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Revealing the Molecular Mechanisms of Alzheimer's Disease Based on Network Analysis.

ABSTRACT: The complex pathology of Alzheimer's disease (AD) emphasises the need for comprehensive modelling of the disease, which may lead to the development of efficient treatment strategies. To address this challenge, we analysed transcriptome data of post-mortem human brain samples of healthy elders and individuals with late-onset AD from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MayoRNAseq) studies in the AMP-AD consortium. In this context, we conducted several bioinformatics and systems medicine analyses including the construction of AD-specific co-expression networks and genome-scale metabolic modelling of the brain in AD patients to identify key genes, metabolites and pathways involved in the progression of AD. We identified AMIGO1 and GRPRASP2 as examples of commonly altered marker genes in AD patients. Moreover, we found alterations in energy metabolism, represented by reduced oxidative phosphorylation and ATPase activity, as well as the depletion of hexanoyl-CoA, pentanoyl-CoA, (2E)-hexenoyl-CoA and numerous other unsaturated fatty acids in the brain. We also observed that neuroprotective metabolites (e.g., vitamins, retinoids and unsaturated fatty acids) tend to be depleted in the AD brain, while neurotoxic metabolites (e.g., β-alanine, bilirubin) were more abundant. In summary, we systematically revealed the key genes and pathways related to the progression of AD, gained insight into the crucial mechanisms of AD and identified some possible targets that could be used in the treatment of AD.

SUBMITTER: Bayraktar A

PROVIDER: S-EPMC8584243 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHuanglian Jiedu decoction (HLJDD) is a famous traditional Chinese medicine prescription, which is widely used in the treatment of Alzheimer's disease (AD). However, the interaction between bioactive substances in HLJDD and AD-related targets has not been well elucidated.AimA network pharmacology-based approach combined with molecular docking was performed to determine the bioactives, key targets, and potential pharmacological mechanism of HLJDD against AD, through the regulation of microbial flora.Materials and methodsBioactives and potential targets of HLJDD, as well as AD-related targets, were retrieved from Traditional Chinese Medicine Systems Pharmacology Analysis Database (TCMSP). Key bioactive components, potential targets, and signaling pathways were obtained through bioinformatics analysis, including protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Subsequently, molecular docking was performed to predict the binding of active compounds with core targets.Results102 bioactive ingredients of HLJDD and 76 HLJDD-AD-related targets were screened. Bioinformatics analysis revealed that kaempferol, wogonin, beta-sitosterol, baicalein, acacetin, isocorypalmine, (S)-canadine, (R)-canadine may be potential candidate agents. AKT1, TNF, TP53, VEGFA, FOS, PTGS2, MMP9 and CASP3 could become potential therapeutic targets. 15 important signaling pathways including the cancer pathway, VEGF signaling pathway, and NF-κB signaling pathway might play an important role in HLJDD against AD. Moreover, molecular docking analysis suggested that kaempferol, wogonin, beta-sitosterol, baicalein, acacetin, isocorypalmine, (S)-canadine, and (R)-canadine combined well with AKT1, TNF, TP53, VEGFA, FOS, PTGS2, MMP9, CASP3, respectively.ConclusionOur results comprehensively illustrated the bioactives, potential targets, and possible molecular mechanisms of HLJDD against AD. HLJDD may regulate the microbiota flora homeostasis to treat AD through multiple targets and multiple pathways. It also provided a promising strategy for the use of traditional Chinese medicine in treating human diseases.

Project description:ObjectiveTo investigate the genetic crosstalk mechanisms that link periodontitis and Alzheimer's disease (AD).BackgroundPeriodontitis, a common oral infectious disease, is associated with Alzheimer's disease (AD) and considered a putative contributory factor to its progression. However, a comprehensive investigation of potential shared genetic mechanisms between these diseases has not yet been reported.MethodsGene expression datasets related to periodontitis were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis was performed to identify differentially expressed genes (DEGs). Genes associated with AD were downloaded from the DisGeNET database. Overlapping genes among the DEGs in periodontitis and the AD-related genes were defined as crosstalk genes between periodontitis and AD. The Boruta algorithm was applied to perform feature selection from these crosstalk genes, and representative crosstalk genes were thus obtained. In addition, a support vector machine (SVM) model was constructed by using the scikit-learn algorithm in Python. Next, the crosstalk gene-TF network and crosstalk gene-DEP (differentially expressed pathway) network were each constructed. As a final step, shared genes among the crosstalk genes and periodontitis-related genes in DisGeNET were identified and denoted as the core crosstalk genes.ResultsFour datasets (GSE23586, GSE16134, GSE10334, and GSE79705) pertaining to periodontitis were included in the analysis. A total of 48 representative crosstalk genes were identified by using the Boruta algorithm. Three TFs (FOS, MEF2C, and USF2) and several pathways (i.e., JAK-STAT, MAPK, NF-kappa B, and natural killer cell-mediated cytotoxicity) were identified as regulators of these crosstalk genes. Among these 48 crosstalk genes and the chronic periodontitis-related genes in DisGeNET, C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 were shared and identified as the most pivotal candidate links between periodontitis and AD.ConclusionsExploration of available transcriptomic datasets revealed C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 as the top candidate molecular linkage genes between periodontitis and AD.

Project description:BackgroundHuangqi Sijunzi decoction (HQSJZD) is a commonly used conventional Chinese herbal medicine prescription for invigorating Qi, tonifying Yang, and removing dampness. Modern pharmacology and clinical applications of HQSJZD have shown that it has a certain curative effect on Alzheimer's disease (AD).MethodsThe active components and targets of HQSJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The genes corresponding to the targets were retrieved using UniProt and GeneCard database. The herb-compound-target network and protein-protein interaction (PPI) network were constructed by Cytoscape. The core targets of HQSJZD were analysed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HQSJZD were docked with acetylcholinesterase (AChE). In vitro experiments were conducted to detect the inhibitory and neuroprotective effects of AChE.ResultsCompound-target network mainly contained 132 compounds and 255 corresponding targets. The main compounds contained quercetin, kaempferol, formononetin, isorhamnetin, hederagenin, and calycosin. Key targets contained AChE, PTGS2, PPARG, IL-1B, GSK3B, etc. There were 1708 GO items in GO enrichment analysis and 310 signalling pathways in KEGG, mainly including the cAMP signalling pathway, the vascular endothelial growth factor (VEGF) signalling pathway, serotonergic synapses, the calcium signalling pathway, type II diabetes mellitus, arginine and proline metabolism, and the longevity regulating pathway. Molecular docking showed that hederagenin and formononetin were the top 2 compounds of HQSJZD, which had a high affinity with AChE. And formononetin has a good neuroprotective effect, which can improve the oxidative damage of nerve cells.ConclusionHQSJZD was found to have the potential to treat AD by targeting multiple AD-related targets. Formononetin and hederagenin in HQSJZD may regulate multiple signalling pathways through AChE, which might play a therapeutic role in AD.

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Revealing the Molecular Mechanisms of Alzheimer's Disease Based on Network Analysis.

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