Dataset Information

Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis.

ABSTRACT: As DNA sequencing becomes faster and cheaper, genomics-based approaches are being explored for their use in personalized diagnoses and treatments. Here, we provide a proof of principle for disease monitoring using personal metagenomic sequencing and traditional clinical microbiology by focusing on three adults with cystic fibrosis (CF). The CF lung is a dynamic environment that hosts a complex ecosystem composed of bacteria, viruses, and fungi that can vary in space and time. Not surprisingly, the microbiome data from the induced sputum samples we collected revealed a significant amount of species diversity not seen in routine clinical laboratory cultures. The relative abundances of several species changed as clinical treatment was altered, enabling the identification of the climax and attack communities that were proposed in an earlier work. All patient microbiomes encoded a diversity of mechanisms to resist antibiotics, consistent with the characteristics of multidrug-resistant microbial communities that are commonly observed in CF patients. The metabolic potentials of these communities differed by the health status and recovery route of each patient. Thus, this pilot study provides an example of how metagenomic data might be used with clinical assessments for the development of treatments tailored to individual patients.

SUBMITTER: Lim YW

PROVIDER: S-EPMC3911355 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis.

Lim Yan Wei YW Evangelista Jose S JS Schmieder Robert R Bailey Barbara B Haynes Matthew M Furlan Mike M Maughan Heather H Edwards Robert R Rohwer Forest F Conrad Douglas D

Journal of clinical microbiology 20131120 2

As DNA sequencing becomes faster and cheaper, genomics-based approaches are being explored for their use in personalized diagnoses and treatments. Here, we provide a proof of principle for disease monitoring using personal metagenomic sequencing and traditional clinical microbiology by focusing on three adults with cystic fibrosis (CF). The CF lung is a dynamic environment that hosts a complex ecosystem composed of bacteria, viruses, and fungi that can vary in space and time. Not surprisingly, t ...[more]

PMID: 24478471

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Project description:Lung function, acute pulmonary exacerbations (APE), and weight are the best clinical predictors of survival in cystic fibrosis (CF); however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6) years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD]?=1.75) predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005), number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression) and time-to-lung transplantation or death (HR=1.59, p=0.02). At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26) was significantly associated with APE-associated declines in lung function (-10.8 FEV(1)% points per log-unit GM-CSF, p<0.001 by linear regression). Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM-CSF identifies patients with large acute declines in FEV(1)%, possibly providing a laboratory-based objective decision-support tool for determination of an APE diagnosis. These biomarkers are potential CF reporting tools and treatment targets for slowing long-term progression and reducing short-term severity.

Dataset Information

Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis.

Publications

Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis.

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