A Novel Approach to Partition Central and Peripheral Airway Nitric Oxide

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1 CHEST A Novel Approach to Partition Central and Peripheral Airway Nitric Oxide Paolo Paredi, MD, PhD ; Sergei A. Kharitonov, MD, PhD ; Sally Meah, RGN ; Peter J. Barnes, DM, DSc, Master FCCP ; and Omar S. Usmani, MBBS, PhD Original Research ALLERGY AND AIRWAY Background: Determining the site of airways inflammation may lead to the targeting of therapy. Nitric oxide (NO) is a biomarker of airway inflammation and can be measured at multiple exhalation flow rates to allow partitioning into bronchial (large/central airway maximal nitric oxide flux [J aw NO] ) and peripheral (peripheral/small airway/alveolar nitric oxide concentration [C ANO ]) airway contributions by linear regression. This requires a minimum of three exhalations. We developed a simple and practical method to partition NO. Methods: In 29 healthy subjects (FEV 1, 97% 3% predicted), 13 patients with asthma (FEV 1, 90% 4% predicted), 14 patients with COPD (FEV 1, 59% 3% predicted), and 12 patients with cystic fibrosis (CF) (FEV 1, 60% 3% predicted), we measured the area under the curve of the NO concentration/exhalation time plot (AUC-NO) at exhalation flow rates of 50, 100, 200, and 300 ml/s. We determined the change of the total AUC-NO production ( AUC-NO) among the four different exhalation flow rates and compared these levels to C ANO and J aw NO indices measured conventionally by linear regression. Results: The change in AUC-NO between increasing exhalation flow rates of 50 to 200 ml/s ( AUC-NO ) was strongly correlated with J aw NO in all patient groups as follows: healthy subjects ( r , P,.001), patients with asthma ( r , P,.001), patients with COPD ( r , P,.001), and patients with CF ( r , P,.05). In all subjects, AUC-NO at an exhalation flow rate of 200 ml/s (AUC-NO 200 ) correlated with C ANO ( r , P,.01). Conclusions: The bronchial production of NO can be determined by measuring AUC-NO , whereas AUC-NO 200 measures its peripheral concentration. This approach is simple, quick, and does not require sophisticated equipment or mathematical models. CHEST 2014; 145(1): Abbreviations: AUC 5 area under the curve; AUC-NO 5 area under the curve of the nitric oxide concentration/exhalation time plot; C ano 5 peripheral/small airway/alveolar nitric oxide concentration; CF 5 cystic fibrosis; F eno 5 fraction of exhaled nitric oxide; J aw no 5 large/central airway maximal nitric oxide flux; NO 5 nitric oxide; ppb 5 parts per billion Nitric oxide (NO) is a biomarker of airways inflammation and an adjunct in the diagnosis and management of respiratory diseases such as asthma, 1-4 a s approved by the Food and Drug Administration. 5 The single exhalation breath measurement of NO (fraction of exhaled NO [F eno ]) is simple, reproducible, and noninvasive, and most notably, the methodology for Manuscript received April 24, 2013; revision accepted July 8, Affiliations: From the Airways Disease Section, National Heart and Lung Institute, Imperial College London and Royal Brompton Hospital, London, England. Funding/Support: Dr Usmani is a recipient of a UK National Institute for Health Research (NIHR) Career Development Fellowship. This project was supported by the NIHR Respiratory Disease Biomedical Research Unit at the Royal Brompton & Harefield NHS Foundation Trust and Imperial College London. its detection has been standardized. 6 Currently, there is immense interest in assessing the predominant site of airways inflammation (peripheral vs central) in various pulmonary diseases, and this may be important in targeting antiinflammatory therapy. 7-9 This interest has encouraged the development of mathematical models to interpret the flow-dependent physiology of NO dynamics, 10,11 and the measurement of exhaled NO at different exhalation flow rates has Correspondence to: Paolo Paredi, MD, PhD, Airways Disease Section, National Heart and Lung Institute, Dovehouse St, London, SW3 6LY, England; p.paredi@imperial.ac.uk 2014 American College of Chest Physicians. Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details. DOI: /chest journal.publications.chestnet.org CHEST / 145 / 1 / JANUARY

