Article Text

Phenotypic characteristics of asthma and morbidity are associated with distinct longitudinal changes in L-arginine metabolism
  1. Meghan Dolan Althoff1,
  2. Ryan Peterson2,3,
  3. Max McGrath2,3,
  4. Ying Jin2,3,
  5. Hartmut Grasemann4,
  6. Sunita Sharma1,
  7. Alex Federman5,6,
  8. Juan Pablo Wisnivesky5,6 and
  9. Fernando Holguin1
  1. 1Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado - Anschutz Medical Campus, Aurora, Colorado, USA
  2. 2Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
  3. 3Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA
  4. 4Respiratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
  5. 5Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  6. 6Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  1. Correspondence to Dr Fernando Holguin; fernando.holguin{at}


Background The L-arginine metabolome is dysregulated in asthma, though it is not understood how longitudinal changes in L-arginine metabolism differ among asthma phenotypes and relate to disease outcomes.

Objectives To determine the longitudinal associations between phenotypic characteristics with L-arginine metabolites and their relationships with asthma morbidity.

Methods This is a prospective cohort study of 321 patients with asthma followed semiannually for over 18 months with assessments of plasma L-arginine metabolites, asthma control, spirometry, quality of life and exacerbations. Metabolite concentrations and ratios were transformed using the natural logarithm.

Results There were many differences in L-arginine metabolism among asthma phenotypes in the adjusted models. Increasing body mass index was associated with increased asymmetric dimethylarginine (ADMA) and depleted L-citrulline. Latinx was associated with increased metabolism via arginase, with higher L-ornithine, proline and L-ornithine/L-citrulline levels, and was found to have higher L-arginine availability compared with white race. With respect to asthma outcomes, increasing L-citrulline was associated with improved asthma control and increasing L-arginine and L-arginine/ADMA were associated with improved quality of life. Increased variability in L-arginine, L-arginine/ADMA, L-arginine/L-ornithine and L-arginine availability index over 12 months were associated with increased exacerbations, OR 4.70 (95% CI 1.35 to 16.37), OR 8.69 (95% CI 1.98 to 38.08), OR 4.17 (95% CI 1.40 to 12.41) and OR 4.95 (95% CI 1.42 to 17.16), respectively.

Conclusions Our findings suggest that L-arginine metabolism is associated with multiple measures of asthma control and may explain, in part, the relationship between age, race/ethnicity and obesity with asthma outcomes.

  • asthma
  • asthma epidemiology
  • asthma mechanisms

Data availability statement

Data are available on reasonable request.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

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  • Worse asthma severity is associated with increased arginase activity and having lower arginine levels with greater exacerbation risk. In obese late-onset asthmatics, systemic lower L-arginine/asymmetric di-methyl arginine ratios are related to lower lung function, poor asthma-related quality of life and more frequent respiratory symptoms. L-citrulline supplementation can improve asthma control and lung function while augmenting exhaled nitric oxide (NO). From these and other studies, we know that changes in the L-arginine metabolism impact airway NO, lung function and symptoms across different asthma phenotypes.


  • Our understanding of L-arginine metabolism and asthma is limited to cross-sectional studies. This cohort of 321 participants with over 18 months of follow-up and 1019 total observations evaluates, for the first time, the longitudinal association between L-arginine metabolism and asthma morbidity. It shows, among other things, that greater variability in L-arginine metabolism is a strong risk factor for asthma exacerbations.


  • Variability in L-arginine and its metabolic derivatives was not previously recognised as a risk factor for increased asthma morbidity. These results support the therapeutic potential of intervening in this metabolic pathway to improve asthma related outcomes across different clinical phenotypes.


Asthma is a heterogeneous syndrome characterised by reversible airflow obstruction with distinct underlying endotypes, which represent clusters of shared phenotypic characteristics and mechanisms.1 The mechanisms underlying different endotypes are not completely understood.

