Role of SNAREs in Neurodegenerative Diseases

Margiotta, Azzurra

doi:10.3390/cells10050991

Cited by 44 publications

(32 citation statements)

References 113 publications

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“…This experimental study found that after Radix Rhei Et Rhizome treatment, its expression was significantly increased compared with the model group, indicating that Radix Rhei Et Rhizome may resist synapse damage or promote synaptic regeneration after cerebral ischemia. Synapse protein I gene (SYN1) mainly mediates the delivery of synaptic vesicles and circulation [ 73 ] and plays an important role in neurodegenerative diseases [ 74 ], such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. This study suggests that SYN1 may be a potential drug target for neurodegenerative diseases caused by CI, among which Radix Rhei Et Rhizome can reduce CI by interfering with SYN1.…”

Section: Resultsmentioning

confidence: 99%

Mechanism of Radix Rhei Et Rhizome Intervention in Cerebral Infarction: A Research Based on Chemoinformatics and Systematic Pharmacology

Wang

Long

Zeng

et al. 2021

Evidence-Based Complementary and Alternative Medicine

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Objective. To explore the therapeutic targets, network modules, and coexpressed genes of Radix Rhei Et Rhizome intervention in cerebral infarction (CI), and to predict significant biological processes and pathways through network pharmacology. To explore the differential proteins of Radix Rhei Et Rhizome intervention in CI, conduct bioinformatics verification, and initially explain the possible therapeutic mechanism of Radix Rhei Et Rhizome intervention in CI through proteomics. Methods. The TCM database was used to predict the potential compounds of Radix Rhei Et Rhizome, and the PharmMapper was used to predict its potential targets. GeneCards and OMIM were used to search for CI-related genes. Cytoscape was used to construct a protein-protein interaction (PPI) network and to screen out core genes and detection network modules. Then, DAVID and Metascape were used for enrichment analysis. After that, in-depth analysis of the proteomics data was carried out to further explore the mechanism of Radix Rhei Et Rhizome intervention in CI. Results. (1) A total of 14 Radix Rhei Et Rhizome potential components and 425 potential targets were obtained. The core components include sennoside A, palmidin A, emodin, toralactone, and so on. The potential targets were combined with 297 CI genes to construct a PPI network. The targets shared by Radix Rhei Et Rhizome and CI include ALB, AKT1, MMP9, IGF1, CASP3, etc. The biological processes that Radix Rhei Et Rhizome may treat CI include platelet degranulation, cell migration, fibrinolysis, platelet activation, hypoxia, angiogenesis, endothelial cell apoptosis, coagulation, and neuronal apoptosis. The signaling pathways include Ras, PI3K-Akt, TNF, FoxO, HIF-1, and Rap1 signaling pathways. (2) Proteomics shows that the top 20 proteins in the differential protein PPI network were Syp, Syn1, Mbp, Gap43, Aif1, Camk2a, Syt1, Calm1, Calb1, Nsf, Nefl, Hspa5, Nefh, Ncam1, Dcx, Unc13a, Mapk1, Syt2, Dnm1, and Cltc. Differential protein enrichment results show that these proteins may be related to synaptic vesicle cycle, vesicle-mediated transport in synapse, presynaptic endocytosis, synaptic vesicle endocytosis, axon guidance, calcium signaling pathway, and so on. Conclusion. This study combined network pharmacology and proteomics to explore the main material basis of Radix Rhei Et Rhizome for the treatment of CI such as sennoside A, palmidin A, emodin, and toralactone. The mechanism may be related to the regulation of biological processes (such as synaptic vesicle cycle, vesicle-mediated transport in synapse, presynaptic endocytosis, and synaptic vesicle endocytosis) and signaling pathways (such as Ras, PI3K-Akt, TNF, FoxO, HIF-1, Rap1, and axon guidance).

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Section: Resultsmentioning

confidence: 99%

Mechanism of Radix Rhei Et Rhizome Intervention in Cerebral Infarction: A Research Based on Chemoinformatics and Systematic Pharmacology

Wang

Long

Zeng

et al. 2021

Evidence-Based Complementary and Alternative Medicine

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“…The top 10 KEGG pathways (those enriched in the shortest paths) are shown in Table 6 ( Turi et al, 2019 ; Jia et al, 2021 ; Chothani et al, 2019 ; Yin et al, 2021 ; Manhas and Rath, 2020 ; Li et al, 2018 ; Nakajima et al, 2019 ; Hosseini et al, 2021 ; Critchley et al, 2018 ; Lathe et al, 2014 ; Margiotta, 2021 ; Nickel et al, 2002 ; Chen et al, 2020 ; Luo et al, 2020 ; Miller et al, 2021 ; Stadtman et al, 2005 ; Bonifácio et al, 2021 ; Blachier et al, 2020 ; Kumar et al, 2017 ; Récher, 2021 ; Klemm and Ruland, 2006 ). The most frequently enriched KEGG pathway was “ribosome” (enriched in eight shortest paths; Figure 4A ).…”