2 been used to partition peripheral (peripheral/small airway/alveolar NO concentration [C ano]) from central (large/central airway maximal NO flux [J aw no]) airways NO production. The latter technique is based on a two-compartment model, 10 which contrary to the single-compartment model, accounts for the production and contribution of central airways NO, explaining the exhalation flow dependency of this gas. 11 This approach requires a minimum of three exhalation flows, and both J aw no and Cano are calculated by a linear regression analysis. This technique has been used to show elevated J aw no in patients with mild to moderate asthma 10 and C ano in patients with refractory asthma, 12 older healthy subjects, 13 patients with COPD, 14 patients with cystic fibrosis (CF), 15 and patients with scleroderma. 16 We revisited and simplified the method for NO partitioning from the two-compartment model to show that the complicated mathematical equations used in the linear regression method could be replaced with the measurement of the area under the curve (AUC) of the NO concentration/exhalation time plot (AUC-NO) obtained at one slow (50 ml/s) and one fast (200 ml/s) patient exhalation flow. In addition, we compared this new technique with a method described by Condorelli et al, 17 which takes into account the axial back diffusion of bronchial NO into the alveolar space. Patients Materials and Methods Twenty-nine healthy volunteers (20 men; mean age, 38 2 years; FEV 1, 97% 3% predicted) were enrolled in the study ( Table 1 ). We also studied 13 steroid-naive patients with asthma (eight men; mean age, 48 8 years; FEV 1, 90% 4% predicted) whose condition was diagnosed according to American Thoracic Society criteria18 ; 14 patients with COPD (10 men; mean age, 63 2 years; FEV 1, 59% 3% predicted), all ex-smokers with a 20-pack-year smoking history and without a history of allergic disease or reversibility of airflow obstruction (. 15% or. 200 ml after 400 mg salbutamol through a metered-dose inhaler); and 12 patients with CF (eight men; mean age, 21 4 years; FEV 1, 60% 3% predicted). The study was approved by the local research ethics committee (reference number 08/H0709/2). Patients with a respiratory tract infection or respiratory disease exacerbation were excluded from the study. Active and passive smokers (exposure for. 0.5 h/d) were excluded. Exhaled NO Measurement Multiple Flows Linear Regression Method: Exhaled NO concentrations were measured by a chemiluminescence analyzer (NIOX; Aerocrine) at expiratory flow rates of 50, 100, 200, and 300 ml/s by applying resistances of 50, 100, 200, and 300 cm H 2 O/mL/s to maintain the target exhalation flow rates. Patients inhaled NO-free air and exhaled through a fixed flow restriction to increase pressure in the mouth up to 10 cm H 2 O, which is effective in closing the soft palate and isolating the nasopharynx. Dead space air was excluded from the analysis. The analyzer was calibrated with a known NO concentration (200 parts/million). Every subject performed two exhalations at each exhalation flow. The bronchial production of NO (J aw no ) and its alveolar concentration (C ano ) were calculated by linear regression according to the equation of Tsoukias and George, 10 where the slope and the intercept of the regression line between NO output and exhalation flow indicates C ano and J awno, respectively. In addition, J aw no and C ano were also calculated using the Condorelli adjustment for the axial diffusion of NO as follows 17 : J aw no ( I ) and C ano 5 [( S ) 2 (I )]/(740 ml/s), where S is the slope and I is the y-intercept by simple linear regression. Dual Flows Measurement by AUC Method: The database containing the measurements of C ano and J aw no calculated by the linear regression method was downloaded from the NO analyzer and transferred to a computer. For each expiratory flow rate (50, 100, 200, and 300 ml/s), the point-by-point values of the NO concentrations were plotted graphically against the exhalation time (up to 10 s) ( Fig 1 ). The AUC-NO was calculated by the average of two measurements at each expiratory flow rate with Prism version 5.03 (GraphPad Software, Inc) ( Fig 1 ). The software calculated the AUC by the trapezoidal method. This process was straightforward and took, 1 min to compute. We then studied the change in the AUC-NO between increasing exhalation flow rates of 50 to 100 ml/s ( DAUC-NO ), 50 to 200 ml/s ( DAUC-NO ), and 50 to 300 ml/s ( DAUC-NO ). We compared the average AUC-NO values with the J aw no and C ano values calculated by conventional linear regression and with values calculated by the Condorelli adjustment method with the same data as described previously. Lung Function Tests All patients underwent pulmonary function testing. Testing included spirometry and lung volumes by body plethysmography (Jaeger Master Laboratory Compact Transfer; Erich Jaeger Ltd). Statistical Analysis Comparisons between patient groups were made by one-way analysis of variance with Bonferroni correction. Kruskal-Wallis one-way analysis of variance was used to analyze nonparametric data. Correlations are presented as nonparametric Spearman rank correlation coefficients. Data were expressed as mean SEM and CIs of differences. Significance was defined as P,.05. Agreement between methods was confirmed with Bland-Altman plots. Results Single-Breath F ENO and Linear Regression Method F eno was significantly elevated in patients with asthma ( parts per billion [ppb], P,.01), whereas it was significantly reduced in patients with CF ( ppb, P,.01) compared with healthy subjects ( ppb). Patients with COPD ( ppb) had similar levels to those of the healthy subjects ( Fig 2A ). J aw no was significantly elevated in patients with asthma ( ng/s, P,.01) but significantly reduced in patients with CF ( ng/s, P,.05) compared with healthy subjects ( ng/s). Patients with COPD had comparable values to the healthy subjects ( ng/s, P..05) (Fig 2B ). 114 Original Research

3 Table 1 Patient Characteristics Characteristic Asthma (n 5 13) COPD (n 5 14) CF (n 5 12) Healthy Subjects (n 5 29) Age, y Male (female) sex 8 (5) 10 (4) 8 (4) 20 (9) FEV 1, % predicted F eno, ppb J aw no, ng/s a b C ano, ppb a b a J aw no /DAUC-NO correlation C ano /AUC200 correlation Data are presented as mean SEM or R 2 unless otherwise indicated. AUC area under the curve of the nitric oxide concentration/exhalation time plot at a high exhalation flow rate of 200 ml/s; AUC-NO area under the curve of the nitric oxide concentration/exhala tion time plot between exhalation flow rates of 50 to 200 ml/s; C ano 5 peripheral/small airway/alveolar nitric oxide concentration; CF 5 cystic fibrosis; F eno 5 fraction of exhaled nitric oxide; J aw no 5 large/central airway maximal nitric oxide flux; ppb 5 parts per billion. a P,.01. b P,.05. Similarly, Cano was significantly higher in patients with asthma ( ppb, P,.01) and significantly lower in patients with CF ( ppb, P 5.01) compared with healthy subjects ( ppb). However, in contrast to the J aw no results, C ano was significantly elevated in patients with COPD ( ppb, P,.05) (Fig 2C ). Dual Flow Rates Measurement With AUC Method Patients with asthma consistently showed significantly elevated AUC-NO values at every exhalation flow rate (50, 100, 200, and 300 ml/s) compared with healthy subjects, whereas patients with CF had significantly lower AUC-NO values at all exhalation flow rates ( Fig 3 ). The AUC-NO values of the patients with COPD were similar to those of healthy subjects at 50, 100, and 200 ml/s but were significantly higher at exhalation flow rates of 300 ml/s. There was far greater variability in the AUC-NO measurements for patients with asthma compared with the other groups. An exhalation flow rate dependency of AUC-NO was observed in all groups, especially in patients with asthma, who had the greatest fall in the AUC-NO values with increasing exhalation flows compared with all other groups ( Figs 3, 4 ). The decrease in AUC-NO in patients with CF was significantly lower than in healthy subjects, whereas patients with COPD had a similar magnitude of AUC-NO change to healthy subjects ( Fig 4 ). Additionally, the observation of the fall in AUC-NO was also consistent among all exhalation flow comparisons ( D AUC-NO , D AUC-NO , and DAUC-NO ) in all groups. J aw NO Agreement With AUC-NO AUC-NO was significantly correlated with J aw no as measured by linear regression in healthy subjects ( r , P,.001) ( Table 1 ), patients with asthma ( R , P,.001), patients with COPD ( R , P,.001), and patients with CF ( R , P,.001 ). These agreements were also confirmed by Bland-Altman plot 17 ( Fig 5A ). The same strong correlations between J aw no and D AUC-NO were consistent after J aw no correction for axial diffusion of NO. 17 Figure 1. A, Exhaled NO/time tracings at flow rates of 50 ml/s in healthy subjects and all study groups. B, An example of the AUCs calculated at flow rates of 50 and 200 ml/s to provide AUC AUC 5 area under the curve; AUC change in the area under the curve between increasing exhalation flow rates of 50 to 200 ml/s; CF 5 cystic fibrosis; NO 5 nitric oxide; ppb 5 parts per billion. journal.publications.chestnet.org CHEST / 145 / 1 / JANUARY

4 Figure 2. A-C, F E NO levels (A), bronchial production (J awno) (B), and alveolar concentrations (CANO) (C) in healthy subjects ( ) and patients with COPD ( ), CF ( ), and asthma ( ). CANO 5 peripheral/small airway/alveolar nitric oxide concentration; F E NO 5 fraction of exhaled nitric oxide; J awno 5 large/central airway maximal nitric oxide flux. See Figure 1 legend for expansion of other abbreviations. C ANO Agreement With AUC-NO Not surprising, DAUC-NO was not significantly correlated with C ano in any of the study groups except in the patients with asthma, where a positive correlation was observed ( R , P,.05). However, AUC-NO at a high exhalation flow rate of 200 ml/s (AUC-NO 200 ) was significantly correlated with C ano measured by linear regression in patients with asthma ( R , P,.001) and COPD ( R , P,.05). The same strong correlations between C ano and AUC-NO 200 were consistent after correction for axial diffusion of NO 17 ( R [ P,.001] vs r [ P,.01] in patients with asthma vs COPD, respectively) and for all the subjects together ( R , P,.01). This agreement was confirmed by Bland-Altman plot (Fig 5B ). Reproducibility of AUC-NO The difference in the AUC-NO values measured during two successive exhalations (n 5 15) at 5-min