Deletions in DNAL1 Cause Primary Ciliary Dyskinesia Across North American Indigenous Populations.

We report 4 cases of primary ciliary dyskinesia in unrelated indigenous North American children caused by identical, homozygous, likely pathogenic deletions in the DNAL1 gene. These shared DNAL1 deletions among dispersed indigenous populations suggest that primary ciliary dyskinesia accounts for more lung disease with bronchiectasis than previously recognized in indigenous North Americans.

A scoping review of asthma and machine learning.

OBJECTIVE: The objective of this study was to determine the extent of machine learning (ML) application in asthma research and to identify research gaps while mapping the existing literature. DATA SOURCES: We conducted a scoping review. PubMed, ProQuest, and Embase Scopus databases were searched with an end date of September 18, 2020. STUDY SELECTION: DistillerSR was used for data management. Inclusion criteria were an asthma focus, human participants, ML techniques, and written in English. Exclusion criteria were abstract only, simulation-based, not human based, or were reviews or commentaries. Descriptive statistics were presented. RESULTS: A total of 6,317 potential articles were found. After removing duplicates, and reviewing the titles and abstracts, 102 articles were included for the full text analysis. Asthma episode prediction (24.5%), asthma phenotype classification (16.7%), and genetic profiling of asthma (12.7%) were the top three study topics. Cohort (52.9%), cross-sectional (20.6%), and case-control studies (11.8%) were the study designs most frequently used. Regarding the ML techniques, 34.3% of the studies used more than one technique. Neural networks, clustering, and random forests were the most common ML techniques used where they were used in 20.6%, 18.6%, and 17.6% of studies, respectively. Very few studies considered location of residence (i.e. urban or rural status). CONCLUSIONS: The use of ML in asthma studies has been increasing with most of this focused on the three major topics (>50%). Future research using ML could focus on gaps such as a broader range of study topics and focus on its use in additional populations (e.g. location of residence).Supplemental data for this article is available online at http://dx.doi.org/ .

Chronic tracheostomy care of ventilator-dependent and -independent children: Clinical practice patterns of pediatric respirologists in a publicly funded (Canadian) healthcare system.

OBJECTIVES: To describe the current clinical practice patterns of Canadian pediatric respirologists at pediatric tertiary care institutions regarding chronic tracheostomy tube care and management of home invasive ventilation. METHODS: A pediatric respirologist/pediatrician with expertise in tracheostomy tube care and home ventilation was identified at each Canadian pediatric tertiary care center to complete a 59-item survey of multiple choice and short answer questions. Domains assessed included tracheostomy tube care, caregiver competency and home monitoring, speaking valves, medical management of tracheostomy complications, decannulation, and long-term follow-up. RESULTS: The response rate was 100% (17/17) with all Canadian tertiary care pediatric centers represented and heterogeneity of practice was observed in all domains assessed. For example, though most centers employ Bivona™ (17/17) and Shiley™ (15/17) tracheostomy tubes, variability was observed around tube change, re-use, and cleaning practices. Most centers require two trained caregivers (14/17) and recommend 24/7 eyes on care and oxygen saturation monitoring. Discharge with an emergency tracheostomy kit was universal (17/17). Considerable heterogeneity was observed in the timing and use of speaking valves and speech-language assessment. Inhaled anti-pseudomonal antibiotics are employed by most centers (16/17) though the indication, agent, and protocol varied by center. Though decannulation practices varied considerably, the requirement of upper airway patency was universally required to proceed with decannulation (17/17) independent of ongoing ventilatory support requirements. CONCLUSION: Considerable variability in pediatric tracheostomy tube care practice exists across Canada. These results will serve as a starting point to standardize and evaluate tracheostomy tube care nationally.

Effectiveness of polyvalent bacterial lysate for pediatric asthma control: a retrospective propensity score-matched cohort study.

