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

Abstract

BackgroundIdiopathic 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.MethodsThis 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.ResultsFive 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.ConclusionsPatients 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 registrationClinicalTrials.gov (NCT01915511).

Identification of a unique temporal signature in blood and BAL associated with IPF progression

“…Evaluating signature components allowed for further investigation of potential proteomic relationships and pathways associated with progression. Our identified signature was enriched for processes involving immune system regulation in non-progressors, which echoes results from other studies 20 , 22 , 23 , and also included 4 of the 6 proteins previously identified in the COMET cohort as an index of IPF progression 20 . The complement cascade has also previously been associated with IPF disease severity 22 .…”

“…Our identified signature was enriched for processes involving immune system regulation in non-progressors, which echoes results from other studies 20,22,23 , and also included 4 of the 6 proteins previously identified in the COMET cohort as an index of IPF progression 20 . The complement cascade has also previously been associated with IPF disease severity 22 . Interestingly, our identified signature did not include MMP-7, which has been linked to IPF progression in several other studies 21,23,34 , though some proteins in our signature did have proteolytic function (legumain, PSD7).…”

“…The use of quantitative approaches to capture individual proteins within large clinical “omics” data sets has become a useful way to find new proteins associated with disease progression. Groups of proteins associated with progression that were identified by these approaches were characterized by biologically relevant functions, such as involvement in the immune system 20 – 22 , tissue reorganization 20 , 21 , 23 , and epithelial cell function 23 . While these results have highlighted potential prognostic biomarkers and biological functions associated with IPF progression, many of the techniques used in these discoveries emphasize the additive significance of each protein’s individual ability to differentiate progression status but do not capture protein “signatures”, or take into account potential protein networks associated with progression.…”

HSP90 Inhibition and Modulation of the Proteome: Therapeutical Implications for Idiopathic Pulmonary Fibrosis (IPF)

“…The IPF-PRO registry, a multicenter cohort study, analyzed over 1300 proteins in peripheral blood of patients with IPF and compared them to healthy controls, identifying nine proteins that accurately distinguished patients with IPF from controls. The circulating proteome differed for apolipoprotein A-1 (APOA1), complement C1r subcomponent, intracellular adhesion molecule 5 (ICAM5), C-C motif chemokine 18, 14-3-3 protein sigma (SFN), sonic hedgehog protein, oxidized low-density lipoprotein receptor 1, matrix metalloproteinase 3 (MMP3), macrophage-capping protein, and heat shock protein 90 beta-1 (HSP90β1) [49] (Table 1). Even though the profile of circulating proteins differs from lung proteins, it can still provide insight into biological pathways linked to a persistent overexpression of inflammatory markers, adhesion molecules, complement proteins and HSPs.…”

Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis

“…Transcriptomics studies of patients with IPF have demonstrated that transcriptional changes are involved in the pathophysiologic mechanisms of these diseases (Yang et al, 2007;Zuo et al, 2002). Genes that are differentially expressed in different groups are almost always associated with a particular disease phenotype (Huang et al, 2015;Konishi et al, 2009;Todd et al, 2019). Yang and colleagues (2013) analyzed the transcriptional profiles of lung tissue, collected from IPF patients and non-diseased controls, and found that the elevated expression of cilium genes was associated with more extensive microscopic honeycombing.…”