Inflammatory and metabolic dysregulation in a murine model of COPD-like lung injury with acute Aspergillus fumigatus challenge

Patients with chronic obstructive pulmonary disease (COPD) are susceptible to Aspergillus-related disease, but associated host-response alterations remain incompletely understood. We conducted an exploratory study in male C57BL/6 mice ( n = 3/group) assigned to control, COPD-like lung injury, acute Aspergillus fumigatus challenge, or combined challenge. COPD-like lung injury was induced by cigarette-smoke exposure and intranasal lipopolysaccharide administration, whereas acute A. fumigatus challenge was established by repeated intranasal inoculation of conidia. Cytokines, secretory IgA (sIgA), MAPK-related transcripts and proteins, histopathology, and lung metabolomes were assessed. The combined-challenge group showed numerically greater changes in inflammatory, mucosal immune, and MAPK-related measures, including higher levels of IL-17, IL-23, and TNF-α and lower levels of IL-10, IFN-γ, and sIgA in lung tissue and oral fluid. Untargeted metabolomics identified alterations involving glycerophospholipid, nucleotide-sugar, and energy-related pathways; ferroptosis-pathway enrichment was observed without assessment of canonical ferroptosis markers. Exploratory two-way ANOVA identified main effects of COPD-like injury and/or fungal challenge for multiple outcomes, but no interaction remained significant after Benjamini–Hochberg correction. Correlations between selected metabolites and inflammatory or MAPK-related markers were exploratory and non-causal. Overall, acute A. fumigatus challenge in mice with COPD-like lung injury was associated with concurrent inflammatory, mucosal immune, MAPK-related, and metabolic alterations. Given the absence of a consistent statistically significant interaction, these group-level differences are interpreted as descriptive and hypothesis-generating rather than evidence of a combined-condition-specific mechanism or causal relationship. Larger studies with adequately powered factorial designs and functional validation are required to determine whether the combined condition induces a distinct biological response.