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Background: Pulmonary fibrosis results from alveolar injury, leading to extracellular matrix remodelling and impaired lung function. This study aimed to classify patients with pulmonary fibrosis according to blood biomarkers to differentiate distinct disease patterns, known as endotypes., Methods: In this cluster analysis, we first classified patients from the PROFILE study, a multicentre, prospective, observational cohort of individuals with incident idiopathic pulmonary fibrosis or non-specific interstitial pneumonia in the UK (Nottingham University Hospitals, Nottingham; and Royal Brompton Hospital, London). 13 blood biomarkers representing extracellular matrix remodelling, epithelial stress, and thrombosis were measured by ELISA in the PROFILE study. We classified patients by unsupervised consensus clustering. To evaluate generalisability, a machine learning classifier trained on biomarker signatures derived from consensus clustering was applied to a replication dataset from the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR). Biomarker associations with mortality and change in percentage of predicted forced vital capacity (FVC%) were assessed, adjusting for age, gender, baseline FVC%, and antifibrotic treatment and steroid treatment before and after baseline. Mortality risk associated with the clusters in the PROFILE cohort was evaluated with Cox proportional hazards models, and mixed-effects models were used to analyse how clustering was associated with longitudinal FVC% in the PROFILE and AIPFR cohorts., Findings: 455 of 580 participants from the PROFILE study (348 [76%] men and 107 [24%] women; mean age 72·4 years [SD 8·3]) were included in the analysis. Within this group, three clusters were identified based on blood biomarkers. A basement membrane collagen (BM) cluster (n=248 [55%]) showed high concentrations of PRO-C4, PRO-C28, C3M, and C6M, whereas an epithelial injury (EI) cluster (n=109 [24%]) showed high concentrations of MMP-7, SP-D, CYFRA211, CA19-9, and CA-125. The third cluster (crosslinked fibrin [XF] cluster; n=98 [22%]) had high concentrations of X-FIB. In the replication dataset (117 of 833 patients from AIPFR; 87 [74%] men and 30 [26%] women; mean age 72·9 years [SD 7·9]), we identified the same three clusters (BM cluster, n=93 [79%]; EI cluster, n=8 [7%]; XF cluster, n=16 [14%]). These clusters showed similarities with clusters in the PROFILE dataset regarding blood biomarkers and phenotypic signatures. In the PROFILE dataset, the EI and XF clusters were associated with increased mortality risk compared with the BM cluster (EI vs BM: adjusted hazard ratio [HR] 1·88 [95% CI 1·42-2·49], p<0·0001; XF vs BM: adjusted HR 1·53 [1·13-2·06], p=0·0058). The EI cluster showed the greatest annual FVC% decline, followed by the BM and XF clusters. A similar FVC% decline pattern was observed in these clusters in the AIPFR replication dataset., Interpretation: Blood biomarker clustering in pulmonary fibrosis identified three distinct blood biomarker signatures associated with lung function and prognosis, suggesting unique pulmonary fibrosis biomarker patterns. These findings support the presence of pulmonary fibrosis endotypes with the potential to guide targeted therapy development., Funding: None., Competing Interests: Declaration of interests YM reports personal fees for advisory board work from Boehringer Ingelheim and Roche, outside the submitted work. TJC reports fees for work on scientific advisory boards for Boehringer Ingelheim, Roche, Bristol Myers Squibb, Vicore, Pliant, Endeavour Bioscience, and DevPro, and grants from Boehringer Ingelheim, Roche, Bristol Myers Squibb, Galapagos, and Biogen, outside the submitted work. DJL and JMBS are employees and shareholders of Nordic Bioscience. MAK is an employee and shareholder of Nordic Bioscience and holds patents relating to neoepitopes. AUW reports receiving consulting, lecture, or educational fees from Boehringer Ingelheim and Veracyte, and holds the honorary position of President of the World Association of Sarcoidosis and Other Granulomatous Diseases. LVW reports funding from, consultancy for, or collaboration with GSK, Genentech, Orion Pharma, and Galapagos. PLM has received, via his institution, industry-academic funding from AstraZeneca and has received speaker and consultancy fees from Boehringer Ingelheim and Roche, outside the submitted work. TMM has received industry-academic funding from GSK R&D and UCB, and consultancy or speaker's fees from Apellis, AstraZeneca, Bayer, Biogen Idec, Boehringer Ingelheim, Galapagos, GSK R&D, Indalo, Pliant, ProMetic, Roche, Samumed, UCB, and Celgene. RGJ has grants or contracts from AstraZeneca, Biogen, Galecto, GSK, Nordic Bioscience, Redx, and Pliant, with all payments going to his institutions. RGJ has also served as a consultant to Bristol Myers Squibb, Chiesi, Daewoong, Veracyte, Resolution Therapeutics, and Pliant, has received payment or honoraria for lectures, presentations, speaker bureaus, manuscript writing, or educational events from Boehringer Ingelheim, Chiesi, Roche, PatientMPower, and AstraZeneca, has participated on a data safety monitoring board or advisory board for Boehringer Ingelheim, Galapagos, and Vicore, and has an unpaid role in an advisory board at NuMedii. RGJ is also a trustee of Action for Pulmonary Fibrosis. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)