Extended exhaled nitric oxide analysis in field surveys of schoolchildren: a pilot test

Longitudinal hierarchical Bayesian models of covariate effects on airway and alveolar nitric oxide

Biomarkers such as exhaled nitric oxide (FeNO), a marker of airway inflammation, have applications in the study of chronic respiratory disease where longitudinal studies of within-participant changes in the biomarker are particularly relevant. A cutting-edge approach to assessing FeNO, called multiple flow FeNO, repeatedly assesses FeNO across a range of expiratory flow rates at a single visit and combines these data with a deterministic model of lower respiratory tract NO to estimate parameters quantifying airway wall and alveolar NO sources. Previous methodological work for multiple flow FeNO has focused on methods for data from a single participant or from cross-sectional studies. Performance of existing ad hoc two-stage methods for longitudinal multiple flow FeNO in cohort or panel studies has not been evaluated. In this paper, we present a novel longitudinal extension to a unified hierarchical Bayesian (L_U_HB) model relating longitudinally assessed multiple flow FeNO to covariates. In several simulation study scenarios, we compare the L_U_HB method to other unified and two-stage frequentist methods. In general, L_U_HB produced unbiased estimates, had good power, and its performance was not sensitive to the magnitude of the association with a covariate and correlations between NO parameters. In an application relating height to longitudinal multiple flow FeNO in schoolchildren without asthma, unified analysis methods estimated positive, statistically significant associations of height with airway and alveolar NO concentrations and negative associations with airway wall diffusivity while estimates from two-stage methods were smaller in magnitude and sometimes non-significant.

Asthma clustering methods: a literature-informed application to the children's health study data

OBJECTIVE

The heterogeneity of asthma has inspired widespread application of statistical clustering algorithms to a variety of datasets for identification of potentially clinically meaningful phenotypes. There has not been a standardized data analysis approach for asthma clustering, which can affect reproducibility and clinical translation of results. Our objective was to identify common and effective data analysis practices in the asthma clustering literature and apply them to data from a Southern California population-based cohort of schoolchildren with asthma.

METHODS

As of January 1, 2020, we reviewed key statistical elements of 77 asthma clustering studies. Guided by the literature, we used 12 input variables and three clustering methods (hierarchical clustering, k-medoids, and latent class analysis) to identify clusters in 598 schoolchildren with asthma from the Southern California Children's Health Study (CHS).

RESULTS

Clusters of children identified by latent class analysis were characterized by exhaled nitric oxide, FEV₁/FVC, FEV₁ percent predicted, asthma control and allergy score; and were predictive of control at two year follow up. Clusters from the other two methods were less clinically remarkable, primarily differentiated by sex and race/ethnicity and less predictive of asthma control over time.

CONCLUSION

Upon review of the asthma phenotyping literature, common approaches of data clustering emerged. When applying these elements to the Children's Health Study data, latent class analysis clusters-represented by exhaled nitric oxide and spirometry measures-had clinical relevance over time.

Impact of different fixed flow sampling protocols on flow-independent exhaled nitric oxide parameter estimates using the Bayesian dynamic two-compartment model

Exhaled nitric oxide (FeNO) is an established respiratory biomarker with clinical applications in the diagnosis and management of asthma. Because FeNO depends strongly on the flow (exhalation) rate, early protocols specified that measurements should be taken when subjects exhaled at a fixed rate of 50 ml/s. Subsequently, multiple flow (or "extended") protocols were introduced which measure FeNO across a range of fixed flow rates, allowing estimation of parameters including Caw NO and CA NO which partition the physiological sources of NO into proximal airway wall tissue and distal alveolar regions (respectively). A recently developed dynamic model of FeNO uses flow-concentration data from the entire exhalation maneuver rather than plateau means, permitting estimation of Caw NO and CA NO from a wide variety of protocols. In this paper, we use a simulation study to compare Caw NO and CA NO estimation from a variety of fixed flow protocols, including: single maneuvers (30, 50,100, or 300 ml/s) and three established multiple maneuver protocols. We quantify the improved precision with multiple maneuvers and the importance of low flow maneuvers in estimating Caw NO. We conclude by applying the dynamic model to FeNO data from 100 participants of the Southern California Children's Health Study, establishing the feasibility of using the dynamic method to reanalyze archived online FeNO data and extract new information on Caw NO and CA NO in situations where these estimates would have been impossible to obtain using traditional steady-state two compartment model estimation methods.

