Skip to main content

Association of Circulating Proteins with Death or Lung Transplant in Patients with Idiopathic Pulmonary Fibrosis in the IPF-PRO Registry Cohort

A Correction to this article was published on 15 February 2022

This article has been updated

Abstract

Idiopathic pulmonary fibrosis (IPF) is a progressive and ultimately fatal disease with a variable clinical course. Biomarkers that predict patient outcomes are needed. We leveraged data from 300 patients in the multicenter IPF-PRO Registry to determine associations between circulating proteins and the composite outcome of respiratory death or lung transplant. Plasma collected at enrollment was analyzed using aptamer-based proteomics (1305 proteins). Over a median follow-up of 30.4 months, there were 76 respiratory deaths and 26 lung transplants. In unadjusted univariable analyses, 61 proteins were significantly associated with the outcome (hazard ratio > 2 or < 0.5, corrected p ≤ 0.05). In multivariable analyses, a set of 4 clinical measures and 47 unique proteins predicted the probability of respiratory death or lung transplant with an optimism-corrected C-index of 0.76. Our results suggest that select circulating proteins strongly associate with the risk of mortality in patients with IPF and confer information independent of clinical measures.

Introduction

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a variable clinical course but poor prognosis [1]. Several clinical and radiological characteristics have been associated with mortality in patients with IPF; however, the course of disease for an individual patient remains difficult to predict [2]. The identification and validation of blood biomarkers that are predictive of clinically relevant outcomes in patients with IPF would be of value in improving patient care.

Proteomic profiling plays an important role in the discovery of biomarkers. Patients with IPF have been shown to have a unique peripheral blood proteome [3, 4]. Furthermore, a recent report suggested that the circulating proteome may differentiate patients with IPF who will experience progression over the following 80 weeks from those who will remain stable over this period [5]. We examined the associations between circulating proteins and respiratory death or lung transplant, and the variable importance of circulating proteins as predictors of this outcome, in a cohort of patients from the IPF-PRO Registry.

Methods

Study Cohort

The IPF-PRO Registry is a multi-center US registry that enrolled patients with IPF that was diagnosed or confirmed at the enrolling center in the past 6 months, based on the 2011 ATS/ERS/JRS/ALAT diagnostic guidelines [6]. The design of the IPF-PRO Registry has been described [7]. The current analyses were based on data from 300 patients enrolled between March 2016 and February 2017. Outcomes were ascertained from enrollment to June 2019.

Proteomic Assays

Plasma samples taken at enrollment were assayed using an aptamer-based platform encompassing 1305 proteins (SOMAscan, SOMALogic Inc., Boulder, CO). Protein data were log2 transformed prior to analysis.

Analyses

The univariable association between each protein and the composite outcome of respiratory death or lung transplant was determined using Cox proportional hazards modelling. Linearity and proportional hazards assumptions were assessed prior to fitting each model. Analyses were performed in an unadjusted fashion and adjusted for sex, age, % predicted forced vital capacity (FVC), % predicted diffusing capacity for carbon monoxide (DLco), oxygen use at rest and oxygen use with activity (all assessed at enrollment). p-values were corrected for multiple comparisons using the Benjamini–Hochberg method to control the false discovery rate (FDR) at 5%. Proteins for which the hazard ratio was > 2 or < 0.5 and the FDR-corrected p-value was ≤ 0.05 were regarded as significantly associated with the outcome.

Multivariable analyses using Cox regression modelling with the elastic net penalty identified a set of candidate predictors for the composite outcome of respiratory death or lung transplant. First, only proteins were considered in the pool of potential predictors and second, both proteins and clinical factors (sex, age, % predicted FVC, % predicted DLco, oxygen use at rest, oxygen use with activity [all assessed at enrollment]) were considered. The variable importance of the predictors selected by each model was plotted. The performance of each model was assessed using Harrell’s C-index and the optimism-corrected C-index. For the model including both proteins and clinical factors, the C-indices were also computed in groups based on antifibrotic drug use (i.e. taking or not taking an approved antifibrotic drug for IPF at enrollment). A multivariable model that included only the clinical factors was constructed and the C-index computed, such that its performance could be compared with that of the protein-inclusive models.

Results

Cohort

A total of 300 patients were included. At enrollment, median (Q1, Q3) age was 70 (65, 75) years, 74% were male, 94% were white, 99% were former or current smokers. Median (Q1, Q3) FVC % predicted and DLco % predicted were 69.7 (61.0, 80.2) and 40.5 (31.1, 49.3), respectively. The majority of patients were taking an approved antifibrotic medication for IPF (35% pirfenidone, 19% nintedanib). Median (Q1, Q3) duration of follow-up was 30.4 (20.1, 41.1) months. In total, 76 respiratory deaths and 26 lung transplants occurred.

Relationship Between Circulating Proteins and Respiratory Death or Lung Transplant

In unadjusted univariable analyses, 61 proteins were significantly associated with the composite of respiratory death or lung transplant. After adjustment for clinical factors, 22 proteins remained significantly associated with the composite outcome (Table 1).

Table 1 Circulating proteins associated with respiratory death or lung transplant in patients with IPF in univariable analyses adjusted for clinical factors

In multivariable analyses considering proteins only, a set of 54 proteins predicted the probability of the composite of respiratory death or lung transplant with a C-index of 0.83 (optimism-corrected C-index of 0.76). The variable importance of the selected proteins is shown in Fig. 1. Among the proteins of greatest importance in discriminating the outcome were spondin-1 (SPON1), intracellular adhesion molecule 5 (ICAM5), C-X-C motif chemokine 13 (CXCL13), alpha 2 HS glycoprotein (AHSG) and protein inhibitor of activated STAT4 (PIAS4).

Fig. 1
figure 1

Variable importance of 54 proteins selected using a multivariable model to identify candidate proteins associated with the outcome of respiratory death or lung transplant in patients with IPF. For CKM, two piece-wise linear components are shown

Multivariable analyses considering both proteins and clinical factors identified a set of 51 predictors (47 proteins, 4 clinical factors) with a C-index of 0.84 (optimism-corrected C-index of 0.76). Model performance was similar in patients who were and were not taking antifibrotic therapy at enrollment (C-index 0.84 and optimism-corrected C-index 0.77 in treated patients; C-index 0.82 and optimism-corrected C-index 0.74 in untreated patients). The variable importance of the selected predictors is shown in Fig. 2. In general, the same protein predictors were retained, but all were of lower importance than oxygen use and measures of lung function. Notably, the performance of the model including both proteins and clinical factors was superior to a model that considered only the clinical factors, for which the C-index was 0.75 and the optimism-corrected C-index was 0.73.

Fig. 2
figure 2

Variable importance of 47 proteins and 4 clinical factors selected using a multivariable model to identify candidate predictors of the outcome of respiratory death or lung transplant in patients with IPF. For CKM, two piece-wise linear components are shown

Discussion

In this analysis of data from 300 patients with IPF, we identified several circulating proteins that strongly associated with a composite outcome of respiratory death or lung transplant, after adjusting for clinical variables known to be associated with mortality in this population [8]. Many of these proteins have functions in inflammation, immune activation/regulation, cell–cell adhesion, or pathways reported to play a role in fibrogenesis (e.g. TGF-β signaling, bone morphogenetic protein signaling, Janus kinase signaling).

While some of our findings are consistent with previous data, such as the association between elevated levels of chemokine CXCL13 and reduced survival [9], our analyses identified several additional candidate proteins as biomarkers of mortality risk, including proteins not measured in previous studies. These results extend previous analyses of data from the IPF-PRO Registry that identified several proteins that associated with clinical measures of IPF severity (% predicted FVC, % predicted DLco, composite physiologic index) at enrollment [3]. In the current analyses, each of the proteins that was associated with all three disease severity measures in this prior work (SPON1, ICAM5, roundabout homolog-2 [ROBO2], polymeric immunoglobulin receptor [PIGR]) was selected by the multivariable model that considered both proteins and clinical factors. While none of these proteins has been well characterized in lung fibrosis, it has been shown that ROBO2 is overexpressed in a mouse model of toxin-induced liver fibrosis, and that the interaction between ROBO2 and its ligand promotes fibrogenic activity within stellate cells [10]. Notably, inclusion of the proteins along with the clinical measures enhanced the discriminatory ability of the model compared with a model that included only clinical factors. This suggests that proteins may confer information that is independent from that captured by measures commonly performed in the clinic.

