Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.

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U-BIOPRED cohort n=91 epithelial brushings or biopsies IL-17 High Clinical phenotype Nasal polyps Smoking Antibiotic use Epithelial Gene Expression Profile Clinical phenotype FeNO Exacerbations Gene expression shared with psoriasis IDO1 IL1B DEFB4B S100A8, S100A9 PI3 CXCL3, CXCL8 CXCL10, CCL20 Gene signature SERPINB2 POSTN CLCA1 IL-13 High T cell infiltration Neutrophilia Eosinophilia IL-17-high asthma with features of a psoriasis immunophenotype From a the Respiratory,

A sensor array based on heterojunctions between semiconducting organic layers and single walled carbon nanotube (SWCNT) films was produced to explore applications in breathomics, the molecular analysis of exhaled breath. The array was exposed to gas/volatiles relevant to specific diseases (ammonia, ethanol, acetone, 2-propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). Then, to evaluate its capability to operate with real relevant biological samples the array was exposed to human breath exhaled from healthy subjects. Finally, to provide a proof of concept of its diagnostic potential, the array was exposed to exhaled breath samples collected from subjects with chronic obstructive pulmonary disease (COPD), an airway chronic inflammatory disease not yet investigated with CNT-based sensor arrays, and the results were compared to those from of healthy subjects breathprints. Principal component analysis showed that the sensor array was able to detect various target gas/volatiles with a clear fingerprint on a 2D subspace, was suitable for breath profiling in exhaled human breath, and was able to distinguish subjects with COPD from healthy subjects based on their breathprints. This classification ability was further improved by selecting the most responsive sensors to nitrogen dioxide, which has been proposed as a biomarker of COPD.