肠道菌群
腰围
医学
微生物群
餐食
代谢综合征
成分
生理学
内科学
肥胖
食品科学
生物
免疫学
生物信息学
作者
Shuo Wang,Lingling Zhang,Di Wang,Meiqin Huang,Jingyu Zhao,Vasanti Malik,Xiaoran Liu,Liang Sun,Xu Lin,Yan Chen
标识
DOI:10.1002/mnfr.202001051
摘要
Peanuts are widely consumed as a meal ingredient and a snack, and are commonly considered as a healthy food based on their nutrient profile. Peanut consumption has been associated with a lower risk of metabolic syndrome (MetS) in epidemiological studies. This study aims to investigate whether consuming peanuts affects the gut microbiota in adults with risk of MetS and whether the intervention effect of peanuts is associated with gut microbiota composition.This study analyzes the gut microbiota of subjects from a 12-week randomized clinical trial comparing consumption of either peanuts or isocaloric carbohydrate bars. It is observed that there is high inter-individual variability on multiple clinical and anthropometrical parameters in response to peanut consumption. Meanwhile, the gut microbiota composition is also highly person-specific and have minor changes when compared laterally or longitudinally. This study employs a machine-learning algorithm and establishes prediction models using the microbiome data and the responsiveness data of different parameters in subjects with peanut intervention. As a result, it is found that the improvement of MetS risk and numerous parameters, including diastolic blood pressure, body weight, waist circumference, and fasting blood glucose level can be predicted for responsiveness with high accuracy that has a value of area under curve over 0.70 by receiver operating characteristic analysis.Together, the findings of this study suggest that individual gut microbiota configuration may modulate host metabolism and alter an individual's response to peanut intervention, thus highlighting the importance of personalized nutrition.
科研通智能强力驱动
Strongly Powered by AbleSci AI