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利用灵长类动物的系统地理学链接预测来优先筛选人类寄生虫。

Using phylogeographic link-prediction in primates to prioritize human parasite screening.

机构信息

Department of Evolutionary Anthropology, Duke University, Durham, NC, USA.

Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey.

出版信息

Am J Biol Anthropol. 2023 Dec;182(4):583-594. doi: 10.1002/ajpa.24604. Epub 2022 Aug 26.

Abstract

OBJECTIVES

The ongoing risk of emerging infectious disease has renewed calls for understanding the origins of zoonoses and identifying future zoonotic disease threats. Given their close phylogenetic relatedness and geographic overlap with humans, non-human primates (NHPs) have been the source of many infectious diseases throughout human evolution. NHPs harbor diverse parasites, with some infecting only a single host species while others infect species from multiple families.

MATERIALS AND METHODS

We applied a novel link-prediction method to predict undocumented instances of parasite sharing between humans and NHPs. Our model makes predictions based on phylogenetic distances and geographic overlap among NHPs and humans in six countries with high NHP diversity: Columbia, Brazil, Democratic Republic of Congo, Madagascar, China and Indonesia.

RESULTS

Of the 899 human parasites documented in the Global Infectious Diseases and Epidemiology Network (GIDEON) database for these countries, 12% were shared with at least one other NHP species. The link prediction model identified an additional 54 parasites that are likely to infect humans but were not reported in GIDEON. These parasites were mostly host generalists, yet their phylogenetic host breadth varied substantially.

DISCUSSION

As human activities and populations encroach on NHP habitats, opportunities for parasite sharing between human and non-human primates will continue to increase. Our study identifies specific infectious organisms to monitor in countries with high NHP diversity, while the comparative analysis of host generalism, parasite taxonomy, and transmission mode provides insights to types of parasites that represent high zoonotic risk.

摘要

目的

新发传染病的持续风险再次呼吁人们了解人畜共患病的起源,并确定未来的人畜共患疾病威胁。由于非人灵长类动物(NHPs)与人类在进化上密切相关,且在地理上有重叠,因此它们一直是许多传染病的源头。NHPs 携带多种寄生虫,其中一些寄生虫只感染单一宿主物种,而另一些寄生虫则感染来自多个科的物种。

材料和方法

我们应用了一种新的链接预测方法来预测人类和 NHP 之间未记录的寄生虫共享实例。我们的模型基于灵长类动物和人类在六个非人灵长类动物多样性高的国家(哥伦比亚、巴西、刚果民主共和国、马达加斯加、中国和印度尼西亚)的系统发育距离和地理重叠进行预测。

结果

在所研究的六个国家的全球传染病和流行病学网络(GIDEON)数据库中记录的 899 个人类寄生虫中,有 12%与至少一种其他 NHP 物种共享。链接预测模型还确定了另外 54 种可能感染人类但未在 GIDEON 中报告的寄生虫。这些寄生虫大多是宿主泛化种,但它们的系统发育宿主范围差异很大。

讨论

随着人类活动和人口侵占 NHP 栖息地,人类和非人类灵长类动物之间寄生虫共享的机会将继续增加。我们的研究确定了在非人灵长类动物多样性高的国家需要监测的特定传染病原体,而宿主泛化、寄生虫分类学和传播方式的比较分析为代表高人畜共患病风险的寄生虫类型提供了见解。

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本文引用的文献

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Predicting missing links in global host-parasite networks.预测全球宿主-寄生虫网络中的缺失环节。
J Anim Ecol. 2022 Apr;91(4):715-726. doi: 10.1111/1365-2656.13666. Epub 2022 Feb 7.
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The future of zoonotic risk prediction.动物传染病风险预测的未来。
Philos Trans R Soc Lond B Biol Sci. 2021 Nov 8;376(1837):20200358. doi: 10.1098/rstb.2020.0358. Epub 2021 Sep 20.
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Intensity and frequency of extreme novel epidemics.极端新型传染病的强度和频率。
Proc Natl Acad Sci U S A. 2021 Aug 31;118(35). doi: 10.1073/pnas.2105482118.
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Zoonotic spillover: Understanding basic aspects for better prevention.人畜共患病传播:了解基本方面以实现更好的预防。
Genet Mol Biol. 2021 Jun 4;44(1 Suppl 1):e20200355. doi: 10.1590/1678-4685-GMB-2020-0355. eCollection 2021.

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