Utilizing centralized biorepository samples for biomarkers of cystic fibrosis lung disease severity

J Cyst Fibros. 2020 Jul;19(4):632-640. doi: 10.1016/j.jcf.2019.12.007. Epub 2019 Dec 20.


Background: Circulating biomarkers reflective of lung disease activity and severity have the potential to improve patient care and accelerate drug development in CF. The objective of this study was to leverage banked specimens to test the hypothesis that blood-based biomarkers discriminate CF children segregated by lung disease severity.

Methods: Banked serum samples were selected from children who were categorized into two extremes of phenotype associated with lung function ('mild' or 'severe') based on CF-specific data and were matched on age, gender, CFTR genotype, and P. aeruginosa infection status. Targeted inflammatory proteins, lipids, and discovery metabolite profiles were measured in these serum samples.

Results: The severe cohort, characterized by a lower CF-specific FEV1 percentile, had significantly higher circulating concentrations of high sensitivity C-reactive protein, serum amyloid A, granulocyte colony stimulating factor, and calprotectin compared to the mild cohort. The mild cohort tended to have higher serum linoleic acid concentrations. The metabolite arabitol was lower in the severe cohort while other CF relevant metabolic pathways showed non-significant differences after adjusting for multiple comparisons. A sensitivity analysis to correct for biased estimates that may result from selecting subjects using an extremes of phenotype approach confirmed the protein biomarker findings.

Conclusions: Circulating inflammatory proteins differ in CF children segregated by lung function. These findings serve to demonstrate the value of maintaining centralized, high quality patient derived samples for future research, with linkage to clinical information to answer testable hypotheses in biomarker development.

Keywords: Biomarkers; Cystic fibrosis; Lipids; Metabolomics; Proteins.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural