Critical Network Structures and Medical Ecology Mechanisms Underlying Human Microbiome-Associated Diseases
Critical Network Structures and Medical Ecology Mechanisms Underlying Human Microbiome-Associated Diseases
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DOI：
10.1016/j.isci.2020.101195
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发表时间：
2020-06-26
期刊：
影响因子：
5.8
通讯作者：
Ma, Zhanshan (Sam)
中科院分区：
文献类型：
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作者：
Ma, Zhanshan (Sam)
人类微生物组相关疾病（MAD）研究的一个基本问题是了解微生物组结构与宿主健康状况之间的关系。例如，几乎所有关于MAD的研究都对物种多样性指标进行了常规评估，但最近的一项荟萃分析显示，只有大约三分之一的情况下，多样性和疾病有关。在这项研究中，我们询问Hubbell的中性理论（补充了归一化随机性比率[NSR]）或关键微生物组网络结构是否可以提供更好的替代方案。而中性理论和NSR侧重于随机过程，我们使用核心/外围和高。突出骨架网络，以评估确定性，不对称的生态位效应，假设所有物种或其相互作用不是“出生”平等，并侧重于非中性，关键的网络结构。我们发现，关键网络结构的属性更能反映疾病的影响。总结了有关MADs的医学生态学机制的7个发现（机制、解释和假设）。
A fundamental problem in studies on human microbiome-associated diseases (MADs) is to understand the relationships between microbiome structures and health status of hosts. For example, species diversity metrics have been routinely evaluated in virtually all studies on MADs, yet a recent meta-analysis revealed that, in only approximately one-third of the cases, diversity and diseases were related. In this study, we ask whether Hubbell's neutral theory (supplemented with the normalized stochasticity ratio [NSR]) or critical microbiome network structures may offer better alternatives. Whereas neutral theory and NSR focus on stochastic processes, we use core/periphery and high. salience skeleton networks to evaluate deterministic, asymmetrical niche effects, assuming that all species or their interactions were not "born" equal and focusing on non-neutral, critical network structures. We found that properties of critical network structures are more indicative of disease effects. seven findings (mechanisms, interpretations, and postulations) regarding medical ecology mechanisms underlying MADs were summarized.