Gut Microbiota Composition is Associated with Responses to Peanut Intervention in Multiple Parameters Among Adults with Metabolic Syndrome Risk

Introduction 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. Methods and Results 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. Conclusion 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.

Automated summary

This study suggests that peanut intervention in adults with MetS risk is associated with gut microbiota composition, and responsiveness data can predict improvements in MetS risk and various parameters.