Figure 1. The Impact of Diet on Blood Glucose Is Highly Variable, but Predictable.

(A) Personal and microbiome properties are analyzed in response to diet (including clinical and anthropometric measures, lifestyle, medical background, and the functional pathways and taxonomic composition/species of the gut microbiome). These properties markedly affect the glycemic response over time to various food items for each individual. One person, for example, may have a high postprandial (post-meal) glycemic response to bananas and a low response to cookies, while this ordering may be reversed for another person. (B) Using large-scale data on such personal and microbiome properties, along with continuous glucose monitoring and detailed dietary logs, Zeevi et al., (2015) developed an algorithm to predict with high accuracy, individual glycemic responses for each meal (computer symbol). (C) With this algorithm, it is possible to generate personalized intervention diets designed to regulate glycemic responses, promoting either low (“good” diet) or high responses (“bad” diet). (D) “Good” intervention diets can promote microbiome shifts towards a healthier composition, lowering the abundance of specific bacteria previously associated with diabetes and/or obesity (“blue” coded), while increasing the abundance of bacteria associated with good health (“green” coded).