Worby Colin J, Chang Hsiao-Han, Hanage William P, Lipsitch Marc
Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115
Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115.
Genetics. 2014 Dec;198(4):1395-404. doi: 10.1534/genetics.114.171538. Epub 2014 Oct 13.
Whole-genome sequencing of pathogens has recently been used to investigate disease outbreaks and is likely to play a growing role in real-time epidemiological studies. Methods to analyze high-resolution genomic data in this context are still lacking, and inferring transmission dynamics from such data typically requires many assumptions. While recent studies have proposed methods to infer who infected whom based on genetic distance between isolates from different individuals, the link between epidemiological relationship and genetic distance is still not well understood. In this study, we investigated the distribution of pairwise genetic distances between samples taken from infected hosts during an outbreak. We proposed an analytically tractable approximation to this distribution, which provides a framework to evaluate the likelihood of particular transmission routes. Our method accounts for the transmission of a genetically diverse inoculum, a possibility overlooked in most analyses. We demonstrated that our approximation can provide a robust estimation of the posterior probability of transmission routes in an outbreak and may be used to rule out transmission events at a particular probability threshold. We applied our method to data collected during an outbreak of methicillin-resistant Staphylococcus aureus, ruling out several potential transmission links. Our study sheds light on the accumulation of mutations in a pathogen during an epidemic and provides tools to investigate transmission dynamics, avoiding the intensive computation necessary in many existing methods.
病原体的全基因组测序最近已被用于调查疾病爆发，并且很可能在实时流行病学研究中发挥越来越重要的作用。在这种情况下，分析高分辨率基因组数据的方法仍然缺乏，并且从这些数据推断传播动态通常需要许多假设。虽然最近的研究提出了基于来自不同个体的分离株之间的遗传距离来推断谁感染了谁的方法，但流行病学关系与遗传距离之间的联系仍未得到很好的理解。在本研究中，我们调查了在一次疾病爆发期间从受感染宿主采集的样本之间成对遗传距离的分布。我们提出了一种对此分布易于分析处理的近似方法，它提供了一个框架来评估特定传播途径的可能性。我们的方法考虑了遗传多样的接种物的传播，这是大多数分析中被忽视的一种可能性。我们证明，我们的近似方法可以对疾病爆发中传播途径的后验概率提供稳健的估计，并且可用于在特定概率阈值下排除传播事件。我们将我们的方法应用于耐甲氧西林金黄色葡萄球菌爆发期间收集的数据，排除了几个潜在的传播联系。我们的研究揭示了病原体在疫情期间突变的积累，并提供了调查传播动态的工具，避免了许多现有方法中所需的密集计算。