Alterations in the metabolism of L-arginine, a semiessential amino acid that is metabolised by nitric oxide synthase (NOS) isozymes to L-citrulline and nitric oxide (NO) and via arginase into L-ornithine and urea, have been implicated in asthma pathogenesis. In animal models, airway hyperresponsiveness (AHR) is caused by reduced L-arginine availability, NO deficiency and increased arginase activity.2–4 In humans, L-arginine metabolism via arginase is associated with increased exacerbation rates, obesity and decreased markers of T2 inflammation.2 4–7 However, expression and activity of inducible NOS is associated with eosinophilic inflammation and asthma severity.2–4 8 9 The endogenous NOS inhibitor asymmetric dimethylarginine (ADMA), a product of protein degradation, has been shown to be linked to increased airway tone and decrease fraction of exhaled NO (FeNO),3 10 and was found to correlate with increasing airflow obstruction in asthma patients following an allergic challenge.11 In addition, preliminary clinical studies suggest that increasing the bioavailability of L-arginine for NOS may lead to decreased AHR and less asthma exacerbations.2 9 12

Differences in L-arginine metabolism have been noted across age, sex, race and body weight in both asthma and non-asthma states. For instance, men have been found to have higher FeNO than women in studies of healthy13 and asthma participants.14 Advanced age has been associated with higher ADMA levels in studies of individuals with15 and without asthma.16 17 Studies of L-arginine metabolism and race have revealed conflicting results in populations without asthma with respect to ADMA.18–20 FeNO has been shown to be higher in black compared with white children and adults with asthma, however, results for Latinx patients with asthma have not been consistent across studies.21–23 Finally, obesity, a well-recognised driver of a late-onset, typically low T2 asthma endotype, has been associated with low FeNO and decreased L-arginine/ADMA.24–27

The goal of this study was to test the overarching hypothesis that L-arginine metabolites are longitudinally associated with asthma morbidity and that these associations differ across phenotypic characteristics such as age, sex, race/ethnicity, body mass index (BMI) and T2 inflammation.


This is a prospective cohort study of adult participants with asthma. Participants were recruited from primary care and pulmonary clinics in New York City, New York and Aurora, Colorado with patient catchment areas that are racially and socioeconomically diverse. Inclusion criteria were (1) physician-diagnosed asthma and current use of asthma controller medications, (2) age 21 or older and (3) English-speaking or Spanish-speaking. Participants were excluded if they (1) were diagnosed with chronic obstructive pulmonary disease or other comorbid pulmonary disease, (2) had a greater than 15 pack-year history of smoking or (3) had a diagnosis of dementia. Participants were recruited to ensure balance of obese and non-obese participants and late (>12 years of age) and early asthma onset. Sociodemographic data, and asthma characteristics and medications were collected at baseline interview. Participants underwent anthropomorphic measurements, fasting blood samples, FeNO and spirometry every 6 months for a total of 18 months of follow-up. Past 12-month systemic corticosteroid use was collected at baseline and at the 12-month visit. Data on absolute eosinophil count (AEC) and IgE were obtained from chart review. Recruitment and follow-up visits took place between January 2017 and May 2021.

Patient and public involvement

Patients and the public were not involved in the design, conduct, reporting or dissemination of this research.

Exposure and outcome measurement

L-arginine metabolites were quantified from fasting plasma samples obtained at each study visit using liquid chromatography with tandem mass spectrometry as previously described.27–29 L-arginine metabolites measured were L-arginine, L-citrulline, ADMA, L-ornithine and proline and reported in nanogram per millilitre (ng/mL). Ratios of metabolites were calculated as indirect measurements of enzyme activity (L-arginine/L-citrulline for NOS, L-arginine/ornithine for arginase and L-ornithine/proline for ornithine aminotransferase), approximate NOS impairment (L-arginine/ADMA) and L-arginine availability for NOS (L-ornithine/ L-citrulline). Arginine Available Index (AAI), a marker of overall L-arginine bioavailability, was calculated by dividing L-arginine by the sum of L-citrulline and L-ornithine.

Outcome variables included asthma control, asthma quality of life, forced expiratory volume in 1 s (FEV1) and asthma exacerbations. Asthma control was measured by the Asthma Control Questionnaire (ACQ),30 and quality of life was assessed with the mini-Asthma Quality of Life Questionnaire (AQLQ).31 Airflow limitation was quantified by FEV1 in litres. ACQ, AQLQ and FEV1 were collected at every follow-up visit. Asthma exacerbations were defined as patient-reported use of systemic corticosteroids in the past year (categorised as none, 1, 2, 3+).

