Abstract Introduction Bronchiectasis is a chronic inflammatory airway disease marked by recurrent infection, leading to a substantial healthcare burden. Among pathogens complicating bronchiectasis, nontuberculous mycobacteria (NTM) are the most frequent in the United States, with infection rates varying by geography and rising particularly in older adults. Not all bronchiectasis patients acquire NTM, and disease manifestations vary widely, suggesting that host factors strongly influence susceptibility and outcomes. However, the mechanisms underlying this variability remain poorly defined. Understanding host-driven immune and metabolic pathways that govern NTM persistence or tolerance could identify novel therapeutic targets beyond antibiotics. This study aimed to integrate plasma proteomics, and cytokine profiling to define host–pathogen interactions in bronchiectasis with and without NTM infection. Methods Patients with bronchiectasis with and without NTM pulmonary infection were prospectively enrolled at the University of Texas Health Science Center at Tyler after informed consent. NTM infection was confirmed by multiple sequential sputum cultures. Plasma proteomics were profiled using Olink’s Proximity Extension Assay (PEA) platform, quantifying approximately 5,400 proteins and compared between NTM-positive and NTM-negative bronchiectasis patients. Cytokines were measured using multiplexed laser bead immunoassays to assess inflammatory and immune signatures associated with NTM infection. LASSO regression and Random Forest modeling was used to identify if shared signatures differentiated the two groups. Results A total of 110 patients were enrolled. NTM pulmonary infection was present in 48.1% (53/110) patients. The majority, 86.7% (46/53) of patients with NTM infection had Mycobacterium avium complex infections and the remaining patients, 13.2%% (7/53), had M. abscessus infection. Using LASSO regression and Random Forest modeling, we identified a shared 20-protein signature that differentiated the two groups.The overlapping features included apolipoproteins (APOA1, APOE), complement and acute-phase proteins (C3, C4A/B, SERPINs), and all three fibrinogen chains (FGA, FGG), reflecting coordinated changes in lipid metabolism, immune activation, and coagulative pathways. Pathway enrichment analysis revealed significant overrepresentation of terms related to epidermal growth factor receptor (EGFR) signaling and interleukin-4 and interleukin-13 signaling, indicating involvement of epithelial repair and type 2 immune pathways in NTM-associated bronchiectasis. This multidimensional “systemic inflammation and lipid–immune interface” signature was reproducibly detected across both linear and nonlinear models. Conclusion A reproducible 20-protein plasma signature involving lipid transport, complement activation, coagulation, and cytokine signaling distinguishes NTM-positive from NTM-negative bronchiectasis. These findings implicate epithelial and type 2 immune pathways as potential contributors to systemic host responses in NTM-associated disease. This abstract is funded by: None
Mcshane et al. (Fri,) studied this question.