Background: Previous studies showed bacterial lysates were effective for pediatric asthma. However, evidence of polyvalent bacterial lysate Qipian is lacking. Methods: In this real-world retrospective cohort study, data of children with asthma, aged six months to 14 years old, attending to Jiangxi Provincial Children's Hospital from January 2021 to April 2022, prescribed routine treatment for asthma plus Qipian (Qipian group) or not (control group) were extracted. To minimize the impact of confounders on the outcomes, baseline characteristics were utilized to perform propensity score matching through a multivariable logistic regression model. After matching, asthma control, exacerbation, etc. were compared. Results: Totally, 795 patients were included (337 in the Qipian group and 458 in the control group), with 278 pairs (556 patients) matched. Most baseline characteristics were well-balanced. The proportion of males were 68.3% and 70.1% in the two groups. The Qipian group favored better asthma control, with more "controlled" [3-month: 257 (92.4%) vs. 240 (86.3%); 6-month: 246 (88.5%) vs. 235 (84.5%)], and fewer "poorly/very poorly controlled" patients, compared with the control group (P=0.004 and 0.025, respectively). Patients in the Qipian group had lower risks of exacerbation. Incidence rate ratios (IRR) for any exacerbation were 0.56 [95% confidence interval (CI): 0.33 to 0.93] in the 3-month period and 0.83 (95% CI: 0.55 to 1.26) in the 6-month period. IRR for severe exacerbations were 0.09 (95% CI: 0.01 to 0.71) in the 3-month period and 0.20 (95% CI: 0.06 to 0.70) in the 6-month period (compared to the control group). Qipian significantly reduced the cumulative dose of short-acting beta-agonist (3-month: 3.22±10.37 vs. 8.08±16.71 mg; P<0.001; 6-month: 6.56±16.23 vs. 11.81±24.41 mg; P=0.002). There was no difference in incidences of respiratory tract infection or fever due to respiratory tract infection between the two groups. Numbers of antibacterial agent prescription were fewer in the Qipian group compared to the control group (3-month: 0.67±1.16 vs. 1.04±1.45; P=0.001; 6-month: 1.14±1.69 vs. 1.51±2.12; P=0.023). Conclusions: According to this retrospective study, Qipian may be effective for improved pediatric asthma control. Safety profile and mechanisms of action of Qipian need further investigation. Further randomized controlled trials are warranted to confirm our results.

Development of a predictive algorithm to identify pre-school children at risk for behavior changes associated with sleep-related breathing disorders.

STUDY OBJECTIVES: Children with late-onset (2-5 years) or persistent (3 months-5 years) sleep-related breathing disorder (SRBD) have an increased risk of behavior problems compared to children with no or early-onset SRBD. We sought to determine whether a combination of urine metabolites and sleep questionnaires could identify children at risk for SRBD-associated behavior problems. METHODS: Urine and data were analyzed from the Edmonton site of the CHILD birth cohort study. We measured urine metabolites (random, mid-stream) at age three-years among a sub-cohort of participants (n = 165). Random Forest with a Boruta wrapper was used to identify important metabolites (creatinine-corrected, z-scores) for late/persistent SRBD versus no/early SRBD (reference). An algorithm was subsequently generated to predict late/persistent SRBD in children with a history of snoring using a metabolite composite score (z-scores < or ≥ 0) plus the SDBeasy score defined as [age (yrs.) of most recent positive SRBD]2 - [age (yrs.) first reported ever snoring]2. RESULTS: Of the 165 children with SRBD data, 40 participants had late/persistent SRBD. Seven urinary metabolites in addition to the SDBeasy score were confirmed as important for late/persistent SRBD (AUC = 0.87). Among children with an ever-snoring history and a metabolite composite score ≥0, those with SDBeasy score ≥3 were over 13-fold more likely to have late/persistent SRBD (OR 13.7; 95%CI: 3.0, 62.1; p = 0.001). This algorithm has a Sensitivity of 69.6%, Specificity of 85.7% and a positive likelihood ratio (+LR) of 4.9. CONCLUSIONS: We developed a predictive algorithm using a combination of questionnaires and urine metabolites at age three-years to identify children with late/persistent SRBD by five-years of age.

Two children with extra-nodal Mycobacterium avium complex infection.

Mycobacterium avium complex (MAC) is usually considered an opportunistic organism, which infects immunocompromised children or those with structural airway abnormalities. We present two cases of MAC infection affecting immune competent children, likely from hot tubs with primary involvement of pulmonary and urinary systems. These cases highlight the importance of asking about hot tub use in immune competent children with suspected or confirmed MAC infections.

STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY.

Metabolomics is a dynamically evolving field, with a major application in identifying biomarkers for drug development and personalized medicine. Numerous metabolomic studies have identified endogenous metabolites that, in principle, are eligible for translation to clinical practice. However, few metabolomic-derived biomarker candidates have been qualified by regulatory bodies for clinical applications. Such interruption in the biomarker qualification process can be largely attributed to various reasons including inappropriate study design and inadequate data to support the clinical utility of the biomarkers. In addition, the lack of robust assays for the routine quantification of candidate biomarkers has been suggested as a potential bottleneck in the biomarker qualification process. In fact, the nature of the endogenous metabolites precludes the application of the current validation guidelines for bioanalytical methods. As a result, there have been individual efforts in modifying existing guidelines and/or developing alternative approaches to facilitate method validation. In this review, three main challenges for method development and validation for endogenous metabolites are discussed, namely matrix effects evaluation, alternative analyte-free matrices, and the choice of internal standards (ISs). Some studies have modified the equations described by the European Medicines Agency for the evaluation of matrix effects. However, alternative strategies were also described; for instance, calibration curves can be generated in solvents and in biological samples and the slopes can be compared through ratios, relative standard deviation, or a modified Stufour suggested approaches while quantifying mainly endogenous metabolitesdent t-test. ISs, on the contrary, are diverse; in which seven different possible types, used in metabolomics-based studies, were identified in the literature. Each type has its advantages and limitations; however, isotope-labeled ISs and ISs created through isotope derivatization show superior performance. Finally, alternative matrices have been described and tested during method development and validation for the quantification of endogenous entities. These alternatives are discussed in detail, highlighting their advantages and shortcomings. The goal of this review is to compare, apprise, and debate current knowledge and practices in order to aid researchers and clinical scientists in developing robust assays needed during the qualification process of candidate metabolite biomarkers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

CCL5 persists in RSV stocks following sucrose-gradient purification.

Respiratory syncytial virus (RSV) is associated with bronchiolitis in infancy and the later development of asthma. Research on RSV in vitro requires preparation of a purified RSV stock. The objective for this work was to develop best methods for RSV purification, while monitoring the samples for potential contaminating proinflammatory mediators. Using polyethylene glycol concentration, and sucrose-gradient ultracentrifugation, we collected samples at each step of purification and measured the values of RSV titer, total protein (µg/mL), and proinflammatory cytokines (ELISA). We analyzed the efficacy of each step in the purification procedure. In so doing, we also determined that despite optimal purification methods, a well-known chemokine in the field of allergic disease, CCL5 (RANTES), persisted within the virus preparations, whereas other cytokines did not. We suggest that researchers should be aware that CCL5 appears to co-purify with RSV. Despite reasonable purification methods, a significant level of CCL5 (RANTES) persists in the virus preparation. This is relevant to the study of RSV-induced allergic disease.

Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach.

The diagnosis of asthma and chronic obstructive pulmonary disease (COPD) can be challenging due to the overlap in their clinical presentations in some patients. There is a need for a more objective clinical test that can be routinely used in primary care settings. Through an untargeted 1H NMR urine metabolomic approach, we identified a set of endogenous metabolites as potential biomarkers for the differentiation of asthma and COPD. A subset of these potential biomarkers contains 7 highly polar metabolites of diverse physicochemical properties. To the best of our knowledge, there is no liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that evaluated more than two of the target metabolites in a single analytical run. The target metabolites belong to the families of monosaccharides, organic acids, amino acids, quaternary ammonium compounds and nucleic acids, rendering hydrophilic interaction liquid chromatography (HILIC) an ideal technology for their quantification. Since a clinical decision is to be made from patients data, a fully validated analytical method is required for biomarker validation. Method validation for endogenous metabolites is a daunting task since current guidelines were designed for exogenous compounds. As such, innovative approaches were adopted to meet the validation requirements. Herein, we describe a sensitive HILIC-MS/MS method for the quantification of the 7 endogenous urinary metabolites. Detection was achieved in the multiple reaction monitoring (MRM) mode with polarity switching, using quadrupole-linear ion trap instrument (QTRAP 6500) as well as single ion monitoring in the negative-ion mode. The method was fully validated according to the regulatory guidelines. Linearity was established between 6 and 21000 ng/mL and quality control samples demonstrated acceptable intra- and inter-day accuracy (85.7%-112%), intra- and inter-day precision (CV% <11.5%) as well as stability under various storage and sample processing conditions. To illustrate the method's applicability, the validated method was applied to the analysis of a small set of urine samples collected from asthma and COPD patients. Preliminary modelling of separation was generated using partial least square discriminant analysis (R2 0.752 and Q2 0.57). The adequate separation between patient samples confirms the diagnostic potential of these target metabolites as a proof-of-concept for the differentiation between asthma and COPD. However, more patient urine samples are needed in order to increase the statistical power of the analytical model.

Comparison of accuracy and precision between multipoint calibration, single point calibration, and relative quantification for targeted metabolomic analysis.

Targeted metabolomics requires accurate and precise quantification of candidate biomarkers, often through tandem mass spectrometric (MS/MS) analysis. Differential isotope labeling (DIL) improves mass spectrometric (MS) analysis in metabolomics by derivatizing metabolites with two isotopic forms of the same reagent. Despite its advantages, DIL-liquid chromatographic (LC)-MS/MS can result in substantial increase in workload when fully validated quantitative methods are required. To decrease the workload, we hypothesized that single point calibration or relative quantification could be used as alternative methods. Either approach will result in significant saving in resources and time. To test our hypothesis, six urinary metabolites were selected as model compounds. Urine samples were analyzed using a fully validated multipoint dansyl chloride-DIL-LC-MS/MS method. Samples were reprocessed using single point calibration and relative quantification modes. Our results demonstrated that the performance of single point calibration or relative quantification was inferior, for some metabolites, to multipoint calibration. The lower limit of quantification failed in the quantification of ethanolamine in most of participant samples using single point calibration. In addition, its precision was not acceptable in one participant during serine and ethanolamine quantification. On the other hand, relative quantification resulted in the least accurate data. In fact, none of the data generated from relative quantification for serine was comparable to that obtained from multipoint calibration. Finally, while single point calibration showed an overall acceptable performance for the majority of the model compounds, we cannot extrapolate the findings to other metabolites within the same analytical run. Analysts are advised to assess accuracy and precision for each metabolite in which single point calibration is the intended quantification mean.

Asthma diagnosis among children along an urban-rural gradient.

OBJECTIVE: Studies have reported lower asthma prevalence in rural compared to urban areas. While environmental factors have mostly been implicated for these differences, the lower asthma prevalence could also be linked to asthma under-diagnosis in rural children. We investigate if rural children experience under-diagnosis of asthma more compared to urban children. METHODS: In 2013, we conducted a cross-sectional survey of schoolchildren across an urban-rural gradient in Saskatchewan, Canada. The participants formed sampling frame for future studies. In 2015, we approached those who gave consent in 2013 for further testing, repeated the survey, and conducted clinical testing. Based on survey responses, children were classified into "no asthma," "at-risk-for-asthma," and "diagnosed asthma." We then classified asthma status as either "no asthma" or "probable asthma" based on a validated asthma algorithm. RESULTS: The study population of 335 schoolchildren (aged 7-17 years) comprised of 73.4% from large urban, 13.7% from small urban, and 12.8% from rural areas. Proportion with report of physician-diagnosed asthma was 28.5% (Large urban), 34.8% (Small urban), and 20.9% (Rural). Mean percent predicted FEV1 and FEF25%-75% were lower in rural compared to small urban and large urban children (p < 0.05). Among those not classified as with "diagnosed asthma" by the survey, the algorithm further identified presence of asthma in 5.5% large urban, 8.1% small urban, and 18.8% rural children (p = 0.03). CONCLUSION: The study revealed evidence of asthma underdiagnosis in rural areas and further supports the use of objective measures in addition to symptoms history when investigating asthma across urban-rural gradients.

Comparative analysis of creatinine and osmolality as urine normalization strategies in targeted metabolomics for the differential diagnosis of asthma and COPD.

INTRODUCTION: Urine is an ideal matrix for metabolomics investigation due to its non-invasive nature of collection and its rich metabolite content. Despite the advancements in mass spectrometry and 1H-NMR platforms in urine metabolomics, the statistical analysis of the generated data is challenged with the need to adjust for the hydration status of the person. Normalization to creatinine or osmolality values are the most adopted strategies, however, each technique has its challenges that can hinder its wider application. We have been developing targeted urine metabolomic methods to differentiate two important respiratory diseases, namely asthma and chronic obstructive pulmonary disease (COPD). OBJECTIVE: To assess whether the statistical model of separation of diseases using targeted metabolomic data would be improved by normalization to osmolality instead of creatinine. METHODS: The concentration of 32 metabolites was previously measured by two liquid chromatography-tandem mass spectrometry methods in 51 human urine samples with either asthma (n = 25) or COPD (n = 26). The data was normalized to creatinine or osmolality. Statistical analysis of the normalized values in each disease was performed using partial least square discriminant analysis (PLS-DA). Models of separation of diseases were compared. RESULTS: We found that normalization to creatinine or osmolality did not significantly change the PLS-DA models of separation (R2Q2 = 0.919, 0.705 vs R2Q2 = 0.929, 0.671, respectively). The metabolites of importance in the models remained similar for both normalization methods. CONCLUSION: Our findings suggest that targeted urine metabolomic data can be normalized for hydration using creatinine or osmolality with no significant impact on the diagnostic accuracy of the model.

Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers.

Obstructive airways inflammatory diseases sometimes show overlapping symptoms that hinder their early and correct diagnosis. Current clinical tests are tedious and are of inadequate specificity in special population such as the elderly and children. Therefore, we are developing tandem mass spectrometric (MS/MS) methods for targeted analysis of urine biomarkers. Recently, proton-nuclear magnetic resonance (1H-NMR) analysis proposed 50 urinary metabolites as potential diagnostic biomarkers among asthma and chronic obstructive pulmonary disease (COPD) patients. Metabolites are divided into 3 groups based on chemical nature. For group 1 (amines and phenols, 19 urinary metabolites), we developed and validated a high performance liquid chromatographic (HPLC)-MS/MS method using differential isotope labeling (DIL) with dansyl chloride. Method development included the optimization of the derivatization reaction, the MS/MS conditions, and the chromatographic separation. Linearity varied from 2 to 4800 ng/mL and the use of 13C2-labeled derivatives allowed for the correction of matrix effects as well as the unambiguous confirmation of the identity of each metabolite in the presence of interfering isomers in urine. Despite the challenges associated with method validation, the method was fully validated as per the food and drug administration (FDA) and the European medicines agency (EMA) recommendations. Validation criteria included linearity, precision, accuracy, dilution integrity, selectivity, carryover, and stability. Challenges in selectivity experiments included the isotopic contributions of the analyte towards its internal standard (IS), that was addressed via the optimization of the IS concentration. In addition, incurred sample analysis was performed to ensure that results from patient samples are accurate and reliable. The method was robust and reproducible and is currently being applied in a cohort of asthma and COPD patient urine samples for biomarker discovery purposes.

Virus-induced asthma attack: The importance of allergic inflammation in response to viral antigen in an animal model of asthma.

Asthma exacerbation can be a life-threatening condition, and is most often triggered by common respiratory viruses. Poor asthma control and worsening of respiratory function is associated with increased airway inflammation, including eosinophilia. Prevention of asthma exacerbation relies on treatment with corticosteroids, which preferentially inhibit allergic inflammation like eosinophils. Human studies demonstrate that inactivated virus can trigger eosinophil activation in vitro through antigen presentation and memory CD4+ lymphocytes. We hypothesized that animals with immunologic memory to a respiratory virus would also develop airway hyperresponsiveness in response to a UV-inactivated form of the virus if they have pre-existing allergic airway inflammation. Guinea pigs were ovalbumin-sensitized, infected with live parainfluenza virus (PIV), aerosol-challenged with ovalbumin, and then re-inoculated 60 days later with live or UV-inactivated PIV. Some animals were either treated with dexamethasone prior to the second viral exposure. Lymphocytes were isolated from parabronchial lymph nodes to confirm immunologic memory to the virus. Airway reactivity was measured and inflammation was assessed using bronchoalveolar lavage and lung histology. The induction of viral immunologic memory was confirmed in infected animals. Allergen sensitized and challenged animals developed airway hyperreactivity with eosinophilic airway inflammation when re-exposed to UV-inactivated PIV, while non-sensitized animals did not. Airway hyperreactivity in the sensitized animals was inhibited by pre-treatment with dexamethasone. We suggest that the response of allergic inflammation to virus antigen is a significant factor causing asthma exacerbation. We propose that this is one mechanism explaining how corticosteroids prevent virus-induced asthma attack.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017.

A Pediatric Case of Diffuse Alveolar Hemorrhage Secondary to Poststreptococcal Glomerulonephritis.

This report summarizes a case of a 4-year-old girl with poststreptococcal glomerulonephritis and diffuse alveolar hemorrhage, an atypical presentation in this age group and type of vasculitic disease. We propose that her rapid improvement in clinical status was due to her treatment, continuous renal replacement therapy (CRRT). This mechanism would have impacted recovery by removing factors such as endothelial microparticles, superantigens, and immune complexes that have been postulated as the pulmonary-renal link. This may be an interesting avenue of exploration going forward given the lack of evidence in treating such conditions and emergence of CRRT.

Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study.

BACKGROUND: Clinicians lack objective tests to help determine the severity of bronchiolitis or to distinguish a viral from bacterial causes of respiratory distress. We hypothesized that children with respiratory syncytial virus (RSV) infection would have a different metabolomic profile compared to those with bacterial infection or healthy controls, and this might also vary with bronchiolitis severity. METHODS: Clinical information and urine-based metabolomic data were collected from healthy age-matched children (n = 37) and those admitted to hospital with a proven infection (RSV n = 55; Non-RSV viral n = 16; bacterial n = 24). Nuclear magnetic resonance (NMR) measured 86 metabolites per urine sample. Partial least squares discriminant analysis (PLS-DA) was performed to create models of separation. RESULTS: Using a combination of metabolites, a strong PLS-DA model (R2 = 0.86, Q2 = 0.76) was created differentiating healthy children from those with RSV infection. This model had over 90 % accuracy in classifying blinded infants with similar illness severity. Two other models differentiated length of hospitalization and viral versus bacterial infection. CONCLUSION: While the sample sizes remain small, this is the first report suggesting that metabolomic analysis of urine samples has the potential to become a diagnostic aid. Future studies with larger sample sizes are required to validate the utility of metabolomics in pediatric patients with respiratory distress.

Metabolomic profiling of asthma and chronic obstructive pulmonary disease: A pilot study differentiating diseases.

BACKGROUND: Differentiating asthma from other causes of chronic airflow limitation, such as chronic obstructive pulmonary disease (COPD), can be difficult in a typical outpatient setting. The inflammation of asthma typically is different than that of COPD, and the degree of inflammation and cellular damage varies with asthma severity. Metabolomics is the study of molecules created by cellular metabolic pathways. OBJECTIVES: We hypothesized that the metabolic activity of adults with asthma would differ from that of adults with COPD. Furthermore, we hypothesized that nuclear magnetic resonance spectroscopy (NMR) would measure such differences in urine samples. METHODS: Clinical and urine-based NMR data were collected on adults meeting the criteria of asthma and COPD before and after an exacerbation (n = 133 and 38, respectively) and from patients with stable asthma or COPD (n = 54 and 23, respectively). Partial least-squares discriminant analysis was performed on the NMR data to create models of separation (86 metabolites were measured per urine sample). Some subjects' metabolomic data were withheld from modeling to be run blindly to determine diagnostic accuracy. RESULTS: Partial least-squares discriminant analysis of the urine NMR data found unique differences in select metabolites between patients with asthma and those with COPD seen in the emergency department and even in follow-up after exacerbation. By using these select metabolomic profiles, the model could correctly diagnose blinded asthma and COPD with greater than 90% accuracy. CONCLUSION: This is the first report showing that metabolomic analysis of human urine samples could become a useful clinical tool to differentiate asthma from COPD.