Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity.
Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity.
复制标题
肠道微生物群为肥胖患者提供短期低碳水化合物饮食 (LCD) 干预的可预测结果。
DOI：
10.1128/spectrum.00223-21
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发表时间：
2021-10-31
影响因子：
3.7
通讯作者：
Sun J
中科院分区：
文献类型：
--
作者：
Zhang S;Wu P;Tian Y;Liu B;Huang L;Liu Z;Lin N;Xu N;Ruan Y;Zhang Z;Wang M;Cui Z;Zhou H;Xie L;Chen H;Sun J
到目前为止，肥胖患者的饮食治疗已经取得了很大进展。在过去的十年里，低碳水化合物饮食(LCD)在临床上的应用已经复苏，但其机制和疗效尚不明确。肠道微生物群被认为可以促进能量收集。在这里，我们认为肠道微生物区系导致了LCD下不一致的结果。为了验证这一假设，肥胖患者或超重患者被随机分配到正常饮食(ND)组或自由摄入能量的液晶组，持续12 周。采用配对抽样的方法，检测了基线和终点的微生物群落组成。液晶屏干预12 周后，丁酸产生菌的相对丰度显著增加，包括卟啉单胞菌属、副杆菌属和瘤胃球菌科振荡杆菌属。此外，在LCD组中，基线时类杆菌相对丰度较高的参与者对LCD干预的反应更好，并取得了更好的减肥效果。然而，采用基于人工神经网络(ANN)的预测模型在预测LCD干预后的体重减轻结果方面远远超过一般的线性模型。因此，肠道微生物区系是一个积极的结果预测因子，并有可能预测短期LCD干预后的减肥结果。肠道微生物区系可能有助于指导临床应用短期LCD干预，以制定有效的减肥策略。(本研究已在中国临床试验注册中心注册，批准号：ChiCTR1800015156)。肥胖及其相关并发症对人类健康构成严重威胁。不限制卡路里的短期低碳水化合物饮食(LCD)干预对超重/肥胖者有显著的减肥效果。此外，类杆菌科类杆菌的相对丰度是短期LCD干预后个体体重减轻的积极结果预测因子。此外，利用基线上这些不同的肠道微生物结构，我们建立了基于人工神经网络(ANN)算法的预测模型，可用于在每次临床试验(中国专利号2021104655623)之前估计减肥潜力。这将有助于指导临床应用短期LCD干预，提高减肥策略。
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.