Abstract
Background
Prostasin is expressed in the lung epithelium where it regulates fluid and electrolyte balance via sodium channel proteolysis. We investigated whether circulating prostasin levels are associated with the presence and severity of idiopathic pulmonary fibrosis (IPF) and whether prostasin levels, or changes in them, are associated with mortality.
Methods
Patients with IPF came from the IPF-PRO Registry. Controls without lung disease had a similar age/sex distribution. Prostasin was quantified in plasma taken at enrolment and, in the IPF cohort, ∼6 months post-enrolment, by immunoassay. Linear regression was used to compare prostasin levels at enrolment in patients with IPF versus controls and, in the IPF cohort, determine associations between prostasin level and lung function. Multivariable Cox proportional hazards models determined associations between prostasin level at enrolment and change in prostasin level over 6 months and respiratory death.
Results
Prostasin level at enrolment was higher in patients with IPF (n=624) versus controls (n=100) (fold-difference 1.75; p<0.001). In the IPF cohort, the difference in disease severity per 1 standard deviation (sd) difference in prostasin was −3.85 for forced vital capacity % predicted and −4.24 for diffusing capacity of the lung for carbon monoxide % predicted (both p<0.001). The adjusted hazard ratio (HR) for respiratory death per 1 sd difference in prostasin at enrolment was 1.20 (95% CI 1.04–1.40, p=0.014, n=624). The adjusted HR for subsequent respiratory death per 1 sd difference in change in prostasin over 6 months was 1.33 (95% CI 1.01–1.74, p=0.041, n=290).
Conclusions
Circulating prostasin is an independent marker of mortality risk in patients with IPF.
Shareable abstract
In patients with idiopathic pulmonary fibrosis in the IPF-PRO Registry, the circulating level of prostasin was an independent marker of mortality risk https://bit.ly/3D0Vmhx
Introduction
Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease (ILD) associated with decline in lung function and high mortality [1]. IPF has a variable clinical course and there remains an unmet need to identify prognostic biomarkers. The pathobiology of IPF is believed to involve aberrant responses in airway and alveolar epithelial cells. These cells may serve as sensors, integrating the complex interplay of genetic and environmental risk factors, processes associated with ageing and profibrotic responses to injury [2, 3]. Epithelial-derived protein biomarkers have shown promise with regard to risk stratification in patients with IPF [4–7].
Prostasin is a trypsin-like serine protease expressed in epithelial cells where it regulates fluid and electrolyte balance via sodium channel proteolysis [8] and modulates signalling mediated by the epidermal growth factor receptor [9]. In a prospective study, a higher level of circulating prostasin was associated with the presence of IPF, but not with progression of IPF over 12 months [10]. In a study of 385 patients with progressive fibrosing ILDs other than IPF, prostasin was selected as part of a multiprotein signature that predicted 12-month progression [11]. In a recent analysis of data from 871 patients with IPF in the Pulmonary Fibrosis Foundation patient registry, prostasin was among the proteins most strongly associated with 3-year transplant-free survival [12]. While these studies have identified prostasin as a potential prognostic biomarker in patients with ILDs, they have largely relied on semi-quantitative data generated by proximity extension assays. Weak correlations have been observed between some proteins measured by such methods compared to quantitative assays [12], suggesting that they have poor specificity. In addition, it remains uncertain whether longitudinal measurement of prostasin could add prognostic information over a single measurement, or whether the use of antifibrotic therapies influences prostasin levels or their prognostic significance.
The IPF-PRO Registry is a multicentre US registry of patients with IPF [13]. We used data from this registry to investigate associations between prostasin levels and the presence and severity of IPF and between prostasin levels at enrolment and during early follow-up and mortality.
Materials and methods
Study population
Patients with IPF that was diagnosed or confirmed at the enrolling centre in the past 6 months were enrolled into the IPF-PRO Registry (NCT01915511) at 46 sites across the USA. Data for this analysis came from 624 patients with prostasin measurements at enrolment, of whom 292 (46.8%) also had a prostasin measurement at 6±3 months post-enrolment, with most samples collected within 1 month of the 6-month timepoint (supplementary figure S1). A control cohort was drawn from the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) study, a longitudinal cohort study of adults in North Carolina in which self-reported health information and biological samples are collected [14]. The control cohort comprised 100 individuals of similar age, sex and smoking status distribution to the IPF cohort without known lung disease (see supplementary material).
The IPF-PRO Registry obtained ethics approval at the data coordinating centre (Duke Clinical Research Institute, Duke Institutional Review Board Protocol Number Pro00046131) and at every enrolling centre (listed in the Acknowledgements). Ethics approval was granted by the Duke Institutional Review Board Protocol Number Pro00082241 to use the biosamples obtained as part of the IPF-PRO Registry for the analyses contained herein. All participants provided written informed consent. The MURDOCK study community registry and biorepository was approved by the Duke University Health Institutional Review Board (Pro00011196), and all participants provided written informed consent.
Prostasin quantification
Prostasin levels were quantified in plasma samples using immunoassay (Myriad RBM, Austin, TX, USA). All samples rendered values (µg·L−1) within the range of assay detection.
Statistical analysis
Descriptive statistics were used to analyse baseline characteristics in the IPF and control cohorts. Linear regression was used to compare prostasin levels between the IPF cohort (overall and by use of antifibrotic therapy (nintedanib or pirfenidone) at enrolment) and the control cohort. Scatter plots and Spearman's correlation coefficients (rho) were used to describe relationships between prostasin level and continuous measures of disease severity at enrolment including forced vital capacity (FVC) and diffusing capacity of the lung for carbon monoxide (DLCO) % predicted. Linear regression was used to determine associations between prostasin level and continuous measures of disease severity, reported as the difference in disease severity per 1 standard deviation (sd) difference in prostasin level. These analyses were performed in the overall cohort unadjusted and adjusted for use of antifibrotic therapy at enrolment.
The cumulative incidence of respiratory death stratified by prostasin level above or below the median at enrolment was described in the overall IPF cohort and in subsets by use of antifibrotic therapy at enrolment. Cox proportional hazards models, unadjusted and adjusted for age, sex, FVC % predicted and DLCO % predicted at enrolment, were used to determine the association between prostasin level at enrolment and respiratory death in the overall IPF cohort. The area under the receiver operating curve (ROC) was computed at 12 and 24 months after enrolment to assess the discriminative ability of the adjusted model for respiratory death.
The absolute change in prostasin between enrolment and 6 months was described in the overall IPF cohort and in subsets defined by the pattern of antifibrotic therapy (continued antifibrotic therapy, initiated antifibrotic therapy, or remained untreated) over the same period. Correlations between the absolute change in prostasin over 0–6 months and absolute changes in FVC % predicted and DLCO % predicted over 0–6 months and 0–12 months were assessed using the Spearman correlation coefficient. Associations between absolute change in prostasin over 0–6 months and subsequent respiratory death were analysed using Cox proportional hazards models landmarked at the follow-up sample collection date. In a minimally adjusted model, the model was adjusted for the enrolment prostasin level only. In a fully adjusted model, the model was adjusted for prostasin, age, sex, FVC % predicted and DLCO % predicted, all assessed at enrolment. The area under the ROC was computed at 12 and 24 months after the follow-up sample to assess the discriminative ability of the adjusted model for respiratory death.
To understand internal validity, for the baseline and longitudinal risk modelling two-step iterative resampling was used to test the internal validity of the associations. The analysis cohort was randomly split into discovery and replication cohorts in a 7:3 ratio and 100 random splits were taken. The model was considered validated if p1<α1=0.1 and p2<α2=0.5 in split1 and split2, respectively [15]. We assessed the proportion of 100 random splits where the association was validated. Findings were to be considered internally robust if they were replicated in ≥20% of the random splits [15].
As prostasin is known to be expressed in male tissues (i.e. testes, prostate) [16], for all models, interactions between prostasin and sex were examined. In the event of a significant interaction (interaction p-value <0.05), results were presented overall and stratified by sex.
Multiple imputation was used to account for missing data for adjustment covariates and missing data were filled in five times to generate five complete data sets as per the Full Conditional Specification method. The five complete data sets were analysed using the models described above, and the results from the five complete datasets were combined using Rubin's rules to produce the final inferential results [17].
Results
Cohort characteristics
At enrolment, the IPF cohort (n=624) had a mean±sd age of 69.8±7.8 years; 74.4% were male, 91.1% were white and 66.8% had a history of smoking (table 1). Mean±sd FVC % predicted and DLCO % predicted were 72.5±18.5 and 43.6±15.1, respectively. Almost half (48.4%) of the cohort were taking antifibrotic therapy (table 1). In the control cohort (n=100), the mean±sd age was 66.7±5.2 years, 74.0% were male, all subjects were white, and 68.0% had a history of smoking.
