A Systems Neuroscience Approach Identifies IL1B-CASP3 Signaling as a Molecular Link Between Polystyrene Exposure and Alzheimer's Disease
Gupta, R.; Lakhanpal, S.; Gupta, S.; Kumar, S.
Show abstract
The widespread presence of microplastics and nanoplastics has emerged as a significant environmental concern, with increasing evidence suggesting potential adverse effects on neurological health. However, the molecular mechanisms linking polystyrene exposure to Alzheimers disease (AD) remain poorly understood. In this study, an integrative systems biology framework was employed to investigate the molecular interplay between environmental polystyrene exposure and AD pathogenesis. AD-associated genes were retrieved from the Comparative Toxicogenomics Database (CTD) and DisGeNET, while polystyrene-responsive genes were obtained from CTD. Integration of these datasets identified 16 shared genes potentially connecting polystyrene exposure with AD. Transcriptomic analysis of the hippocampal dataset GSE29378 revealed significant differential expression of several overlapping genes between AD and healthy controls. Functional enrichment analyses demonstrated that these genes are predominantly involved in oxidative stress, inflammatory signaling, apoptosis, and synaptic function, all of which are central to AD pathology. Weighted gene co-expression network analysis (WGCNA) further identified disease-associated modules containing multiple intersecting genes strongly correlated with AD clinical traits. Protein-protein interaction analysis highlighted IL1B, CASP3, BCL2, ACHE, and APOE as key hub genes, indicating their potential roles in integrating environmental stress responses with neurodegenerative pathways. Independent validation using the GSE48350 dataset confirmed the robust diagnostic performance of several hub genes in discriminating AD from control samples. Collectively, these findings suggest that environmental polystyrene exposure may promote AD progression through neuroinflammation, oxidative stress, apoptosis, and synaptic dysfunction, providing novel mechanistic insights and identifying promising molecular targets for future experimental, clinical, and epidemiological investigations.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Subacute Inhalation of Ultrafine Particulate Matter Triggers Inflammation Without Altering Amyloid Beta Load in 5xFAD mice. 95%
- Effects of mixed metal exposures on MRI diffusion features in the medial temporal lobe 93%
- Acute wood smoke exposure is associated with cell-specific hippocampal transcriptomic responses in an accelerated ovarian failure mouse model 92%
Similar papers in this journal
- Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls 93%
- Differential responses of primary neuron-secreted MCP-1 and IL-9 to type 2 diabetes and Alzheimer's disease-associated metabolites 91%
- Lack of pulmonary fibrogenicity and carcinogenicity of titanium dioxide nanoparticles in 26-week inhalation study in rasH2 mouse model 91%
Similar papers in this journal
- Synchrotron XRF imaging reveals manganese accumulation in the Golgi and post-synapses of neurons and enhanced uptake in astrocytes 92%
- A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes 92%
- Metabolic bypass rescues aberrant S-nitrosylation-induced TCA cycle inhibition and synapse loss in Alzheimer's disease human neurons 88%
Similar papers in this journal
- Transcriptomics effects of per- and polyfluorinated alkyl substances in differentiated neuronal cells 92%
- A patient-derived blood-brain barrier model for screening copper bis(thiosemicarbazone) complexes as potential therapeutics in Alzheimer's disease 90%
- An exploratory study of gastrointestinal redox biomarkers in the presymptomatic and symptomatic Tg2576 mouse model of familial Alzheimer's disease - phenotypic correlates and the effects of chronic oral D-galactose 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.