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Population-level Diversity-disease Relationship (p-DDR) in the Human Microbiome Associated Diseases
论文题目: Population-level Diversity-disease Relationship (p-DDR) in the Human Microbiome Associated Diseases
作者: Li, Wendy; Ma, Zhanshan Sam
联系作者: ma@vandals.uidaho.edu
发表年度: 2021
DOI: DOI:10.1016/j.csbj.2021.04.032
摘要: Diversity-disease relationship (DDR) is a de facto standard analysis in the studies of human microbiome associated diseases (MADs). For example, the species richness or Shannon entropy are routinely compared between the healthy and diseased groups. Nevertheless, the basic scale of the standard diversity analysis is individual subject rather than a cohort or population because the diversity is computed for individual samples, not for the group. Here we aim to expand the current DDR study from individual focus to population level, which can offer important insights for understanding the epidemiology of MADs. We analyzed the diversity-disease relationship at cohort scale based on a collection of 23 datasets covering the major human MADs. Methodologically, we harness the power of a recent extension to the classic species-area relationship (SAR), i.e., the diversity-area relationship (DAR), to achieve the expansion from individual DDR to inter-subject diversity scaling analysis. Specifically, we apply the DAR analysis to estimate and compare the potentially maximal accrual diversities of the healthy and diseases groups, as well as the inter-subject diversity scaling parameters and the individual-to-population diversity ratios. It was shown that, except for the potential diversity (Dmax) at the cohort level in approximately 5.4% cases of MADs, DAR parameters displayed no significant differences between healthy and diseased treatments. That is, the DAR parameters are rather resilient against MADs, except for the potential diversity in some diseases. We compared our population-level DDR with the existing individual-level DDR patterns and proposed a hypothesis to interpret their differences
刊物名称: Computational and Structural Biotechnology Journal
论文出处: https://www.sciencedirect.com/science/article/pii/S2001037021001446?via%3Dihub
影响因子: 6.018(2019年)
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