Paper reading (九十)：Can Gut Microbiota Composition Predict Response to Dietary Treatments

论文题目：Can Gut Microbiota Composition Predict Response to Dietary Treatments

scholar 引用：4

页数：15

发表时间：2019.05

发表刊物：nutrients

作者：Jessica R Biesiekierski , Jonna Jalanka, and Heidi M Staudacher

作者单位：Department of Dietetics, Nutrition & Sport, School of Allied Health Human Services & Sport, La Trobe University

摘要：

Dietary intervention is a challenge in clinical pracetice because of inter-individual variability in clinical response. Gut microbiota is mechanistically relevant for a number of disease states and consequently has been incorporated as a key variable in personalised nutrition models withiin the research context. This paper aims to review the evidence related to the predictive capacity of baseline microbiota for clinical response to dietary intervention in two specific health conditions, namely, obesity and irritable bowel syndrome (IBS). Clinical trials and larger predictive modelling studies were identified and critically evaluated. The findings reveal inconsistent evidience to support baseline microbiota as an accurate predictor of weight loss or glycaemic response in obesity, or as a predictor of symptom improvement in irritable bowel syndrome., in dietary intervention trials. Desite advancement in quatification methodologies, research in this area remains challenging and larger scale studies are needed until personalised nutrition is realistically achievable and can be translated to clinical practice.

keywords: personalised nutrition; microbiota; dietary intervention; obesity; irritable bowel syndrome; gastrointestinal symptoms

正文组织架构：

1. Introduction

1.1 Clinical condition1: Obesity

1.2 Clinical condition2: Irritable Bowel Syndrome 肠易激综合征

1.3 Purpose of Review

1.4 Role of Intestinal Microbiota (肠道菌群) in Obesity

1.5 Impact of Dietary Treatment on Microbiome in Obesity

1.6 Microbiome as a Predictor for Dietary Treatment Response in Obesity

1.7 Role of Intestinal Microbiota in IBS

1.8 Impact of Dietary Treatment on the Micrombiome in IBS

1.9 Microbiome as a Predictor for Dietary Treatment Response in IBS

2. General Discussion and Limitations

3. Conclusions

正文部分内容摘录：

1. 健康还是特定疾病？多少个体和组别？就是说这些组别的个体是对健康个体进行干预，还是特定疾病的人在干预？

特定疾病： obesity and IBS
The low FODMAP diet, an approach restricting the intake of specific fermentable carbohydrates (i.e., oligo-, di-, mono-saccharides and polyols) is a second-line dietary intervention. 这个没有说是益生菌或益生元的干预哦。
Efficacy of probiotics and faecal microbiota transplantation (FMT) (via colonisation with “lean microbiota”) to induce weight loss in obese individuals implies that attempts at “correcting” the microbial equilibrium can influence body weight and adiposity in obesity. 在IBS中提到了益生菌的作用
Table 1. Summary of recent trials reporting on the association between baseline gut microbiota composition and association with clinical response in obesity. 这个表格总结了8个study的数据集的饮食干预方式和主要发现。
however, many did not report on other external factors that could influence microbiota composition (e.g., probiotics), which may have contributed to the heterogeneity of findings.
Finally, although it is still unclear whether a divergent microbiota is a primary phenomenon, the efficacy of therapies such as probiotics and FMT implies that attempts at “correcting” the abnormality lead to at least partial restoration of microbial and GI equilibrium
the trend toward efficacy of Bifidobacteria-containing probiotic supplements in IBS
如下的表格中又总结了几组跟IBS相关的干预实验。
There are obvious challenges in interpreting the evidence from these trials. Pre-intervention environmental factors (e.g., medication, probiotic intake) that could impact on baseline microbiota composition are not always reported or controlled.
Few human studies (summarised in Table 1 and Table 2) have been conducted investigating whether specific microbial signatures predict response to dietary interventions.

2. 有哪些组学数据可利用？

Personalised nutrition models integrate a variety of host-specific variables including current diet, biological or phenotypical characteristics of the individual (age, stage of life, gender, body mass index (BMI), disease or health status) and genotypic characteristics. 基因型特征就是组学数据吧？

3. 组学数据的下载ID是什么？

没有提到组学数据的下载ID。

4. 研究的干预基本结果和结论是什么？

饮食是肠道菌群重要决定因素之一，但是饮食与菌群之间的关系很复杂，目前尚不明了。
personalised nutrition models that predict clinical response to dietary treatment based on the microbial composition are still extremely challenging to test in the research context.
Some evidence of associations between gut microbiota and response to dietary treatments for both obesity and IBS suggests that links exist between microbiota composition and inter-individuality in host response to diet. 有一些证据证明两者有联系
然而：personalised nutrition research is in its infancy and specific microbiota signatures that predict individualised responses to dietary treatment are still elusive; advancements in analysis technologies and consistent bioinformatic approaches will be important for progress. 个性化饮食的研究目前还是起步阶段
table1和table2中总结的所有study的局限：

First, microbial sampling (i.e., faecal or biopsy) and quantification methodologies applied across studies thus far have been inconsistent. 实验定量方法不一样，也就是说缺乏统一规范。
Second, there are several shortcomings in the predictive modelling analysis methods utilised. Studies may be limited to exploratory statistical analysis until clinical studies can be adequately designed and powered for primary analysis. 很多预测方法都是探索性的。
Third, there are many problematic confounding factors that can impact on baseline microbiota composition.These factors include, but are not limited to, the host genetic makeup, long-term dietary habits, ethnicity, sanitation, geographical location, exercise and lifestyle habits, and antibiotic use. 影响因素太多了。。。这也是为什么老是提出只是假设变化趋势是一样的，而不是说初始态和终态会有相似性。
Finally, for ultimate translation into clinical practice, there is a need to understand if the results gained from short-term studies predicting host response can be translated into durable responses over time, leading to long-term positive health outcomes. Longer duration of studies and intervention periods are also needed. 需要更长时间的干预和观察来验证假设

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