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Metabolomics analysis identifies novel plasma biomarkers of cystic fibrosis pulmonary exacerbation.
Laguna, Theresa A; Reilly, Cavan S; Williams, Cynthia B; Welchlin, Cole; Wendt, Chris H.
Afiliación
  • Laguna TA; Department of Pediatrics, University of Minnesota Medical School and The University of Minnesota Masonic Children's Hospital, Minneapolis, Minnesota.
  • Reilly CS; School of Public Health, Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota.
  • Williams CB; Department of Pediatrics, University of Minnesota Medical School and The University of Minnesota Masonic Children's Hospital, Minneapolis, Minnesota.
  • Welchlin C; Department of Pediatrics, University of Minnesota Medical School and The University of Minnesota Masonic Children's Hospital, Minneapolis, Minnesota.
  • Wendt CH; Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Minnesota School of Medicine and Veterans Administration Medical Center, Minneapolis, Minnesota.
Pediatr Pulmonol ; 50(9): 869-77, 2015 Sep.
Article en En | MEDLINE | ID: mdl-26115542
ABSTRACT

BACKGROUND:

Cystic fibrosis (CF) lung disease is characterized by infection, inflammation, lung function decline, and intermittent pulmonary exacerbations. However, the link between pulmonary exacerbation and lung disease progression remains unclear. Global metabolomic profiling can provide novel mechanistic insight into a disease process in addition to putative biomarkers for future study. Our objective was to investigate how the plasma metabolomic profile changes between CF pulmonary exacerbation and a clinically well state.

METHODS:

Plasma samples and lung function data were collected from 25 CF patients during hospitalization for a pulmonary exacerbation and during quarterly outpatient clinic visits. In collaboration with Metabolon, Inc., the metabolomic profiles of matched pair plasma samples, one during exacerbation and one at a clinic visit, were analyzed using gas and liquid chromatography coupled with mass spectrometry. Compounds were identified by comparison to a library of standards. Mixed effects models that controlled for nutritional status and lung function were used to test for differences and principal components analysis was performed.

RESULTS:

Our population had a median age of 27 years (14-39) and had a median FEV1 % predicted of 65% (23-105%). 398 total metabolites were identified and after adjustment for confounders, five metabolites signifying perturbations in nucleotide (hypoxanthine), nucleoside (N4-acetylcytidine), amino acid (N-acetylmethionine), carbohydrate (mannose), and steroid (cortisol) metabolism were identified. Principal components analysis provided good separation between the two clinical phenotypes.

CONCLUSIONS:

Our findings provide putative metabolite biomarkers for future study and allow for hypothesis generation about the pathophysiology of CF pulmonary exacerbation.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Fibrosis Quística / Metaboloma Tipo de estudio: Etiology_studies / Guideline / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Pediatr Pulmonol Asunto de la revista: PEDIATRIA Año: 2015 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Fibrosis Quística / Metaboloma Tipo de estudio: Etiology_studies / Guideline / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Pediatr Pulmonol Asunto de la revista: PEDIATRIA Año: 2015 Tipo del documento: Article