Statistical analysis

To assess for L-arginine metabolites and ratio of biomarkers stability within participant over time, we calculated intraclass correlation coefficients (ICC) for each metabolite using random intercept models.

To assess the relationships of participant characteristics and L-arginine metabolites over the study period, we fit a set of linear mixed effects models (LMMs) with fixed effects for relevant covariates and random effects corresponding to individual-specific intercepts and slopes. Each L-arginine metabolite and ratio was modelled separately. Covariates included in models for L-arginine metabolites and asthma morbidity outcomes were selected based on prior knowledge about L-arginine metabolism in asthma and other disease states; age, sex, race/ethnicity (white, black, Hispanic/Latino, further referred to as Latinx and other), baseline BMI in kg/m2 and T2 inflammation. T2 inflammation was dichotomised into high versus low; T2 high was defined as AEC≥300 cells/µL, IgE≥200 or FeNO≥30 parts per billion (ppb) by the highest recorded value since AEC and IgE were not regularly collected at each follow-up visit. Metabolites and ratios were right-skewed and were, therefore, transformed using the natural logarithm prior to subsequent analyses.

To understand the impact of L-arginine metabolite levels on asthma morbidity, we fit random-intercept, random-slope LMMs. For each of our three outcomes, we fit a model with only relevant covariates, and a set of models where each L-arginine metabolite and ratio was added separately to assess for independent effects of each aspect of L-arginine metabolism. To aid interpretability, logged metabolites and ratios were further transformed into z-scores to produce standardised adjusted coefficients which correspond to the expected change in the outcome for a z-score increase in the logged biomarker. In these models, missing L-arginine observations were assumed to be missing completely at random.

Past 12-month rates of asthma exacerbation were assessed at baseline and the 12-month visit; we treated the 12-month measurement as our outcome and controlled for baseline exacerbations and all other relevant predictors for other outcome models as covariates. Under this formulation, there is a single, ordinal outcome per participant, so we used an ordinal logistic regression model. L-arginine metabolite values for each participant were aggregated into individual-specific means and SDs. Similar to our analyses for the other outcomes, we fit a model with only relevant covariates, and a set of models where z-scores pertaining to individuals’ mean and SD of each L-arginine metabolite and ratio was added separately.

All hypothesis tests were performed to generate new insights from this secondary data; therefore, p values have not been adjusted for multiplicity; significant findings should be interpreted as exploratory. Analyses were performed using R V.


Three hundred and twenty-one participants were recruited into this cohort, 188 (58.6%) from New York and 133 (41.4%) from Colorado. There were 1849 potential participants assessed for enrolment, of those 497 were ineligible. The remainder were unable to be contacted or declined participation (online supplemental figure E1). The cohort was predominantly female (81.6%) with significant racial/ethnic diversity, 109 (34.0%) white, 75 (23.4%) black and 99 (30.8%) Latinx. Approximately half of the study population was obese (58.3%), had late-onset asthma (61.4%) and were T2 high (61.7%) (table 1). There was very little current tobacco use with only 8 (2.5%) reporting regular tobacco use in the 3 months prior to study visit, 15 (4.8%) reporting any current smoking and 79 (24.6%) were former smokers. All participants with tobacco use had less than 15 total pack-years of exposure.

Table 1

Description of cohort

Of the 1019 total observations during the study period, there were 256 (25.1%) missing observations for the outcomes (L-arginine metabolites), which includes both those lost to follow-up (36.1% by end of follow-up) and participants who did not provide blood samples at each visit (4.0%, 33.6%, 36.3% and 34.6% at baseline, 6, 12 and 18 months, respectively); these data were assumed to be missing at random.