TABLE 1.
Characteristics of the idiopathic pulmonary fibrosis cohort at enrolment (n=624)
| Age years | 69.8±7.8 |
| Male | 464 (74.4) |
| White# | 500 (91.1) |
| Ever-smoker ¶ | 416 (66.8) |
| FVC % predicted | 72.5±18.5 |
| DLCO % predicted | 43.6±15.1 |
| Taking antifibrotic therapy | 302 (48.4) |
| Nintedanib | 157 (25.2) |
| Pirfenidone | 145 (23.2) |
Data are presented as n (%) or mean±sd. FVC: forced vital capacity; DLCO: diffusing capacity of the lung for carbon monoxide. #: n=549 analysed. ¶: n=623 analysed.
Prostasin level and IPF presence/severity
At enrolment, the mean±sd prostasin level was 466.3±158.8 µg·L−1 in the IPF cohort and 267.0±107.6 µg·L−1 in the control cohort (figure 1). The prostasin level was significantly higher in patients with IPF versus controls (fold-difference 1.75; p<0.001), a finding that was similar in both females and males (fold-differences of 2.08, p<0.001 and 1.66, p<0.001, respectively). The prostasin level was higher in patients with IPF versus controls regardless of use of antifibrotic therapy (supplementary table S1).
FIGURE 1.
Prostasin levels at enrolment in the control and idiopathic pulmonary fibrosis (IPF) cohorts. Markers in the boxes denote means, midlines of the boxes medians, boundaries of the boxes 25th and 75th percentiles, whiskers minimum and maximum values.
In the IPF cohort, prostasin levels were higher among patients with lower FVC or DLCO % predicted at enrolment (figure 2). The difference in disease severity per 1 sd difference in prostasin level was −3.85 for FVC % predicted and −4.24 for DLCO % predicted (both p<0.001). These associations were similar after adjustment for use of antifibrotic therapy (−3.85 for FVC % predicted and −4.28 for DLCO % predicted). There was a significant interaction between enrolment prostasin level and sex with respect to FVC % predicted (interaction p=0.002), with a difference in FVC % predicted per 1 sd difference in prostasin level of −3.22 in females and −4.10 in males. There was no significant interaction between enrolment prostasin and sex with respect to DLCO % predicted (interaction p=0.129).
FIGURE 2.
Scatter plots of prostasin level and a) forced vital capacity (FVC) % predicted or b) diffusing capacity of the lung for carbon monoxide (DLCO) % predicted at enrolment. Spearman correlation coefficients with 95% confidence intervals are shown and the fitted linear regression model is overlaid.
Prostasin level and respiratory death
Over a median follow-up of 37.2 months, the cumulative incidence of respiratory death was higher among patients with a prostasin level above versus below the median at enrolment (figure 3a). This finding was consistent between patients taking versus not taking antifibrotic therapy at enrolment (figure 3b). Among all patients, enrolment prostasin level was significantly associated with a higher risk for respiratory death (adjusted hazard ratio (HR) per 1 sd difference in prostasin level 1.20; 95% CI 1.04–1.40; p=0.014) (supplementary figure S2). Two-step iterative resampling demonstrated the robustness of these findings, with the association validated in 97% and 47% of the random splits for the unadjusted and adjusted analyses, respectively. The adjusted model including enrolment prostasin level had good discriminatory ability with respect to the risk of respiratory death at 12 or 24 months post-enrolment (supplementary figure S3).
FIGURE 3.
Cumulative incidence of respiratory death over follow-up a) stratified by prostasin level above or below the median or b) stratified by prostasin level and antifibrotic therapy at enrolment.
Interaction analyses demonstrated a significant interaction between enrolment prostasin level and sex with respect to the outcome of respiratory death (interaction p=0.006). As shown in figure 4, prostasin levels at enrolment were more strongly associated with respiratory death among females (unadjusted HR 1.98; 95% CI 1.46–2.67; p<0.001; validated in 97% of the random splits) than among males (unadjusted HR 1.24; 95% CI 1.05–1.47; p=0.011; validated in 67% of the random splits). After adjustment for age, sex, FVC % predicted and DLCO % predicted at enrolment, the significant association of prostasin with respiratory death persisted among females (adjusted HR 1.80; 95% CI 1.32–2.46; p<0.001; validated in 93% of the random splits) but was attenuated among males (adjusted HR 1.06; 95% CI 0.89–1.27; p=0.505). The adjusted model including enrolment prostasin level demonstrated excellent ability to discriminate respiratory death at 12 or 24 months post-enrolment among females (C-indices of 0.95 and 0.81, respectively), but the performance of the model was less robust for males (C indices of 0.75 and 0.72, respectively) (figure 5).
FIGURE 4.
Analyses of enrolment prostasin level and the outcome of respiratory death, stratified by sex. a) Among females, distribution of prostasin levels at enrolment and estimated hazard ratios (HRs) and 95% CIs for respiratory death based on an adjusted Cox model. The red square is the estimated HR per 1 sd difference in prostasin level at enrolment. The green square is the estimated HR per 2 sd difference in prostasin level at enrolment. b) Among females, estimated associations between prostasin levels at enrolment and time to respiratory death in unadjusted and adjusted Cox models. c) Among males, distribution of prostasin levels at enrolment and estimated HRs and 95% CIs for respiratory death based on an adjusted Cox model. The red square is the estimated HR per 1 sd difference in prostasin level at enrolment. The green square is the estimated HR per 2 sd difference in prostasin level at enrolment. d) Among males, estimated associations between prostasin levels at enrolment and time to respiratory death in unadjusted and adjusted Cox models.
FIGURE 5.
Receiver operating curve for the adjusted model including enrolment prostasin level for respiratory death at 12 months or 24 months after enrolment, stratified by sex: a) females; b) males. AUC: area under the curve.
Changes in prostasin levels and outcomes
In the subset of patients with prostasin measurements 6±3 months post-enrolment (n=292), 45.9% of patients experienced an increase in prostasin level, 53.4% a decrease in prostasin level and 0.7% no change in prostasin level. Absolute changes in prostasin level over 6 months were generally similar across groups based on pattern of antifibrotic therapy use (continued antifibrotic therapy, initiated antifibrotic therapy, remained untreated) (supplementary table S2).
Absolute changes in prostasin from enrolment to 6 months were significantly correlated with lung function changes over this same time-frame (figure 6). Specifically, there was a moderate negative correlation between absolute change in prostasin level over 0–6 months and absolute change in FVC % predicted over the same period (rho= −0.28; 95% CI −0.39 to −0.15). The correlation between absolute change in prostasin level over 0–6 months and absolute change in FVC % predicted over 0–12 months was also moderately negative (rho= −0.17; 95% CI, −0.30 to −0.03) (figures 6a and b). There were weak to moderate negative correlations between absolute change in prostasin level over 0–6 months and absolute change in DLCO % predicted over 0–6 months (rho= −0.14; 95% CI −0.28 to 0.00) or 0–12 months (rho= −0.23; 95% CI −0.37 to −0.07) (figures 6c and d).
FIGURE 6.
Relationship between absolute change in prostasin from enrolment to 6 months and a) absolute change in forced vital capacity (FVC) % predicted from enrolment to 6 months, b) absolute change in FVC % predicted from enrolment to 12 months, c) absolute change in diffusing capacity of the lung for carbon monoxide (DLCO) % predicted from enrolment to 6 months, and d) absolute change in DLCO % predicted from enrolment to 12 months.
The results of the Cox models of associations between absolute change in prostasin level over 0–6 months and subsequent respiratory death are shown in figure 7. In minimally adjusted models, the HR per 1 sd difference in change in prostasin level over 6 months was 1.28 (95% CI 0.98 to 1.67; p=0.074). In the fully adjusted model, the HR per 1 sd difference in change in prostasin level over 6 months was 1.33 (95% CI 1.01 to 1.74; p=0.041). The HR per 1 sd difference was validated in 27% of the random splits. There was no evidence of a significant interaction between change in prostasin over 6 months and sex (interaction p=0.521), suggesting that the influence of short-term changes in circulating prostasin on the risk of respiratory death was similar in females and males. The adjusted model for respiratory death 12 or 24 months after the follow-up blood sample that included absolute change in prostasin over 6 months showed good discriminatory ability (figure 8).
FIGURE 7.
Analyses of absolute change in prostasin in patients with idiopathic pulmonary fibrosis (IPF). a) Distribution of absolute change in prostasin over 6 months post-enrolment and estimated hazard ratios (HRs) and 95% CIs for respiratory death from adjusted Cox model landmarked at the 6-month blood collection date. The red square is the estimated HR per 1 sd difference in absolute change in prostasin level over 6 months. The green square is the estimated HR per 2 sd difference in the absolute change in prostasin level over 6 months. b) Estimated associations between absolute change in prostasin over 6 months and respiratory death based on minimally and fully adjusted models.
FIGURE 8.
Receiver operating curve for the adjusted model including absolute change in prostasin level between enrolment and 6 months for respiratory death at 12 months or 24 months after the follow-up blood sample. AUC: area under the curve.
Discussion
In this study, we demonstrated that circulating levels of prostasin were associated with the presence of IPF and were highly correlated with measures of the severity of IPF, irrespective of use of antifibrotic therapy. The associations between prostasin level and measures of lung function were stronger than those observed for other epithelial-derived protein biomarkers studied in the IPF-PRO Registry cohort, including surfactant protein D [18]. Higher levels of prostasin at enrolment were associated with an increased risk of respiratory death during follow-up. This finding was particularly striking among females, in whom the effect persisted after adjustment for clinical variables that may influence mortality. We also demonstrated an association between change in prostasin level over 6 months and subsequent risk of respiratory death, suggesting that dynamic changes in prostasin level may provide information about mortality risk beyond that provided by a single measurement. To our knowledge, this is the first report on the prognostic potential of prostasin in a contemporary cohort of patients with IPF based on quantitative measurements.
Evidence of the potential role of prostasin in pulmonary disease comes mainly from research in cystic fibrosis. The expression of processed prostasin is increased on the surface of airway epithelial cells from patients with cystic fibrosis [19], and in these cells, inhibition of prostasin and other channel-activating proteases improves mucociliary function [20]. Among patients with cystic fibrosis, sputum trypsin-like protease activity was inversely correlated with FVC % predicted and was higher in individuals who died within the following 5 years [21]. Nasal administration of a prostasin inhibitor reduced sodium transport in the airway of patients with cystic fibrosis [22]. While these data support the idea that prostasin dysregulation may play a role in the progression of lung disease, the mechanisms of its involvement in the pathobiology of IPF are yet to be determined.
In the search for prognostic biomarkers in IPF, the potential impact of antifibrotic therapy should be considered. In a recent analysis of data from 48 patients with IPF, among 26 proteins studied, seven, including surfactant proteins A1 and D and intercellular adhesion molecule 1, were elevated in patients receiving versus not receiving antifibrotic therapy, but associations with outcomes were not assessed [23]. In a study conducted in 325 patients with IPF, several protein biomarkers associated with prognosis in the era before the availability of antifibrotic therapy were shown to predict mortality both in patients who were and were not receiving antifibrotic therapy, but the thresholds predictive of reduced survival were higher in the patients receiving antifibrotic therapy [24]. In our analyses, we found that a higher prostasin level was associated with the presence of IPF and with worse lung function in patients with IPF irrespective of use of antifibrotic therapy. Further, our finding that the incidence of respiratory death was higher among patients with a higher prostasin level at enrolment was consistent between patients taking versus not taking antifibrotic therapy at enrolment.
Our findings highlight the importance of considering sex as a variable in the search for prognostic biomarkers in IPF. This may be particularly relevant when considering circulating biomarkers. Our analyses demonstrated a much stronger association between enrolment prostasin and respiratory death in females than males. This association persisted in females after accounting for clinical factors that may influence outcomes such as lung function. A model that included enrolment prostasin level had excellent discriminatory ability for respiratory death in females, while model performance metrics were more modest in males.
Strengths of our analyses include the quantitative measurement of prostasin, the longitudinal assessment of prostasin levels that enabled us to analyse associations between changes in prostasin levels and respiratory death, and the assessment of associations in subgroups based on use of antifibrotic therapy. Our internal validation approach supported the robustness of our observations. Our study also had limitations. Although we employed a quantitative assay for prostasin measurement, the assay employed is not a clinical grade assay and further assay validation should be conducted. While our findings suggest that prostasin is a promising biomarker of disease progression in patients with IPF, we acknowledge that a multiprotein signature will likely be needed to provide an accurate assessment of prognosis in these patients. Finally, while our analyses adjusted for several clinical variables that may confound the relationship between prostasin level and outcomes in patients with IPF, there could be other unmeasured confounders.
