Autoimmune diseases initiated by pathogen infection: Mathematical modeling
Autoimmune diseases initiated by pathogen infection: Mathematical modeling
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DOI：
10.1016/j.jtbi.2020.110296
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发表时间：
2020-08-07
影响因子：
2
通讯作者：
Iwasa, Yoh
中科院分区：
文献类型：
--
作者：
Hara, Akane;Iwasa, Yoh
人类许多不治之症都与自身免疫有关，最初是由病毒感染引起的。据推测，该病毒的抗原的表位与宿主身体成分中的表位相似，从而使其能够逃避免疫监视。病毒感染会激活免疫系统，从而清除病毒。感染后，增强的免疫系统可能开始攻击宿主的细胞、组织和器官。在这项研究中，我们开发了一个简单的数学模型，在该模型中我们确定了触发自身免疫反应所需的条件。该模型考虑了辅助 T 细胞 (Th) 细胞、病毒、自身抗原和记忆 T 细胞的动态。病毒感染会导致病毒丰度暂时增加，而病毒丰度会被 Th 细胞数量的增加所抑制。为了将病毒从体内清除，即使体内没有病毒，Th细胞的水平也必须维持在一定阈值以上，以防止病毒复制。这一作用是由颞叶病毒感染期间产生的记忆 T 细胞实现的。因此，我们研究了病毒感染后免疫反应增强所需的条件，并得出结论，交叉免疫对于阴性选择和T细胞激活来说一定很弱，但对于抗原抑制反应来说一定很强。我们还讨论了交叉免疫的替代模型和模型的可能扩展。 (C) 2020 作者。由爱思唯尔有限公司出版
Many incurable diseases in humans are related to autoimmunity and are initially induced by a viral infection. Presumably, the virus has antigens with epitopes similar to those found in components of the host's body, thus allowing it to evade immune surveillance. Viral infection activates the immune system, which results in viral clearance. After infection, the enhanced immune system may begin to attack the host's cells, tissues, and organs. In this study, we developed a simple mathematical model in which we identify the conditions needed to trigger an autoimmune response. This model considers the dynamics of T helper (Th) cells, viruses, self-antigens, and memory T cells. Viral infection results in a temporal increase in viral abundance, which is suppressed by an increase in the number of Th cells. For the virus to be eliminated from the body, the level of Th cells must be maintained above a certain threshold to prevent viral replication, even in the absence of virus in the body. This role is realized by memory T cells produced during temporal viral infections. Thus, we investigated the conditions needed for the immune response to be enhanced after viral infection and concluded that cross-immunity must be weak for negative selection and T-cell activation but strong for antigen-suppressing reactions. We also discuss alternative models of cross-immunity and possible extensions of the model. (C) 2020 The Author(s). Published by Elsevier Ltd.