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感染复数的多种定义。

The many definitions of multiplicity of infection.

作者信息

Schneider Kristan Alexander, Tsoungui Obama Henri Christian Junior, Kamanga George, Kayanula Loyce, Adil Mahmoud Yousif Nessma

机构信息

Department of Applied Computer- and Biosciences, University of Applied Sciences, Mittweida, Germany.

出版信息

Front Epidemiol. 2022 Oct 5;2:961593. doi: 10.3389/fepid.2022.961593. eCollection 2022.

Abstract

The presence of multiple genetically different pathogenic variants within the same individual host is common in infectious diseases. Although this is neglected in some diseases, it is well recognized in others like malaria, where it is typically referred to as multiplicity of infection (MOI) or complexity of infection (COI). In malaria, with the advent of molecular surveillance, data is increasingly being available with enough resolution to capture MOI and integrate it into molecular surveillance strategies. The distribution of MOI on the population level scales with transmission intensities, while MOI on the individual level is a confounding factor when monitoring haplotypes of particular interests, e.g., those associated with drug-resistance. Particularly, in high-transmission areas, MOI leads to a discrepancy between the likelihood of a haplotype being observed in an infection (prevalence) and its abundance in the pathogen population (frequency). Despite its importance, MOI is not universally defined. Competing definitions vary from verbal ones to those based on concise statistical frameworks. Heuristic approaches to MOI are popular, although they do not mine the full potential of available data and are typically biased, potentially leading to misinferences. We introduce a formal statistical framework and suggest a concise definition of MOI and its distribution on the host-population level. We show how it relates to alternative definitions such as the number of distinct haplotypes within an infection or the maximum number of alleles detectable across a set of genetic markers. It is shown how alternatives can be derived from the general framework. Different statistical methods to estimate the distribution of MOI and pathogenic variants at the population level are discussed. The estimates can be used as plug-ins to reconstruct the most probable MOI of an infection and set of infecting haplotypes in individual infections. Furthermore, the relation between prevalence of pathogenic variants and their frequency (relative abundance) in the pathogen population in the context of MOI is clarified, with particular regard to seasonality in transmission intensities. The framework introduced here helps to guide the correct interpretation of results emerging from different definitions of MOI. Especially, it excels comparisons between studies based on different analytical methods.

摘要

在同一宿主个体内存在多个基因不同的致病变体在传染病中很常见。尽管在某些疾病中这一点被忽视了,但在其他疾病如疟疾中却得到了充分认识,在疟疾中它通常被称为感染复数(MOI)或感染复杂性(COI)。在疟疾中,随着分子监测的出现,越来越有足够分辨率的数据可用于捕捉MOI并将其纳入分子监测策略。MOI在人群水平上的分布与传播强度相关,而在个体水平上,MOI在监测特定感兴趣的单倍型(例如与耐药性相关的单倍型)时是一个混杂因素。特别是在高传播地区,MOI导致在感染中观察到单倍型的可能性(流行率)与其在病原体群体中的丰度(频率)之间存在差异。尽管MOI很重要,但它并没有被普遍定义。相互竞争的定义从文字描述到基于简洁统计框架的定义各不相同。MOI的启发式方法很流行,尽管它们没有挖掘出可用数据的全部潜力,而且通常存在偏差,可能导致错误推断。我们引入了一个正式的统计框架,并提出了MOI及其在宿主群体水平上分布的简洁定义。我们展示了它与其他定义的关系,例如感染内不同单倍型的数量或一组遗传标记中可检测到的最大等位基因数。展示了如何从一般框架中推导出替代定义。讨论了在人群水平上估计MOI和致病变体分布的不同统计方法。这些估计值可以用作插件来重建个体感染中最可能的感染MOI和感染单倍型集。此外,在MOI的背景下,阐明了致病变体的流行率与其在病原体群体中的频率(相对丰度)之间的关系,特别是关于传播强度的季节性。这里介绍的框架有助于指导对MOI不同定义产生的结果的正确解释。特别是,它在基于不同分析方法的研究之间的比较中表现出色。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f78b/10910904/42c36d766c7d/fepid-02-961593-g0001.jpg

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