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1.
J Infect Dis ; 2024 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-39194054

RESUMO

Chagas disease is a neglected tropical infection that affects millions of people. This study explores transcriptomic changes in T. cruzi-infected subjects before and after treatment. Using total RNA sequencing, gene transcription was analyzed in peripheral blood mononuclear cells from asymptomatic (n=19) and symptomatic (n=8) T. cruzi-infected individuals, and non-infected controls (n=15). Differential expression was compared across groups, and before/after treatment in infected subgroups. Untreated infection showed 12 upregulated and 206 downregulated genes in all T. cruzi-infected subjects, and 47 upregulated and 215 downregulated genes in the symptomatic group. Few differentially expressed genes were found after treatment and between the different infected groups. Gene set enrichment analysis highlighted immune-related pathways activated during infection, with therapy normalizing immune function. Changes in the kynurenine/tryptophan ratio, increased pre-treatment, suggested chronic immune fatigue, which was restored post-treatment. These differentially expressed genes offer insights for potential biomarkers and pathways associated with disease progression and treatment response.

2.
Res Rep Trop Med ; 14: 1-19, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37337597

RESUMO

Chagas disease is the most important protozoan infection in the Americas, and constitutes a significant public health concern throughout the world. Development of new medications against its etiologic agent, Trypanosoma cruzi, has been traditionally slow and difficult, lagging in comparison with diseases caused by other kinetoplastid parasites. Among the factors that explain this are the incompletely understood mechanisms of pathogenesis of T. cruzi infection and its complex set of interactions with the host in the chronic stage of the disease. These demand the performance of a variety of in vitro and in vivo assays as part of any drug development effort. In this review, we discuss recent breakthroughs in the understanding of the parasite's life cycle and their implications in the search for new chemotherapeutics. For this, we present a framework to guide drug discovery efforts against Chagas disease, considering state-of-the-art preclinical models and recently developed tools for the identification and validation of molecular targets.

3.
Expert Rev Anti Infect Ther ; 21(12): 1287-1299, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37933443

RESUMO

INTRODUCTION: Chagas disease, caused by parasite Trypanosoma cruzi, is the most important neglected tropical disease in the Americas. Two drugs are available for treatment, but access to them is challenging, in part due to complex diagnostic algorithms. These are stage-dependent, involve multiple tests, and are ill-adapted to the reality of vast areas where the disease is endemic. Molecular and serologic tools are used to detect acute and chronic infections, with the performance of the latter showing geographic differences. Breakthroughs in the development of new diagnostic tools include the validation of a loop-mediated isothermal amplification assay for acute infections (T. cruzi-LAMP), and the regional validation of several rapid diagnostic tests (RDTs) for chronic infection, which simplify testing in resource-limited settings. The literature search was carried out in the MEDLINE database until 1 August 2023. AREAS COVERED: This review outlines existing algorithms, and proposes new ones focused on point-of-care testing. EXPERT OPINION: Integrating point-of-care testing into existing diagnostic algorithms in certain endemic areas will increase access to timely diagnosis and treatment. However, additional research is needed to validate the use of these techniques across a wider geography, and to better understand the cost-effectiveness of their large-scale implementation.


Assuntos
Doença de Chagas , Trypanosoma cruzi , Humanos , Doença de Chagas/diagnóstico , Doença de Chagas/epidemiologia , Testes Imediatos , Testes de Diagnóstico Rápido , Algoritmos
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