Noninvasive integrative approach applied to children in the context of recent air pollution exposure demonstrates association between fractional exhaled nitric oxide (FeNO) and urinary CC16.

Exposure to the air pollutant particulate matter (PM) is associated with increased risks of respiratory diseases and enhancement of airway inflammation in children. In the context of large scale air pollution studies, it can be challenging to measure fractional exhaled nitric oxide (FeNO) as indicator of lung inflammation. Urinary CC16 (U-CC16) is a potential biomarker of increased lung permeability and toxicity, increasing following short-term PM exposure. The single nucleotide polymorphism (SNP) CC16 G38A (rs3741240) affects CC16 levels and respiratory health. Our study aimed at assessing the use of U-CC16 (incl. CC16 G38A from saliva) as potential alternative for FeNO by investigating their mutual correlation in children exposed to PM. Samples from a small-scale study conducted in 42 children from urban (n = 19) and rural (n = 23) schools examined at two time points, were analysed. When considering recent (lag1) low level exposure to PM as air pollution measurement, we found that U-CC16 was positively associated with FeNO (β = 0.23; 95% CI [-0.01; 0.47]; p = 0.06) in an adjusted analysis using a linear mixed effects model. Further, we observed a positive association between PM and FeNO (β = 0.56; 95% CI [0.02; 1.09]; p = 0.04) and higher FeNO in urban school children as compared to rural school children (β = 0.72; 95% CI [0.12; 1.31]; p = 0.02). Although more investigations are needed, our results suggest that inflammatory responses evidenced by increased FeNO are accompanied by potential increased lung epithelium permeability and injury, evidenced by increased U-CC16. In future large scale studies, where FeNO measurement is less feasible, the integrated analysis of U-CC16 and CC16 G38A, using noninvasive samples, might be a suitable alternative to assess the impact of air pollution exposure on the respiratory health of children, which is critical for policy development at population level.