 by Dr. Alois Alzheimer, Alzheimer's disease (AD) has been the most common type of dementia. Initially thought to be caused by age-associated accumulation of plaques, in recent years, research has increasingly associated AD with lysosomal storage and metabolic disorders, and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions. However, the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined. Here, we applied a disease similarity approach to identify unknown molecular targets of AD by using transcriptomic data from congenital diseases known to increase AD risk, namely Down Syndrome, Niemann Pick Disease Type C (NPC), and Mucopolysaccharidoses I. We uncovered common pathways, hub genes, and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of AD pathology, many of which have never been associated with AD. We then investigated common molecular alterations in brain samples from an NPC disease mouse model by juxtaposing them with brain samples of both human and mouse models of AD. Detailed phenotypic and molecular analyses revealed that the NPC mut mouse model can serve as a potential short-lived in vivo model for AD research and for understanding molecular factors affecting brain aging. This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on AD research while highlighting shortcomings and lack of correlation in diverse in vitro models. Considering the lack of an AD mouse model that recapitulates the physiological hallmarks of brain aging, the characterization of a short-lived NPC mouse model will further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of AD from a perspective of accelerated brain aging.

Beneficial Effects of Echinacoside on Cognitive Impairment and Diabetes in Type 2 Diabetic db/db Mice

INTRODUCTION

Cognitive dysfunction is an important comorbidity of diabetes. Insulin resistance may play a critical role in diabetes-related cognitive impairment. Echinacoside (ECH), a natural phenylethanoid glycoside, is the active component of anti-diabetes prescriptions in traditional Chinese medicine. Its effect on modulating insulin resistance has been confirmed but modulating neurodegenerative disease remains unclear.

METHODS

Db/db mice, a spontaneous type 2 diabetes mode, were intragastrically administered ECH by 300 mg/kg or an equivalent volume of saline. Weight, blood glucose, and insulin resistance index were measured. Morris water maze test was performed to observe the compound effects on cognition. Hippocampal lesions were observed by histochemical analysis.

RESULTS

In db/db mice, ECH alleviated diabetes symptoms, memory loss, and hippocampal neuronal damage. Next, the expression of CD44 and phosphorylated tau was upregulated in diabetic mice. In addition, the insulin receptor substrate-1/phosphatidylinositol 3-kinase /protein kinase B signaling pathway was dysregulated in diabetic mice. All these dysregulations could be reversed by ECH.

DISCUSSION

This study provides theoretical support and experimental evidence for the future application of ECH in diabetic cognition dysfunction treatment, promoting the development of traditional medicines.

Inhibition of ADORA3 promotes microglial phagocytosis and alleviates chronic ischemic white matter injury

BACKGROUND

Adenosine A3 receptor (ADORA3) belongs to the adenosine receptor families and the role of ADORA3 in vascular dementia (VaD) is largely unexplored. The present study sought to determine the therapeutic role of ADORA3 antagonist in a mouse model of VaD.

METHODS

The GSE122063 dataset was selected to screen the differential expression genes and pathways between VaD patients and controls. A mouse model of bilateral carotid artery stenosis (BCAS) was established. The cognitive functions were examined by the novel object recognition test, Y maze test, and fear of conditioning test. The white matter injury (WMI) was examined by 9.4 T MRI, western blot, and immunofluorescence staining. The mechanisms of ADORA3-regulated phagocytosis by microglia were examined using qPCR, western blot, dual immunofluorescence staining, and flow cytometry.

RESULTS

The expression of ADORA3 was elevated in brain tissues of VaD patients and ADORA3 was indicated as a key gene for VaD in the GSE122063. In BCAS mice, the expression of ADORA3 was predominantly elevated in microglia in the corpus callosum. ADORA3 antagonist promotes microglial phagocytosis to myelin debris by facilitating cAMP/PKA/p-CREB pathway and thereby ameliorates WMI and cognitive impairment in BCAS mice. The therapeutic effect of ADORA3 antagonist was partially reversed by the inhibition of the cAMP/PKA pathway.

CONCLUSIONS

ADORA3 antagonist alleviates chronic ischemic WMI by modulating myelin clearance of microglia, which may be a potential therapeutic target for the treatment of VaD.

In need of a specific antibody against the oxytocin receptor for neuropsychiatric research: A KO validation study

Antibodies are one of the most utilized tools in biomedical research. However, few of them are rigorously evaluated, as there are no accepted guidelines or standardized methods for determining their validity before commercialization. Often, an antibody is considered validated if it detects a band by Western blot of the expected molecular weight and, in some cases, if blocking peptides result in loss of staining. Neither of these approaches are unquestionable proof of target specificity. Since the oxytocin receptor has recently become a popular target in neuropsychiatric research, the need for specific antibodies to be used in brain has arisen. In this work, we have tested the specificity of six commercially available oxytocin receptor antibodies, indicated by the manufacturers to be suitable for Western blot and with an available image showing the correct size band (45-55 KDa). Antibodies were first tested by Western blot in brain lysates of wild-type and oxytocin receptor knockout mice. Uterus tissue was also tested as control for putative differential tissue specificity. In brain, the six tested antibodies lacked target specificity, as both wild-type and receptor knockout samples resulted in a similar staining pattern, including the expected 45-55 KDa band. Five of the six antibodies detected a selective band in uterus (which disappeared in knockout tissue). These five specific antibodies were also tested for immunohistochemistry in uterus, where only one was specific. However, when the uterine-specific antibody was tested in brain tissue, it lacked specificity. In conclusion, none of the six tested commercial antibodies are suitable to detect oxytocin receptor in brain by either Western blot or immunohistochemistry, although some do specifically detect it in uterus. The present work highlights the need to develop standardized antibody validation methods, including a proper negative control, in order to grant quality and reproducibility of the generated data.

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Identification of immune-associated genes in vascular dementia by integrated bioinformatics and inflammatory infiltrates

Objective

Dysregulation of the immune system plays a vital role in the pathological process of vascular dementia, and this study aims to spot critical biomarkers and immune infiltrations in vascular dementia employing a bioinformatics approach.

Methods

We acquired gene expression profiles from the Gene Expression Database. The gene expression data were analyzed using the bioinformatics method to identify candidate immune-related central genes for the diagnosis of vascular dementia. and the diagnostic value of nomograms and Receiver Operating Characteristic (ROC) curves were evaluated. We also examined the role of the VaD hub genes. Using the database and potential therapeutic drugs, we predicted the miRNA and lncRNA controlling the Hub genes. Immune cell infiltration was initiated to examine immune cell dysregulation in vascular dementia.

Results

1321 immune genes were included in the combined immune dataset, and 2816 DEGs were examined in GSE122063. Twenty potential genes were found using differential gene analysis and co-expression network analysis. PPI network design and functional enrichment analysis were also done using the immune system as the main subject. To create the nomogram for evaluating the diagnostic value, four potential core genes were chosen by machine learning. All four putative center genes and nomograms have a solid diagnostic value (AUC ranged from 0.81 to 0.92). Their high confidence level became unquestionable by validating each of the four biomarkers using a different dataset. According to GeneMANIA and GSEA enrichment investigations, the pathophysiology of VaD is strongly related to inflammatory responses, drug reactions, and central nervous system degeneration. The data and Hub genes were used to construct a ceRNA network that includes three miRNAs, 90 lncRNA, and potential VaD therapeutics. Immune cells with varying dysregulation were also found.

Conclusion

Using bioinformatic techniques, our research identified four immune-related candidate core genes (HMOX1, EBI3, CYBB, and CCR5). Our study confirms the role of these Hub genes in the onset and progression of VaD at the level of immune infiltration. It predicts potential RNA regulatory pathways control VaD progression, which may provide ideas for treating clinical disease.

Shared Proteins and Pathways of Cardiovascular and Cognitive Diseases: Relation to Vascular Cognitive Impairment

One of the primary goals of systems medicine is the detection of putative proteins and pathways involved in disease progression and pathological phenotypes. Vascular cognitive impairment (VCI) is a heterogeneous condition manifesting as cognitive impairment resulting from vascular factors. The precise mechanisms underlying this relationship remain unclear, which poses challenges for experimental research. Here, we applied computational approaches like systems biology to unveil and select relevant proteins and pathways related to VCI by studying the crosstalk between cardiovascular and cognitive diseases. In addition, we specifically included signals related to oxidative stress, a common etiologic factor tightly linked to aging, a major determinant of VCI. Our results show that pathways associated with oxidative stress are quite relevant, as most of the prioritized vascular cognitive genes and proteins were enriched in these pathways. Our analysis provided a short list of proteins that could be contributing to VCI: DOLK, TSC1, ATP1A1, MAPK14, YWHAZ, CREB3, HSPB1, PRDX6, and LMNA. Moreover, our experimental results suggest a high implication of glycative stress, generating oxidative processes and post-translational protein modifications through advanced glycation end-products (AGEs). We propose that these products interact with their specific receptors (RAGE) and Notch signaling to contribute to the etiology of VCI.

Oxytocin activity in the paraventricular and supramammillary nuclei of the hypothalamus is essential for social recognition memory in rats

Oxytocin plays an important role in modulating social recognition memory. However, the direct implication of oxytocin neurons of the paraventricular nucleus of the hypothalamus (PVH) and their downstream hypothalamic targets in regulating short- and long-term forms of social recognition memory has not been fully investigated. In this study, we employed a chemogenetic approach to target the activity of PVH oxytocin neurons in male rats and found that specific silencing of this neuronal population led to an impairment in short- and long-term social recognition memory. We combined viral-mediated fluorescent labeling of oxytocin neurons with immunohistochemical techniques and identified the supramammillary nucleus (SuM) of the hypothalamus as a target of PVH oxytocinergic axonal projections in rats. We used multiplex fluorescence in situ hybridization to label oxytocin receptors in the SuM and determined that they are predominantly expressed in glutamatergic neurons, including those that project to the CA2 region of the hippocampus. Finally, we used a highly selective oxytocin receptor antagonist in the SuM to examine the involvement of oxytocin signaling in modulating short- and long-term social recognition memory and found that it is necessary for the formation of both. This study discovered a previously undescribed role for the SuM in regulating social recognition memory via oxytocin signaling and reinforced the specific role of PVH oxytocin neurons in regulating this form of memory.

Identification of mitochondrial related signature associated with immune microenvironment in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the most common neurodegenerative disease. Mitochondrial dysfunction and immune responses are important factors in the pathogenesis of AD, but their crosstalk in AD has not been studied. In this study, the independent role and interaction of mitochondria-related genes and immune cell infiltration in AD were investigated using bioinformatics methods.

METHODS

The datasets of AD were obtained from NCBI Gene Expression Omnibus (GEO), and the data of mitochondrial genes was from MitoCarta3.0 database. Subsequently, differential expression genes (DEGs) screening and GSEA functional enrichment analysis were performed. The intersection of DEGs and mitochondrial related genes was used to obtain MitoDEGs. The MitoDEGs most relevant to AD were determined by Least absolute shrinkage and selection operator and multiple support vector machine recursive feature elimination, as well as protein-protein interactions (PPI) network and random forest. The infiltration of 28 kinds of immune cells in AD was analyzed by ssGSEA, and the relationship between hub MitoDEGs and the proportion of immune infiltration was studied. The expression levels of hub MitoDEGs were verified in cell models and AD mice, and the role of OPA1 in mitochondrial damage and neuronal apoptosis was investigated.

RESULTS

The functions and pathways of DEGs were significantly enriched in AD, including immune response activation, IL1R pathway, mitochondrial metabolism, oxidative damage response and electron transport chain-oxphos system in mitochondria. Hub MitoDEGs closely related to AD were obtained based on PPI network, random forest and two machine learning algorithms. Five hub MitoDEGs associated with neurological disorders were identified by biological function examination. The hub MitoDEGs were found to be correlated with memory B cell, effector memory CD8 T cell, activated dendritic cell, natural killer T cell, type 17 T helper cell, Neutrophil, MDSC, plasmacytoid dendritic cell. These genes can also be used to predict the risk of AD and have good diagnostic efficacy. In addition, the mRNA expression levels of BDH1, TRAP1, OPA1, DLD in cell models and AD mice were consistent with the results of bioinformatics analysis, and expression levels of SPG7 showed a downward trend. Meanwhile, OPA1 overexpression alleviated mitochondrial damage and neuronal apoptosis induced by Aβ1-42.

CONCLUSIONS

Five potential hub MitoDEGs most associated with AD were identified. Their interaction with immune microenvironment may play a crucial role in the occurrence and prognosis of AD, which provides a new insight for studying the potential pathogenesis of AD and exploring new targets.

Development and validation of a 13-gene signature associated with immune function for the detection of Alzheimer's disease

Current knowledge of Alzheimer's disease (AD) etiology and effective therapy remains limited. Thus, the identification of biomarkers is crucial to improve the detection and treatment of patients with AD. Using robust rank aggregation method to analyze the microarray data from Gene Expression Omnibus database, we identified 1138 differentially expressed genes in AD. We then explored 13 hub genes by weighted gene co-expression network analysis, least absolute shrinkage, and selection operator, and logistic regression in the training dataset. The detection model, which composed of CD163, CDC42SE1, CECR6, CSF1R, CYP27A1, EIF4E3, H2AFJ, IFIT2, IL10RA, KIAA1324, PSTPIP1, SLA, and TBC1D2 genes, along with APOE gene, showed that the area under the curve for detecting AD was 0.821 (95% confidence interval [CI] = 0.782-0.861) and the model was validated in ADNI dataset (area under the curve = 0.776; 95%CI = 0.686-0.865). Notably, the 13 genes in the model were highly enriched in immune function. These findings have implications for the detection and therapeutic target of AD.

Human early-onset dementia caused by DAP12 deficiency reveals a unique signature of dysregulated microglia

The TREM2-DAP12 receptor complex sustains microglia functions. Heterozygous hypofunctional TREM2 variants impair microglia, accelerating late-onset Alzheimer's disease. Homozygous inactivating variants of TREM2 or TYROBP-encoding DAP12 cause Nasu-Hakola disease (NHD), an early-onset dementia characterized by cerebral atrophy, myelin loss and gliosis. Mechanisms underpinning NHD are unknown. Here, single-nucleus RNA-sequencing analysis of brain specimens from DAP12-deficient NHD individuals revealed a unique microglia signature indicating heightened RUNX1, STAT3 and transforming growth factor-β signaling pathways that mediate repair responses to injuries. This profile correlated with a wound healing signature in astrocytes and impaired myelination in oligodendrocytes, while pericyte profiles indicated vascular abnormalities. Conversely, single-nuclei signatures in mice lacking DAP12 signaling reflected very mild microglial defects that did not recapitulate NHD. We envision that DAP12 signaling in microglia attenuates wound healing pathways that, if left unchecked, interfere with microglial physiological functions, causing pathology in human. The identification of a dysregulated NHD microglia signature sparks potential therapeutic strategies aimed at resetting microglia signaling pathways.

Identification of TAC1 Associated with Alzheimer's Disease Using a Robust Rank Aggregation Approach

BACKGROUND

Alzheimer's disease (AD) brings heavy burden to society and family. There is an urgent need to find effective methods for disease diagnosis and treatment. The robust rank aggregation (RRA) approach that could aggregate the resulting gene lists has been widely utilized in genomic data analysis.

OBJECTIVE

To identify hub genes using RRA approach in AD.

METHODS

Seven microarray datasets in frontal cortex from GEO database were used to identify differential expressed genes (DEGs) in AD patients using RRA approach. STRING was performed to explore the protein-to-protein interaction (PPI). Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were utilized for enrichment analysis. Human Gene Connectome and Gene Set Enrichment Analysis were used for functional annotation. Finally, the expression levels of hub genes were validated in the cortex of 5xFAD mice by quantitative real-time polymerase chain reaction.

RESULTS

After RRA analysis, 473 DEGs (216 upregulated and 257 downregulated) were identified in AD samples. PPI showed that DEGs had a total of 416 nodes and 2750 edges. These genes were divided into 17 clusters, each of which contains at least three genes. After functional annotation and enrichment analysis, TAC1 is identified as the hub gene and may be related to synaptic function and inflammation. In addition, Tac1 was found downregulated in cortices of 5xFAD mice.

