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Blood Biomarker Analysis Identifies Distinct Endotypes in Pulmonary Fibrosis

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The identification of unique pulmonary fibrosis endotypes is an important step in the development of precision medicine approaches for the incurable condition.

Three distinct blood biomarker signatures were associated with lung function and prognosis in pulmonary fibrosis in a study published in The Lancet Respiratory Medicine.1 The findings suggest there might be pulmonary fibrosis endotypes that could be useful in guiding targeted therapy development for this incurable condition.

In most cases, the cause of pulmonary fibrosis, a type of interstitial lung disease that causes progressive lung scarring and breathing difficulty, is not known.2 In these cases, it is classified as idiopathic pulmonary fibrosis (IPF). Among patients with pulmonary fibrosis, there is substantial heterogeneity that makes it difficult to identify which patients are at a higher mortality risk.1 The variation seen across clinical phenotypes and responses to treatment indicates there could be distinct molecular endotypes, according to the authors of the new study.

“Endotypes are specific genetic or molecular profiles with potentially distinct clinical features and have been identified in lung diseases such as asthma or sepsis,” the authors explained. “A particular endotype's response to targeted therapy might be due to unique biological mechanisms, as seen with anti-interleukin (IL)-5 and anti-IL-13 therapy in asthma. Although specific pulmonary fibrosis endotypes have not been characterized, distinct clinical and biomarker profiles suggest the potential presence of pulmonary fibrosis endotypes.”

To the authors’ knowledge, their study is the first to comprehensively analyze patient heterogeneity in both IPF and non-specific interstitial pneumonitis using blood-derived protein biomarkers. The analysis included patients from the PROFILE study (NCT01110694), which aimed to identify blood and lung biomarkers in the lungs of patients with IPF that would allow noninvasive diagnosis, prediction of disease aggressiveness, and help predict treatment responses.1,3

Three distinct blood biomarker signatures were associated with lung function and prognosis in pulmonary fibrosis. | Image credit: meeboonstudio-stock.adobe.com

Three distinct blood biomarker signatures were associated with lung function and prognosis in pulmonary fibrosis. | Image credit: meeboonstudio-stock.adobe.com

The analysis included 455 participants in the PROFILE study, 399 (88%) of whom had IPF and 56 (12%) who had non-specific interstitial pneumonia.1 The median age was 72.4 years, and the population included 348 men (76%) and 107 women (24%). A machine learning classifier was trained on biomarker signatures derived from consensus clustering. The classifier was also applied to a dataset from the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR) to gauge generalizability.

A cluster analysis based on 13 blood biomarkers showed 3 unique clusters, the largest of which comprised 248 patients (55%) who had high concentrations of basement membrane collagen neoepitopes (BM cluster). The second largest cluster included 109 individuals (24%) with high concentrations of epithelial injury biomarkers (EI cluster), and the smallest cluster had 96 individuals (22%) who had high concentrations of crosslinked fibrin (X-FIB), or the XF cluster.

The analysis assessed 13 biomarkers:

  • Type I collagen degraded by matrix metalloproteinase (MMP)-2/9/13
  • Type III collagen degraded by MMP-9 (C3M)
  • Type VI collagen degraded by MMP-2 (C6M)
  • N-terminal propeptide of type III collagen reflecting formation
  • 7S domain of type IV collagen (PRO-C4)
  • C5 domain of type VI collagen, endotrophin, reflecting formation
  • C-terminal fragment of type XXVIII collagen (PRO-C28)
  • X-FIB
  • Cytokeratin 19 fragment (CYFRA211)
  • Surfactant protein D (SP-D)
  • MMP-7
  • Cancer antigen 125 (CA-125)
  • Carbohydrate antigen 19-9 (CA19-9)

The BM cluster had high concentrations of PRO-C4, PRO-C28, C3M, and C6M; the EI cluster had high concentrations of MMP-7, SP-D, CYFRA211, CA19-9, and CA-125; and the XF cluster had high concentrations of X-FIB.

The AIPFR dataset replicated the population from the PROFILE study, with 117 total patients including 87 men (74%) and 30 women (26%) with an overall mean age of 72.9 years. This population showed the same 3 clusters, with 93 patients in the BM cluster (79%); 8 in the EI cluster (7%); and 16 in the XF cluster (14%).

The EI and XF clusters were associated with a greater mortality risk compared with the BM cluster in the PROFILE cohort. The adjusted HR (aHR) for EI vs BM was 1.88 (95% CI 1.42-2.49; P < .0001) and the aHR for XF vs BM was 1.53 (1.13-2.06; P = .0058).

Patients in the EI cluster had the greatest mean annual declines in percentage of predicted forced vital capacity (FVC%) from baseline at –12% in the PROFILE cohort and –5.8% in the AIPFR cohort. The BM cluster showed declines of –8.5% in the PROFILE cohort and –2.7% in the AIPFR cohort. The XF cluster had declines of –8.5% in the PROFILE cohort and –2.6% in the AIPFR cohort.

While the study was observational and could have been impacted by selection bias relating to the effects of therapy on biomarkers, the similar key findings in both studies addresses some of this bias potential.

“The molecular clusters identified in this study support the existence of distinct endotypes, which might underlie some of the heterogeneity associated with pulmonary fibrosis,” the authors wrote. “The identification of distinct endotypes is an important step in the development of precision medicine approaches. Although there are currently no therapies that specifically target the epithelium or promote basement membrane repair, the availability of anticoagulants offers the potential to improve outcomes for appropriately stratified patients with pulmonary fibrosis.”

References

1. Fainberg HP, Moodley Y, Triguero I, et al. Cluster analysis of blood biomarkers to identify molecular patterns in pulmonary fibrosis: assessment of a multicentre, prospective, observational cohort with independent validation. Lancet Respir Med. Published online July 15, 2024. doi:10.1016/S2213-2600(24)00147-4

2. Introduction to pulmonary fibrosis. American Lung Association. Updated June 7, 2024. Accessed August 12, 2024. https://www.lung.org/lung-health-diseases/lung-disease-lookup/pulmonary-fibrosis/introduction

3. Prospective observation of fibrosis in the lung clinical endpoints study (PROFILE). ClinicalTrials.gov. Updated March 27, 2019. https://clinicaltrials.gov/study/NCT01110694

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