Role of exhaled nitric oxide as a predictor of atopy
© Romero et al.; licensee BioMed Central Ltd. 2013
Received: 11 February 2013
Accepted: 26 April 2013
Published: 2 May 2013
The fractional exhaled nitric oxide (FeNO) is a quantitative, noninvasive and safe measure of airways inflammation that may complement the assessment of asthma. Elevations of FeNO have recently been found to correlate with allergic sensitization. Therefore, FeNO may be a useful predictor of atopy in the general population. We sought to determine the diagnostic accuracy of FeNO in predicting atopy in a population-based study.
We conducted a cross-sectional study in an age- and sex- stratified random sample of 13 to 15 year-olds in two communities in Peru. We asked participants about asthma symptoms, environmental exposures and sociodemographics, and underwent spirometry, assessment of FeNO and an allergy skin test. We used multivariable logistic regression to model the odds of atopy as a function of FeNO, and calculated area-under-the-curves (AUC) to determine the diagnostic accuracy of FeNO as a predictor of atopy.
Of 1441 recruited participants, 1119 (83%) completed all evaluations. Mean FeNO was 17.6 ppb (SD=0.6) in atopics and 11.6 ppb (SD=0.8) in non-atopics (p<0.001). In multivariable analyses, a FeNO>20 ppb was associated with an increase in the odds of atopy in non-asthmatics (OR=5.3, 95% CI 3.3 to 8.5) and asthmatics (OR=16.2, 95% CI 3.4 to 77.5). A FeNO>20 ppb was the best predictor for atopy with an AUC of 68% (95% CI 64% to 69%). Stratified by asthma, the AUC was 65% (95% CI 61% to 69%) in non-asthmatics and 82% (95% CI 71% to 91%) in asthmatics.
FeNO had limited accuracy to identify atopy among the general population; however, it may be a useful indicator of atopic phenotype among asthmatics.
KeywordsAllergic sensitization Asthma Exhaled nitric Allergic rhinitis
The fractional exhaled nitric oxide (FeNO) is a non-invasive and sensitive biomarker of ongoing eosinophilic airway inflammation [1, 2]. FeNO may be a useful marker in the assessment of asthma status and control [3, 4]. It has shown potential promise as a non-invasive biomarker for asthma because it is a simple, well tolerated test with no risk to the participant  and it provides real-time, reproducible results in children aged ≥4 years [1–3, 6–9]. For these reasons, FeNO has been recently recommended as a clinical endpoint for the characterization of study populations, in clinical trials and observational studies . Recent studies, however, have reported high levels of FeNO even in well-controlled asthma [1, 6, 11], indicating that other factors may play a role in the determination of FeNO levels [12–15]. One potential factor that could explain variability in FeNO levels is atopic status.
Atopy is a clinical definition for an IgE-antibody responder, i.e., a personal tendency to become sensitized and produce IgE antibodies in response to allergens. Atopic individuals have an increased risk of developing asthma and other allergic diseases . The definition of atopy, however, should only be considered when there is reported sensitization to allergen-specific IgE antibodies in serum or with a positive skin prick test to a specific allergen . Recent studies have reported a strong association between FeNO and atopy [1, 7, 16, 17]. Scott et al. reported a positive correlation between FeNO and the number of positive skin prick tests in a cohort of asthmatics. Previous studies have also correlated aeroallergen sensitization with FeNO levels in atopic children [7, 13, 16, 19, 20]. These findings underscore the relevance of evaluating allergen sensitization status when FeNO is used as a biomarker in the diagnosis and monitoring of asthma . More importantly, it also supports the hypothesis that FeNO may serve as a biomarker of atopy. The fact that atopy cannot always be identified using an allergy skin test , and the underlying risks involved in the determination of allergic skin sensitization increases the importance of studying the validity of FeNO as a simple, non-invasive biomarker for atopy [2, 4, 17].
The presence of a low to normal FeNO level in patients with chronic respiratory symptoms could also be helpful to rule out atopic status [20, 22], however, there is a lack of strong evidence to support the role of FeNO in identifying atopy [2, 5, 11, 23–25]. One recent study by Yao et al. reported that FeNO was a better marker of allergic sensitization than it was of asthma . In this study, we seek to determine the clinical utility of FeNO as a non-invasive marker of atopy in a population-based study.
The study design is described in detail elsewhere . We conducted a cross-sectional study of asthma prevalence in two regions in Peru. In December 2008, we selected a random sample of children aged 13 to 15 years from community censuses and visited them for enrollment into the study between April 2009 and December 2010. We asked participants about asthma and allergy symptoms, sociodemographics and environmental exposures, obtained anthropometry and a blood sample, and conducted an allergy skin test, a FeNO test and spirometry before and after bronchodilators. We used a previously validated Spanish version of the ISAAC questionnaire . This study was approved by the Institutional Review Boards of the Johns Hopkins Bloomberg School of Public Health (Baltimore, USA) and A.B. PRISMA (Lima, Peru).
We measured FeNO using a portable chemiluminescence analyzer (NIOXMINO, Aerocrine, Solna, Sweden) according to joint ERS/ATS recommendations [4, 25]. No assessments were made if a participant reported a respiratory infection in the last 2 weeks or if the participant was on oral corticosteroids. We categorized FeNO levels using cut-off values of <20 ppb, 20-35 ppb and >35 ppb, respectively .
Assessment of atopy
Allergy skin tests were performed using the Multi-Test II system (Lincoln Diagnostics, Decatur, IL) with allergen extracts made by ALK-Abello (Round Rock, TX). We used 10 allergens in the assessment: cockroach (Blattella germanica), dust mite mix (Dermatophagoides farinae and D. pteronyssinus), cat hair, dog epithelium, mouse epithelium, and mixed molds (Alternaria, Cladosporium, mixed Aspergillus, and mixed Penicillium). We also applied a histamine solution (10mg/ml) as a positive control and saline (0.9%) as a negative control. As per manufacturer’s instructions, we recorded vertical and horizontal measurements of induration and erythema, alongside 0–2 scales of itchiness and pseudopodia 20 minutes after application. Atopy was defined as a positive skin response to any of the allergen specificities as previously described [16, 20, 26].
We defined current asthma symptoms as wheeze or use of asthma medications in the past 12 months; allergic rhinitis as nasal symptoms (i.e., rhinorrhea, nasal discharge, nasal obstruction or nasal-ocular pruritus) without cold or flu symptoms in the past 12 months; and, smoking as self-reported tobacco use. We defined allergic symptoms if a child had either asthma symptoms or allergic rhinitis in the past 12 months. We calculated body mass index (BMI) percentile according to World Health Organization reference values . We classified underweight as <5th percentile; normal as 5th to 84th percentiles; overweight as 85th to 94th percentiles, and obese as ≥95th percentile for their age and sex. We defined current inhaled corticosteroid use if the child used it in the last week.
We compared continuous variables between two subgroups with t-tests if normally distributed and with Wilcoxon rank-sum tests if not normally distributed, and compared dichotomous or categorical values between two subgroups with chi-square tests. We used multiple linear regression to identify risk factors associated with log-transformed FeNO in our study population. We used multiple logistic regression to estimate the odds of atopy for FeNO first as a continuous variable and then as a categorical variable using the above defined cut-offs, adjusted for sex, allergy symptoms, BMI, personal history of tobacco use, secondhand smoke, seasonality and site. We excluded current use of inhaled corticosteroids as a covariate because only 2 participants reported such intake. To assess the diagnostic accuracy of FeNO to predict atopy, we constructed receiver-operating-characteristic (ROC) curves and calculated the areas-under-the-curve (AUC) using five-fold cross validation . We also conduced stratified analyses by asthmatic and rhinitis status. We conducted statistical analyses in STATA 11 (STATA Corp., College Station, USA).
Characteristics of the study population
Children with FeNO and atopy data
Children with incomplete data
Male, % (n)
Age, mean (range)
Height in cm, mean (SD)
Current Asthma, % (n)
Allergic rhinitis, % (n)
Rural, % (n)
BMI, mean (range)
21.1 (13.9 – 39.2)
21.8 (15.1 – 36.6)
Secondhand smoke, % (n)
History of tobacco use, % (n)
Factors associated with FeNO
Single variable and multivariable analyses of factors associated with Fractional exhaled nitric oxide (FeNO)
Fractional exhaled nitric oxide in ppb
Geometric mean (SD)
Coefficient in log ppb
Season of FeNO measurement
Personal history of tobacco smoke
Body mass index (kg/m 2 )
Second hand smoke
Predictors of atopy
Multivariable analyses of predictors of atopy in 1199 Peruvian children
Crude Odds ratio
Adjusted Odds Ratio (95% CI)
Fractional exhaled nitric oxide
Season of Fractional exhaled nitric oxide measurement
Body mass index
Second hand smoke
Diagnostic accuracy of FeNO for atopy and asthma
Diagnostic accuracy of Fractional exhaled nitric oxide (FeNO) for atopy
AUC% (95% CI)
FeNO > 20 ppb
FeNO > 25 ppb
FeNO > 35 ppb
By asthma status (FeNO > 20 ppb)
We found that there was gradient between the number of positive reactions and the prevalence of atopy. Specifically, mean FeNO for non-atopics was 14.2 ppb (SD=13.3); 17.0 ppb for atopics with 1 positive reaction (SD=15.4); 29.2 ppb (SD=33.0) for atopics with 2 positive reactions; and, 33.9 ppb (SD=33.6) for atopics with ≥3 positive reactions (p<0.001). The AUC increased from to 67% (95% CI 64% to 71%) to 73% (95% CI 70% to 76%) if we considered atopy in participants with ≥2 positive skin tests. Using similar analytical methods, we evaluated the same three FeNO cut-offs in relation to current asthma symptoms, and found that a FeNO>35 ppb had a AUC of 80% (95% CI 74% to 85%).
Our results suggest that FeNO had a modest ability to identify either atopy alone or asthma alone in our study population; however, our data suggest that it may be a useful aid in differentiating between atopic and non-atopic phenotypes among asthmatic children. We found that a FeNO>20 ppb may have sufficient discriminatory power to identify the asthmatic atopic phenotype.
Our results showed that FeNO had limited accuracy in identifying atopy in the general population. These findings contrast with those reported by Yao et al., who reported a better discrimination of FeNO for allergic sensitization in the general population than that reported by our group (AUC of 80%, 95% CI 77% to 82%). Differences between the study conducted by Yao et al. and our current study could be attributed to the target population and assessment of atopy. Previous studies have described that age contributes to the variability of FeNO [4, 5, 8, 18, 20, 25]. Our study had an older but narrower age range than the study by Yao et al. (5–18 years). Other studies suggest that FeNO may be more useful in young children, who often have no correlation with spirometric assessments or the manifestation of symptoms, but in whom a screening, early diagnosis, and preventive measures would be useful [19, 20]. Other differences included the method of atopic assessment. Yao et al. conducted atopic assessment using the multi-allergen screen for serum specific IgE (e.g. Phadiatop), whereas we used allergy skin testing. Because allergy skin prick testing does not always identify atopy accurately, measurement of a panel of serum specific IgE is the best method to assess atopy. Some studies report a concordance between 85% and 95%, depending on the allergen being tested, between allergy skin testing and measurement of serum specific IgE ; however, it is still unclear if these two tests can be used interchangeably to determine atopic sensitization or if both should be used for the diagnosis of atopy [29–31]. Finally, another difference between both studies were that the study by Yao et al. and ours used different chemiluminescence analyzers for FeNO.
Variables such as sex, current asthma, allergic rhinitis, personal history of tobacco use, current use of inhaled corticosteroids, atopy and seasonality have all been previously identified as important explanatory factors that influence FeNO levels [17, 20, 24, 32]. While our study corroborates the importance of these variables in our study setting, we also found that rural dwelling (i.e., living in Tumbes vs. Lima) was additional important explanatory factor associated with FeNO levels. Indeed, few studies have considered the rural versus urban setting in their analysis or study design, despite well-recognized differences in the prevalence of asthma and allergic disease between these two environments [26, 33, 34]. This is particularly relevant to investigations in low- and middle-income countries, as two recent studies conducted in South America, one in Ecuador  and another conducted by our team in Peru  have shown that urbanization increases the risk of both asthma and allergic diseases. The differences in FeNO levels are explained by the higher prevalence and increased severity of both asthma and atopy in Lima compared to Tumbes . Use of tobacco could impact assessment of FeNO, and if under-reported, could have affected our results. We found an overall low prevalence of daily smokers in previous surveys of tobacco use in our study population. Using a previously-validated, Spanish questionnaires of tobacco smoke in the region, our group reported a low prevalence of daily smoking in adults .
Our findings may help to explain previous inconsistences that other studies have reported when using FeNO levels as a criterion in the diagnosis or management of asthma [6, 8, 12, 15, 22, 23]. We found that FeNO>35 ppb predicted asthma with better accuracy than cutoffs of 20 ppb or 25 ppb. This points to the importance of proper characterization of the atopic phenotype when interpreting the relationship between FeNO and asthma, and also the proper consideration of particular cut-off FeNO values by atopic status, age and sex. Another explanation for previous inconsistences with other studies using FeNO levels could be related to methodology mostly related to flow dependence and the type of device used to measure FeNO. Recently, Malinovschi et al. compared several methods of measuring FeNO and found a better association between asthma control using exhaled breath condensate nitrates rather than with chemiluminescence analyzers for FeNO, which is currently considered the gold standard [25, 36, 37].
Our study has some potential shortcomings. First, our findings are cross-sectional and we do not evaluate longitudinal changes in FeNO values within individuals. Studies have reported different coefficient of variations from 10% (about 4ppb) in healthy individuals to 40% in asthmatics [10–12]. Second, we assessed only at a narrow age range, and predictive cut-offs may change with age. Future investigations should include younger children or cover a broad age range, consider within-individual changes in FeNO levels and assessment of environmental allergenic exposures [10, 21, 25, 34, 37]. Third, we measured atopic sensitization to indoor aeroallergens only and did not include pollen or food allergens.
We chose not to measure pollens because Lima is located in a semi-arid, tropical region where there are few tree and grass allergens. While it is possible that food allergy may affect our overall prevalence of atopy and potentially the values of fractional exhaled nitric oxide ; however, the incidence of food allergies in our study population is unknown and understudied. Fourth, we did not conduct an evaluation of parasitic infections in our study children; however, previous population-based evaluations by our team on the burden of soil-based helminths in our study areas have been previously found to be low . Finally, another aspect to consider is that potential genetic differences may exist between our study sites, which were settled by different ethnic groups; despite that phenotypically, these populations are similar (i.e., mestizo).
In summary, our data suggest that FeNO had modest discriminatory power to identify atopy among the general population. It appeared to be a more useful tool to identify atopic phenotype among asthmatics. If this finding is further validated, FeNO may provide a simple, real-time non-invasive screen for atopy among asthmatics especially in resource-poor countries with limited access to medical specialists.
Other PURA study investigators include: Juan Combe MD (A.B. PRISMA, Lima, Peru), Alfonso Gomez MD (A.B. PRISMA, Lima, Peru), Guillermo Gonzalvez MD (PAHO Lima, Peru), Lilia Cabrera RN (A.B. PRISMA, Lima, Peru), Robert Wise (Johns Hopkins University, Baltimore, USA), Kathleen Barnes PhD (Johns Hopkins University, Baltimore, USA), Patrick Breysse PhD (Johns Hopkins University, Baltimore, USA), D’Ann Williams PhD (Johns Hopkins University, Baltimore, USA).
Area under the curve
Positive predictive value
Negative predictive value
Fractional exhaled nitric oxide
Parts per billion
Receiver operating characteristic.
This study was supported in part by the Johns Hopkins Center for Global Health. Karina Romero was a Fogarty International Center Research Fellow during the conduct of this work (R25TW009340). Nadia Hansel and William Checkley were supported by a R01 grant from the National Institutes of Environmental Health Sciences (R01ES018845). William Checkley was further supported by a Pathway to Independence Award (R00HL096955) from the National Heart, Lung and Blood Institute, National Institutes of Health and by a contract (HHSN268200900033C) with the National Heart, Lung and Blood Institute, National Institutes of Health. Colin Robinson was a Fogarty International Clinical Research Scholar during the time of this work and was further supported by Tufts University School of Medicine. Lauren Baumann was supported by a pre-doctoral NIH T35 Training Grant (T35AI065385). Study sponsors played no role in the study design, data collection, data analysis, data interpretation or the decision to submit the article for publication. Publication of this article was funded in part by the Open Access Promotion Fund of the Johns Hopkins University Libraries.
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