Among the top protein predictors of the composite of respiratory death or lung transplant were AHSG and PIAS4. Higher AHSG levels and lower PIAS4 levels were associated with reduced risk. These proteins have opposing roles in regulating TGF-β signalling, a pathway known to be important in IPF. Thus it is plausible that they may contribute to the development or progression of IPF. In experimental models, AHSG is an antagonist of TGF-β, with animals genetically lacking in AHSG expression showing increased SMAD2 phosphorylation [11, 12]. Furthermore, TGF-β-mediated suppression of immune cell function was exaggerated in AHSG-deplete animals, as shown by inhibition of macrophage activation [12]. In an experimental model of liver fibrosis, PIAS4 silencing blocked recruitment of SMAD3, decreasing pro-fibrotic gene expression and ameliorating hepatic fibrosis [13]. In the context of these experimental data, our findings compel mechanistic and clinical studies to define the contribution of these proteins to the pathogenesis of IPF and clarify their potential as biomarkers of IPF progression.

Strengths of our analysis include the multi-center nature of the cohort and the adjustment for clinical variables known to influence survival in patients with IPF. Our analyses also have limitations. First, the cohort was a population of mainly white patients enrolled at expert centers in the US, thus our findings may not be applicable to all patients with IPF. Second, while a broad array of proteins were analyzed, some potentially important proteins may have been missed as they were not included on the platform. An aptamer-based approach to protein detection does not always produce results that are reproducible using ELISA and analyses using ELISA are planned.

In conclusion, we identified several novel candidate circulating protein biomarkers for predicting respiratory death or lung transplant in patients with IPF. These data underscore the opportunity to develop biomarker-inclusive algorithms that provide meaningful risk stratification for patients with IPF.

Data Availability

All the data relevant to the study are included in the article.

Code Availability

Not applicable.

Change history

References

  1. Raghu G, Remy-Jardin M, Myers JL et al (2018) Diagnosis of idiopathic pulmonary fibrosis. An official ATS/ERS/JRS/ALAT clinical practice guideline. Am J Respir Crit Care Med 198:e44–e68

    Article  Google Scholar 

  2. Wuyts WA, Wijsenbeek M, Bondue B et al (2020) Idiopathic pulmonary fibrosis: best practice in monitoring and managing a relentless fibrotic disease. Respiration 99:73–82

    Article  Google Scholar 

  3. Todd JL, Neely ML, Overton R et al (2019) Peripheral blood proteomic profiling of idiopathic pulmonary fibrosis biomarkers in the multicentre IPF-PRO Registry. Respir Res 20:227

    Article  Google Scholar 

  4. O’Dwyer DN, Norman KC, Xia M et al (2017) The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes. Sci Rep 7:46560

    Article  Google Scholar 

  5. Norman KC, O’Dwyer DN, Salisbury ML et al (2020) Identification of a unique temporal signature in blood and BAL associated with IPF progression. Sci Rep 10:12049

    CAS  Article  Google Scholar 

  6. Raghu G, Collard HR, Egan JJ et al (2011) An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 183:788–824

    Article  Google Scholar 

  7. O’Brien EC, Durheim MT, Gamerman V et al (2016) Rationale for and design of the Idiopathic Pulmonary Fibrosis–PRospective Outcomes (IPF-PRO) Registry. BMJ Open Respir Res 3:e000108

    Article  Google Scholar 

  8. Snyder L, Neely ML, Hellkamp AS et al (2019) Predictors of death or lung transplant after a diagnosis of idiopathic pulmonary fibrosis: insights from the IPF-PRO Registry. Respir Res 20:105

    Article  Google Scholar 

  9. Vuga LJ, Tedrow JR, Pandit KV et al (2014) C-X-C motif chemokine 13 (CXCL13) is a prognostic biomarker of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 189:966–974

    CAS  Article  Google Scholar 

  10. Zeng Z, Wu Y, Cao Y et al (2018) Slit2-Robo2 signaling modulates the fibrogenic activity and migration of hepatic stellate cells. Life Sci 203:39–47

    CAS  Article  Google Scholar 

  11. Szweras M, Liu D, Partridge EA et al (2002) α2-HS glycoprotein/fetuin, a transforming growth factor-β/bone morphogenetic protein antagonist, regulates postnatal bone growth and remodeling. J Biol Chem 277:19991–19997

    CAS  Article  Google Scholar 

  12. Swallow CJ, Partridge EA, Macmillan JC et al (2004) α2HS-glycoprotein, an antagonist of transforming growth factor in vivo, inhibits intestinal tumor progression. Cancer Res 64:6402–6409

    CAS  Article  Google Scholar 

  13. Xu H, Fan Z, Tian W, Xu Y (2016) Protein inhibitor of activated STAT 4 (PIAS4) regulates liver fibrosis through modulating SMAD3 activity. J Biomed Res 30:496–501

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the principal investigators and enrolling centers in the IPF-PRO Registry. The authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors (ICMJE). The authors did not receive payment for development of this article. Writing support was provided by Elizabeth Ng and Wendy Morris of Fleishman-Hillard, London, UK, which was contracted and funded by Boehringer Ingelheim Pharmaceuticals, Inc. Boehringer Ingelheim was given the opportunity to review the article for medical and scientific accuracy as well as intellectual property considerations.

Funding

The IPF-PRO™ Registry is funded by Boehringer Ingelheim Pharmaceuticals, Inc. and coordinated by the Duke Clinical Research Institute.

Author information

Authors and Affiliations

Authors

Consortia

Contributions

JLT, MLN, RO, HM, TBL, CH and SMP were involved in the design of the study. JAL, JAdA, MG, HH, IN, JAB and KRF were involved in data acquisition. MLN, RO and HM were involved in data analysis. All the authors were involved in the interpretation of the data and in the writing and critical review of the manuscript and have approved the final version.

Corresponding author

Correspondence to Jamie L. Todd.

Ethics declarations

Conflict of interest

The authors have reported to Lung the following conflicts of interest: JLT, MLN, RO, HM and SMP are employees of the Duke Clinical Research Institute, which was funded by Boehringer Ingelheim Pharmaceuticals, Inc to conduct this research. JR reports grants and personal fees from Boehringer Ingelheim and grants from Genentech, Galapagos, Syneos Health, Bellerophon Therapeutics, FibroGen, and the National Institutes of Health. JAL reports personal fees from Biogen, Boehringer Ingelheim, Galecto, Roche/Genentech and Veracyte. JAdA reports personal fees from Boehringer Ingelheim. MG reports personal fees, non-financial support, and other support from the France Foundation; grants, non-financial support and other support from Boehringer Ingelheim and the Pulmonary Fibrosis Foundation; and personal fees from Genentech. HH is on a speaker panel for Boehringer Ingelheim. IN reports personal fees from Boehringer Ingelheim, Genentech, and ImmuneWorks. JAB has no disclosures. KRF reports grants and personal fees from Boehringer Ingelheim and Roche/Genentech and personal fees from FibroGen, Sanofi, Genzyme, and Veracyte. TBL was an employee of Boehringer Ingelheim at the time this study was conducted. CH is an employee of Boehringer Ingelheim.

Ethical Approval

The IPF-PRO Registry was approved by the Duke University Institutional Review Board (Pro00046131). The IPF-PRO Registry protocol was also approved by the relevant Institutional Review Boards and/or local Independent Ethics Committees prior to patient enrolment at each site.

Consent to Participate

All patients provided informed consent.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised due to retrospective OA order.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Todd, J.L., Neely, M.L., Overton, R. et al. Association of Circulating Proteins with Death or Lung Transplant in Patients with Idiopathic Pulmonary Fibrosis in the IPF-PRO Registry Cohort. Lung 200, 11–18 (2022). https://doi.org/10.1007/s00408-021-00505-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00408-021-00505-y

Keywords

  • Biomarkers
  • Interstitial lung diseases
  • Observational study
  • Proteomics