Quantitative Veterinary Epidemiology, Wageningen University & Research, 6700AH, Wageningen, The Netherlands.
Animal Breeding and Genomics Group, Wageningen University & Research, 6700AH, Wageningen, The Netherlands.
Genetics. 2021 Apr 15;217(4). doi: 10.1093/genetics/iyab024.
Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).
遗传选择以提高疾病抗性是农业中对抗传染病策略的重要组成部分。然而，对二元疾病状态的数量遗传分析表明，大多数疾病的遗传力都很低，这限制了疾病流行率的遗传降低速度。此外，常见的易患性阈值模型表明，通过遗传选择根除传染病是不可能的，因为当流行率接近零时，观察到的遗传力趋于零。然而，从传染病流行病学的角度来看，我们知道根除传染病是可能的，无论是在理论上还是实践中，因为正反馈机制导致了众所周知的群体免疫现象。然而，常见的数量遗传模型忽略了这些反馈机制。在这里，我们将二元疾病状态的数量遗传分析与传染病传播的流行病学模型相结合，旨在确定减少地方性传染病流行率的选择响应的潜力。结果表明，二元疾病状态的典型遗传力值对应于个体间疾病易感性的非常大的遗传变异。此外，我们的结果表明，通过遗传选择根除传染病在原则上是可能的。这些发现与基于常见数量遗传模型的预测强烈不一致，后者忽略了在降低传染病传播时发生的正反馈效应。这些反馈效应是一种特定的间接遗传效应；它们对选择响应和群体免疫的发展（即有效繁殖率小于 1）有很大贡献。
