It’s known that pulmonary fibrosis arises from alveolar injury, causing extracellular matrix remodeling and impaired lung function.
With that in mind, researchers from the NIHR Imperial Biomedical Respiratory Research Centre at Imperial College in London looked to classify patients with pulmonary fibrosis based on blood biomarkers to identify distinct disease patterns, referred to as endotypes.
Their research, published July 15 in The Lancet Respiratory Medicine, identified three blood biomarker profiles associated with varying survival and lung function changes, suggesting unique pulmonary fibrosis biomarker patterns.
The groundbreaking study was led by Hernan P Fainberg, PhD, a research fellow at the college, who examined the clusters with the research team. It’s believed to be the first comprehensive investigation of patient heterogeneity via the use of blood-derived protein biomarkers in patients with both idiopathic pulmonary fibrosis and non-specific interstitial pneumonitis.
The cluster analysis was done by classifying patients from the PROFILE study, a multicenter, prospective, observational cohort of individuals with incident idiopathic pulmonary fibrosis or non-specific interstitial pneumonia from the UK.
The team measured 13 blood biomarkers, looking closely at extracellular matrix remodeling, epithelial stress and thrombosis, and patients were classified by unsupervised consensus clustering.
The researchers utilized a machine learning classifier trained on biomarker signatures derived from consensus clustering and applied it to a replication dataset from the Australian Idiopathic Pulmonary Fibrosis Registry to better evaluate generalizability.
By doing that, biomarker associations with mortality and change in percentage of predicted forced vital capacity (FVC) could be assessed, with the study authors making adjustments for age, gender, baseline FVC percentage, and antifibrotic treatment and steroid treatment before and after baseline.
The mortality risk associated with the clusters from those in the cohort were evaluated with Cox proportional hazards models, while mixed-effects models were used to better analyze how clustering was associated with longitudinal FVC percentage.
Fainberg and the team discovered the BM cluster exhibited the highest number of participants in both cohorts, the best overall survival rates, the lowest mortality risk and elevated levels of basement membrane-associated extracellular matrix biomarkers.
Meanwhile, the EI cluster had the highest mortality risk, the greatest reduction in lung function and increased concentrations of biomarkers associated with epithelial dysfunction; while the XF cluster, associated with high X-FIB concentrations, showed a higher mortality risk compared to the BM cluster.
“The biomarkers characterizing each cluster reflect lung parenchymal changes associated with key fibrotic processes—basement membrane repair or dysfunction, epithelial injury and thrombosis,” the authors wrote. “These clusters could signify distinct endotypes, facilitating patient management and clinical trial stratification regardless of clinical phenotype, age, sex and baseline lung function.”
Their findings support the presence of pulmonary fibrosis endotypes with the potential to guide targeted therapy development.
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