32 research outputs found

    Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study

    Get PDF
    Introduction Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. Methods Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12–18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. Results A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10−20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10−4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. Conclusions This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma

    Epithelial dysregulation in obese severe asthmatics with gastro-oesophageal reflux

    Get PDF

    Temporal Fluctuation of Systemic Markers in Urine During a Nasal Rhinovirus Challenge in Healthy and Asthmatic Subjects

    No full text
    International audienceBiological processes are dynamic as reflected by temporal fluctuations of biomarkers. These dynamics underline the adaptive capacity of physiological systems to respond to external perturbations. We have captured differences in the pattern of fluctuations in biomarkers sampled locally at the sites of respiratory infection between healthy individuals and asthma patients, before and after perturbation by rhinovirus exposure [Sinha et al, eLife]. The detection of fluctuating biomarker signals in a systemic matrix, e.g. urine could aid in the development of better prognostic, non-invasive markers for monitoring disease progression especially during loss-of-control/exacerbation events due to viral exposures in asthma. Aims:Probe and compare temporal fluctuations of metabolomic signatures in the systemic circulation (urine) after a rhinovirus (RV-16) challenge in healthy and asthmatic subjects. Methods: In this prospective follow-up study, urine from 12 healthy individuals and 12 asthma patients was sampled thrice weekly for 3 months. After two months (stable phase) individuals were exposed to a 100 TCID50 Rhinovirus 16 and followed for another month (unstable phase). Non-targeted metabolomics data were acquiredwith liquid chromatography-mass spectrometry (LC-MS) using HILIC chromatography in positive ionization mode. Urine specific gravity (SG) was measured to normalize urine concentration and to reduce matrix effects. Data was processed independently using MZmine, MS-DIAL and Profinder software packages.A modified robust regression analysis technique, LASSO (least absolute shrinkage and selection operator) was applied on the mass spectrometric fragments to compare healthy and asthma groups both before and after rhinovirus challenge interventions. The machine learning pipeline was applied to the non-targeted metabolomics dataset and selected features were identified using an in-house chemical library. Results: We have identified a total of 164 metabolites in urine, several of which were found differentially regulated in healthy and asthmatic volunteers before and after the challenge (See Figure 1). Interestingly carnitine species decreased during the Rhinovirus challenge. Decreases in urinary carnitines have been previously observed in relationto asthma severity levels which confirm and substantiate our findings. Derivates of GABA (γ-aminobutyric acid) were also found to be differentially regulated. Conclusions: Our studyreports for the first time the fluctuating signals of metabolites in systemic signals in response to an exogenous trigger in the local nasal compartment in healthy and asthmaticsubjects. Carnitine compounds could prove to be useful markers of viral infection. The differential regulation of urinary metabolites could be useful to monitor patient prognosis andspot viral infections

    The carnitine pathway is dysregulated in asthma in an oral corticosteroid-independent mechanism

    No full text
    Background: Asthma is a heterogeneous disease with poorly defined phenotypes. Aim: To identify metabolic dysregulations associated with asthma severity and evaluate the effects of asthma medication upon observed metabotypes. Methods: Baseline urine was collected from healthy controls (HC, n=108), mild-to-moderate asthmatics (MMA, n=87) and severe asthmatics (SA, n=418) from the U-BIOPRED cohort. 12-18 month longitudinal samples were collected from the SA cohort (n=305). Metabolomic data were acquired using mass spectrometry and analyzed using multivariate statistics. Gene set variation analysis (GSVA) was performed on bronchial brushing transcriptomic data. Results: 90 metabolites were identified with 40 altered in asthma (FDR<0.1). Multivariate modeling showed that HC and MMA differed significantly from all SA (p=1.4 ×10-14) and that oral corticosteroid (OCS)-treated asthmatics differed significantly from non-treated (p=9.52 ×10-4). Longitudinal samples were metabolically stable relative to baseline. OCS affected the levels of 25% of the metabolites, while theophylline affected 12%, and omalizumab had a minimal effect. Carnitine levels decreased in SA in an OCS-independent fashion. Carnitine is involved in long-chain fatty acid metabolism in mitochondria, which decreased along with levels of the carnitine transporter SLC22A5 in association with asthma severity in bronchial brushings, with differences strengthened by Th2 high/low stratification. Conclusions: SA have a dysregulated urinary metabolic profile that is strongly confounded by OCS treatment. Altered carnitine metabolism is independent of OCS and associated with mitochondrial dysfunction, presenting a potential target for intervention
    corecore