Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections
The dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequ...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-08-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2021.696755/full |
| _version_ | 1819148108692455424 |
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| author | Hung D. Nguyen Hung D. Nguyen Sidhartha Chaudhury Adam T. Waickman Heather Friberg Jeffrey R. Currier Anders Wallqvist |
| author_facet | Hung D. Nguyen Hung D. Nguyen Sidhartha Chaudhury Adam T. Waickman Heather Friberg Jeffrey R. Currier Anders Wallqvist |
| author_sort | Hung D. Nguyen |
| collection | DOAJ |
| description | The dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequent infections from a different serotype. We developed a stochastic model of the adaptive immune response to dengue infections. We first delineated the mechanisms initiating and sustaining adaptive immune responses during primary infections. We then contrasted these immune responses during secondary infections of either a homotypic or heterotypic serotype to understand the role of pre-existing and reactivated immune pathways on disease severity. Comparison of non-symptomatic and severe cases from heterotypic infections demonstrated that overproduction of specific antibodies during primary infection induces an enhanced population of cross-reactive antibodies during secondary infection, ultimately leading to severe disease manifestations. In addition, the level of disease severity was found to correlate with immune response kinetics, which was dependent on beginning lymphocyte levels. Our results detail the contribution of specific lymphocytes and antibodies to immunity and memory recall that lead to either protective or pathological outcomes, allowing for the understanding and determination of mechanisms of protective immunity. |
| first_indexed | 2024-12-22T13:40:28Z |
| format | Article |
| id | doaj.art-5570f83ee3c740fbbd66a66cd3b5f949 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-22T13:40:28Z |
| publishDate | 2021-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-5570f83ee3c740fbbd66a66cd3b5f9492022-12-21T18:23:57ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-08-011210.3389/fimmu.2021.696755696755Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue InfectionsHung D. Nguyen0Hung D. Nguyen1Sidhartha Chaudhury2Adam T. Waickman3Heather Friberg4Jeffrey R. Currier5Anders Wallqvist6Biotechnology High Performance Computing (HPC) Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, United StatesHenry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United StatesCenter for Enabling Capabilities, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesDepartment of Microbiology and Immunology, State University of New York Upstate Medical University, Syracuse, NY, United StatesViral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesViral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesBiotechnology High Performance Computing (HPC) Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, United StatesThe dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequent infections from a different serotype. We developed a stochastic model of the adaptive immune response to dengue infections. We first delineated the mechanisms initiating and sustaining adaptive immune responses during primary infections. We then contrasted these immune responses during secondary infections of either a homotypic or heterotypic serotype to understand the role of pre-existing and reactivated immune pathways on disease severity. Comparison of non-symptomatic and severe cases from heterotypic infections demonstrated that overproduction of specific antibodies during primary infection induces an enhanced population of cross-reactive antibodies during secondary infection, ultimately leading to severe disease manifestations. In addition, the level of disease severity was found to correlate with immune response kinetics, which was dependent on beginning lymphocyte levels. Our results detail the contribution of specific lymphocytes and antibodies to immunity and memory recall that lead to either protective or pathological outcomes, allowing for the understanding and determination of mechanisms of protective immunity.https://www.frontiersin.org/articles/10.3389/fimmu.2021.696755/fulldengue infectionaffinity maturationimmune responsecross-reactive antibodieshumoral immunitycellular immunity |
| spellingShingle | Hung D. Nguyen Hung D. Nguyen Sidhartha Chaudhury Adam T. Waickman Heather Friberg Jeffrey R. Currier Anders Wallqvist Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections Frontiers in Immunology dengue infection affinity maturation immune response cross-reactive antibodies humoral immunity cellular immunity |
| title | Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections |
| title_full | Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections |
| title_fullStr | Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections |
| title_full_unstemmed | Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections |
| title_short | Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections |
| title_sort | stochastic model of the adaptive immune response predicts disease severity and captures enhanced cross reactivity in natural dengue infections |
| topic | dengue infection affinity maturation immune response cross-reactive antibodies humoral immunity cellular immunity |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2021.696755/full |
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