title: The influence of radiographic phenotype and smoking status on peripheral blood biomarker patterns in chronic obstructive pulmonary disease.
abstract: BACKGROUND
  Chronic obstructive pulmonary disease (COPD) is characterized by both airway remodeling and parenchymal destruction. The identification of unique biomarker patterns associated with airway dominant versus parenchymal dominant patterns would support the existence of unique phenotypes representing independent biologic processes. A cross-sectional study was performed to examine the association of serum biomarkers with radiographic airway and parenchymal phenotypes of COPD.
  
  
  RESULTS
  Serum from 234 subjects enrolled in a CT screening cohort was analyzed for 33 cytokines and growth factors using a multiplex protein array. The association of serum markers with forced expiratory volume in one second percent predicted (FEV1%) and quantitative CT measurements of airway thickening and emphysema was assessed with and without stratification for current smoking status. Significant associations were found with several serum inflammatory proteins and measurements of FEV1%, airway thickening, and parenchymal emphysema independent of smoking status. The association of select analytes with airway thickening and emphysema was independent of FEV1%. Furthermore, the relationship between other inflammatory markers and measurements of physiologic obstruction or airway thickening was dependent on current smoking status.
  
  
  CONCLUSIONS
  Airway and parenchymal phenotypes of COPD are associated with unique systemic serum biomarker profiles. Serum biomarker patterns may provide a more precise classification of the COPD syndrome, provide insights into disease pathogenesis and identify targets for novel patient-specific biological therapies.
authors.affiliation: Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. bonjm@upmc.edu
authors.forename: Jessica M
authors.initials: JM
authors.lastname: Bon
authors.forename: Joseph K
authors.initials: JK
authors.lastname: Leader
authors.forename: Joel L
authors.initials: JL
authors.lastname: Weissfeld
authors.forename: Harvey O
authors.initials: HO
authors.lastname: Coxson
authors.forename: Bin
authors.initials: B
authors.lastname: Zheng
authors.forename: Robert A
authors.initials: RA
authors.lastname: Branch
authors.forename: Venkateswarlu
authors.initials: V
authors.lastname: Kondragunta
authors.forename: Janet S
authors.initials: JS
authors.lastname: Lee
authors.forename: Yingze
authors.initials: Y
authors.lastname: Zhang
authors.forename: Augustine M K
authors.initials: AM
authors.lastname: Choi
authors.forename: Anna E
authors.initials: AE
authors.lastname: Lokshin
authors.forename: Naftali
authors.initials: N
authors.lastname: Kaminski
authors.forename: David
authors.initials: D
authors.lastname: Gur
authors.forename: Frank C
authors.initials: FC
authors.lastname: Sciurba
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood*; D015331:Cohort Studies; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D008297:Male; D008875:Middle Aged; D029424:Pulmonary Disease, Chronic Obstructive / Q000097:blood* / Q000000981:diagnostic imaging / Q000503:physiopathology; D012907:Smoking / Q000097:blood*; D014057:Tomography, X-Ray Computed
chemical_list: D015415:Biomarkers