CONCLUSION

In the current study, TAC1 is identified as a key gene in the frontal cortex of AD, providing insight into the possible pathogenesis and potential therapeutic targets for this disease.

Roles of the Oxytocin Receptor (OXTR) in Human Diseases

The oxytocin receptor (OXTR), encoded by the OXTR gene, is responsible for the signal transduction after binding its ligand, oxytocin. Although this signaling is primarily involved in controlling maternal behavior, it was demonstrated that OXTR also plays a role in the development of the nervous system. Therefore, it is not a surprise that both the ligand and the receptor are involved in the modulation of behaviors, especially those related to sexual, social, and stress-induced activities. As in the case of every regulatory system, any disturbances in the structures or functions of oxytocin and OXTR may lead to the development or modulation of various diseases related to the regulated functions, which in this case include either mental problems (autism, depression, schizophrenia, obsessive-compulsive disorders) or those related to the functioning of reproductive organs (endometriosis, uterine adenomyosis, premature birth). Nevertheless, OXTR abnormalities are also connected to other diseases, including cancer, cardiac disorders, osteoporosis, and obesity. Recent reports indicated that the changes in the levels of OXTR and the formation of its aggregates may influence the course of some inherited metabolic diseases, such as mucopolysaccharidoses. In this review, the involvement of OXTR dysfunctions and OXTR polymorphisms in the development of different diseases is summarized and discussed. The analysis of published results led us to suggest that changes in OXTR expression and OXTR abundance and activity are not specific to individual diseases, but rather they influence processes (mostly related to behavioral changes) that might modulate the course of various disorders. Moreover, a possible explanation of the discrepancies in the published results of effects of the OXTR gene polymorphisms and methylation on different diseases is proposed.

[Emergent role of astrocytes in oxytocin-mediated modulatory control of neuronal circuits and brain functions]

The neuropeptide oxytocin has been in the focus of scientists for decades due to its profound and pleiotropic effects on physiology, activity of neuronal circuits and behaviors. Until recently, it was believed that oxytocinergic action exclusively occurs through direct activation of neuronal oxytocin receptors. However, several studies demonstrated the existence and functional relevance of astroglial oxytocin receptors in various brain regions in the mouse and rat brain. Astrocytic signaling and activity are critical for many important physiological processes including metabolism, neurotransmitter clearance from the synaptic cleft and integrated brain functions. While it can be speculated that oxytocinergic action on astrocytes predominantly facilitates neuromodulation via the release of gliotransmitters, the precise role of astrocytic oxytocin receptors remains elusive. In this review, we discuss the latest studies on the interaction between the oxytocinergic system and astrocytes, and give details of underlying intracellular cascades.

Acupuncture Therapy on Dementia: Explained with an Integrated Analysis on Therapeutic Targets and Associated Mechanisms

BACKGROUND

Dementia, mainly Alzheimer's disease (AD) and vascular dementia (VaD), remains a global health challenge. Previous studies have demonstrated the benefits of acupuncture therapy (AT) in improving dementia. Nevertheless, the therapeutic targets and integrated biological mechanisms involved remain ambiguous.

OBJECTIVE

To identify therapeutic targets and biological mechanisms of AT in treating dementia by integrated analysis strategy.

METHODS

By the identification of differentially expressed genes (DEGs) of AD, VaD, and molecular targets of AT active components, the acupuncture therapeutic targets associated with the biological response to AD and VaD were extracted. Therapeutic targets-based functional enrichment analysis was conducted, and multiple networks were constructed. AT-therapeutic crucial targets were captured by weighted gene co-expression network analysis (WGCNA). The interactions between crucial targets with AT active components were verified by molecular docking.

RESULTS

Our results demonstrated that 132 and 76 acupuncture therapeutic targets were associated with AD and VaD. AT-therapeutic crucial targets including 58 for AD and 24 for VaD were captured by WGCNA, with 11 in shared, including NMU, GRP, TAC1, ADRA1D, and SST. In addition, 35 and 14 signaling pathways were significantly enriched by functional enrichment analysis, with 6 mutual pathways including neuroactive ligand-receptor interaction, GABAergic synapse, calcium signaling pathway, cAMP signaling pathway, chemokine signaling pathway, and inflammatory mediator regulation of TRP channels.

CONCLUSION

The improvement of AD and VaD by AT was associated with modulation of synaptic function, immunity, inflammation, and apoptosis. Our study clarified the therapeutic targets of AT on dementia, providing valuable clues for complementing and combining pharmacotherapy.

Exploration of novel biomarkers in Alzheimer's disease based on four diagnostic models

Background

Despite tremendous progress in diagnosis and prediction of Alzheimer's disease (AD), the absence of treatments implies the need for further research. In this study, we screened AD biomarkers by comparing expression profiles of AD and control tissue samples and used various models to identify potential biomarkers. We further explored immune cells associated with these biomarkers that are involved in the brain microenvironment.

Methods

By differential expression analysis, we identified differentially expressed genes (DEGs) of four datasets (GSE125583, GSE118553, GSE5281, GSE122063), and common expression direction of genes of four datasets were considered as intersecting DEGs, which were used to perform enrichment analysis. We then screened the intersecting pathways between the pathways identified by enrichment analysis. DEGs in intersecting pathways that had an area under the curve (AUC) > 0.7 constructed random forest, least absolute shrinkage and selection operator (LASSO), logistic regression, and gradient boosting machine models. Subsequently, using receiver operating characteristic curve (ROC) and decision curve analysis (DCA) to select an optimal diagnostic model, we obtained the feature genes. Feature genes that were regulated by differentially expressed miRNAs (AUC > 0.85) were explored further. Furthermore, using single-sample GSEA to calculate infiltration of immune cells in AD patients.

Results

Screened 1855 intersecting DEGs that were involved in RAS and AMPK signaling. The LASSO model performed best among the four models. Thus, it was used as the optimal diagnostic model for ROC and DCA analyses. This obtained eight feature genes, including ATP2B3, BDNF, DVL2, ITGA10, SLC6A12, SMAD4, SST, and TPI1. SLC6A12 is regulated by miR-3176. Finally, the results of ssGSEA indicated dendritic cells and plasmacytoid dendritic cells were highly infiltrated in AD patients.

Conclusion

The LASSO model is the optimal diagnostic model for identifying feature genes as potential AD biomarkers, which can supply new strategies for the treatment of patients with AD.

Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer's disease

Background

We developed a novel system for quantifying DNA damage response (DDR) to help diagnose and predict the risk of Alzheimer's disease (AD).

Methods

We thoroughly estimated the DDR patterns in AD patients Using 179 DDR regulators. Single-cell techniques were conducted to validate the DDR levels and intercellular communications in cognitively impaired patients. The consensus clustering algorithm was utilized to group 167 AD patients into diverse subgroups after a WGCNA approach was employed to discover DDR-related lncRNAs. The distinctions between the categories in terms of clinical characteristics, DDR levels, biological behaviors, and immunological characteristics were evaluated. For the purpose of choosing distinctive lncRNAs associated with DDR, four machine learning algorithms, including LASSO, SVM-RFE, RF, and XGBoost, were utilized. A risk model was established based on the characteristic lncRNAs.

Results

The progression of AD was highly correlated with DDR levels. Single-cell studies confirmed that DDR activity was lower in cognitively impaired patients and was mainly enriched in T cells and B cells. DDR-related lncRNAs were discovered based on gene expression, and two different heterogeneous subtypes (C1 and C2) were identified. DDR C1 belonged to the non-immune phenotype, while DDR C2 was regarded as the immune phenotype. Based on various machine learning techniques, four distinctive lncRNAs associated with DDR, including FBXO30-DT, TBX2-AS1, ADAMTS9-AS2, and MEG3 were discovered. The 4-lncRNA based riskScore demonstrated acceptable efficacy in the diagnosis of AD and offered significant clinical advantages to AD patients. The riskScore ultimately divided AD patients into low- and high-risk categories. In comparison to the low-risk group, high-risk patients showed lower DDR activity, accompanied by higher levels of immune infiltration and immunological score. The prospective medications for the treatment of AD patients with low and high risk also included arachidonyltrifluoromethane and TTNPB, respectively.

Conclusions

In conclusion, immunological microenvironment and disease progression in AD patients were significantly predicted by DDR-associated genes and lncRNAs. A theoretical underpinning for the individualized treatment of AD patients was provided by the suggested genetic subtypes and risk model based on DDR.

Integration of network pharmacology and molecular docking to explore the molecular mechanism of Cordycepin in the treatment of Alzheimer's disease

Background

Cordycepin is a nucleoside adenosine analog and an active ingredient isolated from the liquid fermentation of Cordyceps. This study sought to explore the mechanism underlying the therapeutic effect of Cordycepin against Alzheimer's disease using network pharmacology and molecular docking technology.

Methods

TCMSP, SYMMAP, CTD, Super-pred, SEA, GeneCards, DisGeNET database, and STRING platform were used to screen and construct the target and protein interaction network of Cordycepin for Alzheimer's disease. The results of Gene Ontology annotation and KEGG pathway enrichment analysis were obtained based on the DAVID database. The Omicshare database was also applied in GO and KEGG pathway enrichment analysis of the key targets. The protein-protein interaction network was constructed using the STRING database, and the potential effective targets for AD were screened based on the degree values. The correlation between the potential targets of Cordycepin in the treatment of AD and APP, MAPT, and PSEN2 was analyzed using (GEPIA) databases. We obtained potential targets related to aging using the Aging Altas database. Molecular docking analysis was performed by AutoDock Vina and Pymol software. Finally, we validated the significant therapeutic targets in the Gene Expression Omnibus (GEO) database.

Results

A total of 74 potential targets of Cordycepin for treating Alzheimer's disease were identified. The potential targets of Cordycepin for the treatment of AD mainly focused on Lipid and atherosclerosis (hsa05417), Platinum drug resistance (hsa01524), Apoptosis (hsa04210), and Pathways in cancer (hsa05200). Our findings suggest that the therapeutic effect of Cordycepin on AD is primarily associated with these biological processes. We obtained 12 potential therapeutic targets for AD using the degree value in Cytoscape. Interestingly, AKT1, MAPK8, BCL2L1, FOXO3, and CTNNB1 were not only significantly associated with pathogenic genes (APP, MAPT, and PSEN2) but also with longevity in Alzheimer's Disease. Thus we speculated that the five target genes were potential core targets mediating the therapeutic effect of Cordycepin against AD. Moreover, molecular docking results analysis showed good binding affinity between Cordycepin and the five core targets. Overall, MAPK8, FOXO3 and CTNNB1 may have significant clinical and treatment implications.

Conclusion

Network pharmacology demonstrated that Cordycepin exerts a therapeutic effect against Alzheimer's disease via multiple targets and signaling pathways and has huge prospects for application in treating neurodegenerative diseases.

Identification of immune microenvironment subtypes and signature genes for Alzheimer's disease diagnosis and risk prediction based on explainable machine learning

Background

Using interpretable machine learning, we sought to define the immune microenvironment subtypes and distinctive genes in AD.

Methods

ssGSEA, LASSO regression, and WGCNA algorithms were used to evaluate immune state in AD patients. To predict the fate of AD and identify distinctive genes, six machine learning algorithms were developed. The output of machine learning models was interpreted using the SHAP and LIME algorithms. For external validation, four separate GEO databases were used. We estimated the subgroups of the immunological microenvironment using unsupervised clustering. Further research was done on the variations in immunological microenvironment, enhanced functions and pathways, and therapeutic medicines between these subtypes. Finally, the expression of characteristic genes was verified using the AlzData and pan-cancer databases and RT-PCR analysis.

Results

It was determined that AD is connected to changes in the immunological microenvironment. WGCNA revealed 31 potential immune genes, of which the greenyellow and blue modules were shown to be most associated with infiltrated immune cells. In the testing set, the XGBoost algorithm had the best performance with an AUC of 0.86 and a P-R value of 0.83. Following the screening of the testing set by machine learning algorithms and the verification of independent datasets, five genes (CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12) that were closely associated with AD pathological biomarkers and allowed for the accurate prediction of AD progression were found to be immune microenvironment-related genes. The feature gene-based nomogram may provide clinical advantages to patients. Two immune microenvironment subgroups for AD patients were identified, subtype2 was linked to a metabolic phenotype, subtype1 belonged to the immune-active kind. MK-866 and arachidonyltrifluoromethane were identified as the top treatment agents for subtypes 1 and 2, respectively. These five distinguishing genes were found to be intimately linked to the development of the disease, according to the Alzdata database, pan-cancer research, and RT-PCR analysis.

Conclusion

The hub genes associated with the immune microenvironment that are most strongly associated with the progression of pathology in AD are CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12. The hypothesized molecular subgroups might offer novel perceptions for individualized AD treatment.

Bioinformatics-based study reveals that AP2M1 is regulated by the circRNA-miRNA-mRNA interaction network and affects Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurological disease that worsens with time. The hallmark illnesses include extracellular senile plaques caused by β-amyloid protein deposition, neurofibrillary tangles caused by tau protein hyperphosphorylation, and neuronal loss accompanying glial cell hyperplasia. Noncoding RNAs are substantially implicated in related pathophysiology, according to mounting data. However, the function of these ncRNAs is mainly unclear. Circular RNAs (circRNAs) include many miRNA-binding sites (miRNA response elements, MREs), which operate as miRNA sponges or competing endogenous RNAs (ceRNAs). The purpose of this study was to look at the role of circular RNAs (circRNAs) and microRNAs (miRNAs) in Alzheimer's disease (AD) as possible biomarkers. The Gene Expression Omnibus (GEO) database was used to obtain an expression profile of Alzheimer's disease patients (GSE5281, GSE122603, GSE97760, GSE150693, GSE1297, and GSE161435). Through preliminary data deletion, 163 genes with significant differences, 156 miRNAs with significant differences, and 153 circRNAs with significant differences were identified. Then, 10 key genes, led by MAPT and AP2M1, were identified by the mediation center algorithm, 34 miRNAs with obvious prognosis were identified by the cox regression model, and 16 key circRNAs were selected by the database. To develop competitive endogenous RNA (ceRNA) networks, hub circRNAs and mRNAs were used. Finally, GO analysis and clinical data verification of key genes were carried out. We discovered that a down-regulated circRNA (has_circ_002048) caused the increased expression of numerous miRNAs, which further inhibited the expression of a critical mRNA (AP2M1), leading to Alzheimer's disease pathology. The findings of this work contribute to a better understanding of the circRNA-miRNA-mRNA regulating processes in Alzheimer's disease. Furthermore, the ncRNAs found here might become novel biomarkers and potential targets for the development of Alzheimer's drugs.

Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer's disease

BACKGROUND

Protein glycosylation has been confirmed to be involved in the pathological mechanisms of Alzheimer's disease (AD); however, there is still a lack of systematic analysis of the immune processes mediated by protein glycosylation-related genes (PGRGs) in AD.

MATERIALS AND METHODS

Transcriptomic data of AD patients were obtained from the Gene Expression Omnibus database and divided into training and verification datasets. The core PGRGs of the training set were identified by weighted gene co-expression network analysis, and protein glycosylation-related subtypes in AD were identified based on k-means unsupervised clustering. Protein glycosylation scores and neuroinflammatory levels of different subtypes were compared, and functional enrichment analysis and drug prediction were performed based on the differentially expressed genes (DEGs) between the subtypes. A random forest model was used to select important DEGs as diagnostic markers between subtypes, and a line chart model was constructed and verified in other datasets. We evaluated the differences in immune cell infiltration between the subtypes through the single-sample gene set enrichment analysis, analyzed the correlation between core diagnostic markers and immune cells, and explored the expression regulation network of the core diagnostic markers.

RESULTS

Eight core PGRGs were differentially expressed between the training set and control samples. AD was divided into two subtypes with significantly different biological processes, such as vesicle-mediated transport in synapses and neuroactive ligand-receptor interactions. The high protein glycosylation subtype had a higher level of neuroinflammation. Riluzole and sulfasalazine were found to have potential clinical value in this subtype. A reliable construction line chart model was constructed based on nine diagnostic markers, and SERPINA3 was identified as the core diagnostic marker. There were significant differences in immune cell infiltration between the two subtypes. SERPINA3 was found to be closely related to immune cells, and the expression of SERPINA3 in AD was found to be regulated by a competing endogenous RNA network that involves eight long non-coding RNAs and seven microRNAs.

