Development and Validation of a Novel Microbiome-Based Biomarker of Post-antibiotic Dysbiosis and Subsequent Restoration.
Development and Validation of a Novel Microbiome-Based Biomarker of Post-antibiotic Dysbiosis and Subsequent Restoration.
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DOI：
10.3389/fmicb.2021.781275
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发表时间：
2021
影响因子：
5.2
通讯作者：
Shannon WD
中科院分区：
文献类型：
--
作者：
Blount K;Jones C;Walsh D;Gonzalez C;Shannon WD
背景资料：人类肠道微生物群对健康和健康很重要，而微生物群稳态被破坏或“生态失调”可能会导致或促成许多胃肠道疾病状态。菌群失调可以由许多因素引起，最明显的是抗生素治疗。为了纠正生态失调并恢复更健康的微生物群，几种研究性的基于微生物群的活生物群产品（LBP）正在正式的临床开发中。为了更好地指导和完善LBP的发展，并更好地了解和管理抗生素给药的风险，需要区分抗生素后微生态失调与健康微生物群的生物标志物。在这里，我们报告了抗生素后生态失调（MHI-A）的原型微生物组健康指数的发展。研究方法：MHI-A是使用来自RBX 2660和RBX 7455临床试验参与者的纵向肠道微生物组数据开发和验证的，RBX 2660和RBX 7455是用于减少复发性艰难梭菌感染（rCDI）的研究性LBP。MHI-A算法涉及RBX 2660或RBX 7455治疗后变化最大的微生物组分类类别的相对丰度，其与临床应答强烈相关，并且反映了被认为对rCDI重要的生物学机制。MHI-A的诊断效用使用来自健康或经抗微生物治疗的人群的公开可用的微生物组数据得到加强。结果：MHI-A在区分抗生素后微生态失调与健康微生物群方面具有较高的准确性。MHI-A值在多个健康人群中是一致的，并且被已知改变微生物群组成的抗生素治疗显著改变，被微生物群保留抗生素改变较少。对RBX 2660和RBX 7455的临床应答与MHI-A从微生态失调值向健康值的转变相关。结论：MHI-A是抗生素后微生态失调和随后恢复的一个有前途的生物标志物。MHI-A可用于抗生素的微生物群破坏作用的排序，并作为微生物群恢复的药效学措施。
Background: The human gut microbiota are important to health and wellness, and disrupted microbiota homeostasis, or “dysbiosis,” can cause or contribute to many gastrointestinal disease states. Dysbiosis can be caused by many factors, most notably antibiotic treatment. To correct dysbiosis and restore healthier microbiota, several investigational microbiota-based live biotherapeutic products (LBPs) are in formal clinical development. To better guide and refine LBP development and to better understand and manage the risks of antibiotic administration, biomarkers that distinguish post-antibiotic dysbiosis from healthy microbiota are needed. Here we report the development of a prototype Microbiome Health Index for post-Antibiotic dysbiosis (MHI-A). Methods: MHI-A was developed and validated using longitudinal gut microbiome data from participants in clinical trials of RBX2660 and RBX7455 – investigational LBPs in development for reducing recurrent Clostridioides difficile infections (rCDI). The MHI-A algorithm relates the relative abundances of microbiome taxonomic classes that changed the most after RBX2660 or RBX7455 treatment, that strongly correlated with clinical response, and that reflect biological mechanisms believed important to rCDI. The diagnostic utility of MHI-A was reinforced using publicly available microbiome data from healthy or antibiotic-treated populations. Results: MHI-A has high accuracy to distinguish post-antibiotic dysbiosis from healthy microbiota. MHI-A values were consistent across multiple healthy populations and were significantly shifted by antibiotic treatments known to alter microbiota compositions, shifted less by microbiota-sparing antibiotics. Clinical response to RBX2660 and RBX7455 correlated with a shift of MHI-A from dysbiotic to healthy values. Conclusion: MHI-A is a promising biomarker of post-antibiotic dysbiosis and subsequent restoration. MHI-A may be useful for rank-ordering the microbiota-disrupting effects of antibiotics and as a pharmacodynamic measure of microbiota restoration.
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影响因子：
16.6
作者：
Duvallet C;Gibbons SM;Gurry T;Irizarry RA;Alm EJ
通讯作者：
Alm EJ
影响因子：
12.2
作者：
Magruder M;Edusei E;Zhang L;Albakry S;Satlin MJ;Westblade LF;Malha L;Sze C;Lubetzky M;Dadhania DM;Lee JR
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Lee JR
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8.7
作者：
Pickard JM;Zeng MY;Caruso R;Núñez G
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Núñez G
影响因子：
3.7
作者：
La Rosa PS;Brooks JP;Deych E;Boone EL;Edwards DJ;Wang Q;Sodergren E;Weinstock G;Shannon WD
通讯作者：
Shannon WD
影响因子：
56.3
作者：
Kokai-Kun, John F.;Roberts, Tracey;Sliman, Joseph
通讯作者：
Sliman, Joseph