000307446 001__ 307446
000307446 005__ 20251231120304.0
000307446 0247_ $$2doi$$a10.1038/s41598-025-32565-y
000307446 0247_ $$2pmid$$apmid:41436524
000307446 0247_ $$2pmc$$apmc:PMC12738762
000307446 037__ $$aDKFZ-2025-03045
000307446 041__ $$aEnglish
000307446 082__ $$a600
000307446 1001_ $$0P:(DE-He78)928cfe90c9ba53a9d24391f31b14ce95$$aFrey, Dario$$b0$$eFirst author$$udkfz
000307446 245__ $$aSputOMICs identifies common and distinct markers in cystic fibrosis and chronic obstructive pulmonary disease.
000307446 260__ $$a[London]$$bSpringer Nature$$c2025
000307446 3367_ $$2DRIVER$$aarticle
000307446 3367_ $$2DataCite$$aOutput Types/Journal article
000307446 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1767096222_1386403
000307446 3367_ $$2BibTeX$$aARTICLE
000307446 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000307446 3367_ $$00$$2EndNote$$aJournal Article
000307446 500__ $$a#EA:B200#LA:B200#
000307446 520__ $$aCystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) are muco-obstructive lung diseases. Knowledge of molecular processes has much improved therapeutic options in CF, whereas much less is known for COPD, a disease affecting an increasing number of patients. Here, we report a multilayer workflow integrating microbiome, inflammation and proteome profiling with clinical data to identify disease specific characteristics in sputum. Our proof-of-concept study shows that CF sputum is dominated by Pseudomonas and Staphylococcus, exhibits heightened neutrophilic inflammation, and a severe protease-antiprotease imbalance. In contrast, COPD displays heterogeneous microbiome composition, eosinophilic inflammation, and altered extracellular matrix remodeling. Proteome-based cellular deconvolution identifies disease-specific immune cell signatures, underscoring the complexity, especially in COPD. Multi-omics factor analysis suggests that matrisome and nucleotide metabolism changes may act as disease discriminators, though future confirmation in larger cohorts is needed. These findings highlight the potential of our integrated approach to uncover sputum biomarkers as tools for patient stratification and personalized therapeutic strategies in CF and COPD.
000307446 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000307446 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000307446 650_7 $$2Other$$aBiomarkers
000307446 650_7 $$2Other$$aCOPD
000307446 650_7 $$2Other$$aCystic fibrosis
000307446 650_7 $$2Other$$aMicrobiome
000307446 650_7 $$2Other$$aMulti-omics
000307446 650_7 $$2Other$$aProteomics
000307446 650_7 $$2NLM Chemicals$$aBiomarkers
000307446 650_7 $$2NLM Chemicals$$aProteome
000307446 650_2 $$2MeSH$$aCystic Fibrosis: metabolism
000307446 650_2 $$2MeSH$$aCystic Fibrosis: microbiology
000307446 650_2 $$2MeSH$$aHumans
000307446 650_2 $$2MeSH$$aPulmonary Disease, Chronic Obstructive: metabolism
000307446 650_2 $$2MeSH$$aPulmonary Disease, Chronic Obstructive: microbiology
000307446 650_2 $$2MeSH$$aSputum: microbiology
000307446 650_2 $$2MeSH$$aSputum: metabolism
000307446 650_2 $$2MeSH$$aBiomarkers: metabolism
000307446 650_2 $$2MeSH$$aBiomarkers: analysis
000307446 650_2 $$2MeSH$$aFemale
000307446 650_2 $$2MeSH$$aMale
000307446 650_2 $$2MeSH$$aMicrobiota
000307446 650_2 $$2MeSH$$aProteome
000307446 650_2 $$2MeSH$$aProteomics: methods
000307446 650_2 $$2MeSH$$aAdult
000307446 7001_ $$0P:(DE-He78)1c49e2bc4134e93b5dc7d9845e30c039$$aHelm, Barbara$$b1$$udkfz
000307446 7001_ $$aGuerra, Matteo$$b2
000307446 7001_ $$aHagner, Matthias$$b3
000307446 7001_ $$aLu, Junyan$$b4
000307446 7001_ $$aDittrich, A Susanne$$b5
000307446 7001_ $$aWege, Sabine$$b6
000307446 7001_ $$aEberhardt, Ralf$$b7
000307446 7001_ $$aHerth, Felix J F$$b8
000307446 7001_ $$aSommerburg, Olaf$$b9
000307446 7001_ $$aSchultz, Carsten$$b10
000307446 7001_ $$aDalpke, Alexander H$$b11
000307446 7001_ $$0P:(DE-He78)860df4ab16c373fb28a815dcd81107a6$$aKlingmüller, Ursula$$b12$$eLast author$$udkfz
000307446 7001_ $$aMall, Marcus A$$b13
000307446 7001_ $$aBoutin, Sébastien$$b14
000307446 773__ $$0PERI:(DE-600)2615211-3$$a10.1038/s41598-025-32565-y$$gVol. 15, no. 1, p. 44418$$n1$$p44418$$tScientific reports$$v15$$x2045-2322$$y2025
000307446 909CO $$ooai:inrepo02.dkfz.de:307446$$pVDB
000307446 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)928cfe90c9ba53a9d24391f31b14ce95$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000307446 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)1c49e2bc4134e93b5dc7d9845e30c039$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000307446 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)860df4ab16c373fb28a815dcd81107a6$$aDeutsches Krebsforschungszentrum$$b12$$kDKFZ
000307446 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000307446 9141_ $$y2025
000307446 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bSCI REP-UK : 2022$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-07-29T15:28:26Z
000307446 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-07-29T15:28:26Z
000307446 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2024-07-29T15:28:26Z
000307446 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-18
000307446 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-18
000307446 9202_ $$0I:(DE-He78)B200-20160331$$kB200$$lB200 Systembiologie der Signaltransduktion$$x0
000307446 9201_ $$0I:(DE-He78)B200-20160331$$kB200$$lB200 Systembiologie der Signaltransduktion$$x0
000307446 9201_ $$0I:(DE-He78)W120-20160331$$kW120$$lProteomics$$x1
000307446 9200_ $$0I:(DE-He78)B200-20160331$$kB200$$lB200 Systembiologie der Signaltransduktion$$x0
000307446 9200_ $$0I:(DE-He78)W120-20160331$$kW120$$lProteomics$$x1
000307446 980__ $$ajournal
000307446 980__ $$aVDB
000307446 980__ $$aI:(DE-He78)B200-20160331
000307446 980__ $$aI:(DE-He78)W120-20160331
000307446 980__ $$aUNRESTRICTED