Conclusions
In a real-world prospective multicentre cohort of patients with IPF, circulating levels of prostasin were highly correlated with measures of disease severity. Further, the prostasin level at baseline, and the absolute change in prostasin level over 6 months, were independently associated with risk of mortality. These findings support the value of prostasin as a prognostic biomarker in patients with IPF.
Acknowledgements
The authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors. 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. We acknowledge the MURDOCK Study and Duke University's CTSA grant (UL1TR002553) from the National Institutes of Health's National Center for Advancing Translational Sciences for providing the control cohort for these analyses.
Footnotes
Provenance: Submitted article, peer reviewed.
Principal investigators and enrolling centres in the IPF-PRO Registry: Albert Baker, Lynchburg Pulmonary Associates, Lynchburg, VA; Scott Beegle, Albany Medical Center, Albany, NY; John A. Belperio, University of California Los Angeles, Los Angeles, CA; Rany Condos, NYU Medical Center, New York, NY; Francis Cordova, Temple University, Philadelphia, PA; Brian Southern (formerly Daniel A. Culver), Cleveland Clinic, Cleveland, OH; Daniel Dilling, Loyola University Health System, Maywood, IL; John Fitzgerald (formerly Leann Silhan), UT Southwestern Medical Center, Dallas, TX; Kevin R. Flaherty, University of Michigan, Ann Arbor, MI; Kevin Gibson, University of Pittsburgh, Pittsburgh, PA; Mridu Gulati, Yale School of Medicine, New Haven, CT; Kalpalatha Guntupalli, Baylor College of Medicine, Houston, TX; Nishant Gupta, University of Cincinnati Medical Center, Cincinnati, OH; Amy Hajari Case, Piedmont Healthcare, Atlanta, GA; David Hotchkin, The Oregon Clinic, Portland, OR; Tristan J. Huie, National Jewish Health, Denver, CO; Robert J. Kaner, Weill Cornell Medical College, New York, NY; Hyun J. Kim, University of Minnesota, Minneapolis, MN; Lisa H. Lancaster (formerly Mark Steele), Vanderbilt University Medical Center, Nashville, TN; Joseph A. Lasky, Tulane University, New Orleans, LA; Doug Lee, Wilmington Health and PMG Research, Wilmington, NC; Timothy Liesching, Lahey Clinic, Burlington, MA; Randolph Lipchik, Froedtert and The Medical College of Wisconsin Community Physicians, Milwaukee, WI; Jason Lobo, UNC Chapel Hill, Chapel Hill, NC; Tracy R. Luckhardt (formerly Joao A. de Andrade), University of Alabama at Birmingham, Birmingham, AL; Yolanda Mageto (formerly Howard Huang), Baylor University Medical Center at Dallas, Dallas, TX; Marta Kokoszynska (formerly Yolanda Mageto, Prema Menon), Vermont Lung Center, Colchester, VT; Lake Morrison, Duke University Medical Center, Durham, NC; Andrew Namen, Wake Forest University, Winston Salem, NC; Justin M. Oldham, University of California, Davis, Sacramento, CA; Tessy Paul, University of Virginia, Charlottesville, VA; David Zhang (formerly Anna Podolanczuk, David Lederer and Nina M. Patel), Columbia University Medical Center/New York Presbyterian Hospital, New York, NY; Mary Porteous (formerly Maryl Kreider), University of Pennsylvania, Philadelphia, PA; Rishi Raj (formerly Paul Mohabir), Stanford University, Stanford, CA; Murali Ramaswamy, PulmonIx LLC, Greensboro, NC; Tonya Russell, Washington University, St Louis, MO; Paul Sachs, Pulmonary Associates of Stamford, Stamford, CT; Zeenat Safdar, Houston Methodist Lung Center, Houston, TX; Shirin Shafazand (formerly Marilyn Glassberg), University of Miami, Miami, FL; Ather Siddiqi (formerly Wael Asi), Renovatio Clinical, The Woodlands, TX; Reginald Fowler (formerly Barry Sigal), Salem Chest and Southeastern Clinical Research Center, Winston Salem, NC; Mary E. Strek (formerly Imre Noth), University of Chicago, Chicago, IL; Hiram Rivas-Perez (formerly Jesse Roman, Sally Suliman), University of Louisville, Louisville, KY; Jeremy Tabak, South Miami Hospital, South Miami, FL; Rajat Walia, St Joseph's Hospital, Phoenix, AZ; Timothy P.M. Whelan, Medical University of South Carolina, Charleston, SC.
