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More than 5% of any population suffers from asthma, and there are indications that these individuals are more sensitive to nanoparticle aerosols than the healthy population. Due to a paucity of data on the molecular-level details and mechanisms involved, we leveraged a realistic air-liquid interface model of inhalation exposure, to investigate global transcriptomic responses in reconstituted three-dimensional airway epithelia of healthy and asthmatic subjects exposed to pristine (nCuO) and carboxylated (nCuOCOOH) copper oxide nanoparticles. A dose-dependent increase in cytotoxicity (highest in asthmatic donor cells) and pro-inflammatory signalling within 24 hours, confirmed the reliability and sensitivity of the system to detect acute inhalation toxicity. Gene expression changes between nanoparticle-exposed versus air-exposed cells were investigated. Hierarchical clustering based on the expression profiles of all differentially expressed genes (DEGs), cell-death-associated DEGs (567 genes) or a subset of 48 highly overlapping DEGs, categorized all samples according to 'exposure severity', wherein nanoparticle surface chemistry and asthma are incorporated into the dose-response axis. For example, asthmatics exposed to low and medium dose nCuO clustered with healthy donor cells exposed to medium and high dose nCuO, respectively. Of note, a set of genes with high relevance to mucociliary clearance, were observed to distinctly differentiate asthmatic and healthy donor cells. These genes also responded differently to nCuO and nCuOCOOH nanoparticles. Additionally, because response to transition metal nanoparticle was a highly enriched Gene Ontology term (FDR 8E-13) from the subset of 48 highly overlapping DEGs, these genes may represent biomarkers to a potentially large variety of metal/metal oxide nanoparticles.

Molecular Signature of Asthma-Enhanced Sensitivity to CuO Nanoparticle Aerosols from 3D Cell Model