Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Oct 1.
Published in final edited form as: J Allergy Clin Immunol. 2022 Mar 15;150(4):965–971.e8. doi: 10.1016/j.jaci.2022.02.026

Lipid mediators are detectable in the nasal epithelium and differ by asthma status in females

Randi K Johnson 1, Jonathan Manke 2, Monica Campbell 1, Michael Armstrong 2, Meher Preethi Boorgula 1, Gabriela Pinheiro 3, Cinthia Vila Nova Santana 3, Rasika A Mathias 4, Kathleen C Barnes 1, Alvaro Cruz 3, Nichole Reisdorph 2, Camila A Figueiredo 3,5
PMCID: PMC9475490  NIHMSID: NIHMS1789135  PMID: 35304161

Abstract

Background:

Lipid mediators, bioactive products of polyunsaturated fatty acid metabolism, contribute to inflammation initiation and resolution in allergic diseases; however, their presence in lung-related biosamples has not been fully described.

Objective:

We aimed to quantify lipid mediators in the nasal airway epithelium and characterize preliminary associations with asthma.

Methods:

Using liquid chromatography mass-spectrometry, we conducted a pilot study to quantify 56 lipid mediators from nasal epithelial samples collected from 11 female participants of an outpatient asthma clinic and community controls (aged 30–55 years). We examined the presence of each compound using descriptive statistics to test whether lipid mediators could distinguish asthma (n=8) from control subjects (n=3) using linear regression and partial least squares-discriminant analysis (PLS-DA). For detailed Methods, please see this article’s Online Repository at www.jacionline.org.

Results:

Fifteen lipid mediators were detectable in all samples, including Resolvin D5 (RVD5), with the highest median concentrations (in pg per μg protein) of 13-HODE (126.481), 15-HETE (32.869), and 13-OxoODE (13.251). From linear regression adjusted for age, prostaglandin E2 (PGE2) had a trend (p<0.1) for higher concentrations in severe asthma cases compared to controls (mean difference = 0.95, 95%CI: −0.04–1.95). Asthma cases had higher scores on principal component 3 compared to controls (mean difference = 2.42, 95%CI: 0.89–3.96), which represented lower levels of pro-resolving 15-HEPE, 19, 20-DiHDPA, RVD5, 14-HDHA, 17-HDHA, and 13-HOTrE. Most of these compounds were most influential in discriminating asthma cases from controls in PLS-DA.

Conclusion:

Lipid mediators are detectable in the nasal epithelium and their levels distinguish asthma cases from controls.

Clinical Trial Registration

NA

Keywords: Lipids, asthma, nasal airway epithelium, pro-resolving lipids, oxylipins, resolvins, PUFAs, EPA, DHA, AA

Capsule Summary

We described lipid mediator concentrations in the nasal epithelium and identified combinations of pro-resolving molecules that discriminate asthma cases from controls. Measurement of these compounds in this tissue is feasible for larger asthma studies.

INTRODUCTION

A growing body of literature supports the role of bioactive lipids in the pathogenesis and severity of asthma, including both pro- and anti-inflammatory products from the metabolism of polyunsaturated fatty acids (PUFAs) such as eicosapentaenoic acid (EPA), docosahexaenoic (DHA) acid, and arachidonic acid (AA). AA produces several pro-inflammatory bioactive lipids, including leukotrienes (LTs) and prostaglandins (PGs), that contribute both to the initiation of inflammation and chronic inflammation in lung diseases, including asthma severity and exacerbation (1, 2). Similarly, isoprostanes, which are products of AA peroxidation have been implicated in asthma exacerbation (3) and significant lipid peroxidation occurs in children with severe asthma (4). An additional consequence of upregulated oxidative stress response involves the generation and liberation of bioactive lipids, including PGs, LTs and pro-resolving lipoxins (LX). Conversely, both EPA and DHA can be metabolized to produce pro-resolving lipids (called specialized pro-resolving mediators; SPMs) (5) that promote resolution of inflammation in many tissues (6, 7) and may be protective against the pathogenesis of asthma (8, 9). Resolvins (Rv), DHA metabolites, are anti-inflammatory, enhance phagocytosis, and are reduced in severe asthma (10–13).

