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Updated: May 26, 2026
Immunometabolic Circuits in Infection for Advancing Host Directed Therapies
Published on: September 13, 2024
Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies
Bettina M Länger1, Cristina Pou-Barreto, Carlos González-Alcón
1Grupo de Tecnología Bioquímica, Departamento de Bioquímica y Biología Molecular, Universidad de La Laguna, 38206, San Cristóbal de La Laguna, Tenerife, Spain.
Background:
The WHO considers leishmaniasis as one of the six most important tropical diseases worldwide. It is caused by parasites of the genus Leishmania that are passed on to humans and animals by the phlebotomine sandfly. Despite all of the research, there is still a lack of understanding on the metabolism of the parasite and the progression of the disease. In this study, a mathematical model of disease progression was developed based on experimental data of clinical symptoms, immunological responses, and parasite load for Leishmania amazonensis in BALB/c mice.
Results:
Four biologically significant variables were chosen to develop a differential equation model based on the GMA power-law formalism. Parameters were determined to minimize error in the model dynamics and time series experimental data. Subsequently, the model robustness was tested and the model predictions were verified by comparing them with experimental observations made in different experimental conditions. The model obtained helps to quantify relationships between the selected variables, leads to a better understanding of disease progression, and aids in the identification of crucial points for introducing therapeutic methods.
Conclusions:
Our model can be used to identify the biological factors that must be changed to minimize parasite load in the host body, and contributes to the design of effective therapies.
Insights
A new mathematical model quantifies leishmaniasis progression by analyzing clinical symptoms, immune responses, and parasite load. This model aids in understanding disease dynamics and identifying therapeutic targets for leishmaniasis.
Area of Science:
- Parasitology
- Mathematical Biology
- Immunology
Background:
- Leishmaniasis is a significant global tropical disease, impacting humans and animals.
- Caused by Leishmania parasites transmitted by sandflies.
- Current understanding of parasite metabolism and disease progression remains limited.
Purpose of the Study:
- To develop a mathematical model for Leishmania amazonensis disease progression.
- To analyze clinical symptoms, immunological responses, and parasite load.
- To improve understanding of disease dynamics in BALB/c mice.
Main Methods:
- Developed a differential equation model using GMA power-law formalism.
- Selected four biologically significant variables.
- Determined parameters by minimizing model-data error and tested model robustness.
Main Results:
- Quantified relationships between key biological variables.
- Validated model predictions against experimental data under varied conditions.
- Gained insights into Leishmania amazonensis disease progression.
Conclusions:
- The model identifies critical biological factors for minimizing parasite load.
- Contributes to designing effective therapeutic strategies for leishmaniasis.
- Enhances understanding of host-parasite interactions.