Short-term effects of airport-associated ultrafine particle exposure on lung function and inflammation in adults with asthma

BACKGROUND

Exposure to ultrafine particles (UFP, particles with aerodynamic diameter < 100 nm) is associated with reduced lung function and airway inflammation in individuals with asthma. Recently, elevated UFP number concentrations (PN) from aircraft landing and takeoff activity were identified downwind of the Los Angeles International Airport (LAX) but little is known about the health impacts of airport-related UFP exposure.

METHODS

We conducted a randomized crossover study of 22 non-smoking adults with mild to moderate asthma in Nov-Dec 2014 and May-Jul 2015 to investigate short-term effects of exposure to LAX airport-related UFPs. Participants conducted scripted, mild walking activity on two occasions in public parks inside (exposure) and outside (control) of the high UFP zone. Spirometry, multiple flow exhaled nitric oxide, and circulating inflammatory cytokines were measured before and after exposure. Personal UFP PN and lung deposited surface area (LDSA) and stationary UFP PN, black carbon (BC), particle-bound PAHs (PB-PAH), ozone (O3), carbon dioxide (CO2) and particulate matter (PM2.5) mass were measured. Source apportionment analysis was conducted to distinguish aircraft from roadway traffic related UFP sources. Health models investigated within-subject changes in outcomes as a function of pollutants and source factors.

RESULTS

A high two-hour walking period average contrast of ~34,000 particles·cm-3 was achieved with mean (std) PN concentrations of 53,342 (25,529) and 19,557 (11,131) particles·cm-3 and mean (std) particle size of 28.7 (9.5) and 33.2 (11.5) at the exposure and control site, respectively. Principal components analysis differentiated airport UFPs (PN), roadway traffic (BC, PB-PAH), PM mass (PM2.5, PM10), and secondary photochemistry (O3) sources. A standard deviation increase in the 'Airport UFPs' factor was significantly associated with IL-6, a circulating marker of inflammation (single-pollutant model: 0.21, 95% CI = 0.08-0.34; multi-pollutant model: 0.18, 0.04-0.32). The 'Traffic' factor was significantly associated with lower Forced Expiratory Volume in 1 s (FEV1) (single-pollutant model: -1.52, -2.28 to -0.77) and elevated sTNFrII (single-pollutant model: 36.47; 6.03-66.91; multi-pollutant model: 64.38; 6.30-122.46). No consistent associations were observed with exhaled nitric oxide.

CONCLUSIONS

To our knowledge, our study is the first to demonstrate increased acute systemic inflammation following exposure to airport-related UFPs. Health effects associated with roadway traffic exposure were distinct. This study emphasizes the importance of multi-pollutant measurements and modeling techniques to disentangle sources of UFPs contributing to the complex urban air pollution mixture and to evaluate population health risks.

Bayesian estimation of physiological parameters governing a dynamic two-compartment model of exhaled nitric oxide

The fractional concentration of nitric oxide in exhaled breath (fe_NO) is a biomarker of airway inflammation with applications in clinical asthma management and environmental epidemiology. fe_NO concentration depends on the expiratory flow rate. Standard fe_NO is assessed at 50 mL/sec, but “extended NO analysis” uses fe_NO measured at multiple different flow rates to estimate parameters quantifying proximal and distal sources of NO in the lower respiratory tract. Most approaches to modeling multiple flow fe_NO assume the concentration of NO throughout the airway has achieved a “steady‐state.” In practice, this assumption demands that subjects maintain sustained flow rate exhalations, during which both fe_NO and expiratory flow rate must remain constant, and the fe_NO maneuver is summarized by the average fe_NO concentration and average flow during a small interval. In this work, we drop the steady‐state assumption in the classic two‐compartment model. Instead, we have developed a new parameter estimation approach based on measuring and adjusting for a continuously varying flow rate over the entire fe_NO maneuver. We have developed a Bayesian inference framework for the parameters of the partial differential equation underlying this model. Based on multiple flow fe_NO data from the Southern California Children's Health Study, we use observed and simulated NO concentrations to demonstrate that our approach has reasonable computation time and is consistent with existing steady‐state approaches, while our inferences consistently offer greater precision than current methods.

