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. 2015 Sep;50(9):869-77.
doi: 10.1002/ppul.23225. Epub 2015 Jun 26.

Metabolomics analysis identifies novel plasma biomarkers of cystic fibrosis pulmonary exacerbation

Theresa A Laguna  1 , Cavan S Reilly  2 , Cynthia B Williams  1 , Cole Welchlin  1 , Chris H Wendt  3
Affiliations

Metabolomics analysis identifies novel plasma biomarkers of cystic fibrosis pulmonary exacerbation

Theresa A Laguna et al. Pediatr Pulmonol. 2015 Sep.

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.

Keywords: infection; inflammation; lung function.

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Conflict of interest statement

Conflict of interest: None.

Figures

Fig. 1
Fig. 1
Nucleotide and Nucleoside Metabolism: (A) Plasma concentration of hypoxanthine is decreased during CF pulmonary exacerbation (SICK) compared to outpatient clinic (WELL) (fold change 0.605, P = 0.0100, q = 0.2211). (B) Plasma concentration of N4-acetylcytidine is also decreased during CF pulmonary exacerbation (fold change 0.681, P = 3.00 × 10−0.4, q = 0.0291). ○ = data point outside of the 1.5 intra-quartile range.
Fig. 2
Fig. 2
Amino Acid Metabolism: Plasma concentration of N-acetylmethionine is decreased during CF pulmonary exacerbation (SICK) compared to outpatient clinic (WELL), (fold change 0.704, P = 1.70 × 10−0.4, q = 0.0219). ○ = data point outside of the 1.5 intra-quartile range.
Fig. 3
Fig. 3
Carbohydrate Metabolism: Plasma concentration of mannose is decreased during CF pulmonary exacerbation (SICK) compared to outpatient clinic (WELL), (fold change = 0.531, P = 1.25 × 10−0.4, q = 0.0219). ○ = data point outside of the 1.5 intra-quartile range.
Fig. 4
Fig. 4
Steroid Metabolism: Plasma concentration of cortisol is decreased during CF pulmonary exacerbation (SICK) compared to outpatient clinic (WELL), (fold change = 0.528, P = 6.34 × 10−0.4, q = 0.0492). ○ = data point outside of the 1.5 intra-quartile range.
Fig. 5
Fig. 5
Principal components analysis utilizing our five identified metabolites shows good separation between a pulmonary exacerbation state (SICK) and a clinically stable state (WELL). ○ = WELL, Δ = SICK.
See this image and copyright information in PMC

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