Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity
ABSTRACT To date, much progress has been made in dietary therapy for obese patients. A low-carbohydrate diet (LCD) has reached a revival in its clinical use during the past decade with undefined mechanisms and debatable efficacy. The gut microbiota has been suggested to promote energy harvesting. He...
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American Society for Microbiology
2021-10-01
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Series: | Microbiology Spectrum |
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Online Access: | https://journals.asm.org/doi/10.1128/Spectrum.00223-21 |
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author | Susu Zhang Peili Wu Ye Tian Bingdong Liu Liujing Huang Zhihong Liu Nie Lin Ningning Xu Yuting Ruan Zhen Zhang Ming Wang Zongbing Cui HongWei Zhou Liwei Xie Hong Chen Jia Sun |
author_facet | Susu Zhang Peili Wu Ye Tian Bingdong Liu Liujing Huang Zhihong Liu Nie Lin Ningning Xu Yuting Ruan Zhen Zhang Ming Wang Zongbing Cui HongWei Zhou Liwei Xie Hong Chen Jia Sun |
author_sort | Susu Zhang |
collection | DOAJ |
description | ABSTRACT To date, much progress has been made in dietary therapy for obese patients. A low-carbohydrate diet (LCD) has reached a revival in its clinical use during the past decade with undefined mechanisms and debatable efficacy. The gut microbiota has been suggested to promote energy harvesting. Here, we propose that the gut microbiota contributes to the inconsistent outcome under an LCD. To test this hypothesis, patients with obesity or patients who were overweight were randomly assigned to a normal diet (ND) or an LCD group with ad libitum energy intake for 12 weeks. Using matched sampling, the microbiome profile at baseline and end stage was examined. The relative abundance of butyrate-producing bacteria, including Porphyromonadaceae Parabacteroides and Ruminococcaceae Oscillospira, was markedly increased after LCD intervention for 12 weeks. Moreover, within the LCD group, participants with a higher relative abundance of Bacteroidaceae Bacteroides at baseline exhibited a better response to LCD intervention and achieved greater weight loss outcomes. Nevertheless, the adoption of an artificial neural network (ANN)-based prediction model greatly surpasses a general linear model in predicting weight loss outcomes after LCD intervention. Therefore, the gut microbiota served as a positive outcome predictor and has the potential to predict weight loss outcomes after short-term LCD intervention. Gut microbiota may help to guide the clinical application of short-term LCD intervention to develop effective weight loss strategies. (This study has been registered at the China Clinical Trial Registry under approval no. ChiCTR1800015156). IMPORTANCE Obesity and its related complications pose a serious threat to human health. Short-term low-carbohydrate diet (LCD) intervention without calorie restriction has a significant weight loss effect for overweight/obese people. Furthermore, the relative abundance of Bacteroidaceae Bacteroides is a positive outcome predictor of individual weight loss after short-term LCD intervention. Moreover, leveraging on these distinct gut microbial structures at baseline, we have established a prediction model based on the artificial neural network (ANN) algorithm that could be used to estimate weight loss potential before each clinical trial (with Chinese patent number 2021104655623). This will help to guide the clinical application of short-term LCD intervention to improve weight loss strategies. |
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language | English |
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spelling | doaj.art-04fb6c85aa9441b19f20cf3ba188b5212022-12-21T16:43:10ZengAmerican Society for MicrobiologyMicrobiology Spectrum2165-04972021-10-019210.1128/Spectrum.00223-21Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with ObesitySusu Zhang0Peili Wu1Ye Tian2Bingdong Liu3Liujing Huang4Zhihong Liu5Nie Lin6Ningning Xu7Yuting Ruan8Zhen Zhang9Ming Wang10Zongbing Cui11HongWei Zhou12Liwei Xie13Hong Chen14Jia Sun15Department of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaState Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, ChinaState Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, ChinaState Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaNephrology Center of Integrated Traditional Chinese and Western Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaState Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, ChinaState Key Laboratory of Organ Failure Research, Microbiome Medicine Center, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaABSTRACT To date, much progress has been made in dietary therapy for obese patients. A low-carbohydrate diet (LCD) has reached a revival in its clinical use during the past decade with undefined mechanisms and debatable efficacy. The gut microbiota has been suggested to promote energy harvesting. Here, we propose that the gut microbiota contributes to the inconsistent outcome under an LCD. To test this hypothesis, patients with obesity or patients who were overweight were randomly assigned to a normal diet (ND) or an LCD group with ad libitum energy intake for 12 weeks. Using matched sampling, the microbiome profile at baseline and end stage was examined. The relative abundance of butyrate-producing bacteria, including Porphyromonadaceae Parabacteroides and Ruminococcaceae Oscillospira, was markedly increased after LCD intervention for 12 weeks. Moreover, within the LCD group, participants with a higher relative abundance of Bacteroidaceae Bacteroides at baseline exhibited a better response to LCD intervention and achieved greater weight loss outcomes. Nevertheless, the adoption of an artificial neural network (ANN)-based prediction model greatly surpasses a general linear model in predicting weight loss outcomes after LCD intervention. Therefore, the gut microbiota served as a positive outcome predictor and has the potential to predict weight loss outcomes after short-term LCD intervention. Gut microbiota may help to guide the clinical application of short-term LCD intervention to develop effective weight loss strategies. (This study has been registered at the China Clinical Trial Registry under approval no. ChiCTR1800015156). IMPORTANCE Obesity and its related complications pose a serious threat to human health. Short-term low-carbohydrate diet (LCD) intervention without calorie restriction has a significant weight loss effect for overweight/obese people. Furthermore, the relative abundance of Bacteroidaceae Bacteroides is a positive outcome predictor of individual weight loss after short-term LCD intervention. Moreover, leveraging on these distinct gut microbial structures at baseline, we have established a prediction model based on the artificial neural network (ANN) algorithm that could be used to estimate weight loss potential before each clinical trial (with Chinese patent number 2021104655623). This will help to guide the clinical application of short-term LCD intervention to improve weight loss strategies.https://journals.asm.org/doi/10.1128/Spectrum.00223-21gut microbiotalow-carbohydrate dietsBacteroidaceae Bacteroidesartificial neural networkobesityweight loss |
spellingShingle | Susu Zhang Peili Wu Ye Tian Bingdong Liu Liujing Huang Zhihong Liu Nie Lin Ningning Xu Yuting Ruan Zhen Zhang Ming Wang Zongbing Cui HongWei Zhou Liwei Xie Hong Chen Jia Sun Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity Microbiology Spectrum gut microbiota low-carbohydrate diets Bacteroidaceae Bacteroides artificial neural network obesity weight loss |
title | Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity |
title_full | Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity |
title_fullStr | Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity |
title_full_unstemmed | Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity |
title_short | Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity |
title_sort | gut microbiota serves a predictable outcome of short term low carbohydrate diet lcd intervention for patients with obesity |
topic | gut microbiota low-carbohydrate diets Bacteroidaceae Bacteroides artificial neural network obesity weight loss |
url | https://journals.asm.org/doi/10.1128/Spectrum.00223-21 |
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