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Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model

BACKGROUND: The immune system is a complex adaptive system of cells and molecules that are interwoven in a highly organized communication network. Primary immune deficiencies are disorders in which essential parts of the immune system are absent or do not function according to plan. X-linked agammag...

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Autor principal: Figge, Marc Thilo
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2685018/
https://www.ncbi.nlm.nih.gov/pubmed/19479057
http://dx.doi.org/10.1371/journal.pone.0005685
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author Figge, Marc Thilo
author_facet Figge, Marc Thilo
author_sort Figge, Marc Thilo
collection PubMed
description BACKGROUND: The immune system is a complex adaptive system of cells and molecules that are interwoven in a highly organized communication network. Primary immune deficiencies are disorders in which essential parts of the immune system are absent or do not function according to plan. X-linked agammaglobulinemia is a B-lymphocyte maturation disorder in which the production of immunoglobulin is prohibited by a genetic defect. Patients have to be put on life-long immunoglobulin substitution therapy in order to prevent recurrent and persistent opportunistic infections. METHODOLOGY: We formulate an immune response model in terms of stochastic differential equations and perform a systematic analysis of empirical therapy protocols that differ in the treatment frequency. The model accounts for the immunoglobulin reduction by natural degradation and by antigenic consumption, as well as for the periodic immunoglobulin replenishment that gives rise to an inhomogeneous distribution of immunoglobulin specificities in the shape space. Results are obtained from computer simulations and from analytical calculations within the framework of the Fokker-Planck formalism, which enables us to derive closed expressions for undetermined model parameters such as the infection clearance rate. CONCLUSIONS: We find that the critical value of the clearance rate, below which a chronic infection develops, is strongly dependent on the strength of fluctuations in the administered immunoglobulin dose per treatment and is an increasing function of the treatment frequency. The comparative analysis of therapy protocols with regard to the treatment frequency yields quantitative predictions of therapeutic relevance, where the choice of the optimal treatment frequency reveals a conflict of competing interests: In order to diminish immunomodulatory effects and to make good economic sense, therapeutic immunoglobulin levels should be kept close to physiological levels, implying high treatment frequencies. However, clearing infections without additional medication is more reliably achieved by substitution therapies with low treatment frequencies. Our immune response model predicts that the compromise solution of immunoglobulin substitution therapy has a treatment frequency in the range from one infusion per week to one infusion per two weeks.
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spelling pubmed-26850182009-05-28 Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model Figge, Marc Thilo PLoS One Research Article BACKGROUND: The immune system is a complex adaptive system of cells and molecules that are interwoven in a highly organized communication network. Primary immune deficiencies are disorders in which essential parts of the immune system are absent or do not function according to plan. X-linked agammaglobulinemia is a B-lymphocyte maturation disorder in which the production of immunoglobulin is prohibited by a genetic defect. Patients have to be put on life-long immunoglobulin substitution therapy in order to prevent recurrent and persistent opportunistic infections. METHODOLOGY: We formulate an immune response model in terms of stochastic differential equations and perform a systematic analysis of empirical therapy protocols that differ in the treatment frequency. The model accounts for the immunoglobulin reduction by natural degradation and by antigenic consumption, as well as for the periodic immunoglobulin replenishment that gives rise to an inhomogeneous distribution of immunoglobulin specificities in the shape space. Results are obtained from computer simulations and from analytical calculations within the framework of the Fokker-Planck formalism, which enables us to derive closed expressions for undetermined model parameters such as the infection clearance rate. CONCLUSIONS: We find that the critical value of the clearance rate, below which a chronic infection develops, is strongly dependent on the strength of fluctuations in the administered immunoglobulin dose per treatment and is an increasing function of the treatment frequency. The comparative analysis of therapy protocols with regard to the treatment frequency yields quantitative predictions of therapeutic relevance, where the choice of the optimal treatment frequency reveals a conflict of competing interests: In order to diminish immunomodulatory effects and to make good economic sense, therapeutic immunoglobulin levels should be kept close to physiological levels, implying high treatment frequencies. However, clearing infections without additional medication is more reliably achieved by substitution therapies with low treatment frequencies. Our immune response model predicts that the compromise solution of immunoglobulin substitution therapy has a treatment frequency in the range from one infusion per week to one infusion per two weeks. Public Library of Science 2009-05-28 /pmc/articles/PMC2685018/ /pubmed/19479057 http://dx.doi.org/10.1371/journal.pone.0005685 Text en Figge. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Figge, Marc Thilo
Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title_full Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title_fullStr Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title_full_unstemmed Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title_short Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model
title_sort optimization of immunoglobulin substitution therapy by a stochastic immune response model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2685018/
https://www.ncbi.nlm.nih.gov/pubmed/19479057
http://dx.doi.org/10.1371/journal.pone.0005685
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