Traffic-related air pollution and alveolar nitric oxide in southern California children

Mechanisms for the adverse respiratory effects of traffic-related air pollution (TRAP) have yet to be established. We evaluated the acute effects of TRAP exposure on proximal and distal airway inflammation by relating indoor nitric oxide (NO), a marker of TRAP exposure in the indoor microenvironment, to airway and alveolar sources of exhaled nitric oxide (FeNO).FeNO was collected online at four flow rates in 1635 schoolchildren (aged 12-15 years) in southern California (USA) breathing NO-free air. Indoor NO was sampled hourly and linearly interpolated to the time of the FeNO test. Estimated parameters quantifying airway wall diffusivity (DawNO) and flux (J'awNO) and alveolar concentration (CANO) sources of FeNO were related to exposure using linear regression to adjust for potential confounders.We found that TRAP exposure indoors was associated with elevated alveolar NO. A 10 ppb higher indoor NO concentration at the time of the FeNO test was associated with 0.10 ppb higher average CANO (95% CI 0.04-0.16) (equivalent to a 7.1% increase from the mean), 4.0% higher J'awNO (95% CI -2.8-11.3) and 0.2% lower DawNO (95% CI -4.8-4.6).These findings are consistent with an airway response to TRAP exposure that was most marked in the distal airways.

Spirometry effects on conventional and multiple flow exhaled nitric oxide in children

OBJECTIVE

Clinical and research settings often require sequencing multiple respiratory tests in a brief visit. Guidelines recommend measuring the concentration of exhaled nitric oxide (FeNO) before spirometry, but evidence for a spirometry carryover effect on FeNO is mixed. Only one study has investigated spirometry carryover effects on multiple flow FeNO analysis. The objective of this study was to evaluate evidence for carryover effects of recent spirometry on three exhaled NO summary measures: FeNO at 50 ml/s, airway wall NO flux [J'awNO] and alveolar NO concentration [CANO] in a population-based sample of schoolchildren.

METHODS

Participants were 1146 children (191 with asthma), ages 12-15, from the Southern California Children's Health Study who performed spirometry and multiple flow FeNO on the same day. Approximately, half the children performed spirometry first. Multiple linear regression was used to estimate differences in exhaled NO summary measures associated with recent spirometry testing, adjusting for potential confounders.

RESULTS

In the population-based sample, we found no evidence of spirometry carryover effects. However, for children with asthma, there was a suggestion that exhaled NO summary measures assessed ≤6 min after spirometry were lower (FeNO: 25.8% lower, 95% CI: -6.2%, 48.2%; J'awNO: 15.1% lower 95% CI: -26.5%, 43.0%; and CANO 0.43 parts per billion lower, 95% CI: -0.12, 0.98).

CONCLUSIONS

In clinical settings, it is prudent to assess multiple flow FeNO before spirometry. In studies of healthy subjects, it may not be necessary to assess FeNO first.

Estimation of parameters in the two-compartment model for exhaled nitric oxide

The fractional concentration of exhaled nitric oxide (FeNO) is a biomarker of airway inflammation that is being increasingly considered in clinical, occupational, and epidemiological applications ranging from asthma management to the detection of air pollution health effects. FeNO depends strongly on exhalation flow rate. This dependency has allowed for the development of mathematical models whose parameters quantify airway and alveolar compartment contributions to FeNO. Numerous methods have been proposed to estimate these parameters using FeNO measured at multiple flow rates. These methods—which allow for non-invasive assessment of localized airway inflammation—have the potential to provide important insights on inflammatory mechanisms. However, different estimation methods produce different results and a serious barrier to progress in this field is the lack of a single recommended method. With the goal of resolving this methodological problem, we have developed a unifying framework in which to present a comprehensive set of existing and novel statistical methods for estimating parameters in the simple two-compartment model. We compared statistical properties of the estimators in simulation studies and investigated model fit and parameter estimate sensitivity across methods using data from 1507 schoolchildren from the Southern California Children's Health Study, one of the largest multiple flow FeNO studies to date. We recommend a novel nonlinear least squares model with natural log transformation on both sides that produced estimators with good properties, satisfied model assumptions, and fit the Children's Health Study data well.

Multiple-flow exhaled nitric oxide, allergy, and asthma in a population of older children

"Extended" (multiple-flow) measurements of exhaled nitric oxide (FeNO) potentially can distinguish proximal and distal airway inflammation, but have not been evaluated previously in large populations. We performed extended NO testing within a longitudinal study of a school-based population, to relate bronchial flux (J'awNO) and peripheral NO concentration (CalvNO) estimates with respiratory health status determined from questionnaires. We measured FeNO at 30, 50, 100, and 300 ml/sec in 1,640 subjects aged 12-15 from eight communities, then estimated J'awNO and CalvNO from linear and nonlinear regressions of NO output versus flow. J'awNO, as well as FeNO at all flows, showed influences of asthma, allergy, Asian or African ancestry, age, and height (positive), and of weight (negative), generally corroborating past findings. By contrast, CalvNO results were inconsistent across different extended NO regression models, and appeared more sensitive to small measurement artifacts.

