Evidence mapPaperPMID 40429672Full record

ArticleInternational journal of molecular sciences2025

Metabolomic Plasma Profile of Chronic Obstructive Pulmonary Disease Patients.

Carme Casadevall, Bella Agranovich, Cesar Jesse Enríquez-Rodríguez, Rosa Faner, Sergi Pascual-Guàrdia, Ady Castro-Acosta, Ramon Camps-Ubach, Judith Garcia-Aymerich, Esther Barreiro, Eduard Monsó and 11 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Plasma Lipidomic Signatures Across the Healthy-Pre-COPD-COPD Continuum Identified by Machine Learning.International journal of chronic obstructive pulmonary disease · 2026
    Observational
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Carme CasadevallHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.ORCID 0000-0001-6458-8972
Bella AgranovichThe Ruth and Bruce Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa 3525433, Israel.
Cesar Jesse Enríquez-RodríguezHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.ORCID 0000-0002-5944-6555
Rosa FanerCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.ORCID 0000-0002-8159-0115
Sergi Pascual-GuàrdiaHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.
Ady Castro-AcostaServicio de Neumología, Hospital 12 de Octubre, 28041 Madrid, Spain.
Ramon Camps-UbachHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.
Judith Garcia-AymerichMELIS Department, Universitat Pompeu Fabra, 08003 Barcelona, Spain.ORCID 0000-0002-7097-4586
Esther BarreiroHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.
Eduard MonsóFundació Institut d'Investigació i Innovació Parc Taulí (I3PT), 08208 Sabadell, Spain.
Luis SeijoCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.
Juan José Soler-CataluñaCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.
Salud SantosCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.ORCID 0000-0002-5835-1028
Germán Peces-BarbaCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.ORCID 0000-0002-4436-8443
José Luis López-CamposCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.
Ciro CasanovaCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.ORCID 0000-0001-7364-7508
Alvar AgustíCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.
Borja G CosíoCentro de Investigación Biomédica en Red, Área de Enfermedades Respiratorias (CIBERES), Instituto de Investigación Carlos III (ISCiii), 28029 Madrid, Spain.ORCID 0000-0002-6388-8209
Ifat AbramovichThe Ruth and Bruce Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa 3525433, Israel.
Joaquim GeaHospital del Mar Research Institute, Servei de Pneumologia, Hospital del Mar, MELIS Department, Universitat Pompeu Fabra, 08013 Barcelona, Spain.
EARLY COPD and BIOMEPOC Groups

Funding

FUCAP 2014Instituto de Salud Carlos III (ISCIII) and European Union PI17/00369, PI18/01008, PI21/00785, FI22/00003, M-BAE BA22/00009 and M-AES MV23/00012Menarini Spain Unrestricted Grant 2015-19SEPAR 2015, 2016 and 2019SOCAP 2020Spanish Ministerio de Economía y Competitividad and the European Union SAF2014-54371
6 · The paper itself

Abstract

The analysis of blood metabolites may help identify individuals at risk of having COPD and offer insights into its underlying pathophysiology. This study aimed to identify COPD-related metabolic alterations and generate a biological signature potentially useful for screening purposes. Plasma metabolomic profiles from 91 COPD patients and 91 controls were obtained using complementary semi-targeted and untargeted LC-MS approaches. Univariate analysis identified metabolites with significant differences between groups, and enrichment analysis highlighted the most affected metabolic pathways. Multivariate analysis, including ROC curve assessment and machine learning algorithms, was applied to assess the discriminatory capacity of selected metabolites. After adjustment for major potential confounders, 56 metabolites showed significant differences between COPD patients and controls. The enrichment analysis revealed that COPD-associated metabolic alterations primarily involved lipid metabolism (especially fatty acids and acylcarnitines), followed by amino acid pathways and xenobiotics. A panel of 10 metabolites, mostly related to lipid metabolism, demonstrated high discriminatory performance for COPD (ROC-AUC: 0.916; 90.1% sensitivity and 89% specificity). These findings may contribute to improving screening strategies and a better understanding of COPD-related metabolic changes. However, our findings remain exploratory and should be interpreted with caution, needing further validation and mechanistic studies.

Indexed as

MetabolomeMetabolomicsPulmonary Disease, Chronic ObstructiveAgedBiomarkersCase-Control StudiesFemaleHumansLipid MetabolismMaleMiddle AgedROC CurveBiomarkersacylcarnitinesamino acidsCOPDfatty acidslipid homeostasismetabolites

Identifiers

PMID40429672
PMCPMC12111085

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.