Identification of Chagas disease biomarkers using untargeted metabolomics

Other authors

Institut Català de la Salut

[Herreros Cabello A] Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Madrid, Spain. Departamento de Biología Molecular, Universidad Autónoma de Madrid (UAM), Madrid, Spain. [Bosch Nicolau P, Salvador F, Sánchez Montalvá A, Molina I] Unitat de Salut Internacional, Servei de Malalties Infeccioses, Vall d’Hebron Hospital Universitari, Barcelona, Spain. PROSICS Barcelona, Barcelona, Spain. Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain. Medicine Department, Universitat Autònoma de Barcelona, Bellaterra, Spain. [Pérez Molina JA, Monge Maillo B] Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain. National Referral Unit for Tropical Diseases, Infectious Diseases Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain. [Rodriguez Palomares JF] Servei de Cardiologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Medicine Department, Universitat Autònoma de Barcelona, Bellaterra, Spain. CIBER de Enfermedades Cardiovasculares, Instituto de Salud Carlos III, Madrid, Spain

Vall d'Hebron Barcelona Hospital Campus

Publication date

2025-02-28T09:13:12Z

2025-02-28T09:13:12Z

2024-08-13



Abstract

Biomarkers; Chagas disease; Untargeted metabolomics


Biomarcadores; Enfermedad de Chagas; Metabolómica no dirigida


Biomarcadors; Malaltia de Chagas; Metabolòmica no dirigida


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.


This project was funded by “Proyectos de investigación en salud” program of the Instituto Carlos III, Ministry of Science, Innovation and Universities of the Spanish Government. Grant number: PI19/01807. Dr Ribeiro is supported in part by CNPq (465518/2014-1 e 310790/2021-2) and FAPEMIG (RED 00192-23). Dr. Sabino is supported in part by NIH grant: 1U01AI168383-01.

Document Type

Article


Published version

Language

English

Publisher

Nature Portfolio

Related items

Scientific Reports;14

https://doi.org/10.1038/s41598-024-69205-w

info:eu-repo/grantAgreement/ES/PE2017-2020/PI19%2F01807

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Attribution-NonCommercial-NoDerivatives 4.0 International

http://creativecommons.org/licenses/by-nc-nd/4.0/

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