Biochemical individuality obsoletes many dietary recommendations and the glycemic index.

An important paper by a Weizmann Institute group has been languishing in my list of potential posts, and Murphy's summary of their work now prods me to pass on their bottom line: the glycemic index, used to rank foods according to their effects on blood sugar, is not really useful, because people differ strikingly in their indivual biochemistries, the way in which they extract energy from different foods. The Weizmann group devised "a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured...and showed that it accurately predicts personalized postprandial glycemic response to real-life meals." Companies like Nutrigenomix have begun to offer personalized nutrition assessment based on individual genomics. Here is the Weizmann Inst. info:

Highlights

•High interpersonal variability in post-meal glucose observed in an 800-person cohort 

•Using personal and microbiome features enables accurate glucose response prediction 

•Prediction is accurate and superior to common practice in an independent cohort 

•Short-term personalized dietary interventions successfully lower post-meal glucose

Summary

Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences.