(Cell) In today's issue of Cell, two groups lead by Eran Elinav and Eran Segal have presented a stunning paper providing startling new insight into the personal nature of nutrition. The Israeli research teams have demonstrated that there exists a high degree of variability in the responses of different individuals to identical meals, and through the elegant application of machine learning have provided insight into the diverse factors underlying this variability.
As genetic factors are known to modulate and individuals innate responses to diseases, medications, and blood metabolites, it may come as no surprise that individuals do not respond to identical foods in the same manner.
Following a meal, glucose levels increase according to the type of foods that are ingested, and currently meal carbohydrate or derived glycemic index are used to estimate the postprandial (post-meal) glycemic responses (PPGR). These factors assume that PPGRs are solely dependent on the intrinsic properties of the ingested food, and this assumption is the basis of universal dietary recommendations.
Advertisement - story continues below
