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

Authors :
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
Source :
Respiratory Research, Vol 20, Iss 1, Pp 1-13 (2019), Respiratory Research
Publication Year :
2019
Publisher :
BMC, 2019.

Abstract

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).

Details

Language :
English
Volume :
20
Issue :
1
Database :
OpenAIRE
Journal :
Respiratory Research
Accession number :
edsair.doi.dedup.....df84770616a5ca14bb44e290d3510a49
Full Text :
https://doi.org/10.1186/s12931-019-1190-z