Microbiome affects blood glucose levels after eating, can help predict glycemic response to foods


Postprandial (post-meal) glycemic response (PPGR) is the effect that food has on blood glucose levels.   Eating a sugary candy, for example, will raise blood glucose levels, whereas drinking water will not.  PPGR remains an important predictor for metabolic syndrome and type II diabetes, so it has an important role the obesity epidemic.  Unfortunately, PPGR is difficult to predict, and efforts that are based on individual foods themselves have failed.  New research shows that there are many factors, including the microbiome, that are important to predicting blood glucose after a meal.  The research out of Israel and published in the journal Cell presents a new model that can more accurately predict PPGR that is based on personalized factors.

The researchers catalogued 800 peoples’ meals over 7 days while continuously measuring their blood glucose levels.  In addition they monitored their gut microbiota, weight, sleep, and various other lifestyle factors.  After evaluating the data, the scientists realized that identical foods had vastly different PPGRs.  For example, bread could have a 8 fold variation in glycemic response depending on the individual.  In order to explain these differences, the scientists identified several significant associations between the microbiome and the PPGR from specific foods.  For example, on the phyla level high abundances of Proteobacteria and Enterobacteriaceae were associated with poor glycemic controls.  On the species level Eubacterium rectale, which is known to ferment fiber, was correlated with low glycemic response, and Parabacteroides distasonis, which had previously been associated with obesity, was correlated with hight glycemic response.  The scientists then aggregated all of their data, including microbiome data, and created a predictive algorithm for the PPGR from foods for individuals.  This algorithm accurately predicted the glycemic response from foods on a personalized level, and was more informative than general food based predictions.

This study speaks to the power of personalized medicine that is based on the microbiome.  Knowledge of our own microbiome could be used to advise our dietary choices in order to choose foods that will lead to low PPGR, and decrease our risk for metabolic syndrome.  Overall, the scientists determined that of all foods, eating fiber was most beneficial because it lowers glycemic response over the long term.

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