Posted Feb 3 , 2016 07:59 AM

Personalized Nutrition by Prediction of Glycemic Responses

Zeevi, D., et al. Cell 2015;163:1079-1094

What were the findings (excerpted from the Abstract)?

Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for pre-diabetes and type 2 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.

Why is this important?

So much of our understanding of and use of nutritional information is at a basic level. We know counting carbs can help insulin dosing, we know that very low carb diets are associated with weight loss, we know or at least we have been taught that glycemic index makes a difference in how we respond to various foods. Yet those understandings are imprecise as any patient can tell you. Some people respond to certain foods with significant increases in blood glucose and others don’t. Indeed, sometimes the glucose response to the same foods is different on different days, frustrating many patients with type 1 diabetes as they try to meticulously manage their diet and insulin responses. This study has confirmed that we probably knew all along, and that is that in a large cohort of people, the determinants of glucose response aren’t quite as simple as we thought, and the food itself is but one of several determinants of patient response. We are becoming increasingly aware of the role of gut microbiota in our response to food, and we know that exercise affects glucose utilization inside our bodies as well as changing the bacteria found in our gut. The authors have developed an algorithm that may help patients and their providers to better tailor food, exercise and perhaps even our gut flora to temper the response to meals and lower glycemic variability. This is an early study, but these principles will likely be studied a lot in the future. Stay tuned!

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