7ef378d0255fb2a9d5f30d9f2c1fac8d 319511.pdf 7bb0b9a04e04e670d90d750583fbf5cfe0ba8d46 319511.pdf 36cc30ed2538481a984dcd95ff3d4d1bd6c267732cdcf778620bb783c5000e57 319511.pdf Title: Metabolomic Plasma Profile of Chronic Obstructive Pulmonary Disease Patients Subject: 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. Keywords: COPD; metabolites; lipid homeostasis; amino acids; fatty acids; acylcarnitines Author: 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, Luis Seijo, Juan José Soler-Cataluña, Salud Santos, Germán Peces-Barba, José Luis López-Campos, Ciro Casanova, Alvar Agustí, Borja G. 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Info: Title: Metabolomic Plasma Profile of Chronic Obstructive Pulmonary Disease Patients Author: 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, Luis Seijo, Juan José Soler-Cataluña, Salud Santos, Germán Peces-Barba, José Luis López-Campos, Ciro Casanova, Alvar Agustí, Borja G. Cosío, Ifat Abramovich and Joaquim Gea Subject: 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. 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