{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mayr CH"],"funding":["Bundesministerium für Bildung und Forschung","Deutsche Zentrum für Lungenforschung","NHLBI NIH HHS","Helmholtz Association","Max-Planck-Gesellschaft","Cordis"],"pagination":["e12871"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8033531"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(4)"],"pubmed_abstract":["The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regul"],"journal":["EMBO molecular medicine"],"pubmed_title":["Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers."],"pmcid":["PMC8033531"],"funding_grant_id":["874656","R01 HL146519"],"pubmed_authors":["Reichenberger F","Silbernagel E","Adler H","Bohm S","Lindner M","Theis FJ","Geyer PE","Hilgendorff A","Leuschner G","Mann M","Kneidinger N","Angelidis I","Prasse A","Maurer B","Simon LM","Schniering J","Behr J","Singh P","Schiller HB","Mayr CH","Ansari M","Strunz M","Eickelberg O"],"additional_accession":[]},"is_claimable":false,"name":"Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers.","description":"The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regul","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Apr","modification":"2026-04-16T11:46:23.22Z","creation":"2022-02-09T16:01:30.122Z"},"accession":"S-EPMC8033531","cross_references":{"pubmed":["33650774"],"doi":["10.15252/emmm.202012871"]}}