L-Arginine metabolites over time

Mean values of the L-arginine metabolites and ratios are listed in table 1. Within participants, there was significant variability over the study duration with ICC ranging from 0.113 for L-arginine to 0.396 for proline (table 2). Individual variability can be visualised in spaghetti plots in the supplemental material (online supplemental figures E2 and E3). The population was stratified by baseline obesity, early versus late asthma onset, sex, baseline asthma control and T2 high versus low. ICC’s for the L-arginine metabolites and ratios did not meaningfully change when stratified among baseline characteristics (table 2).

Table 2

Intraclass correlations of L-arginine metabolites and ratios, overall and stratified by baseline demographics

L-Arginine metabolite models and participant characteristics

Phenotypic characteristics including sex, age at study visit, baseline BMI, race/ethnicity, T2 high versus low and a variable to account for time were included in longitudinal models for each L-arginine metabolite and ratio (figure 1, online supplemental tables E1−E10). BMI was positively associated with L-arginine metabolism via arginase, exhibiting positive effect estimates with L-ornithine (effect estimate 0.05 (95% CI 0.01 to 0.08)) and proline levels (0.06 (95% CI 0.02 to 0.10), L-ornithine/L-citrulline ratio (0.11 (95% CI 0.06 to 0.16)) and with NOS inhibition via positive effect estimates for ADMA (0.05 (95% CI 0.03 to 0.07)) and negative effect estimates for L-arginine/ADMA (−0.07 (95% CI −0.10 to –0.03)) and L-citrulline (−0.06 (95% CI −0.11 to –0.02). Black race had the opposite association with NOS inhibition with negative effect estimates for ADMA (−0.07 (95% CI −0.12 to –0.01)) and positive for L-arginine/ADMA (0.15 (95% CI 0.05 to 0.24)).

Figure 1

Association of asthma phenotypic and endotypic markers on L-arginine metabolites and ratios forrest plots of multivariable linear mixed effects models for each L-arginine metabolite and ratio and asthma phenotypic characteristics. The circle represents the effect estimate and the horizontal lines are the 95% CI. ADMA, asymmetric dimethylarginine; BMI, body mass index.

Those identifying as Latinx had higher adjusted levels for L-arginine (0.19 (95% CI 0.11 to 0.27)), AAI (0.11 (95% CI 0.03 to 0.20)) and L-arginine/ADMA ratio, 0.20 (95% CI 0.11 to 0.28) compared with white participants. However, Latinx participants had higher adjusted levels of L-ornithine (0.14 (95% CI 0.06 to 0.22)), proline (0.13 (95% CI 0.03 to 0.22)), L-ornithine/L-citrulline (0.16 (95% CI 0.06 to 0.26)) and L-arginine/L-citrulline (0.21 (95% CI 0.10 to 0.31)), all suggestive of preferred consumption of L-arginine by arginase compared with NOS.

Male participants had higher adjusted levels of proline, 0.19 (95% CI 0.09 to 0.28), and lower adjusted ratios of L-ornithine/proline −0.16 (95% CI −0.25 to –0.06) compared with female participants. Older age by decade was associated with decreased AAI −0.07 (95% CI −0.09 to –0.04), though was associated in increased downstream products of L-arginine metabolism including higher adjusted levels of L-citrulline (0.07 (95% CI 0.04 to 0.10)), L-ornithine (0.09 (95% CI 0.06 to 0.11)), proline (0.05 (95% CI 0.02 to 0.07)), L-ornithine/proline (0.04 (95% CI 0.01 to 0.07)) and lower adjusted levels of L-arginine/ L-citrulline (−0.06 (95% CI −0.09 to –0.02)). Age was also positively associated with ADMA, 0.03 (95% CI 0.01 to 0.14). T2 high inflammation was only found to be associated with increased ADMA 0.06 (95% CI 0.02 to 0.11).

Asthma morbidity

Airflow obstruction

In the base model, age, black, Latinx and other race relative to white were negatively associated with FEV1, and male sex was positively associated with FEV1 (table 3, online supplemental tables E11−E21). Adjusting for these effects, the L-ornithine/proline ratio was positively associated with FEV1, with a slope of 0.03 L per z-score increase in the logged ratio (95% CI 0.00 to 0.06). AAI was negatively associated with FEV1 in the adjusted model −0.03 (95% CI −0.06 to –0.00).

