Peripheral blood proteomic profiling of idiopathic pulmonary fibrosis biomarkers in the multicentre IPF-PRO Registry

Autor: Kevin R. Flaherty, Timothy P.M. Whelan, Jesse Roman, Nishant Gupta, David J. Lederer, Yolanda Mageto, Maryl Kreider, Paul Sachs, Hyun J Kim, Joseph A. Lasky, Imre Noth, Ramona Schmid, Sally Suliman, Zeenat Safdar, Mridu Gulati, Christian Hesslinger, Prema Menon, L. Kristin Newby, Robert Overton, Andrew Namen, Leann Silhan, Lake Morrison, Thomas Leonard, John A. Belperio, Marilyn K. Glassberg, Albert Baker, Daniel A. Culver, Scott M. Palmer, Francis Cordova, Rishi Raj, Scott Beegle, Benjamin Strobel, Justin M. Oldham, Mary E. Strek, Tristan J. Huie, Daniel F. Dilling, Jamie L. Todd, Robert J. Kaner, Richard Vinisko, David Hotchkin, Lisa Lancaster, Timothy Liesching, Barry Sigal, Jason Lobo, Kalpalatha Guntupalli, Yi Liu, Megan L. Neely, Joao A. de Andrade, Amy Hajari Case, Doug Lee, Randolph J. Lipchik, Katey Durham, Rajat Walia, Murali Ramaswamy, Tonya D. Russell, Howard J. Huang, Jeremy Tabak, Wael Asi, Rany Condos, Janine Roy
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Respiratory Research, Vol 20, Iss 1, Pp 1-13 (2019)
Respiratory Research
Popis: Background Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease for which diagnosis and management remain challenging. Defining the circulating proteome in IPF may identify targets for biomarker development. We sought to quantify the circulating proteome in IPF, determine differential protein expression between subjects with IPF and controls, and examine relationships between protein expression and markers of disease severity. Methods This study involved 300 patients with IPF from the IPF-PRO Registry and 100 participants without known lung disease. Plasma collected at enrolment was analysed using aptamer-based proteomics (1305 proteins). Linear regression was used to determine differential protein expression between participants with IPF and controls and associations between protein expression and disease severity measures (percent predicted values for forced vital capacity [FVC] and diffusion capacity of the lung for carbon monoxide [DLco]; composite physiologic index [CPI]). Multivariable models were fit to select proteins that best distinguished IPF from controls. Results Five hundred fifty one proteins had significantly different levels between IPF and controls, of which 47 showed a |log2(fold-change)| > 0.585 (i.e. > 1.5-fold difference). Among the proteins with the greatest difference in levels in patients with IPF versus controls were the glycoproteins thrombospondin 1 and von Willebrand factor and immune-related proteins C-C motif chemokine ligand 17 and bactericidal permeability-increasing protein. Multivariable classification modelling identified nine proteins that, when considered together, distinguished IPF versus control status with high accuracy (area under receiver operating curve = 0.99). Among participants with IPF, 14 proteins were significantly associated with FVC % predicted, 23 with DLco % predicted, 14 with CPI. Four proteins (roundabout homolog-2, spondin-1, polymeric immunoglobulin receptor, intercellular adhesion molecule 5) demonstrated the expected relationship across all three disease severity measures. When considered in pathways analyses, proteins associated with the presence or severity of IPF were enriched in pathways involved in platelet and haemostatic responses, vascular or platelet derived growth factor signalling, immune activation, and extracellular matrix organisation. Conclusions Patients with IPF have a distinct circulating proteome and can be distinguished using a nine-protein profile. Several proteins strongly associate with disease severity. The proteins identified may represent biomarker candidates and implicate pathways for further investigation. Trial registration ClinicalTrials.gov (NCT01915511).
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje