Identification of molecular signatures of cystic fibrosis disease status with plasma-based functional genomics Academic Article uri icon

abstract

  • Although cystic fibrosis (CF) is attributed to dysfunction of a single gene, the relationships between the abnormal gene product and the development of inflammation and progression of lung disease are not fully understood, which limits our ability to predict an individual patient's clinical course and treatment response. To better understand CF progression, we characterized the molecular signatures of CF disease status with plasma-based functional genomics. Peripheral blood mononuclear cells (PBMCs) from healthy donors were cultured with plasma samples from CF patients ( n = 103) and unrelated, healthy controls ( n = 31). Gene expression levels were measured with an Affymetrix microarray (GeneChip Human Genome U133 Plus 2.0). Peripheral blood samples from a subset of the CF patients ( n = 40) were immunophenotyped by flow cytometry, and the data were compared with historical data for age-matched healthy controls ( n = 351). Plasma samples from another subset of CF patients ( n = 56) and healthy controls ( n = 16) were analyzed by multiplex enzyme-linked immunosorbent assay (ELISA) for numerous cytokines and chemokines. Principal component analysis and hierarchical clustering of induced transcriptional data revealed disease-specific plasma-induced PBMC profiles. Among 1,094 differentially expressed probe sets, 51 genes were associated with pancreatic sufficient status, and 224 genes were associated with infection with Pseudomonas aeruginosa. The flow cytometry and ELISA data confirmed that various immune modulators are relevant contributors to the CF molecular signature. This study provides strong evidence for distinct molecular signatures among CF patients. An understanding of these molecular signatures may lead to unique molecular markers that will enable more personalized prognoses, individualized treatment plans, and rapid monitoring of treatment response.

altmetric score

  • 36.5

author list (cited authors)

  • Levy, H., Jia, S., Pan, A., Zhang, X. i., Kaldunski, M., Nugent, M. L., ... Hessner, M. J.

citation count

  • 8

publication date

  • January 2019