intervals (single-session variability) was 5.4%, whereas the between-session variability (n 5 16) at a 1-day interval was 6.8%. The reproducibility of the test was confirmed by Bland-Altman plot. 22 Discussion This study shows that the bronchial production of NO and its alveolar concentration can be calculated by a novel method that measures the changes in AUC-NO values resulting from exhalations at slow and fast flow rates. The results agree with J aw no and C ano estimated conventionally by a linear regression equation. The advantage of the present method is that it does not require sophisticated calculations and specific software and may allow wider application of these measurements within the academic community. NO is a promising noninvasive biomarker of airway inflammation for many pulmonary conditions. 1,2,4 NO Figure 3. AUC-NO shown at increasing exhalation flow rates (50, 100, 200, and 300 ml/s) in healthy subjects ( ) and in patients with COPD ( ), CF ( l ), and asthma ( ). * P,.05; ** P,.01. AUC-NO 5 area under the curve of the nitric oxide concentration/exhalation time plot. See Figure 1 legend for expansion of other abbreviations. Figure 4. DAUC in healthy subjects ( ) and patients with COPD ( ), CF ( ), and asthma ( ). See Figure 1 legend for expansion of abbreviations. 116 Original Research

5 Figure 5. A, Bland-Altman plot showing agreement between the bronchial production of nitric oxide (J awno) and the AUC method ( DAUC-NO ). B, The agreement between CANO and AUC-NO AUC-NO change in the AUC-NO between increasing exhalation flow rates of 50 to 200 ml/s; AUC-NO AUC-NO at a high exhalation flow rate of 200 ml/s. See Figure 1, 2, and 3 legends for expansion of other abbreviations. exhibits flow-rate dependency such that it can be partitioned into that produced from peripheral (C ano ) and central (J aw no ) airways, allowing identification of where in the pulmonary tree the inflammation is more active 11 in various pulmonary disorders. 12,23-26 Thus, models to interpret NO dynamics have been developed. The one-compartment model took into account only the lung periphery as a source of NO 27 without explaining the exhalation flow dependency of exhaled NO. 28,29 On the contrary, the two-compartment model acknowledged the central airways as a source of NO. 10 Because the two-compartment technique is the most used model, it is considered by most as the gold standard and was chosen for comparison in the current study. However, this model oversimplifies the human lung by describing the millions of alveoli and respiratory bronchioles as a single huge alveolus and the branching bronchial tree as a single rigid tube. 10 This oversimplification assumes that NO parameters are not affected by lung volume changes during the respiratory cycle. In addition, even if the possible error related to NO axial diffusion has been addressed and the technique has been previously simplified, 17 the violation of the linearity condition, particularly at lower expiratory flow rates, has been shown to cause an overestimation of C ano and an underestimation of J aw no in children, 30 contributing to the reluctance to use NO clinically. 31,32 We developed a simplified method that requires only two patient exhalations and the calculation of the AUC of the respective NO concentration/time tracings, and we compared these results with the J aw no and C ano obtained by linear regression equation.10 The measurement of AUC-NO requires only two pairs of exhalations at 50 and 200 ml/s for a total of four measurements, whereas the conventional linear regression requires at least three exhalations at three different flows, totaling nine measurements. This halves the time required to complete the test. Because the present method is based on the direct analysis of the AUC-NO tracings, it is not limited by the assumptions that characterize the mathematical models described previously. 16 In keeping with previous reports, we observed that F eno was elevated in patients with asthma 33 and reduced in patients with CF 34 compared with healthy control subjects. In patients with COPD, F eno is more controversial 35 and was confirmed not to be elevated in the current study. The partitioning of peripheral and bronchial NO was also consistent with previous publications that showed elevated J aw no in patients with asthma 36 and C ano in patients with COPD. 14 Previous studies in patients with CF produced inconsistent results. We found both C ano and J aw no to be reduced in the present CF cohort compared with healthy subjects, which is consistent with a defect in inducible NO synthase expression in CF. 37 AUC-NO levels were elevated in patients with asthma and reduced in patients with CF compared with healthy subjects at every exhalation flow. Patients with COPD showed similar AUC-NO levels to healthy subjects. These results are in keeping with the F eno levels measured in this study because AUC-NO reflects mostly central airway production. With increasing exhalation flows, we noted a progressive decrease in AUC-NO levels in all study groups, but the extent of the reduction in the AUC-NO values among the different exhalation flows was significantly greater in patients with asthma. In contrast, the change in AUC-NO levels with successively increasing exhalation flows was the lowest in patients with CF, whereas healthy subjects and patients with COPD demonstrated a similar extent of change in AUC-NO levels journal.publications.chestnet.org CHEST / 145 / 1 / JANUARY

6 among the different exhalation flows. Because these changes can be affected by the NO output in the conductive airways, the results may be interpreted as a reflection of increased NO production in patients with asthma in contrast to patients with CF. This implication is confirmed by the strong correlation in all subject groups between DAUC-NO and the conventionally calculated J aw no. In contrast to the other study groups, patients with asthma showed a significant, albeit weaker, correlation between DAUC-NO and C ano, and this may have resulted from a greater axial diffusion of higher bronchial NO production in asthma. We also observed that AUC-NO 200 correlated with C ano measured with the linear regression method. Although we acknowledge that the correlation between C ano and AUC-NO 200 was weaker, it was still highly significant, particularly in asthma ( P,.001). When exhaled at high flow rates, NO levels are derived mostly from the lung periphery because alveolar air has little time to be conditioned by NO produced in the central airways, whereas at lower exhalation flow rates, there is more time for NO to condition alveolar air, and the final NO levels may reflect NO produced more proximally in the bronchi. Therefore, we propose that to partition the bronchial and peripheral component of NO, only a slow (50 ml/s) and a fast (200 ml/s) exhalation flow are required. The DAUC-NO will reflect the bronchial production of NO as it correlates with J aw no, whereas the absolute AUC-NO 200 will reflect peripheral NO concentrations as they correlate with C ano. Conclusions This simpler and more patient-friendly method for the partitioning of exhaled NO can be applied in different groups of patients with pulmonary disease. The direct point-by-point measurement takes into account parallel compartments and sequential filling of the alveoli, potentially reducing the limitations associated with the conventional method. Further studies may support the growing evidence that the partitioning of exhaled NO may complement the measurement of total F eno. Clinical studies investigating the AUC in patients with different degrees of airway obstruction are also required, and we believe that the use of the present method will simplify these studies. Acknowledgments Author contributions: Dr Paredi had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr Paredi: contributed to the study design; data analysis; and writing, editing, and final approval of the manuscript. Dr Kharitonov: contributed to the study concept and design and writing, editing, and final approval of the manuscript. Ms Meah: contributed to the study design, recruitment of patients, NO measurements, and reading and final approval of the manuscript. Dr Barnes: contributed to the study concept and design and writing, editing, and final approval of the manuscript. Dr Usmani: contributed to the study design and supervision, data analysis, and writing and final approval of the manuscript. Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr Usmani has received honoraria related to advisory board membership (Zentiva Group, Aerocrine), consultancy (Takeda Pharmaceutical Company Limited, Novartis Corporation, GlaxoSmithKline, Pieris AG), and lectures (Takeda Pharmaceutical Company Limited, Chiesi Ltd) and is involved in research for which his university has received industry grant funding (Prosonix Ltd, AstraZeneca, Takeda Pharmaceutical Company Limited, Chiesi Ltd). Drs Paredi, Kharitonov, and Barnes and Ms Meah have reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article. Role of sponsors: The sponsors had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript. References 1. Barnes PJ, Dweik RA, Gelb AF, et al. Exhaled nitric oxide in pulmonary diseases: a comprehensive review. Chest ; 138 (3): Lim KG, Mottram C. The use of fraction of exhaled nitric oxide in pulmonary practice. Chest ;133(5): Malerba M, Ragnoli B, Radaeli A, Tantucci C. Usefulness of exhaled nitric oxide and sputum eosinophils in the long-term control of eosinophilic asthma. Chest ;134(4): Paredi P, Kharitonov SA, Barnes PJ. Analysis of expired air for oxidation products. Am J Respir Crit Care Med ; 166(12 pt 2):S31-S Silkoff PE, Carlson M, Bourke T, Katial R, Ogren E, Szefler SJ. 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