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Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis.

ABSTRACT: Neutrophilic airway inflammation plays a role in early structural lung disease in cystic fibrosis, but the mechanisms underlying this pathway are incompletely understood.Metabolites associated with neutrophilic inflammation were identified by discovery metabolomics on bronchoalveolar lavage fluid supernatant from 20 preschool children (2.9±1.3?years) with cystic fibrosis. Targeted mass-spectrometric detection of relevant metabolites was then applied to 34 children (3.5±1.5?years) enrolled in the Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF) who underwent chest computed tomography and bronchoalveolar lavage from two separate lobes during 42 visits. Relationships between metabolites and localised structural lung disease were assessed using multivariate analyses.Discovery metabolomics identified 93 metabolites associated with neutrophilic inflammation, including pathways involved in metabolism of adenyl purines, amino acids and small peptides, cellular energy and lipids. In targeted mass spectrometry, products of adenosine metabolism, protein catabolism and oxidative stress were associated with structural lung disease and predicted future bronchiectasis, and activities of enzymes associated with adenosine metabolism were elevated in the samples with early disease.Metabolomics analyses revealed metabolites and pathways altered with neutrophilic inflammation and destructive lung disease. These pathways can serve as biomarkers and potential therapeutic targets for early cystic fibrosis lung disease.

SUBMITTER: Esther CR

PROVIDER: S-EPMC5766264 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis.

Esther Charles R CR Turkovic Lidija L Rosenow Tim T Muhlebach Marianne S MS Boucher Richard C RC Ranganathan Sarath S Stick Stephen M SM

The European respiratory journal 20161111 6

Neutrophilic airway inflammation plays a role in early structural lung disease in cystic fibrosis, but the mechanisms underlying this pathway are incompletely understood.Metabolites associated with neutrophilic inflammation were identified by discovery metabolomics on bronchoalveolar lavage fluid supernatant from 20 preschool children (2.9±1.3 years) with cystic fibrosis. Targeted mass-spectrometric detection of relevant metabolites was then applied to 34 children (3.5±1.5 years) enrolled in the ...[more]

PMID: 27836957

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Project description:BackgroundLung disease as major cause for morbidity in patients with cystic fibrosis (CF) starts early in life. Its large phenotypic heterogeneity is partially explained by the genotype but other contributing factors are not well delineated. The close relationship between mucus, inflammation and infection, drives morpho-functional alterations already early in pediatric CF disease, The TRACK-CF cohort has been established to gain insight to disease onset and progression, assessed by lung function testing and imaging to capture morpho-functional changes and to associate these with risk and protective factors, which contribute to the variation of the CF lung disease progression.Methods and designTRACK-CF is a prospective, longitudinal, observational cohort study following patients with CF from newborn screening or clinical diagnosis throughout childhood. The study protocol includes monthly telephone interviews, quarterly visits with microbiological sampling and multiple-breath washout and as well as a yearly chest magnetic resonance imaging. A parallel biobank has been set up to enable the translation from the deeply phenotyped cohort to the validation of relevant biomarkers. The main goal is to determine influencing factors by the combined analysis of clinical information and biomaterials. Primary endpoints are the lung clearance index by multiple breath washout and semi-quantitative magnetic resonance imaging scores. The frequency of pulmonary exacerbations, infection with pro-inflammatory pathogens and anthropometric data are defined as secondary endpoints.DiscussionThis extensive cohort includes children after diagnosis with comprehensive monitoring throughout childhood. The unique composition and the use of validated, sensitive methods with the attached biobank bears the potential to decisively advance the understanding of early CF lung disease.Ethics and trial registrationThe study protocol was approved by the Ethics Committees of the University of Heidelberg (approval S-211/2011) and each participating site and is registered at clinicaltrials.gov (NCT02270476).

Project description:IntroductionMetabolomics is an emerging area of research and has the potential to identify clinical biomarkers for predicting or diagnosing cystic fibrosis (CF) pulmonary exacerbations (PEx).ObjectiveTo identify clinically promising metabolites across different sample sources that can be used to predict or diagnose PEx in CF.Evidence reviewSearches for original literature were completed through EMBASE, MEDLINE, and all databases on the Web of Science with no restrictions on language or publication date. Gray literature was collected through Google Scholar. Additional studies were obtained by contacting authors and searching reference lists of candidate papers. The patient population included individuals with CF. Studies involving patients who underwent lung transplantation were excluded. The outcome was the prediction or diagnosis of pulmonary exacerbations from metabolites directly measured from biological samples. Search results were downloaded and imported into Covidence and duplicates were removed automatically. Any remaining duplicates were manually tagged and excluded. Two independent reviewers screened each abstract for eligibility and repeated this process for full texts. Risk of bias was conducted using QUADAS-2 by two independent reviewers. A third author resolved any remaining conflicts.ResultsA combined 3974 relevant abstracts were identified and 115 full texts were assessed for eligibility. The final 25 studies underwent data extraction for study design, patient demographics, studied metabolites, concentration values, and diagnostic accuracy values. Included studies differed considerably in methodologies, sample specimen types (exhaled breath condensate [EBC], sputum, saliva, plasma, urine), and disease states. We identified 19 unique metabolites that were measured by two or more studies of which 2 have the potential to predict PEx (EBC 4-hydroxycyclohexylcarboxylic acid [4-HCHC] and lactic acid) and 6 to diagnose PEx (EBC 4-HCHC and lactic acid, sputum lactic acid and nitrate, and plasma arginine and methionine).Conclusion and relevanceThis systematic review has identified promising metabolites for further study in CF. Certain metabolites may provide clinical potential in predicting or diagnosing PEx, but further validation studies are required. With better tools to aid in the earlier identification of PEx, clinicians can implement preventative measures to mitigate airway damage.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/.

Project description:Variability in pulmonary disease severity is found in patients with cystic fibrosis (CF) who have identical mutations in the CF transmembrane conductance regulator (CFTR) gene. We hypothesized that one factor accounting for heterogeneity in pulmonary disease severity is variation in the family of genes affecting the biology of interleukin-1 (IL-1), which impacts acquisition and maintenance of Pseudomonas aeruginosa infection in animal models of chronic infection.We genotyped 58 single nucleotide polymorphisms (SNPs) in the IL-1 gene cluster in 808 CF subjects from the University of North Carolina and Case Western Reserve University (UNC/CWRU) joint cohort. All were homozygous for DeltaF508, and categories of "severe" (cases) or "mild" (control subjects) lung disease were defined by the lowest or highest quartile of forced expired volume (FEV(1)) for age in the CF population. After adjustment for age and gender, genotypic data were tested for association with lung disease severity. Odds ratios (ORs) comparing severe versus mild CF were also calculated for each genotype (with the homozygote major allele as the reference group) for all 58 SNPs. From these analyses, nine SNPs with a moderate effect size, OR < or =0.5 or >1.5, were selected for further testing. To replicate the case-control study results, we genotyped the same nine SNPs in a second population of CF parent-offspring trios (recruited from Children's Hospital Boston), in which the offspring had similar pulmonary phenotypes. For the trio analysis, both family-based and population-based associations were performed.SNPs rs1143634 and rs1143639 in the IL1B gene demonstrated a consistent association with lung disease severity categories (P < 0.10) and longitudinal analysis of lung disease severity (P < 0.10) in CF in both the case-control and family-based studies. In females, there was a consistent association (false discovery rate adjusted joint P-value <0.06 for both SNPs) in both the analysis of lung disease severity in the UNC/CWRU cohort and the family-based analysis of affection status.Our findings suggest that IL1beta is a clinically relevant modulator of CF lung disease.

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Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis.

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Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis.

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