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2000
Volume 22, Issue 6
  • ISSN: 1567-2050
  • E-ISSN: 1875-5828

Abstract

Introduction

Nowadays, the large increase in environmental pollutants has led to the occurrence and development of an increasing number of diseases. Studies have shown that exposure to environmental pollutants, such as methyl-4-hydroxybenzoate (MEP) may lead to Alzheimer's disease (AD). Therefore, the purpose of this study was to elucidate the complex effects and potential molecular mechanisms of environmental pollutants MEP on AD.

Methods

Through exhaustive exploration of databases, such as ChEMBL, STITCH, SwissTargetPrediction, and Gene Expression Omnibus DataSets (GEO DataSets), we have identified a comprehensive list of 46 potential targets closely related to MEP and AD. After rigorous screening using the STRING platform and Cytoscape software, we narrowed the list to nine candidate targets and ultimately identified six hub targets using three proven machine learning methods (LASSO, RF, and SVM): CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5. The “clusterProfiler” R package was used to conduct GO and KEGG enrichment analysis. At the same time, we also constructed disease prediction models for core genes. At last, six hub targets were executed molecular docking.

Results

We derived 46 key target genes related to MEP and AD and conducted gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. MEP might play a role in AD by affecting the pathways of neuroactive ligand-receptor interaction. Nine genes were screened as pivotal targets, followed by machine learning methods to identify six hub targets. Molecular docking analysis showed a good binding ability between MEP and CREBBP, BCL6, CXCR4, GRIN1, GOT2 and ITGA5. In addition, changes in the immune microenvironment revealed a significant impact of immune status on AD.

Discussions

This study revealed that MEP may induce AD through multiple mechanisms, such as oxidative stress, neurotoxicity, and immune regulation, and identified six core targets (CREBBP, BCL6, ) and found that they are related to changes in the immune microenvironment, such as T cells and B cells, providing new molecular targets for AD intervention.

Conclusion

Overall, CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5 have been identified as the crucial targets correlating with AD. Our findings provide a theoretical framework for understanding the complex molecular mechanisms underlying the effects of MEP on AD and provide insights for the development of prevention and treatment of AD caused by exposure to MEP.

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Effective Analysis of Alzheimer's Disease and Mechanisms of Methyl-4-Hydroxybenzoate using Network Toxicology, Molecular Docking, and Machine Learning Strategies
Curr Alzheimer Res 22, 456 (2025); https://doi.org/10.2174/0115672050399031250623062112
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Supplementary material is available on the publisher’s website along with the published article. Supplementary Fig. (). Correction curves and decision curves of predictive models. Supplementary Table . ProTox-3.0 - Prediction of toxicity of chemicals. Supplementary Table . Univariate logistic regression results.

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  • Article Type:     Research Article
Keyword(s): Alzheimer's disease; environmental pollutants; machine learning; Methyl-4-hydroxybenzoate; molecular docking; network toxicology

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