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Study reveals gut microbiome’s person-specific role in glycemic sensitivity

Research highlights the person-specific interplay between gut microbiota and high-carbohydrate diets, uncovering new insights into glycemic sensitivity and precision nutrition.

MicrovilliStudy:Diet-gut microbiome interaction and its impact on host blood glucose homeostasis: a series of nutritional n-of-1 trials. Image Credit: TopMicrobialStock/Shutterstock.com

In a recent study published in eBioMedicine, researchers investigated the dynamic interactions between the gut microbiome and diet, particularly their effects on blood glucose homeostasis, focusing on variability between individuals.

Their findings provide novel insights into how diet can affect the gut microbiome and blood glucose metabolism at an individual level, leading to personalized dietary recommendations promoting metabolic health.

Background

The impact of different macronutrient diets (high-carbohydrate and low-fat (HC) compared to low-carbohydrate (LC)) on metabolic health has been widely debated. HC diets are often recommended due to their lower calorie density compared to fats, but concerns exist regarding their effects on blood sugar and insulin regulation.

Currently, there is no clear evidence to recommend one diet over the other. The gut microbial community plays a crucial role in overall health, playing critical roles in digestion, metabolism, and developing and maintaining the human immune system.

It can be influenced by diet, with the microbiome also affecting how the body responds to dietary changes. The gut microbiome contains both beneficial and harmful strains and differs from person to person. Despite this, the importance of personalized gut microbiota profiles for mediating the effects of LC and HC diets remains unclear.

To address this, the researchers proposed a new study approach, the nutritional n-of-1 trial, which examines individual responses to diets at a personal level. This design may provide valuable insights into the complex relationship between diet, microbiota, and metabolism.

About the study

The study aimed to explore the effects of high-carbohydrate (HC) and low-carbohydrate (LC) diets on gut microbiota and metabolic health, using several nutritional n-of-1 trials. They found that each participant's gut microbiota responded differently to the diets, creating distinct patterns.

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By analyzing these patterns, the researchers developed a "carb-sensitivity score," which linked specific gut microbiota profiles to glycemic responses, particularly during the HC diet.

This score was validated in a larger cohort of 1,219 participants, confirming its ability to predict blood glucose responses based on diet.

The study involved 30 participants who completed three cycles of HC and LC diets, providing extensive data on gut microbiota composition and blood glucose levels.

The findings revealed that the microbiota's response to the HC diet could predict individual glycemic sensitivity, while the LC diet had less influence on blood glucose regulation.

The carb-sensitivity score could help personalize dietary recommendations, optimizing metabolic health based on an individual’s gut microbiome. The study also validated these findings using machine learning and linear regression models in a broader cohort, linking the microbiota with glycemic traits like fasting glucose and HbA1c.

Findings

Researchers found that the gut microbiome's diversity and composition varied significantly between individuals, with each participant showing personalized responses to the diets.

These variations were observed at both the species and phylum levels, notably with opposing responses from dominant gut bacteria like Bacteroidetes and Firmicutes.

Gut microbiota was found to influence glycemic sensitivity, particularly under an HC diet. Principal component analysis (PCA) revealed that certain microbial patterns could predict post-meal blood glucose responses, like the maximum glucose spike (MPG) and the duration of high blood sugar.

These patterns were more strongly linked to glycemic responses during the HC diet. In a larger cohort of 1,219 participants, gut microbiota's predictive ability for pre-diabetes and diabetes was also stronger in those with HC dietary habits.

Researchers developed a "carb-sensitivity score" based on microbial species linked to glycemic responses, showing that this score correlated with improved glucose control, particularly in individuals on HC diets.

Further analysis revealed that microbial carbohydrate-active enzymes (CAZymes) mediated these associations, influencing glucose metabolism.

The metabolomic analysis confirmed that dietary carbohydrates played a key role in linking gut microbiota patterns with serum metabolites related to blood sugar control.

Conclusions

This study identifies a gut microbiome-based feature called the "carb-sensitivity score" that reflects an individual's glycemic response to HC diets. Using personalized n-of-1 trials, researchers discovered both common and unique gut microbial responses to HC and LC diets.

The study suggests that each person's gut microbiome shapes their response to food, especially carbohydrates, and may influence health outcomes like blood glucose levels.

It emphasizes the need for personalized dietary recommendations based on gut microbiome analysis. The findings highlight the complexity of diet-gut interactions and point to a more tailored approach to nutrition.

Overall, these results highlight the importance of personalized dietary interventions based on gut microbiome composition for managing glucose metabolism. They suggest that tailoring dietary advice based on a person's gut microbiome could improve metabolic outcomes, offering a more personalized approach to nutrition.

Journal reference:

Fu, Y., Gou, W., Zhong, H., Tian, Y., Zhao, H., Liang, X., Shuai, M., Zhuo, L., Jiang, Z., Tang, J., Ordovas, J.M., Chen, Y., Zheng, J. (2024) Diet-gut microbiome interaction and its impact on host blood glucose homeostasis: a series of nutritional n-of-1 trials. eBioMedicine. doi:https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(24)00519-X/fulltext

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