Respiratory biomarkers have the potential to identify airway injury by revealing inflammatory processes within the respiratory tract. Currently, there are no respiratory biomarkers suitable for clinical use to identify patients that warrant further diagnostic work-up, counseling, and treatment for toxic inhalant exposures or chronic airway disease. Using a novel, noninvasive method of sampling the nasal epithelial lining fluid, we aimed to investigate if nasal biomarker patterns could distinguish healthy nonsmoking adults from active smokers and those with chronic upper and lower airway disease in this exploratory study. We compared 28 immune mediators from healthy nonsmoking adults (n = 32), former smokers with COPD (n = 22), chronic rhinosinusitis (CRS) (n = 22), and smoking adults without airway disease (n = 13). Using ANOVA, multinomial logistic regressions, and weighted gene co-expression network analysis (WGCNA), we determined associations between immune mediators and each cohort. Six mediators (IL-7, IL-10, IL-13, IL-12p70, IL-15, and MCP-1) were lower among disease groups compared to healthy controls. Participants with lower levels of IL-10, IL-12p70, IL-13, and MCP-1 in the nasal fluid had a higher odds of being in the COPD or CRS group. The cluster analysis identified groups of mediators that correlated with disease status. Specifically, the cluster of IL-10, IL-12p70, and IL-13, was positively correlated with healthy and negatively correlated with COPD groups, and two clusters were correlated with active smoking. In this exploratory study, we preliminarily identified groups of nasal mucosal mediators that differed by airway disease and smoking status. Future prospective, age-matched studies that control for medication use are needed to validate these patterns and determine if nasosorption has diagnostic utility for upper and lower airway disease or injury.

Background: Sampling of the nasal epithelial lining fluid (NELF) is a potential method to assess exposure to air pollution within the respiratory tract among high risk populations. We investigated associations of short- and long-term particulate matter exposure (PM) and pollution-related metals in the nasal fluid of people with COPD. Methods: This study included 20 participants with moderate-to-severe COPD from a larger study who measured long-term personal exposure to PM2.5 using portable air monitors and short-term PM2.5 and black carbon using in-home samplers for the 7 days preceding nasal fluid collection. Nasal fluid was sampled from both nares by nasosorption, and inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the concentration of metals with major airborne sources. Correlations of selected elements (Fe, Ba, Ni, Pb, V, Zn, Cu) were determined within the nasal fluid. Associations between personal long-term PM2.5 and 7-day home PM2.5 and black carbon (BC) exposure and nasal fluid metal concentrations were determined by linear regression. Results: Within nasal fluid samples, concentrations of vanadium and nickel (r=0.8) and lead and zinc (r=0.7) were correlated. 7-day and long-term PM2.5 exposure were both associated with higher levels of copper, lead, and vanadium in the nasal fluid. BC exposure was associated with higher levels of nickel and vanadium in the nasal fluid. Conclusion: Levels of certain metals in the nasal fluid may serve as biomarkers of air pollution exposure in the upper respiratory tract.