DCRI Unveils New Imaging and Translational Biomarker Evidence in Pulmonary Fibrosis and Lung Disease from the IPF-PRO/ILD-PRO Registry

New evidence and results from eight studies based on data from the IPF-PRO/ILD-PRO Registry was shared by the Duke Clinical Research Institute (DCRI) and its collaborators at the American Thoracic Society (ATS) annual conference in San Diego, May 17-22. 

The findings provided a deeper understanding of lung diseases, including novel biomarkers to guide improved patient care and inform future treatment.

ATS Summit Highlights IPF-PRO/ILD-PRO Registry’s Cutting-Edge Approaches to Advance Research

The IPF-PRO/ILD-PRO registry is a collaboration between the DCRI and Boehringer Ingelheim (BI) designed to advance knowledge regarding idiopathic pulmonary fibrosis (IPF) and other interstitial lung diseases (ILDs) from this PRospective Outcomes (PRO) registry.  DCRI serves as the clinical, data, and statistical coordinating center.  The registry has enrolled more than 1,800 patients and has supported nearly 100 conference abstract presentations and 18 published manuscripts since inception.

Scott Palmer, MD, MHS

“The DCRI clinical and operational team have developed an invaluable resource for advancing our understanding of the natural history, response to treatment, and biomarker discovery in care of patients with IPF and ILD. The registry includes serial longitudinal measures of clinical outcomes, patient centered outcomes, and biosample collection in patients for up to five years,” said DCRI Respiratory Director Scott Palmer, MD, MHS. “This real world data brings key insights that cannot be obtained through traditional randomized clinical trials enabling a broad range of research and discovery. The success of the registry reflects hard work of the investigators and coordinators across our US based site network and the highly collaborative nature of the DCRI-BI partnership throughout the course of the project.

The ATS Respiratory Innovation Summit highlighted the DCRI through a poster that featured the IPF-PRO/ILD-PRO registry and its cutting- edge approaches such as the serial collection of patient outcome information in a decentralized manner through the Participant Research Operations Call Center.

Combination of Multigene Profiles and Clinical Factors Improves Outcome Predictability in IPF

The course of idiopathic pulmonary fibrosis can be unpredictable for patients and clinicians, and the biomarkers that could indicate death or progression of the disease are not well understood.

New research presented by DCRI faculty at ATS sheds light on signals to look for that could indicate increased risks for these patients.

Results from a study shared on May 19 by Aparna Swaminathan, MD, show that using patient genetic information in concert with clinical data can help providers predict short-term outcomes in patients with IPF better than with clinical data alone. 

The study assessed a cohort of 261 patients with IPF from the multicenter IPF-PRO Registry who had whole blood total RNA sequencing at enrollment. Researchers assessed patient outcomes of death or disease progression at 12 months and identified differentially expressed genes associated with each outcome. The study team created predictive models for each outcome and compared the performance of models using both genetic and clinical information to the models that only had clinical data. They found that the models that include both circulating gene expression and clinical measures are better able to predict short-term risk of death or progression than models considering only clinical factors. Long non-coding RNAs were particularly important in outcome discrimination, warranting further evaluation of their potential regulatory functions in IPF.

Aparna Swaminathan

“Clinicians need better tools to better predict short-term outcomes in patients with IPF,” Swaminathan said. “If validated, this combination of genes and circulating clinical factors can provide valuable information to patients and guide treatment decisions, such as early referral to lung transplantation in patients with high short-term risk of progression.”

DCRI faculty Megan Neely, PhD and Jamie Todd, MD, also contributed to this research.

Circulating Prostasin: An Independent Risk Marker in IPF

A study focusing on peripheral blood prostasin levels of patients with IPF suggests that the protein could be an independent risk marker for mortality in this population. Observing changes in prostasin over time could also be useful in assessing a patient’s risk of dying.

DCRI’s Jamie Todd, MD, MHS presented the results during an ATS poster discussion session on May 19. Researchers assessed data from 627 patients with newly-diagnosed or confirmed IPF enrolled in the IPF-PRO Registry to show that patients who had a higher level of prostasin in their blood at the start of the study, or who had a greater change in their level of prostasin over the first 6 months of follow-up, were more likely to die from a respiratory cause during the course of the study.

Importantly, peripheral blood prostasin levels provided information about the risk of death not accounted for by common clinical measures previously linked to IPF mortality risk—for example age, lung function, and oxygen use. 

Jamie Todd

“This is an exciting study because it is one of the first to show that dynamic changes in a protein biomarker may provide information about disease behavior in patients with IPF over and above that provided by a single measurement,” Todd said. “The IPF-PRO Registry is uniquely suited to this type of research as biosamples were collected at enrollment and at approximately 6-month intervals throughout the study, creating a rich biorepository on patients with IPF who are well-characterized with respect to a range of clinically relevant outcomes. Identifying and validating prognostic biomarkers could help clinicians better understand the timing of referral for more advanced interventions, such as lung transplantation, or engagement in advanced care planning.”

Additional DCRI faculty contributing to this research include Scott Palmer, MD, MHS, and Megan Neely, PhD and staff include Rosalia Blanco, Jason Blevins, Hillary Mulder and Courtney Page in conjunction with the extended IPF-PRO Registry operations team.

Machine Learning Algorithm Generates Scores That Quantify Lung Damage in Pulmonary Fibrosis Patients

Analysis of a machine learning algorithm revealed it was capable of quantifying lung scarring based on imagery assessments. Scores generated by the algorithm could be used to support providers in better understanding Pulmonary Fibrosis patients’ unique disease severity and improve outcomes.

DCRI faculty member Aparna Swaminathan, MD, presented the results on behalf of the research team that also included Megan Neely, PhD, Jamie Todd, MD, Scott Palmer, MD, MHS, and Jeremy Weber, on May 21.

Using data from the ILD-PRO Registry, researchers evaluated associations between High-Resolution Computed Tomography (HRCT)-derived scores generated by a previously developed machine learning algorithm and disease severity and progression among patients with Progressive Pulmonary Fibrosis (PPF). 

Quantification of fibrotic reticulation or ground glass on the HRCT was associated with physiologic impairment and oxygen use. Higher quantitative lung fibrosis scores were associated with increased risk of short-term disease progression, supporting its use as a biomarker in patients with Progressive Pulmonary Fibrosis.

“CT scans from patients with pulmonary fibrosis contain an enormous amount of lung structural data,” Swaminathan said. “We are just beginning to scratch the surface on how to use machine learning approaches to combine this structural data with lung function to predict outcomes in patients with pulmonary fibrosis.

ATS presentations and abstracts using data from the IPF-PRO/ILD-PRO registry:

Learn more about Respiratory research at the DCRI