Integrative analysis of chronic low-dose microplastics exposure and major depressive disorder: Combining bioinformatics and molecular docking
- VernacularTitle:微塑料慢性低剂量暴露与重性抑郁障碍的关联机制初探：基于生物信息学和分子对接的整合分析
- Author:
Xiaoxi LIU
1
;
Zhaojun YAN
2
Author Information
- Publication Type:Experiment
- Keywords: microplastic; major depressive disorder; network toxicology; molecular docking; environmental neuropsychiatry
- From: Journal of Environmental and Occupational Medicine 2025;42(12):1520-1530
- CountryChina
- Language:Chinese
- Abstract: Background As global environmental pollutants, chronic low-dose exposure to microplastics (MPs) is increasingly recognized for its potential risks to the nervous system. However, the molecular mechanisms linking MPs to major depressive disorder (MDD) remain unclear. Objective To investigate the mechanistic link between chronic environmentally relevant-dose MPs exposure and MDD using bioinformatics, machine learning, and molecular docking approaches, and to identify key targets and evaluate their diagnostic value. Methods Potential MPs-related targets were retrieved from the Comparative Toxicogenomics Database (CTD). Differentially expressed genes in MDD were identified using the GSE98793 dataset (128 patients and 64 healthy controls, aged 18-75 years) from the Gene Expression Omnibus (GEO). MDD-related targets were integrated from multiple databases and intersected with MPs-related genes to identify common targets. A protein-protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and hub genes were identified via six algorithms in CytoHubba. Immune infiltration analysis was performed using single-sample gene set enrichment analysis (ssGSEA) with the Bindea signature to evaluate 19 immune cell types. A competitive endogenous RNA (ceRNA) network was constructed using multiple databases. Molecular docking was performed using AutoDock Vina to evaluate binding affinities between MPs monomers and hub gene-encoded proteins. A diagnostic model was developed and validated using the GSE76826 late-onset MDD cohort (94 patients and 47 controls, age ≥50 years). Least absolute shrinkage and selection operator (Lasso) regression was applied to identify core genes, followed by single-gene gene set enrichment analysis (SG-GSEA). Results A total of 52 common MPs-MDD targets were identified. Six key genes, namely interleukin-1β (IL1B), tumor necrosis factor (TNF), interleukin 6 (IL6), peroxisome proliferator-activated receptor gamma (PPARG), catenin beta 1 (CTNNB1), and chemokine ligand 2 (CCL2), were identified and found to be enriched in neuroinflammatory responses, lipid metabolism disorders, and the Wnt/β-catenin signaling pathway. Construction of the ceRNA network revealed that 32 microRNAs (miRNAs) and 27 circular RNAs (circRNAs) had regulatory relationships with these key genes. The immune infiltration analysis showed increased peripheral eosinophils and decreased Th17 cells in MDD patients (P < 0.05). The results of molecular docking demonstrated stable binding between bisphenol A (BPA) and PPARG (ΔG=–5.82 kcal·mol−1), and between styrene and IL6 (ΔG=–5.61 kcal·mol−1). The diagnostic model showed excellent performance for PPARG in late-onset MDD (AUC=0.942, 95%CI: 0.899, 1.000), with a combined model AUC of 0.954 (95%CI: 0.862, 1.000). The Lasso regression model further identified CCL2 and PPARG as core regulatory genes of MPs-MDD. The SG-GSEA indicated that CCL2 was associated with immune-inflammatory pathways and mitochondrial dysfunction, while PPARG was linked to neuroplasticity and proteostasis. Conclusion Chronic low-dose MPs exposure may contribute to MDD pathogenesis through a multidimensional "immune-metabolic-neural" regulatory network. CCL2 and PPARG may serve as potential biomarkers for environmentally associated MDD, providing new molecular insights into the link between environmental pollution and neuropsychiatric disorders.
