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

Dietary and metabolic nitrate is distributed from the blood to the saliva by active uptake in the salivary glands, and is reduced to nitrite in the oral cavity by the action of certain bacteria. Since it has been reported that nitric oxide may be formed nonenzymatically from nitrite this study aimed to determine whether salivary nitrite could influence measurements of exhaled NO.Ten healthy subjects fasted overnight and ingested 400 mg potassium nitrate, equivalent to~200 g spinach. Exhaled NO and nasal NO were regularly measured with a chemiluminescence technique up to 3 h after the ingestion. Measurements of exhaled NO were performed with a single-breath procedure, standardized to a 20-s exhalation, at a flow of 0.15 L . s -1 , and oral pressure of 8±10 cmH 2 O. Values of NO were registered as NO release rate (pmol . s -1 ) during the plateau of exhalation.Exhaled NO increased steadily over time after nitrate load and a maximum was seen at 120 min (77.0 15.2 versus 31.2 3.0 pmol . s -1 , p<0.01), whereas no increase was detected in nasal NO levels. Salivary nitrite concentrations increased in parallel; at 120 min there was a four-fold increase compared with baseline (1.56 0.44 versus 0.37 0.09 mM, p<0.05). The nitrite-reducing conditions in the oral cavity were also manipulated by the use of different mouthwash procedures. The antibacterial agent chlorhexidine acetate (0.2%) decreased NO release by almost 50% (p<0.01) 90 min after nitrate loading and reduced the preload control levels by close to 30% (p<0.05). Sodium bicarbonate (10%) also reduced exhaled NO levels, but to a somewhat lesser extent than chlorhexidine acetate.In conclusion, salivary nitric oxide formation contributes to nitric oxide in exhaled air and a large intake of nitrate-rich foods before the investigation might be misinterpreted as an elevated inflammatory activity in the airways. This potential source of error and the means for avoiding it should be considered in the development of a future standardized method for measurements of exhaled nitric oxide. Eur Respir J 1999; 13: 327±333. In recent years there has been much interest in measurements of nitric oxide in exhaled air, since increased levels of NO were discovered in exhaled air of asthmatics [1] and enzymatically produced NO was suggested as a marker of inflammation in the respiratory tract [2,3]. However, several factors, such as mixing of NO originally produced in the paranasal sinuses, and variations in the degree of pressure and flow of the exhaled air, have been shown to influence and complicate the measurements [4]. These problems have created a need for a standardized method and a few articles have been published for methodological guidance [3,5]. Furthermore, a novel pathway of nonenzymatic NO production via chemical reduction of nitrite has recently been described [6,7] and this might complicate the methodological approach even further.A variable amount of nitrite, a potential substrate for NO formation, is found in the saliva as a product of nitrate reduction. Th...

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,

Increased levels of exhaled carbon monoxide (fractional concentration of CO in expired gas (FE,CO)), measured with an electrochemical sensor, have been reported in patients with inflammatory airway disorders, such as asthma, rhinitis and cystic fibrosis. This study aimed to evaluate these findings by using a fast-response nondisperse infrared (NDIR) analyser, and to compare these measurements with the fractional concentration of nitric oxide in exhaled air (FE,NO). Thirty-two steroid-naïve asthmatics, 24 steroid-treated asthmatics (16 patients with allergic rhinitis, nine patients with cystic fibrosis), and 30 nonsmoking healthy controls were included. CO measurements with the NDIR analyser were performed simultaneously with nitric oxide (NO) analysis (chemiluminescence technique). After 15 s of breath-hold, single-breath exhalations over 10 s were performed at two flow rates and end-tidal plateau concentrations were registered. An electrochemical CO sensor was used independently with an exhalation to residual volume, after a 15 s breath-hold. None of the two CO analysers gave a significant increase in FE,CO in the groups of patients with inflammatory airway disorders compared to controls. FE,NO was significantly elevated in steroid-naïve asthmatics and subjects with allergic rhinitis, but not in steroid-treated asthmatics and subjects with cystic fibrosis. Reducing exhalation flow rate by 50% gave a two-fold increase in FE,NO, while FE,CO was unaffected. A significant increase was seen in FE.CO, but not in FE,NO, when comparing with and without a 10 s breath-hold. In conclusion, the fractional concentration of carbon monoxide in expired gas was not increased in any of the patient groups, while the fractional concentration of nitric oxide in expired gas was significantly elevated in patients with steroid-naïve asthma and allergic rhinitis. Moreover, carbon monoxide was unaffected by flow rate but increased with breath-hold, suggesting an origin in the alveoli rather than the conducting airways.

Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms.