Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Sci Rep. 2024 Sep 4;14(1):20650. doi: 10.1038/s41598-024-71852-y.
In human microbiome studies, mediation analysis has recently been spotlighted as a practical and powerful analytic tool to survey the causal roles of the microbiome as a mediator to explain the observed relationships between a medical treatment/environmental exposure and a human disease. We also note that, in a clinical research, investigators often trace disease progression sequentially in time; as such, time-to-event (e.g., time-to-disease, time-to-cure) responses, known as survival responses, are prevalent as a surrogate variable for human health or disease. In this paper, we introduce a web cloud computing platform, named as microbiome mediation analysis with survival responses (MiMedSurv), for comprehensive microbiome mediation analysis with survival responses on user-friendly web environments. MiMedSurv is an extension of our prior web cloud computing platform, named as microbiome mediation analysis (MiMed), for survival responses. The two main features that are well-distinguished are as follows. First, MiMedSurv conducts some baseline exploratory non-mediational survival analysis, not involving microbiome, to survey the disparity in survival response between medical treatments/environmental exposures. Then, MiMedSurv identifies the mediating roles of the microbiome in various aspects: (i) as a microbial ecosystem using ecological indices (e.g., alpha and beta diversity indices) and (ii) as individual microbial taxa in various hierarchies (e.g., phyla, classes, orders, families, genera, species). To illustrate its use, we survey the mediating roles of the gut microbiome between antibiotic treatment and time-to-type 1 diabetes. MiMedSurv is freely available on our web server ( http://mimedsurv.micloud.kr ).
在人类微生物组研究中,中介分析最近作为一种实用且强大的分析工具备受关注,用于调查微生物组作为中介的因果作用,以解释医学治疗/环境暴露与人类疾病之间的观察到的关系。我们还注意到,在临床研究中,研究人员经常按时间顺序追踪疾病的进展;因此,时间事件(例如,疾病时间、治愈时间)反应,称为生存反应,作为人类健康或疾病的替代变量很常见。在本文中,我们介绍了一个名为具有生存反应的微生物组中介分析(MiMedSurv)的网络云计算平台,用于在用户友好的网络环境中进行全面的具有生存反应的微生物组中介分析。MiMedSurv 是我们之前的网络云计算平台,名为具有生存反应的微生物组中介分析(MiMed)的扩展,用于生存反应。两个主要的区别特征如下。首先,MiMedSurv 进行一些基本的探索性非中介生存分析,不涉及微生物组,以调查治疗/环境暴露之间生存反应的差异。然后,MiMedSurv 确定微生物组在各个方面的中介作用:(i)作为微生物生态系统,使用生态指数(例如,alpha 和 beta 多样性指数)和(ii)作为各个层次的单个微生物分类群(例如,门、纲、目、科、属、种)。为了说明其用途,我们调查了肠道微生物组在抗生素治疗和 1 型糖尿病时间之间的中介作用。MiMedSurv 可在我们的网络服务器(http://mimedsurv.micloud.kr)上免费使用。