NOS2 as a candidate molecular link between air pollutants and depression: an integrated computational and experimental study

Introduction Studies exploring the molecules and potential mechanisms linking air pollution exposure to depression remain scarce. This study aimed to elucidate the potential regulatory molecules and possible mechanisms associated with air pollutants and depression, thereby providing scientific clues for disease prevention and treatment. Methods Seven air pollutants (SO 2 , NO, benzene, CO, O 3 , NO 2 , and toluene) were included. A multilevel research framework was employed. Network toxicology and the Gene Expression Omnibus (GEO) database were used to identify potential targets and pathways of air pollutants; intersection genes were used to construct machine learning diagnostic models, and the optimal model was selected for validation. Mendelian randomization (MR) was applied to assess the genetic causal association between depression and relevant genes. Single-cell virtual perturbation was performed for network perturbation analysis to dissect potential molecular mechanisms. Molecular docking and molecular dynamics simulations were used to evaluate the binding affinity and complex stability between specific pollutants and depression-related genes. Finally, in vitro cell experiments were conducted to preliminarily validate the computational findings. Results By intersecting air pollution-related targets with the Gene Expression Omnibus depression dataset, nine candidate target genes were identified. Ensemble machine learning analysis suggested that nitric oxide synthase 2 (NOS2) showed expression in depression. Mendelian randomization analysis suggested that elevated NOS2 expression may be associated with depression, supporting a possible genetic causal association between the two. Single-cell virtual perturbation suggested that perturbing NOS2 in microglia could affect inflammation- and oxidative stress-related pathways. Molecular docking predicted that all seven pollutants might bind to NOS2, but the predicted binding energies varied, with benzene and toluene showing relatively higher binding affinity. Molecular dynamics simulations further evaluated the stability of the benzene–and toluene–NOS2 complexes, suggesting that toluene binding to NOS2 was more stable. In vitro cell experiments preliminarily suggested that toluene exposure could induce inflammation and oxidative stress in BV2 cells, and changes in NOS2 expression may be involved in this process. However, these results cannot yet prove that NOS2 is a causal mediator of depression, and further functional experiments are needed for validation. Discussion Integrating computational prediction, genetic association, network perturbation, and cellular validation, NOS2 may be a candidate molecular node linking air pollution exposure to depression, and its potential mechanism may involve neuroinflammation and oxidative stress. This study provides new hypotheses and theoretical clues for the possible molecular mechanisms linking air pollutants and depression, but the underlying mechanisms still require further experimental investigation.

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Journal
Frontiers in Cell and Developmental Biology
Published
2026-10-28
DOI
https://doi.org/10.3389/fcell.2026.1962251
Primary Topic
Air Quality and Health Impacts
Type
article
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article

NOS2 as a candidate molecular link between air pollutants and depression: an integrated computational and experimental study

Jingning Du, Shengyu Cai, Liyuan Su, Bei Yin et al.
7 links
Frontiers in Cell and Developmental Biology
Air Quality and Health Impacts
article

NOS2 as a candidate molecular link between air pollutants and depression: an integrated computational and experimental study

Jingning Du, Shengyu Cai, Liyuan Su, Bei Yin, Siwei Zhang, Huizheng Zhu
article en

Abstract

Introduction Studies exploring the molecules and potential mechanisms linking air pollution exposure to depression remain scarce. This study aimed to elucidate the potential regulatory molecules and possible mechanisms associated with air pollutants and depression, thereby providing scientific clues for disease prevention and treatment. Methods Seven air pollutants (SO 2 , NO, benzene, CO, O 3 , NO 2 , and toluene) were included. A multilevel research framework was employed. Network toxicology and the Gene Expression Omnibus (GEO) database were used to identify potential targets and pathways of air pollutants; intersection genes were used to construct machine learning diagnostic models, and the optimal model was selected for validation. Mendelian randomization (MR) was applied to assess the genetic causal association between depression and relevant genes. Single-cell virtual perturbation was performed for network perturbation analysis to dissect potential molecular mechanisms. Molecular docking and molecular dynamics simulations were used to evaluate the binding affinity and complex stability between specific pollutants and depression-related genes. Finally, in vitro cell experiments were conducted to preliminarily validate the computational findings. Results By intersecting air pollution-related targets with the Gene Expression Omnibus depression dataset, nine candidate target genes were identified. Ensemble machine learning analysis suggested that nitric oxide synthase 2 (NOS2) showed expression in depression. Mendelian randomization analysis suggested that elevated NOS2 expression may be associated with depression, supporting a possible genetic causal association between the two. Single-cell virtual perturbation suggested that perturbing NOS2 in microglia could affect inflammation- and oxidative stress-related pathways. Molecular docking predicted that all seven pollutants might bind to NOS2, but the predicted binding energies varied, with benzene and toluene showing relatively higher binding affinity. Molecular dynamics simulations further evaluated the stability of the benzene–and toluene–NOS2 complexes, suggesting that toluene binding to NOS2 was more stable. In vitro cell experiments preliminarily suggested that toluene exposure could induce inflammation and oxidative stress in BV2 cells, and changes in NOS2 expression may be involved in this process. However, these results cannot yet prove that NOS2 is a causal mediator of depression, and further functional experiments are needed for validation. Discussion Integrating computational prediction, genetic association, network perturbation, and cellular validation, NOS2 may be a candidate molecular node linking air pollution exposure to depression, and its potential mechanism may involve neuroinflammation and oxidative stress. This study provides new hypotheses and theoretical clues for the possible molecular mechanisms linking air pollutants and depression, but the underlying mechanisms still require further experimental investigation.

Frontiers in Cell and Developmental BiologyVol. 14
Jinan University (CN), Southern University of Science and Technology (CN), ShenZhen People’s Hospital (CN)
Good health and well-being
Openalex Percentile: Top 18%
Air Quality and Health Impacts
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