CONCLUSION

Protein glycosylation and its corresponding immune process play an important role in the occurrence and development of AD. Understanding the role of PGRGs in AD may provide a new potential therapeutic target for AD.

HSPA1A, HSPA2, and HSPA8 Are Potential Molecular Biomarkers for Prognosis among HSP70 Family in Alzheimer’s Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disease, which leads to impairment of cognition and memory. The heat shock protein 70 (HSP70) family plays an important role in the pathogenesis of AD. It is known to regulate protein misfolding in a variety of diseases, including inhibition of Aβ aggregation and NFT formation in AD. As yet, the diagnostic molecular markers of AD remain unclear. Herein, we sought to investigate molecular markers of HSP70 family that can affect diagnosis and treatment in AD through computational analysis. In this study, the intersection between HSP70 family members and immune molecules was taken to screen immune-related HSP70 family genes. Based on the datasets from the NCBI-Gene Expression Omnibus (GEO) database, we found that the expression levels of HSPA1A and HSPA2 were significantly increased in AD samples, while HSPA8 significantly decreased. Surprisingly, the combination of the 3 hub genes had a good diagnosis of AD via receiver operating characteristic curve (ROC). Moreover, the clinical value of the 3 hub genes was further assessed by the Spearman correlation analysis with AD-related genes, β-secretase activity, and γ-secretase activity. In terms of immune cell infiltration, we showed that the distribution of seven immune cell types (macrophages M2, neutrophils, T cells CD4 memory activated, macrophages M0, NK cells activated, plasma cells, and T cells follicular helper) was associated with the occurrence of AD by CIBERSORT. Furthermore, our data suggested that EP300, MYC, TP53, JUN, CREBBP, and ESR1 might be key transcription factors (TFs) for the 3 hub genes. In general, these findings suggest that HSPA1A, HSPA2, and HSPA8 are potential molecular biomarkers for prognosis among HSP70 family in AD, and it provides a new perspective on diagnostic and therapeutic targets for AD.

Accelerated aging-related transcriptome alterations in neurovascular unit cells in the brain of Alzheimer’s disease

Alzheimer’s disease (AD) is the most common cause of dementia with no effective therapies. Aging is a dominant risk factor for AD. The neurovascular unit (NVU) plays an important role in maintaining homeostasis of the brain microenvironment. The accelerated aging of NVU cells may directly impair NVU function and contribute to AD pathogenesis. However, the expression patterns of aging-related genes (AGs) in NVU cells of AD remain unclear. In this study, we performed single-nucleus transcriptome analysis of 61,768 nuclei from prefrontal cortical samples of patients with AD and normal control (NC) subjects. Eight main cell types were identified, including astrocytes, microglia, excitatory neurons, inhibitory neurons, oligodendrocytes, oligodendrocyte precursor cells, pericytes, and endothelial cells. Transcriptomic analysis identified the expression patterns of AGs in NVU cells of AD. Gene set enrichment analysis confirmed the key aging-associated cellular pathways enriched in microglia and oligodendrocytes. These aging-related transcriptomic changes in NVU were cross-validated using bulk transcriptome data. The least absolute shrinkage and selection operator regression method was used to select the crucial AGs most associated with AD: IGF1R, MXI1, RB1, PPARA, NFE2L2, STAT5B, FOS, PRKCD, YWHAZ, HTT, MAPK9, HSPA9, SDHC, PRKDC, and PDPK1. This 15-gene model performed well in discriminating AD from NC samples. Among them, IGF1R, MXI1, PPARA, YWHAZ, and MAPK9 strongly correlated with pathologic progression in AD, were identified as critical regulators of AD. Although most AGs showed similar trends of expression changes in different types of NVU cells in AD, certain AGs were expressed in a cell-specific manner. Our comprehensive analysis of brain NVU from patients with AD reveals previously unknown molecular changes associated with aging that may underlie the functional dysregulation of NVU, providing important insights for exploring potential cell-specific therapeutic targets to restore brain homeostasis in AD.

Identification and Experimental Validation of Marker Genes between Diabetes and Alzheimer’s Disease

Currently, Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are widely prevalent in the elderly population, and accumulating evidence implies a strong link between them. For example, patients with T2DM have a higher risk of developing neurocognitive disorders, including AD, but the exact mechanisms are still unclear. This time, by combining bioinformatics analysis and in vivo experimental validation, we attempted to find a common biological link between AD and T2DM. We firstly downloaded the gene expression profiling (AD: GSE122063; T2DM: GSE161355) derived from the temporal cortex. To find the associations, differentially expressed genes (DEGs) of the two datasets were filtered and intersected. Based on them, enrichment analysis was carried out, and the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to identify the specific genes. After verifying in the external dataset and in the samples from the AD and type 2 diabetes animals, the shared targets of the two diseases were finally determined. Based on them, the ceRNA networks were constructed. Besides, the logistic regression and single-sample gene set enrichment analysis (ssGSEA) were performed. As a result, 62 DEGs were totally identified between AD and T2DM, and the enrichment analysis indicated that they were much related to the function of synaptic vesicle and MAPK signaling pathway. Based on the evidence from external dataset and RT-qPCR, CARTPT, EPHA5, and SERPINA3 were identified as the marker genes in both diseases, and their clinical significance and biological functions were further analyzed. In conclusion, discovering and exploring the marker genes that are dysregulated in both 2 diseases could help us better comprehend the intrinsic relationship between T2DM and AD, which may inspire us to develop new strategies for facing the dilemmas of clinical or basic research in cognitive dysfunction.

Endocannabinoid system in the neuroendocrine response to LPS-induced immune challenge

The endocannabinoid system plays a key role in the intersection of the nervous, endocrine, and immune system, regulating not only their functions but also how they interplay with each other. Endogenous ligands, named endocannabinoids, are produced “on demand” to finely regulate the synthesis and secretion of hormones and neurotransmitters, as well as to regulate the production of cytokines and other proinflammatory mediators.

It is well known that immune challenges, such as exposure to lipopolysaccharide (LPS), the main component of the Gram-negative bacteria cell wall, disrupts not only the hypothalamic-pituitary-adrenal axis but also affects other endocrine systems such as the hypothalamic-pituitary-gonadal axis and the release of oxytocin from the neurohypophysis. Here we explore which actors and molecular mechanisms are involved in these processes.

Emerging role of astrocytes in oxytocin-mediated control of neural circuits and brain functions

The neuropeptide oxytocin has been in the focus of scientists for decades due to its profound and pleiotropic effects on physiology, activity of neuronal circuits and behaviors, among which sociality. Until recently, it was believed that oxytocinergic action exclusively occurs through direct activation of neuronal oxytocin receptors. However, several studies demonstrated the existence and functional relevance of astroglial oxytocin receptors in various brain regions in the mouse and rat brain. Astrocytic signaling and activity is critical for many important physiological processes including metabolism, neurotransmitter clearance from the synaptic cleft and integrated brain functions. While it can be speculated that oxytocinergic action on astrocytes predominantly facilitates neuromodulation via the release of specific gliotransmitters, the precise role of astrocytic oxytocin receptors remains elusive. In this review, we discuss the latest studies on the interaction between the oxytocinergic system and astrocytes, including detailed information about intracellular cascades, and speculate about future research directions on astrocytic oxytocin signaling.

Identification of TLR2 as a Key Target in Neuroinflammation in Vascular Dementia

Vascular dementia (VaD) is the second most common cause of dementia. At present, precise molecular processes of VaD are unclear. We attempted to discover the VaD relevant candidate genes, enrichment biological processes and pathways, key targets, and the underlying mechanism by microarray bioinformatic analysis. We selected GSE122063 related to the autopsy samples of VaD for analysis. We first took use of Weighted Gene Co-expression Network Analysis (WGCNA) to achieve modules related to VaD and hub genes. Second, we filtered out significant differentially expressed genes (DEGs). Third, significant DEGs then went through Geno Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Fourth, Gene Set Enrichment Analysis (GSEA) was performed. At last, we constructed the protein–protein interaction (PPI) network. The results showed that the yellow module had the strongest correlation with VaD, and we finally identified 21 hub genes. Toll-like receptor 2 (TLR2) was the top hub gene and was strongly correlated with other possible candidate genes. In total, 456 significant DEGs were filtered out and these genes were found to be enriched in the Toll receptor signaling pathway and several other immune-related pathways. In addition, Gene Set Enrichment Analysis results showed that similar pathways were significantly over-represented in TLR2-high samples. In the PPI network, TLR2 was still an important node with high weight and combined scores. We concluded that the TLR2 acts as a key target in neuroinflammation which may participate in the pathophysiological process of VaD.

