肠道微生物群干扰在化疗放疗反复压力引起的疲劳中的作用:概念验证研究

Advances in Medicine Pub Date : 2020-02-07 eCollection Date: 2020-01-01 DOI:10.1155/2020/6375876
Velda J González-Mercado, Josué Pérez-Santiago, Debra Lyon, Israel Dilán-Pantojas, Wendy Henderson, Susan McMillan, Maureen Groer, Brad Kane, Sara Marrero, Elsa Pedro, Leorey N Saligan
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引用次数: 0

摘要

研究目的这项概念验证研究的目的是:(a) 研究直肠癌成人患者在接受化放疗(CRT)过程中疲劳程度和肠道微生物组多样性的时间变化;(b) 研究在化放疗中期和末期,疲劳和非疲劳患者的肠道微生物组多样性是否存在差异;(c) 研究在 CRT 的中期和末期,疲劳和非疲劳参与者的粪便微生物群在门和属的相对丰度上是否存在差异。研究方法在 CRT 开始前、CRT 中期(12-16 次治疗后)和后期(24-28 次治疗后)收集粪便样本和症状评级。对疲劳进行描述性统计和曼-惠特尼 U 检验。使用 QIIME2 软件分析了肠道微生物组数据:结果:参与者(N = 29)的年龄从 37 岁到 80 岁不等。在 CRT 结束时,疲劳评分的中位数(中位数 = 23.0)与总样本在 CRT 开始前的中位数(中位数 = 17.0;P ≤ 0.05)相比发生了显著变化。在 CRT 中期,疲劳参与者的阿尔法多样性(操作分类单元的丰度)(149.30 ± 53.1)低于非疲劳参与者(189.15 ± 44.18,t(23) = 2.08,p ≤ 0.05)。在CRT中期,疲劳参与者的α多样性(操作分类单元的丰度)(149.30 ± 53.1)低于非疲劳参与者(189.15 ± 44.18),变形菌、固有菌和类杆菌是疲劳参与者的优势菌门,埃希氏菌、巴氏杆菌、粪杆菌和弧菌是疲劳参与者最丰富的菌属:结论:与 CRT 相关的肠道微生物群组成紊乱可能会导致疲劳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Role of Gut Microbiome Perturbation in Fatigue Induced by Repeated Stress from Chemoradiotherapy: A Proof of Concept Study.

The Role of Gut Microbiome Perturbation in Fatigue Induced by Repeated Stress from Chemoradiotherapy: A Proof of Concept Study.

The Role of Gut Microbiome Perturbation in Fatigue Induced by Repeated Stress from Chemoradiotherapy: A Proof of Concept Study.

The Role of Gut Microbiome Perturbation in Fatigue Induced by Repeated Stress from Chemoradiotherapy: A Proof of Concept Study.

Objectives: The objectives of this proof of concept study were to (a) examine the temporal changes in fatigue and diversity of the gut microbiome over the course of chemoradiotherapy (CRT) in adults with rectal cancers; (b) investigate whether there are differences in diversity of the gut microbiome between fatigued and nonfatigued participants at the middle and at the end of CRT; and (c) investigate whether there are differences in the relative abundance of fecal microbiota at the phylum and genus levels between fatigued and nonfatigued participants at the middle and at the end of CRT.

Methods: Stool samples and symptom ratings were collected prior to the inception of CRT, at the middle (after 12-16 treatments) and at the end (after 24-28 treatments) of the CRT. Descriptive statistics and Mann-Whitney U test were computed for fatigue. Gut microbiome data were analyzed using the QIIME2 software.

Results: Participants (N = 29) ranged in age from 37 to 80 years. The median fatigue score significantly changed at the end of CRT (median = 23.0) compared with the median score before the initiation of CRT for the total sample (median = 17.0; p ≤ 0.05). At the middle of CRT, the alpha diversity (abundance of Operational Taxonomic Units) was lower for fatigued participants (149.30 ± 53.1) than for nonfatigued participants (189.15 ± 44.18, t(23) = 2.08, p ≤ 0.05). At the middle of CRT, the alpha diversity (abundance of Operational Taxonomic Units) was lower for fatigued participants (149.30 ± 53.1) than for nonfatigued participants (189.15 ± 44.18, Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla for fatigued participants, and Escherichia, Bacteroides, Faecalibacterium, and Oscillospira were the most abundant genera for fatigued participants.

Conclusion: CRT-associated perturbation of the gut microbiome composition may contribute to fatigue.

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