Table 3

Results from linear mixed models for L-arginine metabolites and asthma morbidity and lung function

Asthma control

In the base ACQ multivariable model, all races/ethnic groups were associated with worse control compared with White (table 3, online supplemental tables E22−E32). Adjusting for these effects, L-citrulline was associated with decreasing ACQ score −0.07 per z-score (95% CI −0.14 to –0.00), indicating improved control with higher L-citrulline levels. The other metabolites and ratios were not associated with ACQ.

Asthma quality of life

In the base adjusted model, black, Latinx and other race were associated with lower quality of life compared with white participants (table 3, online supplemental tables E33−43). Age was also associated with decreased AQLQ, whereas male sex was associated with improved AQLQ. Adjusting for these effects, L-arginine and L-arginine/ADMA were each associated with better AQLQ, 0.08 points per z-score (95% CI 0.02 to 0.15) and 0.07 points per z-score (95% CI 0.00 to 0.14), respectively. There was no evidence of effect modification between race and L-arginine metabolites on any of the outcomes (online supplemental tables E44).

Asthma exacerbations

Prior oral corticosteroid use was strongly associated with the odds of exacerbation at the 12-month follow-up visit in a dose dependent manner. Controlling for prior steroid use, we found no evidence of associations in the patient characteristics in the base model (table 4). In adjusted models, a participant’s mean L-arginine/AMDA was associated with a decreased odds of exacerbation, OR 0.28 per z-score (95% CI 0.08 to 0.93) and the SD was associated with an increased odds of exacerbation, OR 8.69 per z-score (95% CI 1.98 to 38.08). This model had the best predictive performance as measured by Akaike’s information criterion compared with the next best model (online supplemental table E45). Adjusting for demographics, markers of increased variability in L-arginine availability, L-arginine SD and AAI SD, were also associated with higher odds of exacerbation, OR 4.70 (95% CI 1.35 to 16.37) and 4.95 (95% CI 1.42 to 17.16), respectively. L-arginine/L-ornithine SD was also positive associated with exacerbation, OR 4.17 (95% CI 1.40 to 12.41). Finally, variability in proline was also associated with a decreased odd of exacerbation, OR 0.14 (95% CI 0.02 to 0.87).

Table 4

Results from multivariable ordinal logistic regression models for asthma exacerbation, effects of individual mean biomarker levels and variation


This large, longitudinal study evaluated L-arginine metabolism among asthma patients over 18 months of follow-up and provides insight into differences in L-arginine metabolism among asthma phenotypes and outcomes (figure 2). The phenotypic differences seen in our study have not been previously evaluated in L-arginine and asthma, including notable racial/ethnic differences. By better understanding these phenotypic differences in L-arginine metabolism, we aim to identify groups that may benefit from intervention of L-arginine metabolism. Finally, the associations between L-arginine metabolite variability and asthma exacerbations raises questions as to the role that L-arginine as a biomarker for exacerbation risk or whether changes in this metabolic pathway influence the development of exacerbations.

Figure 2

Summary of differences in L-arginine metabolism by phenotype characteristics and asthma outcomes upwards arrow indicates statistically significant positive effect estimate or OR greater than 1 in the multivariable model, downward arrow indicates negative effect estimate or OR less than 1. ADMA, asymmetric dimethylarginine; BMI, body mass index; FEV1, forced expiratory volume in 1 s; NO, nitric oxide; NOS, NO synthase; OAT, ornithine aminotransferase; ODC, ornithine decarboxylase; QOL, quality of life.

Prior studies evaluating race/ethnicity and L-arginine/NO metabolism in asthma populations focused on differences in FeNO by race; however, did not account for other markers of T2 inflammation that may affect FeNO or directly measured L-arginine metabolites.21–23 We found decreased ADMA and increased L-arginine/ADMA in Black compared with white participants in our cohort. Similar findings have been demonstrated in a cohort of healthy older adults18 and teachers,19 though in other studies that focused on women, black participants had higher ADMA levels than white participants,20 33 and others have found no racial differences in ADMA levels.34 35 The heterogeneity in these findings may be a function of the underlying population and disease being studied, but likely also reflects that many factors that influence metabolite differences seen between self-reported races.

Among Latinx-identifying participants, there were increased levels of L-arginine and increased global L-arginine availability compared with white participants. Increased L-arginine was associated with increased quality of life, however, this did not appear to attenuate the effect estimate for decreased quality of life among Latinx participants in the adjusted model. One explanation might be that despite the increased L-arginine, Latinx participants appeared to have preferred metabolism via arginase, as seen by increased ornithine, proline, L-arginine/L-citrulline and L-ornithine/L-citrulline ratio. The differences in L-arginine metabolites among racial/ethnic groups is novel and raises additional questions about what is driving these findings. Prior work has found gene–gene interactions between S-nitrosoglutathione reductase and the beta2-adrenergice receptor that increase the risk for asthma among those with Puerto Rican and combined Puerto Rican and Mexican ancestry,36 providing some evidence that there may be genetic differences that are playing a role in the differences we found in NO metabolism. There are well documented racial disparities in asthma that have complex aetiologies.37 A better understanding of whether these metabolite differences are being driven by environmental exposure, including indoor and outdoor air quality, structural neighbourhood differences and dietary differences, among other, genetic differences or a combination many factors will be important in targeting appropriate groups for intervention.

We found that obesity in asthma was associated with increased circulating levels of NOS inhibitor ADMA and decreased L-arginine/ADMA ratio, a marker of NOS impairment,27 as well as decreased L-citrulline, a product of NOS activity. These findings are consistent with other studies of obesity and asthma.9 27 In addition to results concordant with prior work, we also found increasing BMI to be associated with increased metabolism of L-arginine via the arginase pathway as higher BMI was associated with increased levels of L-ornithine and proline, and higher L-ornithine/L-citrulline ratio. Similarly, Asosingh et al found that asthma patients with a genotype associated with high arginase activity and low FeNO had higher BMI’s.4 Our observations are concordant with their findings in a larger cohort and controls for T2 status. Together, these results suggest that those with obesity-associated asthma are more likely to have reduced L-arginine availability and uncoupling of NOS by ADMA inhibition and increased L-arginine metabolism by arginase.

Regulation of NOS activity via consumption of L-arginine by arginase has been previously suspected to lead to different clinical outcomes in asthma and that this difference in metabolic preference may differ by phenotypic characteristics. Arginase activity results in production of L-ornithine, the precursor of proline and polyamines. Proline has been implicated in collagen deposition and possible development of airway remodelling and fixed obstruction, though primarily in animal studies.11 38 39 We found L-ornithine/proline to be positively associated with FEV1 potentially indicating an inverse relationship between FEV1 and proline, which is in concordance with the animal literature, however, it is worth noting that there was no direction relationship between proline levels and FEV1 in our models. As plasma samples serve as biomarkers rather than direct measurements of lung biology, this finding should be further investigated with lower respiratory tract samples.

ADMA can lead to uncoupling of NOS and subsequent formation of reactive oxygen species that contribute to airway inflammation and increased airway tone,3 and lowered L-arginine/ADMA ratio is an accepted marker of NOS impairment. We found increased L-arginine/ADMA associated with increased quality of life, which is consistent with a smaller study done by Holguin et al,27 and higher L-citrulline levels associated with improved asthma control. L-citrulline, product of NOS activity as well as ADMA degradation, can be recycled back into L-arginine and thereby increase substrate availability for NOS, and subsequently NO production. While we have not measured airway NO, a positive effect of L-citrulline was previously observed in obese patients who showed improvement in asthma control and lung function with L-citrulline supplementation,9 consistent with the observed positive association of plasma L-citrulline with improved asthma control in our study.