Section: Resultsmentioning

confidence: 99%

“…The top enriched KEGG pathway (with the minimum FDR) was “SNARE interactions in vesicular transport” ( p = 4.6346 and FDR = 0.0086; Figure 4B ). The SNARE protein is an essential component in the regulation of vesicle fusion and plays a key part in maintaining cell homeostasis ( Margiotta, 2021 ). Vesicle transport is the main mechanism of protein and lipid exchange between membrane-bound organelles in eukaryotic cells ( Nickel et al, 2002 ); vesicle transport in mitochondria also affects mitochondrial function, which is one of the key characteristics of aging ( Chen et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

The Inflamm-Aging Model Identifies Key Risk Factors in Atherosclerosis

Chen

Yao

et al. 2022

Front. Genet.

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Background: Atherosclerosis, one of the main threats to human life and health, is driven by abnormal inflammation (i.e., chronic inflammation or oxidative stress) during accelerated aging. Many studies have shown that inflamm-aging exerts a significant impact on the occurrence of atherosclerosis, particularly by inducing an immune homeostasis imbalance. However, the potential mechanism by which inflamm-aging induces atherosclerosis needs to be studied more thoroughly, and there is currently a lack of powerful prediction models.Methods: First, an improved inflamm-aging prediction model was constructed by integrating aging, inflammation, and disease markers with the help of machine learning methods; then, inflamm-aging scores were calculated. In addition, the causal relationship between aging and disease was identified using Mendelian randomization. A series of risk factors were also identified by causal analysis, sensitivity analysis, and network analysis.Results: Our results revealed an accelerated inflamm-aging pattern in atherosclerosis and suggested a causal relationship between inflamm-aging and atherosclerosis. Mechanisms involving inflammation, nutritional balance, vascular homeostasis, and oxidative stress were found to be driving factors of atherosclerosis in the context of inflamm-aging.Conclusion: In summary, we developed a model integrating crucial risk factors in inflamm-aging and atherosclerosis. Our computation pipeline could be used to explore potential mechanisms of related diseases.

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“…In addition, the SNARE complex is vital in the formation of vesicle fusion, vesicle recycling and neurotransmitter release. The defects in the formation of the SNARE complex, SNARE-dependent exocytosis, and SNARE-mediated vesicle fusion are associated with neurological diseases 80 .…”

Section: Discussionmentioning

confidence: 99%

A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study

Dehghan¹,

Mirmotalebisohi²,

Sameni³

et al. 2022

AJMB

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Background: Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far. We used systems biology and bioinformatics methods to identify essential genes and molecular mechanisms behind the body response to Doxorubicin and its side effects in breast cancer patients. Methods: Omics data were extracted and analyzed to construct the protein-protein interaction and gene regulatory networks. Network analysis was performed to identify hubs, bottlenecks, clusters, and regulatory motifs to evaluate crucial genes and molecular mechanisms behind the body response to Doxorubicin and its side effects. Results: Analyzing the constructed PPI and gene-TF-miRNA regulatory network showed that MCM3, MCM10, and TP53 are key hub-bottlenecks and seed proteins. Enrichment analysis also revealed cell cycle, TP53 signaling, Forkhead box O (FoxO) signaling, and viral carcinogenesis as essential pathways in response to this drug. Besides, SNARE interactions in vesicular transport and neurotrophin signaling were identified as pathways related to the side effects of Doxorubicin. The apoptosis induction, DNA repair, invasion inhibition, metastasis, and DNA replication are suggested as critical molecular mechanisms underlying Doxorubicin anti-cancer effect. SNARE interactions in vesicular transport and neurotrophin signaling and FoxO signaling pathways in glucose metabolism are probably the mechanisms responsible for side effects of Doxorubicin. Conclusion: Following our model validation using the existing experimental data, we recommend our other newly predicted biomarkers and pathways as possible molecular mechanisms and side effects underlying the response to Doxorubicin in breast cancer requiring further investigations.

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Role of SNAREs in Neurodegenerative Diseases

Cited by 44 publications

References 113 publications

Mechanism of Radix Rhei Et Rhizome Intervention in Cerebral Infarction: A Research Based on Chemoinformatics and Systematic Pharmacology

Mechanism of Radix Rhei Et Rhizome Intervention in Cerebral Infarction: A Research Based on Chemoinformatics and Systematic Pharmacology

The Inflamm-Aging Model Identifies Key Risk Factors in Atherosclerosis

A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study

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