CONCLUSIONS

Extended NO testing is feasible in field surveys of young populations. In interpreting results, size, age, and ethnicity require attention, as well as instrumental and environmental artifacts. J'awNO and conventional FeNO provide similar information, probably reflecting proximal airway inflammation. CalvNO may give additional information relevant to peripheral airway, alveolar, or systemic pathology. However, it needs additional research, including testing of populations with independently verifiable peripheral or systemic pathology, to optimize measurement technique and interpretation.

Alveolar concentration and bronchial flux of nitric oxide: two linear modeling methods evaluated in children and adolescents with allergic rhinitis and atopic asthma

OBJECTIVE

Alveolar concentration (C(A)NO) and bronchial flux (J(aw)NO) of nitric oxide (NO) characterize the contributions of peripheral and proximal airways to exhaled NO. Both parameters can be estimated using a two-compartment model if the fraction of NO in orally exhaled air (FE(NO)) is measured at multiple constant expiratory flow rates (V). The aim of this study was to evaluate how departures from linearity influence the estimates of C(A)NO and J(aw)NO obtained with the help of linear regression analysis of the relationships between FE(NO) and 1/V (method P), and between the NO output (V(NO) = FE(NO) × V) and V (method T). Furthermore, differences between patients with atopic asthma (AA) and allergic rhinitis (AR) and between methods P and T were assessed.

DESIGN

Measurements of FE(NO) were performed with a chemiluminiscence analyzer at five levels of V ranging from 50 to 250 ml/sec in school children and adolescents with mild to moderate-severe AA treated by inhaled corticosteroids (N = 42) and AR (N = 20).

RESULTS

Violation of the linearity condition at V ≤ 100 ml/sec caused shifts between methods with regard to the partition of exhaled NO into alveolar (C(A)NO: P > T) and bronchial (J(aw)NO: T > P) components. Both methods gave similar results in the linear range of 150-250 ml/sec: The mean ratios P/T and limits of agreement calculated in AA and AR patients were 1.03 (0.49-1.56) and 1.07 (0.55-1.59) for C(A)NO and 1.03 (0.73-1.33) and 0.99 (0.90-1.10) for J(aw)NO, respectively. No significant differences between AA and AR were found in C(A)NO and J(aw)NO calculated in the linear range by the T method {medians (inter-quartile ranges): 1.7 ppb (0.9-3.9) vs. 2.3 ppb (0.8-3.7), P = 0.91; 1,800 pl/sec (950-3,560) vs. 1,180 pl/sec (639-1,950), P = 0.061}. However, the flow-dependency of the estimates was markedly higher in AA than in AR patients: C(A) NO was decreased 2.8-fold vs. 1.5-fold and J(aw) NO was increased 1.5-fold vs. 1.2-fold in the linear range as compared to the range of 50-250 ml/sec. In both groups, the median standard errors (SE) of the J(aw) NO estimates were similar for the metods P and T and small (<15%) regardless of the range for expiratory flows. The precision of C(A) NO estimates was less in all ranges. For both methods, the SE of the estimates obtained in the range of 150-250 ml/sec exceeded 50% in asthmatics and 30% in AR patients, respectively. The results show that FE(NO) has to be measured at several expiratory flows ≥100 ml/sec for the accurate estimation of C(A) NO and J(aw) NO using linear methods P and T in children and adolescents with AA and AR. A stepwise procedure for detecting nonlinearity and evaluating the quality of FE(NO) measurements is suggested.

Utility of two-compartment models of exhaled nitric oxide in patients with asthma

Two-compartment models provide more precise information about the contribution of the different portions of the airways to exhaled nitric oxide (NO). Airway wall concentration of NO (Caw,NO) and maximum flux of NO in the airways (J'aw,NO) reflect the tissue production rate of NO and they can be modified by corticosteroids. The airway wall diffusing capacity of NO (Daw,NO) depends on diverse physical and anatomical determinants of the airways, such as gas exchange surface area. Daw,NO can be modified by structural and physiological changes that are characteristic of airway remodeling, which take place over the long term. The alveolar concentration of NO (Calv,NO) represents the degree of small airway inflammation. The persistence of high Calv,NO in patients treated with inhaled corticosteroids could reflect the incapacity of these drugs to reach distal locations due to the heterogeneity of the acinar ventilation. In this review, we evaluate the parameters provided by the compartmentalized analysis of exhaled NO that could be useful in characterizing asthma patients.