title: Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF.
abstract: BACKGROUND
  Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF.
  
  
  METHODS
  Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer) array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC) curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC) when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold.
  
  
  RESULTS
  A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2), cathepsin-S (Cath-S), legumain (LGMN) and soluble vascular endothelial growth factor receptor 2 (VEGFsR2), but low levels of inducible T cell costimulator (ICOS) or trypsin 3 (TRY3)] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2) was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2-126.7, P = 0.006).
  
  
  CONCLUSIONS
  This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression.
authors.affiliation: Graduate Program in Immunology, University of Michigan, Ann Arbor, MI, United States of America.
authors.forename: Shanna L
authors.initials: SL
authors.lastname: Ashley
authors.affiliation: Biostatistics Department, University of Michigan School of Public Health, Ann Arbor, MI, United States of America.
authors.forename: Meng
authors.initials: M
authors.lastname: Xia
authors.affiliation: Biostatistics Department, University of Michigan School of Public Health, Ann Arbor, MI, United States of America.
authors.forename: Susan
authors.initials: S
authors.lastname: Murray
authors.affiliation: Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States of America.
authors.forename: David N
authors.initials: DN
authors.lastname: O'Dwyer
authors.affiliation: MedImmune, Gaithersburg, MD, United States of America.
authors.forename: Ethan
authors.initials: E
authors.lastname: Grant
authors.affiliation: Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States of America.
authors.forename: Eric S
authors.initials: ES
authors.lastname: White
authors.affiliation: Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States of America.
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Flaherty
authors.affiliation: Department of Internal Medicine, Weill Cornell Medical College, New York, NY, United States of America.
authors.forename: Fernando J
authors.initials: FJ
authors.lastname: Martinez
authors.affiliation: Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States of America.|Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, United States of America.
authors.forename: Bethany B
authors.identifier: http://orcid.org/0000-0003-3051-745X
authors.initials: BB
authors.lastname: Moore
mesh_terms: D000368:Aged; D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood; D002403:Cathepsins / Q000378:metabolism; D003546:Cysteine Endopeptidases / Q000378:metabolism; D018450:Disease Progression; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D054990:Idiopathic Pulmonary Fibrosis / Q000276:immunology / Q000378:metabolism / Q000473:pathology*; D060889:Inducible T-Cell Co-Stimulator Protein / Q000378:metabolism; D037102:Lectins / Q000378:metabolism; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010447:Peptide Hydrolases / Q000378:metabolism*; D016016:Proportional Hazards Models; D012372:ROC Curve; D012720:Severity of Illness Index; D012907:Smoking; D040301:Vascular Endothelial Growth Factor Receptor-2 / Q000378:metabolism; D000097604:Ficolins; D000099240:Asparaginyl Endopeptidase
chemical_list: D015415:Biomarkers; D002403:Cathepsins; D003546:Cysteine Endopeptidases; D060889:Inducible T-Cell Co-Stimulator Protein; D037102:Lectins; D010447:Peptide Hydrolases; D040301:Vascular Endothelial Growth Factor Receptor-2; D000097604:Ficolins; D000099240:Asparaginyl Endopeptidase; C000588866:KDR protein, human