Identification of Chagas disease biomarkers using untargeted metabolomics

• Published in: Scientific reports Vol. 14; no. 1; pp. 18768 - 11
• Main Authors: Herreros-Cabello, Alfonso, Bosch-Nicolau, Pau, Pérez-Molina, José A., Salvador, Fernando, Monge-Maillo, Begoña, Rodriguez-Palomares, Jose F., Ribeiro, Antonio Luiz Pinho, Sánchez-Montalvá, Adrián, Sabino, Ester Cerdeira, Norman, Francesca F., Fresno, Manuel, Gironès, Núria, Molina, Israel
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13.08.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/53; 692/700/1750; Adult; Aged; Amino acids; Bilirubin; Biliverdin; Biomarkers; Biomarkers - blood; Cardiomyopathy; Chagas Cardiomyopathy - blood; Chagas Cardiomyopathy - metabolism; Chagas disease; Chagas Disease - blood; Chagas Disease - diagnosis; Chronic chagasic cardiomyopathy; Chronic infection; Coronary artery disease; Cross-Sectional Studies; Female; Heart diseases; Humanities and Social Sciences; Humans; Latency; Male; Metabolites; Metabolome; Metabolomics; Metabolomics - methods; Middle Aged; multidisciplinary; Peptides; Phenols; Science; Science (multidisciplinary); Tropical diseases; Untargeted metabolomics; Vector-borne diseases; Chagas disease; Biomarkers; Untargeted metabolomics; Chronic chagasic cardiomyopathy
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-69205-w

Untargeted metabolomic analysis is a powerful tool used for the discovery of novel biomarkers. Chagas disease (CD), caused by Trypanosoma cruzi , is a neglected tropical disease that affects 6–7 million people with approximately 30% developing cardiac manifestations. The most significant clinical challenge lies in its long latency period after acute infection, and the lack of surrogate markers to predict disease progression or cure. In this cross-sectional study, we analyzed sera from 120 individuals divided into four groups: 31 indeterminate CD, 41 chronic chagasic cardiomyopathy (CCC), 18 Latin Americans with other cardiomyopathies and 30 healthy volunteers. Using a high-throughput panel of 986 metabolites, we identified three distinct profiles among individuals with cardiomyopathy, indeterminate CD and healthy volunteers. After a more stringent analysis, we identified some potential biomarkers. Among peptides, phenylacetylglutamine and fibrinopeptide B (1–13) exhibited an increasing trend from controls to ICD and CCC. Conversely, reduced levels of bilirubin and biliverdin alongside elevated urobilin correlated with disease progression. Finally, elevated levels of cystathionine, phenol glucuronide and vanillactate among amino acids distinguished CCC individuals from ICD and controls. Our novel exploratory study using metabolomics identified potential biomarker candidates, either alone or in combination that if confirmed, can be translated into clinical practice.