A pilot study on proteomic predictors of mortality in stable COPD

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• dc.contributor.author Enríquez Rodríguez, César Jessé
• dc.contributor.author Casadevall Fusté, Carme
• dc.contributor.author Faner, Rosa
• dc.contributor.author Pascual Guàrdia, Sergi, 1979-
• dc.contributor.author Castro-Acosta, Ady Angélica
• dc.contributor.author López Campos, José Luis
• dc.contributor.author Peces-Barba Romero, Germán
• dc.contributor.author Seijo, Luis
• dc.contributor.author Caguana Vélez, Oswaldo Antonio
• dc.contributor.author Monsó Molas, Eduard
• dc.contributor.author Rodríguez Chiaradia, Diego Agustín
• dc.contributor.author Barreiro Portela, Esther
• dc.contributor.author Cosío, Borja G.
• dc.contributor.author Agustí García-Navarro, Àlvar
• dc.contributor.author Gea Guiral, Joaquim
• dc.contributor.author BIOMEPOC group
• dc.date.accessioned 2024-11-12T06:36:37Z
• dc.date.available 2024-11-12T06:36:37Z
• dc.date.issued 2024
• dc.description.abstract Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of global mortality. Despite clinical predictors (age, severity, comorbidities, etc.) being established, proteomics offers comprehensive biological profiling to obtain deeper insights into COPD pathophysiology and survival prognoses. This pilot study aimed to identify proteomic footprints that could be potentially useful in predicting mortality in stable COPD patients. Plasma samples from 40 patients were subjected to both blind (liquid chromatography-mass spectrometry) and hypothesis-driven (multiplex immunoassays) proteomic analyses supported by artificial intelligence (AI) before a 4-year clinical follow-up. Among the 34 patients whose survival status was confirmed (mean age 69 ± 9 years, 29.5% women, FEV1 42 ± 15.3% ref.), 32% were dead in the fourth year. The analysis identified 363 proteins/peptides, with 31 showing significant differences between the survivors and non-survivors. These proteins predominantly belonged to different aspects of the immune response (12 proteins), hemostasis (9), and proinflammatory cytokines (5). The predictive modeling achieved excellent accuracy for mortality (90%) but a weaker performance for days of survival (Q2 0.18), improving mildly with AI-mediated blind selection of proteins (accuracy of 95%, Q2 of 0.52). Further stratification by protein groups highlighted the predictive value for mortality of either hemostasis or pro-inflammatory markers alone (accuracies of 95 and 89%, respectively). Therefore, stable COPD patients' proteomic footprints can effectively forecast 4-year mortality, emphasizing the role of inflammatory, immune, and cardiovascular events. Future applications may enhance the prognostic precision and guide preventive interventions.
• dc.description.sponsorship This research was co-funded by the Spanish Ministerio de Economía y Competitividad and the European Union (project SAF2014-54371); the Instituto de Salud Carlos III (ISCIII) and European Union (projects PI21/00785 and M-BAE BA22/00009); SEPAR Grants (2015, 2016 and 2019); an FUCAP Grant (2014); an SOCAP Grant (2020); and Menarini Spain (unrestricted Grant 2015-19). César J. Enríquez-Rodríguez is a recipient of a Predoctoral Grant PFIS (ref. FI22/00003) and a Mobility of Research Personnel Grant (M-AES MV23/00012) from ISCIII and co-funded by the European Union.
• dc.format.mimetype application/pdf
• dc.identifier.citation Enríquez-Rodríguez CJ, Casadevall C, Faner R, Pascual-Guardia S, Castro-Acosta A, López-Campos JL, et al. A pilot study on proteomic predictors of mortality in stable COPD. Cells. 2024 Aug 14;13(16):1351. DOI: 10.3390/cells13161351
• dc.identifier.doi http://dx.doi.org/10.3390/cells13161351
• dc.identifier.issn 2073-4409
• dc.identifier.uri http://hdl.handle.net/10230/68492
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Cells. 2024 Aug 14;13(16):1351
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/SAF2014-54371
• dc.rights © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword COPD
• dc.subject.keyword Hemostasis
• dc.subject.keyword Immunity
• dc.subject.keyword Mortality
• dc.subject.keyword Prognosis
• dc.subject.keyword Proteomic fingerprint
• dc.title A pilot study on proteomic predictors of mortality in stable COPD
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion