Chang Stewart T, Linderman Jennifer J, Kirschner Denise E
Program in Bioinformatics, Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.
Infect Immun. 2008 Jul;76(7):3221-32. doi: 10.1128/IAI.01677-07. Epub 2008 Apr 28.
Several molecules related to antigen presentation, including gamma interferon (IFN-gamma) and the major histocompatibility complex (MHC), are encoded by polymorphic genes. Some polymorphisms were found to affect susceptibility to tuberculosis (TB) when they were considered singly in epidemiological studies, but how multiple polymorphisms interact to determine susceptibility to TB in an individual remains an open question. We hypothesized that polymorphisms in some genes may counteract or intensify the effects of polymorphisms in other genes. For example, an increase in IFN-gamma expression may counteract the weak binding that a particular MHC variant displays for a peptide from Mycobacterium tuberculosis to establish the same T-cell response as another, more strongly binding MHC variant. To test this hypothesis, we developed a mathematical model of antigen presentation based on experimental data for the known effects of genetic polymorphisms and simulated time courses when multiple polymorphisms were present. We found that polymorphisms in different genes could affect antigen presentation to the same extent and therefore compensate for each other. Furthermore, we defined the conditions under which such relationships could exist. For example, increased IFN-gamma expression compensated for decreased peptide-MHC affinity in the model only above a certain threshold of expression. Below this threshold, changes in IFN-gamma expression were ineffectual compared to changes in peptide-MHC affinity. The finding that polymorphisms exhibit such relationships could explain discrepancies in the epidemiological literature, where some polymorphisms have been inconsistently associated with susceptibility to TB. Furthermore, the model allows polymorphisms to be ranked by effect, providing a new tool for designing association studies.
几种与抗原呈递相关的分子,包括γ干扰素(IFN-γ)和主要组织相容性复合体(MHC),由多态性基因编码。在流行病学研究中单独考虑时,发现一些多态性会影响结核病(TB)易感性,但多个多态性如何相互作用以确定个体对TB的易感性仍是一个悬而未决的问题。我们假设某些基因中的多态性可能会抵消或增强其他基因中多态性的影响。例如,IFN-γ表达的增加可能会抵消特定MHC变体对结核分枝杆菌肽的弱结合,从而建立与另一种结合更强的MHC变体相同的T细胞反应。为了验证这一假设,我们基于遗传多态性已知效应的实验数据建立了一个抗原呈递数学模型,并模拟了存在多个多态性时的时间进程。我们发现不同基因中的多态性可能在相同程度上影响抗原呈递,因此相互补偿。此外,我们定义了这种关系可能存在的条件。例如,在模型中,只有当IFN-γ表达高于一定阈值时,其表达增加才能补偿肽-MHC亲和力的降低。低于该阈值时,与肽-MHC亲和力的变化相比,IFN-γ表达的变化无效。多态性呈现这种关系的发现可以解释流行病学文献中的差异,其中一些多态性与TB易感性的关联并不一致。此外,该模型允许根据效应对多态性进行排序,为设计关联研究提供了一种新工具。