Glycemic responses to foods are determined by total carbohydrates, glycemic index, and addition of fat, fiber, and protein. Interindividual variability in these responses are not well characterized. We propose that postprandial glucose response (PPGR) exhibits variability between individuals with regard to 1) “worst” or most glucose elevating food; 2) degree of mitigation by fat, fiber, or protein. Forty participants, healthy or with prediabetes, were given a repeated series of 7 standardized food challenges with the same amount of carbohydrates but varying in source (rice, bread, potatoes, pasta, berries, grapes, and beans) while wearing a CGM. We summarized PPGR and constructed a typical response to each food challenge. Rice exhibited the highest peak value and potatoes had the longest return to baseline time. However, cluster analysis revealed heterogeneity in PPGR indicating that the “worst” food differed between individuals. Participants were then pretreated with potential mitigators (fat, protein, or fiber) before a standardized food challenge. Cluster analysis revealed heterogeneity of mitigator effect between individuals and foods, and within individuals. Results indicate that diets can be individualized with regard to both carbohydrate choice and addition of fat, protein, or fiber to optimize metabolic health.


A.A.Metwally: Employee; Google LLC, Stock/Shareholder; Google LLC. D.Perelman: Advisory Panel; January, Inc. B.W.Ehlert: None. Y.Wu: None. A.Celli: None. C.Bejikian: None. H.Park: None. T.Mclaughlin: Board Member; January, Inc., Research Support; Merck & Co., Inc., Stock/Shareholder; Eiger Bio. M.Snyder: Advisory Panel; Genapsys, Jupiter, Neuvivo, Swaza, Mitrix, Other Relationship; Personalis, QBio, January, Inc., Fodsel, Filtricine, Protos, RTHM, Iollo, Marble Therapeutics, Mirvie, SensOmics.


Stanford Precision Health and Integrated Diagnostics Center (5R01DK110186)

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