While the mechanistic roles and therapeutic potential of bioactive lipids continue to be explored in asthma and allergic disease, one major roadblock remains the detection of bioactive lipids in accessible biospecimens representative of the lung. For example, while some groups have reported the presence of resolvins in plasma or serum, this has been the subject of some controversy (14). Therefore, we aimed to quantify and characterize lipid mediators in the nasal epithelium, an established proxy of lower airway tissues for other molecular markers including DNA methylation (15) and gene expression (16). In this pilot study, we investigated 56 lipid mediators in nasal epithelial samples collected from 11 female participants of clinical studies from The Program for Control of Asthma in Bahia (ProAR), Salvador, Brazil (17). We aimed to establish the presence and concentrations of various lipid mediators in the nasal epithelium and to characterize preliminary associations with asthma and asthma severity.

RESULTS AND DISCUSSION

We randomly selected 11 ProAR participants with nasal airway epithelial samples collected as part of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA), including three non-atopic non-asthma controls, four atopic cases with mild to moderate asthma (MMA), and four atopic cases with severe asthma (SA) (see Methods in the Online Repository). Asthma was defined using the criteria of the Global Initiative against Asthma (GINA, 2006). Atopy was determined using ImmunoCAP technology, and defined as having a Phadiatop level ≥ 0.35 kU/L. All participants were female, with an average age of 40 years at sample collection (range: 30–55 years, Table E1 in the Online Repository). A panel of 56 bioactive lipid mediators were quantified (in pg per ug of protein) from nasal epithelial cells using well-established liquid chromatography mass-spectrometry methods at the Mass Spectrometry Core Facility in the University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences (18–20) (see Methods in the Online Repository).

Fifteen of the 56 lipid mediators were detectable at or above the limit of quantification (LOQ) in all 11 samples (Figure 1), including: 15-HETE, 5,15-DiHETE, 12-HHTrE, PGE2, PGF2alpha isomers, and 8-HETE derived from AA; 13-HOTrE derived from alpha-linolenic acid (ALA); 15-HETrE derived from dihomo-gamma-linolenic acid (DGLA); 14-HDHA, 17-HDHA, 11-HDoHE and RVD5 derived from DHA; and 13-HODE, 13-OxoODE, and 9,10-DiHOME derived from linoleic (LA) (see Table E2 in the Online Repository for compound annotations). Among these, 13-HODE, 15-HETE, and 13-OxoODE were present in the highest concentrations in the nasal epithelium with median concentrations (in pg per μg protein) of 126.481, 32.869, and 13.251, respectively. An additional eight compounds were detectable at or above the LOQ in at least eight samples and were therefore included in analyses.

Figure 1: Lipid mediator array content and detection performance in nasal epithelium by parent fatty acid precursor and asthma severity group.

Figure 1:

Open in a new tab

Detectable levels defined as sample analyte levels at or above the limit of quantitation (LOQ). Precursor fatty acid abbreviations: AA=arachidonic acid; ALA=alpha-linolenic acid; DGLA=dihomo-gamma-linolenic acid; EPA=eicosapentaenoic acid; LA=linolenic acid.

In descriptive analysis, three compounds showed a trend for a linear relationship between concentration and asthma severity group, including 13-HODE, PGE2, and RVD5 (Figure 2). Only 9,10 DiHOME levels were significantly different across the three groups (p <0.05, Kruskal-Wallis Test), with the lowest levels among severe asthmatics. While many of these lipid mediators have been previously detected and quantified in urine (21), plasma (20), and tissues more proximal to the lung (22), the detection of DHA-derived metabolite RVD5 has, to our knowledge, only been detected in cerebral spinal and synovial fluids (23). In addition, reported measurements of RVD1 in serum and plasma may be due to differences in technical methods, including the use of internal standards and stringency in applying qualifying ions (14, 18, 23). RVD5 acts by the activation DRV1, the D-series Resolvin receptor 1 expressed on human neutrophils, lymphocytes, monocyte-macrophages, as well as in vascular tissues (vascular smooth muscle cells and endothelial cells) (24). RVD5 has reported roles in infection and the immune system and, notably, inhibits inflammatory pain in male, but not female mice (23).

Figure 2: Distribution by asthma status of the 15 lipid mediators with complete quantification in the nasal epithelium.

Figure 2:

Open in a new tab

MMA = Mild/Moderate Asthma, SA = Severe Asthma

We tested for differences between asthma groups using multivariable linear models adjusted for age. A separate regression was performed for each lipid mediator quantified in at least eight samples (m=23) and the top three principal components (PCs) of those 23 compounds. Despite small sample size, we identified prostaglandin E2 (PGE2) with a trend (p<0.1) for higher concentrations in severe asthma cases compared to controls (mean difference = 0.95, 95%CI: −0.0–1.95). A similar trend has been previously described in sputum, where the higher PGE2 levels found in severe and moderate asthma subjects compared to controls were thought to reflect ongoing anti-inflammatory response (22). In addition to its classical pro-inflammatory effects, the AA metabolite PGE2 also has been shown to prevent allergen-induced airway bronchoconstriction, hyperresponsiveness, and inflammation (25).

We also identified significant differences between groups (p<0.05) for scores on PC3 (Figure 3). Asthma cases had higher scores on PC3 compared to controls (mean difference = 2.42, 95%CI: 0.89–3.96). Results were similar comparing the severe asthma (mean difference = 2.25, 95%CI: 0.42–4.07) or mild/moderate asthma (mean difference = 2.63, 95%CI: 0.75–4.51) to controls. Higher scores on PC3 reflected higher concentrations of 13-OxoODE, RVD1, LXA4 Isomers, TXB2, and LXB4, and lower concentrations of 15-HEPE, 19, 20-DiHDPA, 13-HOTrE, RVD5, 14-HDHA, 17-HDHA, 11-HDoHE, and 8-HETE, and as determined by PC loadings more extreme than ± 0.2 (see Figure E2 in the Online Repository). Many of the compounds displaying strong negative correlations with PC3 scores (i.e. those with loadings < −0.2) have pro-resolving activity and are derived from the anti-inflammatory precursor fatty acids EPA (15-HEPE), DHA (19, 20-DiHDPA, RVD5, 14-HDHA, 17-HDHA, 11-HDoHE), and ALA (13-HOTrE). The mean difference of these lipids was similar whether comparing SA/MMA or asthma (any) to controls (Figure 3), suggesting the results were not driven by exposure to inhaled corticosteroids definitional to the severe asthma group. While the PC loadings for compounds such as 13-OxoODE were consistent with bivariate and linear regression results, the relationship of this compound with asthma status seems more important when considered in context of other metabolites (in multivariate PC analysis) than independently. Multivariate analyses, such as these, that consider multiple analytes simultaneously may better reflect biological systems and could provide novel insights into underlying processes.

Figure 3: Mean lipid mediator differences between asthma case compared to controls, and asthma severity group compared to controls.

Figure 3:

Open in a new tab

Results from two multivariable linear regression models adjusted for age, grouped by precursor/parent fatty acid. Mild/Moderate Asthma = MMA, Severe Asthma = SA. Precursor fatty acid abbreviations: AA=arachidonic acid; ALA=alpha-linolenic acid; DGLA=dihomo-gamma-linolenic acid; EPA=eicosapentaenoic acid; LA=linolenic acid.

We also tested whether multivariate profiles of lipid mediators could discriminate asthma cases and controls using partial least squares-discriminant analysis (PLS-DA). Asthma controls and cases were modestly separated by component 1 (Figure 4A). The loadings plot (Figure 4B) shows compounds with the highest contributions to separation between case and control groups in component 1, which include RVD5, 19,20-DiHDPA, 13-HOTrE, 14-HDHA, 11-HDoHE, 15-HEPE, 17-HDHA, PGE2, 12-HHTrE, and TXB2—many of these same compounds contributed to PC3.

Figure 4: Multivariate PLS-DA results for discrimination of asthma cases and controls by 23 quantitative lipids and age.

Figure 4:

Open in a new tab

A) Discrimination of the n=3 controls and n=8 asthma cases by component one and two. B) PLS-DA loadings.

In this pilot study, we achieved detection and quantification of lipid mediators derived from precursor fatty acids AA, ALA, DGLA, EPA, DPA, DHA, and LA in the nasal epithelium. Despite small sample size, we found preliminary evidence that asthma cases had higher levels of PGE2 and lower levels of a combination of certain pro-resolving compounds (15-HEPE, 19, 20-DiHDPA, 13-HOTrE, RVD5, 14-HDHA, 17-HDHA, 11-HDoHE, and 8-HETE) compared to controls. Given the growing evidence base that bioactive lipids contribute to the pathogenesis and severity of asthma combined with the inability to detect some of these compounds in plasma and serum, these novel data establish a baseline and rationale for their measurement in this accessible tissue for larger asthma and allergy studies.

METHODS

Study Population and Case Definitions

The Program for Control of Asthma in Bahia (ProAR) is a clinical study of asthma in Salvador, Brazil (1). The ProAR study population comprises 3 groups: (i) severe asthma (SA) required a combination of LABA and regular inhaled corticosteroids (according to standard definition at the time the clinic was initiated in 2003); (ii) milder forms of asthma (MA) receiving no regular treatment and only as-needed bronchodilators; and (iii) a control group with no asthma. In 2013, a 2-fold case control study was selected from the ProAR cohort, in which 473 SA subjects, 452 MA subjects and 454 no asthma controls were evaluated (all unrelated), to investigate risk factors, endophenotypes and biomarkers of severe asthma (2). All asthmatics previously underwent an evaluation by a specialist to confirm diagnosis using the criteria of the Global Initiative against Asthma (3) and exclude conditions that could interfere in the evaluation of asthma control, followed by a thorough evaluation (2013–2019).

For determination of atopy, blood samples were sent to the Dermatology, Allergy and Clinical Immunology (DACI) Laboratory at The Johns Hopkins Asthma and Allergy Center. Using the UniCap 250 system (Pharmacia and Upjohn), the DACI Laboratory performed Phadia ImmunoCAP® blood tests to detect allergen-specific IgE against several aeroallergens, including food (FP5E), mite-roach (HX2), animal dander (EX2), weed (WX1), grass (GX2), tree (TX3 and RTX10), and mold (MX2). Subjects with Phadiatop level ≥ 0.35 kU/L were considered as “atopic”.

For this pilot study, we selected 11 female participants with atopic severe asthma (SA, n=4), atopic mild/moderate asthma (MMA, n=4) and non-asthmatic non-atopic controls (controls, n=3).

Lung Function

Spirometry was performed using Koko® Spirometer (Ferraris Medical, USA) for measurement of FEV1, FVC and FEV1/FVC ratio before and 15 minutes after inhaling 400 mcg of bronchodilator (salbutamol), as recommended by the American Thoracic Society/European Respiratory Society (ATS/ERS) (4, 5). Airway obstruction was assessed as FEV1/FVC ratio lower than lower limit of normal (LLN) and FEV1 bronchodilator responsiveness was determined by the increase in FEV1 post-bronchodilator less than 12 % and 200 ml (4) using spirometric reference equations developed for Brazilian adults (6).

Nasal Airway Epithelium Sample Collection

Lipids were measured from the nasal epithelial cells collected as previously described by our group (7). Briefly, after the inspection of the patient’s nostrils with an otoscope, the brush was inserted through the nose and it was rolled for ~4 seconds. The brush was removed and placed into a tube with 400 uL of PBS solution. The tube was closed and agitated for a few seconds and then it was centrifuged for 3 min 800 ×g. The supernatant was removed and the pellet was resuspended with 100 uL of methanol 70%. It was stored in a −80°C freezer until the shipment to University of Colorado, Denver, US for sample processing.

Oxylipin Sample Preparation

All standards and internal standards used for LC/MS/MS analysis of arachidonic acid, docosahexaenoic acid and linoleic acid derived lipid mediators were purchased from Cayman Chemical (Ann Arbor, Michigan, USA). All HPLC solvents and extraction solvents were HPLC grade or better.

Nasal brush cell suspension samples were pretreated for solid phase extraction. Briefly, cells were lysed by diluting samples to a 70%methanol, 1%ethanol solution by adding 700ul methanol, 10ul of the internal standard solution (10pg/ul each of 5(S)-HETE-d8, 8-iso-PGF2a-d4, 9(S)-HODE-d4, LTB4-d4, LTD4-d5, LTE4-d5, PGE2-d4, PGF2a-d9 and RvD2-d5 in ethanol) and sufficient water to create 1ml of solution. The samples were then centrifuged for 10 minutes at 4C at 14,000 RPM. The sample supernatant was then dried in a vacuum centrifuge at 55°C until dry and then immediately reconstituted in 1.0ml of 90:10 water:methanol before purification by solid phase extraction (SPE). Sample cell pellets were tested for protein content by Pierce BCA assay and analyzed using a SpectraMax190 (Molecular Devices, LLC. San Jose, California).

SPMs from cells were isolated and purified using SPE as follows. The reconstituted extracts were loaded on a Strata-X 33um 30mg/1ml SPE column (Phenomenex, Torrance, California, USA) preconditioned with 2 volumes of 1.0ml methanol followed by 2 volumes of 1.0ml. The SPE column was then washed with 10% methanol and then eluted directly into a reduced surface activity/maximum recovery glass autosampler vial with 1.0ml of methyl formate. The methyl formate was evaporated completely from the vial with a stream of nitrogen and then the SPE cartridge was then eluted with 1.0ml of methanol directly into the same autosampler vial. The methanol was evaporated to dryness with a stream of nitrogen and then the sample was reconstituted with 20ul of ethanol. The samples are analyzed immediately or frozen at −70C until analysis.

Liquid Chromatography-Mass Spectrometry

Quantitation of lipid mediators was performed using 2-dimensional reverse phase HPLC tandem mass spectrometry (LC/MS/MS) following previously described protocols that optimize accuracy and precision (8). The HPLC system consisted of an Agilent 1290 autosampler (Agilent Technologies, Santa Clara, CA), an Agilent 1200 binary SL loading pump (pump 1), an Agilent 1290 binary analytical pump (pump 2) and a 6 port switching valve. Pump 1 buffers consisted of 0.1% formic acid in water (solvent A) and 9:1 v:v acetonitrile:water with 0.1% formic acid (solvent B). Pump 2 buffers consisted of 0.01% formic acid in water (solvent C) and 1:1 v:v acetonitrile:isopropanol (solvent D).

5ul of extracted sample was injected onto an Agilent SB-C18 2.1×5mm 1.8um trapping column using pump 1 at 2mls/min for 0.5 minutes with a solvent composition of 97% solvent A: 3% solvent B. At 0.51 minutes the switching valve changed the flow to the trapping column from pump 1 to pump 2. The flow was reversed and the trapped lipid mediators were eluted onto an Agilent Eclipse Plus C-18 2.1×150mm 1.8um analytical column using the following gradient at a flow rate of 0.3mls/min: hold at 75% solvent A:25% solvent D from 0–0.5 minutes, then a linear gradient from 25–75% D over 20 minutes followed by an increase from 75–100% D from 20–21 minutes, then holding at 100% D for 2 minutes. During the analytical gradient pump 1 washed the injection loop with 100% B for 22.5 minutes at 0.2mls/min. Both the trapping column and the analytical column were re-equilibrated at starting conditions for 5 minutes before the next injection.

Mass spectrometric analysis was performed on an Agilent 6490 triple quadrupole mass spectrometer in negative ionization mode. The drying gas was 250C at a flow rate of 15mls/min. The sheath gas was 350C at 12mls/min. The nebulizer pressure was 35psi. The capillary voltage was 3500V. Data for lipid mediators was acquired in dynamic MRM mode using experimentally optimized collision energies obtained by flow injection analysis of authentic standards. Calibration standards for each lipid mediator were analyzed over a range of concentrations from 0.25–250pg on column. Calibration curves for each lipid mediator were constructed using Agilent Masshunter Quantitative Analysis software. Samples were quantitated using the calibration curves to obtain the on-column concentration, followed by multiplication of the results by the appropriate dilution factor derived from the initial sample volume and the protein concentration data gathered from the BCA assay to obtain the concentration in pg/ug protein.

For statistical analysis, measurements at the limit of detection (LOD) were calculated as the concentration for each analyte at which the lowest calibration standard injected repeatedly (n=5) produced a response signal-to-noise ratio greater than, or equal to, 5. Measurements at limit of quantification (LOQ) were calculated with an analysis of the same repeated reference standard injections where the average accuracy of the most dilute from protein concentration data to obtain the concentration in pg/ml (8). LOD, LOQ, and range of detectable levels for each compound is provided in Table E2.

Statistical Analysis

We evaluated patterns of missingness for the n=11 nasal epithelium samples across the 56 lipid mediator analytes. An analyte quantified at or above the LOQ in at least eight samples was treated as a continuous/quantitative variable in statistical analyses (number of analytes, m=23; 15 of which were quantified at or above the LOQ in all 11 samples). For the 1 to 3 samples with low analyte abundance for each of the compounds analyzed quantitatively, we substituted the corresponding LOD or LOQ value for analysis. Analytes quantified in four to seven samples were dichotomized into present/absent (m=2). Analytes quantified in three or fewer samples were excluded from statistical analysis (m=31). Comparisons between groups were conducted in two ways: 1) comparing asthma cases (SA and MMA) to controls, and 2) comparing SA cases to MMA cases to controls as a three-level categorical variable.

We evaluated the pairwise relationships between all analytes and phenotypic participant characteristics using a Spearman’s correlation coefficient (Figure E1). After examining analyte distributions using histograms and violin plots by group, we used linear regression to test for differences between groups for each quantitative analyte, adjusting for age at nasal epithelium sample collection. Due to the established biological connections and high correlation between analytes, we also conducted a principal components analysis of all quantitative analytes (m=23, Figure E2) and examined whether scores on the first three principal components (PCs, which explained >80% of the variance) differed between groups using the same linear regression framework. Logistic regression models adjusted for age were used to test for differences between groups for analytes treated as present/absent.

Partial Least Squares-Discriminant Analysis (PLS-DA) (9) in the mixOmics R package (10) was used to identify lipid mediators that contributed most to discrimination between the asthma cases and controls. The m=23 quantitative compounds and age were included in the PLS-DA model.

Ethics

Nasal epithelial samples were collected in accordance with approved protocols from the Colorado Multiple Institutional Review Board (COMIRB)#: 17-1807, as well as National Ethics Committee from Brazil CAAE: 94096318.4.0000.5577.

Supplementary Material

E1

Figure E1: Spearman rank correlations between lipid mediators in the nasal epithelium (quantitative or present/absent, m=25) and participant characteristics in PROAR (n=11). “Case” = Asthma vs. Control, “Group” = Severe Asthma vs. Mild-Moderate Asthma vs. Control.

E2

Figure E2: Principal components analysis loadings plot for lipid mediators (m=23).

1

Key Messages.

  • 15 lipid mediators were present at detectable levels in the nasal epithelium of all subjects, including Resolvin D5, a compound that has been inconsistently detected in other tissues.

  • Asthma cases had higher levels of PGE2, an AA metabolite with both pro-inflammatory and pro-resolving effects, and lower levels of EPA-, DHA-, and ALA-derived pro-resolving lipid mediators compared to controls.

ACKNOWLEDGEMENTS

Many thanks to the ProAR participants for their contributions to the study. This work was supported by the National Institutes of Health NIH-NHLBI grant R01HL104608 to K.C.B. and by NIH-NCRR 1S10OD010366-01A1 and NIH-NHLBI grant R01HL123385 to N.R. This study was financed in part by Programa de Apoio a Núcleos Emergentes (PRONEM) - FAPESB (Fundação de Amparo à Pesquisa do Estado da Bahia); Edital: 009/2014; Pedido: 8305/2014; Termo de outorga: PNE0003/2014.

Abbreviations

AA

Arachidonic acid

ALA

Alpha-linolenic acid

DHA

Docosahexaenoic acid

EPA

Eicosapentaenoic acid

DGLA

Dihomo-gamma-linolenic acid

LA

Linoleic acid

LTs

Leukotrienes

Lx

Lipoxins

PGs

Prostaglandins

PUFAs

Polyunsaturated fatty acids

RV

Resolvins

SPMs

Specialized pro-resolving mediators

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Disclosure of potential conflict of interest

K.C. Barnes receives royalties from UpToDate and is employed by Tempus. The rest of the authors declare that they have no relevant conflicts of interest.

REFERENCES

  • 1.Rabinovitch N, Mauger DT, Reisdorph N, Covar R, Malka J, Lemanske RF Jr, et al. Predictors of asthma control and lung function responsiveness to step 3 therapy in children with uncontrolled asthma. J Allergy Clin Immunol 2014;133:350–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Rabinovitch N, Reisdorph N, Silveira L, Gelfand EW. Urinary leukotriene E4 levels identify children with tobacco smoke exposure at risk for asthma exacerbation. J Allergy Clin Immunol 2011;128:323–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kleniewska P, Pawliczak R. The participation of oxidative stress in the pathogenesis of bronchial asthma. Biomed Pharmacother 2017;94:100–8. [DOI] [PubMed] [Google Scholar]
  • 4.Fitzpatrick AM, Teague WG, Burwell L, Brown MS, Brown LA; NIH/NHLBI Severe Asthma Research ProgramGlutathione oxidation is associated with airway macrophage functional impairment in children with severe asthma. Pediatr Res 2011;69:154–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bannenberg G, Serhan CN. Specialized pro-resolving lipid mediators in the inflammatory response: an update. Biochim Biophys Acta 2010;1801:1260–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Levy BD, Clish CB, Schmidt B, Gronert K, Serhan CN. Lipid mediator class switching during acute inflammation: signals in resolution. Nat Immunol 2001;2: 612–9. [DOI] [PubMed] [Google Scholar]
  • 7.Serhan CN, Petasis NA. Resolvins and protectins in inflammation resolution. Chem Rev 2011;111:5922–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Julia V, Macia L, Dombrowicz D. The impact of diet on asthma and allergic diseases. Nat Rev 2015;15:308–22. [DOI] [PubMed] [Google Scholar]
  • 9.Lambrecht BN, Hammad H. The immunology of asthma. Nat Immunol 2015;16: 45–56. [DOI] [PubMed] [Google Scholar]
  • 10.Levy BD. Resolvin D1 and resolvin E1 promote the resolution of allergic airway inflammation via shared and distinct molecular counter-regulatory pathways. Front Immunol 2012;3:390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Haworth O, Levy BD. Endogenous lipid mediators in the resolution of airway inflammation. Eur Respir J 2007;30:980–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Parameswaran K, Radford K, Fanat A, Stephen J, Bonnans C, Levy BD, et al. Modulation of human airway smooth muscle migration by lipid mediators and Th-2 cytokines. Am J Respir Cell Mol Biol 2007;37:240–7. [DOI] [PubMed] [Google Scholar]
  • 13.Bonnans C, Levy BD. Lipid mediators as agonists for the resolution of acute lung inflammation and injury. Am J Respir Cell Mol Biol 2007;36:201–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Murphy RC. Specialized pro-resolving mediators: do they circulate in plasma? J Lipid Res 2015;56:1641–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Alashkar Alhamwe B, Miethe S, Pogge von Strandmann E, Potaczek DP, Garn H. Epigenetic regulation of airway epithelium immune functions in asthma. Front Immunol 2020;11:1747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Imkamp K, Berg M, Vermeulen CJ, Heijink IH, Guryev V, Kerstjens HAM, et al. Nasal epithelium as a proxy for bronchial epithelium for smoking-induced gene expression and expression Quantitative Trait Loci. J Allergy Clin Immunol 2018; 142:314–7.e15. [DOI] [PubMed] [Google Scholar]
  • 17.Cruz AA, Riley JH, Bansal AT, Ponte EV, Souza-Machado A, Almeida PCA, et al. Asthma similarities across ProAR (Brazil) and U-BIOPRED (Europe) adult cohorts of contrasting locations, ethnicity and socioeconomic status. Respir Med 2020;161: 105817. [DOI] [PubMed] [Google Scholar]
  • 18.Polinski KJ, Armstrong M, Manke J, Seifert J, Crume T, Yang F, et al. Collection and storage of human plasma for measurement of oxylipins. Metabolites 2021;11:137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Vickery TW, Armstrong M, Kofonow JM, Robertson CE, Kroehl ME, Reisdorph NA, et al. Altered tissue specialized pro-resolving mediators in chronic rhinosinusitis. Prostaglandins Leukot Essent Fatty Acids 2021;164:102218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Armstrong M, Manke J, Nkrumah-Elie Y, Shaikh SR, Reisdorph N. Improved quantification of lipid mediators in plasma and tissues by liquid chromatography tandem mass spectrometry demonstrates mouse strain specific differences. Prostaglandins Other Lipid Mediat 2020;151:106483. [DOI] [PubMed] [Google Scholar]
  • 21.Armstrong M, Liu AH, Harbeck R, Reisdorph R, Rabinovitch N, Reisdorph N. Leukotriene-E4 in human urine: comparison of on-line purification and liquid chromatography–tandemmass spectrometry toaffinitypurificationfollowed by enzyme immunoassay. J Chromatogr B Analyt Technol Biomed Life Sci 2009;877:3169–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Aggarwal S, Moodley YP, Thompson PJ, Misso NL. Prostaglandin E2 and cysteinyl leukotriene concentrations in sputum: association with asthma severity and eosinophilic inflammation. Clin Exp Allergy 2010;40:85–93. [DOI] [PubMed] [Google Scholar]
  • 23.Chiang N, Serhan CN. Specialized pro-resolving mediator network: an update on production and actions. Essays Biochem 2020;64:443–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Barnig C, Frossard N, Levy BD. Towards targeting resolution pathways of airway inflammation in asthma. Pharmacol Ther 2018;186:98–113. [DOI] [PubMed] [Google Scholar]
  • 25.Gauvreau GM, Watson RM, O’Byrne PM. Protective effects of inhaled PGE2 on allergen-induced airway responses and airway inflammation. Am J Respir Crit Care Med 1999;159:31–6. [DOI] [PubMed] [Google Scholar]

REFERENCES

  • E1.Cruz AA, Souza-Machado A, Franco R, Souza-Machado C, Ponte EV, Moura Santos P, et al. The impact of a program for control of asthma in a low-income setting. World Allergy Organ J 2010;3:167–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • E2.Cruz AA, Riley JH, Bansal AT, Ponte EV, Souza-Machado A, Almeida PCA, et al. Asthma similarities across ProAR (Brazil) and U-BIOPRED (Europe) adult cohorts of contrasting locations, ethnicity and socioeconomic status. Respir Med 2020;161:105817. [DOI] [PubMed] [Google Scholar]
  • E3.Bateman ED, Hurd SS, Barnes PJ, Bousquet J, Drazen JM, FitzGerald JM, et al. Global strategy for asthma management and prevention: GINA executive summary. Eur Respir J 2008;31:143–78. [DOI] [PubMed] [Google Scholar]
  • E4.Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung function tests. Eur Respir J 2005;26:948–68. [DOI] [PubMed] [Google Scholar]
  • E5.Graham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of spirometry, 2019 update. An official American Thoracic Society and European Respiratory Society technical statement. Am J Respir Crit Care Med 2019;200:e70–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • E6.Pereira CA, Sato T, Rodrigues SC. New reference values for forced spirometry in white adults in Brazil. J Bras Pneumol 2007;33:397–406. [DOI] [PubMed] [Google Scholar]
  • E7.Yang IV, Pedersen BS, Liu AH, O’Connor GT, Teach SJ, Kattan M, et al. DNA methylation changes in nasal epithelia are associated with allergic asthma in the inner city. Ann Am Thorac Soc 2016;13(suppl 1):S99–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • E8.Armstrong M, Manke J, Nkrumah-Elie Y, Shaikh SR, Reisdorph N. Improved quantification of lipid mediators in plasma and tissues by liquid chromatography tandem mass spectrometry demonstrates mouse strain specific differences. Prostaglandins Other Lipid Mediat 2020;151:106483. [DOI] [PubMed] [Google Scholar]
  • E9.Barker M, Rayens W. Partial least squares for discrimination. J Chemometr 2003; 17:166–73. [Google Scholar]
  • E10.Rohart F, Gautier B, Singh A, KA LC. mixOmics: an R package for ’omics feature selection and multiple data integration. PLoS Comput Biol 2017;13: e1005752. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

E1

Figure E1: Spearman rank correlations between lipid mediators in the nasal epithelium (quantitative or present/absent, m=25) and participant characteristics in PROAR (n=11). “Case” = Asthma vs. Control, “Group” = Severe Asthma vs. Mild-Moderate Asthma vs. Control.

NIHMS1789135-supplement-E1.jpg (4.7MB, jpg)
E2

Figure E2: Principal components analysis loadings plot for lipid mediators (m=23).

NIHMS1789135-supplement-E2.jpg (1.7MB, jpg)
1
NIHMS1789135-supplement-1.pdf (167.5KB, pdf)

RESOURCES