This clinical trial is prospectively registered with ClinicalTrials.gov as NCT01915511
Ethics statement: Ethics approval was granted by the Duke Institutional Review Board Protocol Number Pro00082241 to use the biosamples obtained as part of the IPF-PRO Registry for the analyses contained herein. All participants provided written informed consent. The MURDOCK study community registry and biorepository was approved by the Duke University Health Institutional Review Board (Pro00011196) and all participants provided written informed consent.
Conflict of interest: J.L. Todd, C. Page, S.M. Palmer and M.L. Neely are faculty members of the Duke Clinical Research Institute, which receives funding support from Boehringer Ingelheim Pharmaceuticals, Inc. to coordinate the IPF-PRO/ILD-PRO Registry. J.L. Todd also reports grants from AstraZeneca, Boehringer Ingelheim, CareDx and has participated on data safety monitoring or advisory boards for Altavant, Avalyn, Natera, Sanofi and Theravance. S.M. Palmer also reports research funding to Duke University/Duke Clinical Research Institute from Bristol Myers Squibb; royalties or licenses from UpToDate; and consulting fees from Bristol Myers Squibb, Mallinckrodt and Sanofi. P. Wu, C. Hesslinger and T. Schlange are employees of Boehringer Ingelheim. T.B. Leonard was an employee of Boehringer Ingelheim Pharmaceuticals, Inc. at the time that these analyses were performed. J.A. Belperio is a member of the Steering Committee and a site investigator for the IPF-PRO/ILD-PRO Registry. T.M. Maher reports consulting fees from AstraZeneca, Bayer, Blade Therapeutics, Boehringer Ingelheim, Bristol-Myers Squibb, Galapagos, Galecto, GlaxoSmithKline, IQVIA, Pliant, Respivant Sciences, Roche/Genentech, Theravance and Veracyte, and speaker fees from Boehringer Ingelheim and Roche/Genentech.
Support statement: The IPF-PRO Registry is supported by Boehringer Ingelheim Pharmaceuticals, Inc. and run in collaboration with the Duke Clinical Research Institute and enrolling centres. Funding information for this article has been deposited with the Crossref Funder Registry.
Supplementary material
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Supplementary material
00738-2024.SUPPLEMENT
Data availability
The datasets analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.
References
- 1.Raghu G, Remy-Jardin M, Richeldi L, et al. Idiopathic pulmonary fibrosis (an update) and progressive pulmonary fibrosis in adults: an official ATS/ERS/JRS/ALAT clinical practice guideline. Am J Respir Crit Care Med 2022; 205: e18–e47. doi: 10.1164/rccm.202202-0399ST [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Wang ZN, Tang XX. New perspectives on the aberrant alveolar repair of idiopathic pulmonary fibrosis. Front Cell Dev Biol 2020; 8: 580026. doi: 10.3389/fcell.2020.580026 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Chakraborty A, Mastalerz M, Ansari M, et al. Emerging roles of airway epithelial cells in idiopathic pulmonary fibrosis. Cells 2022; 11: 1050. doi: 10.3390/cells11061050 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Maher TM, Oballa E, Simpson JK, et al. An epithelial biomarker signature for idiopathic pulmonary fibrosis: an analysis from the multicentre PROFILE cohort study. Lancet Respir Med 2017; 5: 946–955. doi: 10.1016/S2213-2600(17)30430-7 [DOI] [PubMed] [Google Scholar]
- 5.Wang K, Ju Q, Cao J,et al. Impact of serum SP-A and SP-D levels on comparison and prognosis of idiopathic pulmonary fibrosis. Medicine (Baltimore) 2017; 96: e7083. doi: 10.1097/MD.0000000000007083 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chung C, Kim J, Cho HS, et al. Baseline serum Krebs von den Lungen-6 as a biomarker for the disease progression in idiopathic pulmonary fibrosis. Sci Rep 2022; 12: 8564. doi: 10.1038/s41598-022-12399-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Molyneaux PL, Fahy WA, Byrne AJ, et al. CYFRA 21-1 predicts progression in idiopathic pulmonary fibrosis: a prospective longitudinal analysis of the PROFILE cohort. Am J Respir Crit Care Med 2022; 205: 1440–1448. doi: 10.1164/rccm.202107-1769OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Aggarwal S, Dabla PK, Arora S. Prostasin: an epithelial sodium channel regulator. J Biomark 2013; 2013: 179864. doi: 10.1155/2013/179864 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Chen M, Chen LM, Lin CY, et al. The epidermal growth factor receptor (EGFR) is proteolytically modified by the matriptase-prostasin serine protease cascade in cultured epithelial cells. Biochim Biophys Acta 2008; 1783: 896–903. doi: 10.1016/j.bbamcr.2007.10.019 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Raghu G, Richeldi L, Jagerschmidt A, et al. Idiopathic pulmonary fibrosis: prospective, case-controlled study of natural history and circulating biomarkers. Chest 2018; 154: 1359–1370. doi: 10.1016/j.chest.2018.08.1083 [DOI] [PubMed] [Google Scholar]
- 11.Bowman WS, Newton CA, Linderholm AL, et al. Proteomic biomarkers of progressive fibrosing interstitial lung disease: a multicentre cohort analysis. Lancet Respir Med 2022; 10: 593–602. doi: 10.1016/S2213-2600(21)00503-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Oldham JM, Huang Y, Bose S, et al. Proteomic biomarkers of survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2024; 209: 1111–1120. doi: 10.1164/rccm.202301-0117OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.O'Brien EC, Durheim MT, Gamerman V, et al. Rationale for and design of the Idiopathic Pulmonary Fibrosis-PRospective Outcomes (IPF-PRO) Registry. BMJ Open Respir Res 2016; 3: e000108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bhattacharya S, Dunham AA, Cornish MA, et al. The Measurement to Understand Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) study community registry and biorepository. Am J Transl Res 2012; 4: 458–470. [PMC free article] [PubMed] [Google Scholar]
- 15.Kang G, Liu W, Cheng C, et al. Evaluation of a two-step iterative resampling procedure for internal validation of genome-wide association studies. J Hum Genet 2015; 60: 729–738. doi: 10.1038/jhg.2015.110 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. www.proteinatlas.org/ENSG00000052344-PRSS8/tissue The Human Protein Atlas: PRSS8. Date last accessed: 6 November 2024.
- 17.van Buuren S. Flexible Imputation of Missing Data. 2nd Edn. New York, NY, Chapman and Hall/CRC, 2018: p. 444. doi 10.1201/9780429492259 [DOI] [Google Scholar]
- 18.Todd JL, Mulder H, Neely ML, et al. Circulating prostasin associates with presence and severity of idiopathic pulmonary fibrosis (IPF). Eur Respir J 2023; 62: Suppl. 67, PA1144. [Google Scholar]
- 19.Myerburg MM, McKenna EE, Luke CJ, et al. Prostasin expression is regulated by airway surface liquid volume and is increased in cystic fibrosis. Am J Physiol Lung Cell Mol Physiol 2008; 294: L932–L941. doi: 10.1152/ajplung.00437.2007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Reihill JA, Walker B, Hamilton RA, et al. Inhibition of protease–epithelial sodium channel signaling improves mucociliary function in cystic fibrosis airways. Am J Respir Crit Care Med 2016; 194: 701–710. doi: 10.1164/rccm.201511-2216OC [DOI] [PubMed] [Google Scholar]
- 21.Reihill J, Moffitt K, Douglas L, et al. Sputum trypsin-like protease activity relates to clinical outcome in cystic fibrosis. J Cyst Fibros 2020; 19: 647–653. doi: 10.1016/j.jcf.2019.12.014 [DOI] [PubMed] [Google Scholar]
- 22.Rowe SM, Reeves G, Hathorne H, et al. Reduced sodium transport with nasal administration of the prostasin inhibitor camostat in subjects with cystic fibrosis. Chest 2013; 144: 200–207. doi: 10.1378/chest.12-2431 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ebert C, Walsh AM, Sereda L, et al. Circulating biomarker analyses in a longitudinal cohort of patients with IPF. Am J Physiol Lung Cell Mol Physiol 2024; 326: L303–L312. doi: 10.1152/ajplung.00222.2023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Adegunsoye A, Alqalyoobi S, Linderholm A, et al. Circulating plasma biomarkers of survival in antifibrotic-treated patients with idiopathic pulmonary fibrosis. Chest 2020; 158: 1526–1534. doi: 10.1016/j.chest.2020.04.066 [DOI] [PMC free article] [PubMed] [Google Scholar]
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Supplementary Materials
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Supplementary material
00738-2024.SUPPLEMENT
Data Availability Statement
The datasets analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.