Articulating target-mining techniques to disinter Alzheimer's specific targets for drug repurposing

BACKGROUND AND OBJECTIVES

Alzheimer's Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies.

METHODS

Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of RGS4.

RESULTS

SST and RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target RGS4 was considered for further sequential analysis. Homology model constructed for RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards RGS4.

CONCLUSION

This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.

Oxytocin-Cholinergic Central Interaction: Implications for Non-Social Memory Formation

Oxytocin (OT) and vasopressin (AVP) are two closely related neuropeptides implicated in learning and memory processes, anxiety, nociception, addiction, feeding behavior and social information processing. Regarding learning and memory, OT has induced long-lasting impairment in different behaviors, while the opposite was observed with AVP. We have previously evaluated the effect of peripheral administration of OT or its antagonist (AOT) on the inhibitory avoidance response of mice and on the modulation of cholinergic mechanisms. Here, we replicate and validate those results, but this time through central administration of neuropeptides, considering their poor passage through the blood-brain barrier (BBB). When we delivered OT (0.10 ng/mouse) and its antagonist (0.10 ng/mouse) through intracerebroventricular (ICV) injections, the neuropeptide impaired and AOT enhanced the behavioral performance on an inhibitory avoidance response evaluated 48 h after training in a dose-dependent manner. On top of that, we investigated a possible central interaction between OT and the cholinergic system. Administration of anticholinesterases inhibitors with access to the central nervous system (CNS), the activation of muscarinic acetylcholine (Ach) receptors and the increase of evoked ACh release using linopirdine (Lino) (3-10 µg/kg, IP), reversed the impairment of retention performance induced by OT. Besides, either muscarinic or nicotinic antagonists with unrestricted access to the CNS reduced the magnitude of the performance-facilitating effect of AOT's central infusion. We suggest that OT might induce a cholinergic hypofunction state, resulting in an impairment of IA memory formation, a process for which the cholinergic system is crucially necessary.

Network Pharmacology-Based Strategy to Investigate the Pharmacologic Mechanisms of Coptidis Rhizoma for the Treatment of Alzheimer's Disease

Background

Alzheimer's disease (AD) is becoming a more prevalent public health issue in today's culture. The experimental study of Coptidis Rhizoma (CR) and its chemical components in AD treatment has been widely reported, but the principle of multi-level and multi-mechanism treatment of AD urgently needs to be clarified.

Objective

This study focuses on network pharmacology to clarify the mechanism of CR's multi-target impact on Alzheimer's disease.

Methods

The Phytochemical-compounds of CR have been accessed from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) and Symmap database or HPLC determination. The values of Oral Bioavailability (OB) ≥ 30% and Drug Like (DL) ≥ 0.18 or blood ingredient were used to screen the active components of CR; the interactive network of targets and compounds were constructed by STRING and Cytoscape platform, and the network was analyzed by Molecular Complex Detection (MCODE); Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) and metabolic pathway enrichment of targets were carried out with Metascape, the Database for Annotation, Visualization and Integrated Discovery (DAVID) and MetaboAnalyst platform; Based on CytoHubba, the potential efficient targets were screened by Maximal Clique Centrality (MCC) and Degree, the correlation between potential efficient targets and amyloid β-protein (Aβ), Tau pathology was analyzed by Alzdata database, and the genes related to aging were analyzed by Aging Altas database, and finally, the core targets were obtained; the binding ability between ingredients and core targets evaluated by molecular docking, and the clinical significance of core targets was assessed with Gene Expression Omnibus (GEO) database.

Results

19 active components correspond to 267 therapeutic targets for AD, of which 69 is potentially effective; in module analysis, RELA, TRAF2, STAT3, and so on are the critical targets of each module; among the six core targets, RELA, MAPK8, STAT3, and TGFB1 have clinical therapeutic significance; GO function, including 3050 biological processes (BP), 257 molecular functions (MF), 184 cellular components (CC), whose functions are mainly related to antioxidation, regulation of apoptosis and cell composition; the HIF-1 signaling pathway, glutathione metabolism is the most significant result of 134 KEGG signal pathways and four metabolic pathways, respectively; most of the active components have an excellent affinity in docking with critical targets.

Conclusion

The pharmacological target prediction of CR based on molecular network pharmacology paves the way for a multi-level networking strategy. The study of CR in AD treatment shows a bright prospect for curing neurodegenerative diseases.

Single-nucleus transcriptome analysis reveals disease- and regeneration-associated endothelial cells in white matter vascular dementia

BACKGROUND

Vascular dementia (VaD) is the accumulation of vascular lesions in the subcortical white matter of the brain. These lesions progress and there is no direct medical therapy.

AIMS

To determine the specific cellular responses in VaD so as to provide molecular targets for therapeutic development.

MATERIALS AND METHODS

Single-nucleus transcriptome analysis was performed in human periventricular white matter (PVWM) samples of VaD and normal control (NC) subjects.

RESULTS

Differential analysis shows that cell type-specific transcriptomic changes in VaD are associated with the disruption of specific biological processes, including angiogenesis, immune activation, axonal injury and myelination. Each cell type in the neurovascular unit within white matter has a specific alteration in gene expression in VaD. In a central cell type for this disease, subcluster analysis of endothelial cells (EC) indicates that VaD contains a disease-associated EC subcluster that expresses genes associated with programmed cell death and a response to protein folding. Two other subpopulations of EC in VaD express molecular systems associated with regenerative processes in angiogenesis, and in axonal sprouting and oligodendrocyte progenitor cell maturation.

CONCLUSION

This comprehensive molecular profiling of brain samples from patients with VaD reveals previously unknown molecular changes in cells of the neurovascular niche, and an attempt at regeneration in injured white matter.

Identification and Validation of Aging-Related Genes in Alzheimer’s Disease

Aging is recognized as the key risk factor for Alzheimer’s disease (AD). This study aimed to identify and verify potential aging-related genes associated with AD using bioinformatics analysis. Aging-related differential expression genes (ARDEGs) were determined by the intersection of limma test, weighted correlation network analysis (WGCNA), and 1153 aging and senescence-associated genes. Potential biological functions and pathways of ARDEGs were determined by GO, KEGG, GSEA, and GSVA. Then, LASSO algorithm was used to identify the hub genes and the diagnostic ability of the five ARDEGs in discriminating AD from the healthy control samples. Further, the correlation between hub ARDEGs and clinical characteristics was explored. Finally, the expression level of the five ARDEGs was validated using other four GEO datasets and blood samples of patients with AD and healthy individuals. Five ARDEGs (GFAP, PDGFRB, PLOD1, MAP4K4, and NFKBIA) were obtained. For biological function analysis, aging, cellular senescence, and Ras protein signal transduction regulation were enriched. Diagnostic ability of the five ARDEGs in discriminating AD from the control samples demonstrated a favorable diagnostic value. Eventually, quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) validation test revealed that compared with healthy controls, the mRNA expression level of PDGFRB, PLOD1, MAP4K4, and NFKBIA were elevated in AD patients. In conclusion, this study identified four ARDEGs (PDGFRB, PLOD1, MAP4K4, and NFKBIA) associated with AD. They provide an insight into potential novel biomarkers for diagnosing AD and monitoring progression.

Multi-Omics Characterization of Type 2 Diabetes Mellitus-Induced Cognitive Impairment in the db/db Mouse Model

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder frequently accompanied by cognitive impairment. Contributing factors such as modern lifestyle, genetic predisposition, and gene environmental interactions have been postulated, but the pathogenesis remains unclear. In this study, we attempt to investigate the potential mechanisms and interventions underlying T2DM-induced cognitive deficits from the brain–gut axis perspective. A combined analysis of the brain transcriptome, plasma metabolome, and gut microbiota in db/db mice with cognitive decline was conducted. Transcriptome analysis identified 222 upregulated gene sets and 85 downregulated gene sets, mainly related to mitochondrial respiratory, glycolytic, and inflammation. In metabolomic analysis, a total of 75 significantly altered metabolites were identified, correlated with disturbances of glucose, lipid, bile acid, and steroid metabolism under disease state. Gut microbiota analysis suggested that the species abundance and diversity of db/db mice were significantly increased, with 23 significantly altered genus detected. Using the multi-omics integration, significant correlations among key genes (n = 33), metabolites (n = 41), and bacterial genera (n = 21) were identified. Our findings suggest that disturbed circulation and brain energy metabolism, especially mitochondrial-related disturbances, may contribute to cognitive impairment in db/db mice. This study provides novel insights into the functional interactions among the brain, circulating metabolites, and gut microbiota.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.

Large household reduces dementia mortality: A cross-sectional data analysis of 183 populations

Background

Large households/families may create more happiness and offer more comprehensive healthcare among the members. We correlated household size to dementia mortality rate at population level for analysing its protecting role against dementia mortality.

Methods

This is a retrospective cross-sectional study. Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban population and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearson’s and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearson’s approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression was used to identify significant predictors of dementia mortality.

Results

Household size was in a negative and moderately strong correlation (r = -0.6034, p < 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r = - 0.524, p<0.001) and nonparametric (rho  =  -0.579, p < 0.001) analyses. When we controlled for the contribution of ageing, socio-economic status and urban lifestyle in partial correlation analysis, large household was still in inverse and significant correlation to dementia mortality (r = −0.331, p <0.001). This suggested that, statistically, large household protect against dementia mortality regardless of the contributing effects of ageing, socio-economic status and urban lifestyle. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R² = 0.263 while ageing was placed second increasing R² to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality.

Conclusions

While acknowledging ageing, urban lifestyle and greater GDP associated with dementia mortality, this study suggested that, at population level, household size was another risk factor for dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve.

Identification of Molecular Signatures and Candidate Drugs in Vascular Dementia by Bioinformatics Analyses

Vascular dementia (VaD) is considered to be the second most common form of dementia after Alzheimer’s disease, and no specific drugs have been approved for VaD treatment. We aimed to identify shared transcriptomic signatures between the frontal cortex and temporal cortex in VaD by bioinformatics analyses. Gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) and hub gene identification, hub gene–transcription factor interaction, hub gene–microRNA interaction, and hub gene–drug interaction analyses were performed. We identified 159 overlapping differentially expressed genes (DEGs) between the frontal cortex and temporal cortex that were enriched mainly in inflammation and innate immunity, synapse pruning, regeneration, positive regulation of angiogenesis, response to nutrient levels, and positive regulation of the digestive system process. We identified 10 hub genes in the PPI network (GNG13, CD163, C1QA, TLR2, SST, C1QB, ITGB2, CCR5, CRH, and TAC1), four central regulatory transcription factors (FOXC1, CREB1, GATA2, and HINFP), and four microRNAs (miR-27a-3p, miR-146a-5p, miR-335-5p, and miR-129-2-3p). Hub gene–drug interaction analysis found four drugs (maraviroc, cenicriviroc, PF-04634817, and efalizumab) that could be potential drugs for VaD treatment. Together, our results may contribute to understanding the underlying mechanisms in VaD and provide potential targets and drugs for therapeutic intervention.

Identification of Ferroptosis-Related Genes in Alzheimer’s Disease Based on Bioinformatic Analysis

Introduction

Alzheimer’s disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD.

Materials and Methods

Three microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls.

Results

53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P &lt; 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P &lt; 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD.

Conclusion

We identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring.

Detection of molecular signatures and pathways shared by Alzheimer's disease and type 2 diabetes

Alzheimer's disease (AD) and type 2 diabetes (T2D) are common in the general elderly population, conferring heavy individual, social, and economic stresses on families and society. Accumulating evidence indicates T2D to be a risk factor for AD. However, the underlying mechanisms for this association are largely unknown. This study aimed to identify the shared molecular signatures between AD and T2D through integrated analysis of temporal cortex gene expression data. Gene Ontology (GO) and pathway enrichment analysis, protein over-representation analysis, protein-protein interaction, DEG-transcription factor interactions, DEG-microRNA interactions, protein-drug interactions, gene-disease association analysis, and protein subcellular localization analysis of the common DEGs were performed. We identified 16 common DEGs between the two datasets, which were mainly enriched in the biological processes of apoptosis, autophagy, inflammation, and hemostasis. We also identified five hub proteins encoded by the DEGs, five central regulatory transcription factors, and six microRNAs. Protein-drug interaction analysis showed C1QB to be associated with different drugs. Gene-disease association analysis revealed that hub genes, SFN and ITGB2, were actively engaged in other diseases. Collectively, these findings provide new insights into shared molecular mechanisms between AD and T2D and provide novel candidate targets for therapeutic intervention.

Identification of miRNA and Their Regulatory Effects Induced by Total Flavonoids From Dracocephalum moldavica in the Treatment of Vascular Dementia

Vascular dementia (VaD) is a general term used to describe difficulties in memory, reasoning, judgment, and planning caused by a reduced blood flow to the brain and consequent brain damage, in which microRNAs (miRNAs) are involved. Dracocephalum moldavica L. (D. moldavica) is traditionally used in the treatment of cardiovascular diseases as well as VaD, but the biomolecular mechanisms underlying its therapeutic effect are obscure. In the present study, the molecular mechanisms involved in the treatment of VaD by the total flavonoids from Dracocephalum moldavica L. (TFDM) were explored by the identification of miRNA profiling using bioinformatics analysis and experimental verification. A total of 2,562 differentially expressed miRNAs (DEMs) and 3,522 differentially expressed genes (DEGs) were obtained from the GSE120584 and GSE122063 datasets, in which the gene functional enrichment and protein-protein interaction network of 93 core targets, originated from the intersection of the top DEM target genes and DEGs, were established for VaD gene profiling. One hundred and eighty-five targets interacting with 42 flavonoids in the TFDM were included in a compound-target network, subsequently found that they overlapped with potential targets for VaD. These 43 targets could be considered in the treatment of VaD by TFDM, and included CaMKII, MAPK, MAPT, PI3K, and KDR, closely associated with the vascular protective effect of TFDM, as well as anti-oxidative, anti-inflammatory, and anti-apoptotic properties. The subsequent analysis of the compound-target gene-miRNA network indicated that eight miRNAs that mediated 43 targets had a close interaction with TFDM, suggesting that the neuroprotective effects were principally due to kaempferol, apigenin, luteolin, and quercetin, which were mostly associated with the miR-3184-3p/ESR1, miR-6762-3p/CDK1, miR-6777-3p/ESRRA, and other related axes. Furthermore, the in vitro oxygen-glucose deprivation (OGD) model demonstrated that the dysregulation of miR-3184-3p and miR-6875-5p found by qRT-PCR was consistent with the changes in the bioinformatics analysis. TFDM and its active compounds involving tilianin, luteolin, and apigenin showed significant effects on the upregulation of miR-3184-3p and downregulation of miR-6875-5p in OGD-injured cells, in line with the improved cell viability. In conclusion, our findings revealed the underlying miRNA-target gene network and potential targets of TFDM in the treatment of VaD.

Putative Factors Interfering Cell Cycle Re-Entry in Alzheimer's Disease: An Omics Study with Differential Expression Meta-Analytics and Co-Expression Profiling

BACKGROUND

Neuronal cell cycle re-entry (CCR) is a mechanism, along with amyloid-β (Aβ) oligomers and hyperphosphorylated tau proteins, contributing to toxicity in Alzheimer's disease (AD).

OBJECTIVE

This study aimed to examine the putative factors in CCR based on evidence corroboration by combining meta-analysis and co-expression analysis of omic data.

METHODS

The differentially expressed genes (DEGs) and CCR-related modules were obtained through the differential analysis and co-expression of transcriptomic data, respectively. Differentially expressed microRNAs (DEmiRNAs) were extracted from the differential miRNA expression studies. The dysregulations of DEGs and DEmiRNAs as binary outcomes were independently analyzed by meta-analysis based on a random-effects model. The CCR-related modules were mapped to human protein-protein interaction databases to construct a network. The importance score of each node within the network was determined by the PageRank algorithm, and nodes that fit the pre-defined criteria were treated as putative CCR-related factors.

RESULTS

The meta-analysis identified 18,261 DEGs and 36 DEmiRNAs, including genes in the ubiquitination proteasome system, mitochondrial homeostasis, and CCR, and miRNAs associated with AD pathologies. The co-expression analysis identified 156 CCR-related modules to construct a protein-protein interaction network. Five genes, UBC, ESR1, EGFR, CUL3, and KRAS, were selected as putative CCR-related factors. Their functions suggested that the combined effects of cellular dyshomeostasis and receptors mediating Aβ toxicity from impaired ubiquitination proteasome system are involved in CCR.

CONCLUSION

This study identified five genes as putative factors and revealed the significance of cellular dyshomeostasis in the CCR of AD.

Whole Blood Expression Pattern of Inflammation and Redox Genes in Mild Alzheimer's Disease

Background

Although Alzheimer’s disease (AD) is associated with alterations of the central nervous system, this disease has an echo in blood that might represent a valuable source of biomarkers for improved diagnosis, prognosis and for monitoring drug response.

Methods

We performed a targeted transcriptomics study on 38 mild Alzheimer’s disease (AD) patients and 38 matched controls for evaluating the expression levels of 136 inflammation and 84 redox genes in whole blood. Patients were diagnosed as mild AD based on altered levels of total TAU, phospho-TAU and Abeta_(1–42) in cerebrospinal fluid, and Abeta_(1–40), Abeta_(1–42) and total TAU levels in plasma. Whenever possible, blood and brain comparisons were made using public datasets.

Results

We found 48 inflammation and 34 redox genes differentially expressed in the blood of AD patients vs controls (FC >1.5, p < 0.01), out of which 22 pro-inflammatory and 12 redox genes exhibited FC >2 and p < 0.001. Receiver operating characteristic (ROC) analysis identified nine inflammation and seven redox genes that discriminated between AD patients and controls (area under the curve >0.9). Correlations of the dysregulated inflammation and redox transcripts indicated that RELA may regulate several redox genes including DUOX1 and GSR. Based on the gene expression profile, we have found that the master regulators of inflammation and redox homeostasis, NFκB and NRF2, were significantly disturbed in the blood of AD patients, as well as several zinc finger and helix-loop-helix transcription factors.

Conclusion

The selected inflammation and redox genes might be useful biomarkers for monitoring anti-inflammatory therapy in mild AD.

MicroRNA-Target Interaction Regulatory Network in Alzheimer's Disease

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia; however, early diagnosis of the disease is challenging. Research suggests that biomarkers found in blood, such as microRNAs (miRNA), may be promising for AD diagnostics. Experimental data on miRNA–target interactions (MTI) associated with AD are scattered across databases and publications, thus making the identification of promising miRNA biomarkers for AD difficult. In response to this, a list of experimentally validated AD-associated MTIs was obtained from miRTarBase. Cytoscape was used to create a visual MTI network. STRING software was used for protein–protein interaction analysis and mirPath was used for pathway enrichment analysis. Several targets regulated by multiple miRNAs were identified, including: BACE1, APP, NCSTN, SP1, SIRT1, and PTEN. The miRNA with the highest numbers of interactions in the network were: miR-9, miR-16, miR-34a, miR-106a, miR-107, miR-125b, miR-146, and miR-181c. The analysis revealed seven subnetworks, representing disease modules which have a potential for further biomarker development. The obtained MTI network is not yet complete, and additional studies are needed for the comprehensive understanding of the AD-associated miRNA targetome.

Localization of the hydrogen sulfide and oxytocin systems at the depth of the sulci in a porcine model of acute subdural hematoma

In the porcine model discussed in this review, the acute subdural hematoma was induced by subdural injection of autologous blood over the left parietal cortex, which led to a transient elevation of the intracerebral pressure, measured by bilateral neuromonitoring. The hematoma-induced brain injury was associated with albumin extravasation, oxidative stress, reactive astrogliosis and microglial activation in the ipsilateral hemisphere. Further proteins and injury markers were validated to be used for immunohistochemistry of porcine brain tissue. The cerebral expression patterns of oxytocin, oxytocin receptor, cystathionine-γ-lyase and cystathionine-β-synthase were particularly interesting: these four proteins all co-localized at the base of the sulci, where pressure-induced brain injury elicits maximum stress. In this context, the pig is a very relevant translational model in contrast to the rodent brain. The structure of the porcine brain is very similar to the human: the presence of gyri and sulci (gyrencephalic brain), white matter to grey matter proportion and tentorium cerebelli. Thus, pressure-induced injury in the porcine brain, unlike in the rodent brain, is reflective of the human pathophysiology.

Analysis of Immune-related Key Genes in Alzheimer's Disease

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.

Revelation of Pivotal Genes Pertinent to Alzheimer's Pathogenesis: A Methodical Evaluation of 32 GEO Datasets

Alzheimer’s disease (AD), a dreadful neurodegenerative disorder that affects cognitive and behavioral function in geriatric populations, is characterized by the presence of amyloid deposits and neurofibrillary tangles in brain regions. The International D World Alzheimer Report2018 noted a global prevalence of 50 million AD cases and forecasted a threefold rise to 139 million by 2050. Although there exist numerous genetic association studies pertinent to AD in different ethnicities, critical genetic factors and signaling pathways underlying its pathogenesis remain ambiguous. This study was aimed to analyze the genetic data retrieved from 32 Gene Expression Omnibus datasets belonging to diverse ethnic cohorts in order to identify overlapping differentially expressed genes (DEGs). Stringent selection criteria were framed to shortlist appropriate datasets based on false discovery rate (FDR) p-value and log FC, and relevant details of upregulated and downregulated DEGs were retrieved. Among the 32 datasets, only six satisfied the selection criteria. The GEO2R tool was employed to retrieve significant DEGs. Nine common DEGs, i.e., SLC5A3, BDNF, SST, SERPINA3, RTN3, RGS4, NPTX, ENC1 and CRYM were found in more than 60% of the selected datasets. These DEGs were later subjected to protein–protein interaction analysis with 18 AD-specific literature-derived genes. Among the nine common DEGs, BDNF, SST, SERPINA3, RTN3 and RGS4 exhibited significant interactions with crucial proteins including BACE1, GRIN2B, APP, APOE, COMT, PSEN1, INS, NEP and MAPT. Functional enrichment analysis revealed involvement of these genes in trans-synaptic signaling, chemical transmission, PI3K pathway signaling, receptor–ligand activity and G protein signaling. These processes are interlinked with AD pathways.

Oxytocin and Bone: Review and Perspectives

Recent data demonstrate the anabolic effect of oxytocin on bone. Bone cells express oxytocin receptors. Oxytocin promotes osteoblasts differentiation and function, leading to an increased bone formation with no effect on bone resorption and an improvement of bone microarchitecture. Oxytocin is synthetized by osteoblasts, and this synthesis is stimulated by estrogen. Animal studies demonstrate a direct action of oxytocin on bone, as the systemic administration of oxytocin prevents and reverses the bone loss induced by estrogen deficiency. Although oxytocin is involved in bone formation in both sexes during development, oxytocin treatment has no effect on male osteoporosis, underlining the importance of estrogen that amplifies its local autocrine and paracrine secretion. There are few human data showing a decrease in the oxytocin serum level in anorexia nervosa independently of estrogen and in amenorrheic women associated with impaired bone microarchitecture; in post-menopausal women a higher oxytocin serum level is associated with higher bone density, but not in osteoporotic men. Oxytocin displays many effects that may be beneficial in the management of osteoporosis, cardiovascular diseases, cognitive disorders, breast cancer, diabetes and body fat gain, all age-related diseases affecting elderly women, opening exciting therapeutic perspectives, although the issue is to find a single route, dosage and schedule able to reach all these targets.