Gut Microbiome Activity Contributes to Prediction of Individual Variation in Glycemic Response in Adults

Limiting postprandial glycemic response (PPGR) is an important intervention in reducing the risk of chronic metabolic diseases and has been shown to impart significant health benefits in people with elevated levels of blood sugar. In this study, we collected gut microbiome activity data by assessing the metatranscriptome, and we measured the glycemic responses of 550 adults who consumed more than 30,000 meals, collectively, from omnivore or vegetarian/gluten-free diets. We demonstrate that gut microbiome activity, anthropometric factors, and food macronutrients modulate individual variation in glycemic response. We employ two predictive models, including a mixed-effects linear regression model (R = 0.77) and a gradient boosting machine model (R_train = 0.80/R²_train = 0.64; R_test = 0.64/R²_test = 0.40), which demonstrate variation in PPGR between individuals when ingesting the same foods. All features in the final mixed-effects linear regression model were significant (p < 0.05) except for two features which were retained as suggestive: glutamine production pathways (p = 0.08) and the interaction between tyrosine metabolizers and carbs (p = 0.06). We introduce molecular functions as features in these two models, aggregated from microbial activity data, and show their statistically significant contributions to glycemic control. In summary, we demonstrate for the first time that metatranscriptomic activity of the gut microbiome is correlated with PPGR among adults.