Finally, global L-arginine availability has been associated with AHR and asthma exacerbation rates, and lower L-arginine levels have been found in patients with asthma than their non-asthma counterparts.2 5 12 Our observation of a positive relationship between L-arginine concentrations and improved quality of life is consistent with previous reports.27 A novel finding of our study is the marked within participant variability of all L-arginine metabolites and ratios over the study period. The blood samples were taken under fasting conditions to minimise the influence of diet on L-arginine levels and ratios were also analysed in models to estimate the availability of substrate and the balance between competing enzymes. One potential explanation for the observed association between asthma exacerbations and variability of metabolite levels and ratios within participants over time is a functional link of the L-arginine metabolism with asthma control. Increased L-arginine bioavailability has been associated with decreased exacerbations in smaller studies,12 however, this is the first study to demonstrate variability in plasma levels of L-arginine and the L-ornithine metabolite proline, as well as indices of L-arginine availability (L-arginine/L-ornithine and AAI) and NOS impairment (L-arginine/ADMA) with exacerbations. One explanation for this relationship is that depleted L-arginine stores may predispose to developing an exacerbation. Alternatively, the development of asthma may lead to increased metabolism of L-arginine by NOS, in an attempt to increase airway NO, or, as Morris et al have shown, increased arginase activity may drive L-arginine depletion in those with asthma.5 Further work is needed to determine the mechanism driving this observed relationship.

There are limitations that are important to consider when interpreting our results. There were missing data due to dropouts during the study. Unfortunately, some visits were to take place in 2020 and had to be cancelled or rescheduled because of research shutdowns related to the COVID-19 pandemic. Though there were minimal differences in baseline variables across the study period among those who completed versus started the study, it is possible that bias was introduced through non-random lost to follow-up during this time and it is difficult to predict how this might have impacted our results. Additionally, there may have been some differential misclassification of T2 status among obese participants as peripheral markers of T2 inflammation may be lower in this group and less predicative of airway eosinophilia.40 In the clinical setting, cut-offs for T2 inflammation are not adjusted for obesity, therefore, we elected to use one definition of T2 inflammation for the entire study population.

It is unclear how strong the correlation between circulating levels of these metabolites with pulmonary L-arginine metabolism measures and whether the relationship between blood and lung makers may be affected by extrapulmonary factors including systemic inflammation.5 A small study compared the metabolome in plasma to exhaled breath condensate and showed moderate correlations between the sample sources.41 Finally, as with all observational studies, there may have been additional confounders we did not measure or included in our analyses, and therefore, our results do not necessarily imply causal effects. The goal of this analysis was to find novel associations between L-arginine metabolites and phenotypic profiles and asthma outcomes, therefore, results should be interpreted as exploratory rather than confirmatory, and additional work is needed to validate these results in other populations.

Despite these limitations, results of this large longitudinal study of L-arginine metabolism in patients with asthma show that differences in L-arginine metabolism track with specific population characteristics. These findings offer insight into potential differences in pathophysiology of asthma among racial/ethnic groups, obesity and age. Additional work is needed to understand what is driving these metabolic differences and identify possible specific interventions such as the use of L-citrulline supplementation in obese asthma patients.


In this prospective cohort study of over 300 asthma patients followed for 18 months, we found several differences in the L-arginine metabolism among important phenotypic characteristics including age, sex, race/ethnicity and BMI. We also found variability in L-arginine availability was associated with an increased odds of asthma exacerbation, indicating a possible role of L-arginine depletion in the setting of exacerbations. These findings support previous work on the role of L-arginine and NO dysregulation in asthma and provide insight into differences in metabolism among asthma phenotypes.

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by Colorado Multiple Institution Review Board 16-1666. Participants gave informed consent to participate in the study before taking part.


Supplementary materials

  • Supplementary Data

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  • Presented at This work was presented at the American Thoracic Society International Conference in San Francisco in May 2022 and the Pittsburg Lung Conference in September 2022.

  • Contributors Contributed to the writing and data analysis: MDA, RP, MM, JY and SS. Contributed to writing, data analysis and study design planning: FH, JPW and AF. Measured L-arginine metabolome and contributed to writing and planning: HG. Guarantor for the overall content: MDA.

  • Funding National Heart, Lung and Blood Institute (grant no. T32 HL007085-46) (MDA); Center for Scientific Review (grant no. R01HL129198-01A1) (FH, JPW and AF); National Institute of General Medical Sciences (grant no. R25GM143298) (MDA).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.