{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T16:35:56Z","timestamp":1779986156542,"version":"3.53.1"},"reference-count":45,"publisher":"BMJ","issue":"7","license":[{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Thorax"],"accepted":{"date-parts":[[2023,1,19]]},"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Idiopathic pulmonary fibrosis (IPF) is a debilitating, progressive disease with a median survival time of 3\u20135 years. Diagnosis remains challenging and disease progression varies greatly, suggesting the possibility of distinct subphenotypes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods and results<\/jats:title><jats:p>We analysed publicly available peripheral blood mononuclear cell expression datasets for 219 IPF, 411 asthma, 362 tuberculosis, 151 healthy, 92 HIV and 83 other disease samples, totalling 1318 patients. We integrated the datasets and split them into train (n=871) and test (n=477) cohorts to investigate the utility of a machine learning model (support vector machine) for predicting IPF. A panel of 44 genes predicted IPF in a background of healthy, tuberculosis, HIV and asthma with an area under the curve of 0.9464, corresponding to a sensitivity of 0.865 and a specificity of 0.89. We then applied topological data analysis to investigate the possibility of subphenotypes within IPF. We identified five molecular subphenotypes of IPF, one of which corresponded to a phenotype enriched for death\/transplant. The subphenotypes were molecularly characterised using bioinformatic and pathway analysis tools identifying distinct subphenotype features including one which suggests an extrapulmonary or systemic fibrotic disease.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Integration of multiple datasets, from the same tissue, enabled the development of a model to accurately predict IPF using a panel of 44 genes. Furthermore, topological data analysis identified distinct subphenotypes of patients with IPF which were defined by differences in molecular pathobiology and clinical characteristics.<\/jats:p><\/jats:sec>","DOI":"10.1136\/thorax-2022-219731","type":"journal-article","created":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T18:23:29Z","timestamp":1676917409000},"page":"682-689","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":6,"title":["Topological data analysis identifies molecular phenotypes of idiopathic pulmonary fibrosis"],"prefix":"10.1136","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4147-6956","authenticated-orcid":false,"given":"Andrew","family":"Shapanis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6308-6014","authenticated-orcid":false,"given":"Mark G","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Schofield","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2995-2959","authenticated-orcid":false,"given":"Paul","family":"Skipp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"key":"2024051320394054000_78.7.682.1","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201807-1255ST"},{"key":"2024051320394054000_78.7.682.2","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.00185114"},{"key":"2024051320394054000_78.7.682.3","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.01504-2015"},{"key":"2024051320394054000_78.7.682.4","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201006-0894CI"},{"key":"2024051320394054000_78.7.682.5","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra1705751"},{"key":"2024051320394054000_78.7.682.6","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-134-2-200101160-00015"},{"key":"2024051320394054000_78.7.682.7","doi-asserted-by":"publisher","DOI":"10.1378\/chest.09-1002"},{"key":"2024051320394054000_78.7.682.8","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-142-12_Part_1-200506210-00005"},{"key":"2024051320394054000_78.7.682.9","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.jaci.2019.03.013","article-title":"Stratification of asthma phenotypes by airway proteomic signatures","volume":"144","author":"Schofield","year":"2019","journal-title":"J Allergy Clin Immunol"},{"key":"2024051320394054000_78.7.682.10","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rmed.2019.02.008","article-title":"Sputum proteomic signature of gastro-oesophageal reflux in patients with severe asthma","volume":"150","author":"Tariq","year":"2019","journal-title":"Respir Med"},{"key":"2024051320394054000_78.7.682.11","doi-asserted-by":"crossref","DOI":"10.1186\/s12918-018-0556-z","article-title":"A computational framework for complex disease stratification from multiple large-scale datasets","volume":"12","author":"De Meulder","year":"2018","journal-title":"BMC Syst Biol"},{"key":"2024051320394054000_78.7.682.12","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1164\/rccm.201604-0866OC","article-title":"A severe asthma disease signature from gene expression profiling of peripheral blood from U-BIOPRED cohorts","volume":"195","author":"Bigler","year":"2017","journal-title":"Am J Respir Crit Care Med"},{"key":"2024051320394054000_78.7.682.13","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1016\/j.jaci.2019.03.027","article-title":"IL-17-high asthma with features of a psoriasis immunophenotype","volume":"144","author":"\u00d6stling","year":"2019","journal-title":"J Allergy Clin Immunol"},{"key":"2024051320394054000_78.7.682.14","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1111\/bjd.19485","article-title":"Identification of proteins associated with development of metastasis from cutaneous squamous cell carcinomas (csccs) via proteomic analysis of primary csccs","volume":"184","author":"Shapanis","year":"2021","journal-title":"Br J Dermatol"},{"key":"2024051320394054000_78.7.682.15","unstructured":"Zhou TZW , Ma SF , Wade M , et al . Profiling of gene expression in idiopathic pulmonary fibrosis. NCBI GEO. 2019. Available: https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE38958"},{"key":"2024051320394054000_78.7.682.16","unstructured":"Herazo-Maya JD . Peripheral blood mononuclear cell gene expression profiles may predict poor outcome in idiopathic pulmonary fibrosis. NCBI GEO [agilent]. 2020. Available: https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE28042"},{"key":"2024051320394054000_78.7.682.17","unstructured":"Yong H , Ma S , Martinez FJ , et al . Longitudinal blood transcriptomic changes predict lung function decline in idiopathic pulmonary fibrosis. NCBI GEO. 2022. Available: https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE132607"},{"key":"2024051320394054000_78.7.682.18","unstructured":"Bigler J , Boedigheimer M , Schofield JPR , et al . Expression profiling in blood from subjects with severe asthma, moderate asthma, and non-asthmatics collected in the U-BIOPRED study. NCBI GEO. 2018. Available: https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE69683"},{"key":"2024051320394054000_78.7.682.19","unstructured":"Anderson ST , Crampin AC , Dockrell HM , et al . Genome-wide transcriptional profiling of HIV positive and negative adults with active tuberculosis, latent TB infection and other diseases. NCBI GEO. 2020. Available: https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE37250"},{"key":"2024051320394054000_78.7.682.20","doi-asserted-by":"crossref","DOI":"10.1186\/1471-2105-14-75","article-title":"VirtualArray: a R\/bioconductor package to merge RAW data from different microarray platforms","volume":"14","author":"Heider","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2024051320394054000_78.7.682.21","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-156-10-201205150-00004"},{"key":"2024051320394054000_78.7.682.22","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.3005964","article-title":"Peripheral blood mononuclear cell gene expression profiles predict poor outcome in idiopathic pulmonary fibrosis","volume":"5","author":"Herazo-Maya","year":"2013","journal-title":"Sci Transl Med"},{"key":"2024051320394054000_78.7.682.23","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201310-1917OC"},{"key":"2024051320394054000_78.7.682.24","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3337"},{"key":"2024051320394054000_78.7.682.25","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-10-0824"},{"key":"2024051320394054000_78.7.682.26","doi-asserted-by":"publisher","DOI":"10.1136\/gut.2008.174904"},{"key":"2024051320394054000_78.7.682.27","doi-asserted-by":"publisher","DOI":"10.1016\/j.stem.2016.01.010"},{"key":"2024051320394054000_78.7.682.28","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1080\/15592294.2017.1303581","article-title":"Novel insights into systemic autoimmune rheumatic diseases using shared molecular signatures and an integrative analysis","volume":"12","author":"Hudson","year":"2017","journal-title":"Epigenetics"},{"key":"2024051320394054000_78.7.682.29","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-019-57108-0","article-title":"Transcriptional analysis identifies potential biomarkers and molecular regulators in pneumonia and COPD exacerbation","volume":"10","author":"Bertrams","year":"2020","journal-title":"Sci Rep"},{"key":"2024051320394054000_78.7.682.30","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.00212813"},{"key":"2024051320394054000_78.7.682.31","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s11739-020-02376-2","article-title":"Subclinical liver fibrosis in patients with idiopathic pulmonary fibrosis","volume":"16","author":"Cocconcelli","year":"2021","journal-title":"Intern Emerg Med"},{"key":"2024051320394054000_78.7.682.32","doi-asserted-by":"publisher","DOI":"10.1080\/15384101.2016.1152435"},{"key":"2024051320394054000_78.7.682.33","doi-asserted-by":"crossref","DOI":"10.1038\/srep43446","article-title":"Characterization of gene expression profiles in HBV-related liver fibrosis patients and identification of ITGBL1 as a key regulator of fibrogenesis","volume":"7","author":"Wang","year":"2017","journal-title":"Sci Rep"},{"key":"2024051320394054000_78.7.682.34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhep.2007.01.029"},{"key":"2024051320394054000_78.7.682.35","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1016\/j.kint.2015.12.037","article-title":"The role of PDGF-D in healthy and fibrotic kidneys","volume":"89","author":"Buhl","year":"2016","journal-title":"Kidney Int"},{"key":"2024051320394054000_78.7.682.36","doi-asserted-by":"publisher","DOI":"10.1177\/1535370215597194"},{"key":"2024051320394054000_78.7.682.37","doi-asserted-by":"publisher","DOI":"10.1165\/rcmb.2007-0340OC"},{"key":"2024051320394054000_78.7.682.38","doi-asserted-by":"publisher","DOI":"10.1002\/hep.26761"},{"key":"2024051320394054000_78.7.682.39","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1402582"},{"key":"2024051320394054000_78.7.682.40","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(11)60405-4"},{"key":"2024051320394054000_78.7.682.41","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1402584"},{"key":"2024051320394054000_78.7.682.42","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(17)30866-8"},{"key":"2024051320394054000_78.7.682.43","doi-asserted-by":"publisher","DOI":"10.1164\/ajrccm.158.5.9803115"},{"key":"2024051320394054000_78.7.682.44","doi-asserted-by":"crossref","DOI":"10.1186\/s12931-019-1190-z","article-title":"Peripheral blood proteomic profiling of idiopathic pulmonary fibrosis biomarkers in the multicentre IPF-PRO registry","volume":"20","author":"Todd","year":"2019","journal-title":"Respir Res"},{"key":"2024051320394054000_78.7.682.45","doi-asserted-by":"crossref","unstructured":"Kraven LM , Taylor AR , Molyneaux PL , et al . Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis. Thorax 2022. doi:10.1136\/thoraxjnl-2021-218563 [Epub ahead of print 09 May 2022].","DOI":"10.1136\/thorax-2021-BTSabstracts.2"}],"container-title":["Thorax"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1136\/thorax-2022-219731","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T03:53:56Z","timestamp":1715658836000},"score":1,"resource":{"primary":{"URL":"https:\/\/thorax.bmj.com\/lookup\/doi\/10.1136\/thorax-2022-219731"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,20]]},"references-count":45,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,6,15]]},"published-print":{"date-parts":[[2023,7]]}},"alternative-id":["10.1136\/thorax-2022-219731"],"URL":"https:\/\/doi.org\/10.1136\/thorax-2022-219731","relation":{},"ISSN":["0040-6376","1468-3296"],"issn-type":[{"value":"0040-6376","type":"print"},{"value":"1468-3296","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,20]]}}}