Efficacy of Personalized Nutrition Based on Gut Microbiome and Clinical Data in Prediabetes
11:40 a.m. CT Saturday, June 13
Prediabetes is a leading risk factor for the development of type 2 diabetes mellitus (T2DM) and its metabolic complications. We hypothesized that a personalized data-driven dietary intervention that targets postprandial glucose responses (PPGR) would improve long-term glycemic control and metabolic outcomes in adults with prediabetes compared to the commonly used Mediterranean-style diet. Here, we performed a randomized controlled diet intervention trial, and randomly assigned adults with prediabetes to follow a Mediterranean-style (MED) diet or a Personalized Postprandial-targeting (PPT) diet for a six-month dietary intervention. The PPT diet is based on a machine learning algorithm that integrates clinical and microbiome features to predict personal PPGRs to any food combination. Participants in both arms were connected to continuous glucose monitoring (CGM) sensors during the entire six-month intervention period. Primary outcomes included changes from baseline to six months in total daily time of CGM glucose levels above 140 mg/dl, and HbA1c. Among 225 participants randomized, 200 completed the intervention. At six months, the mean±SD daily time of CGM glucose levels above 140 mg/dl decreased by -29±89% and -65±44% (p=0.001), mean±SD HbA1c levels decreased by -0.08±0.19% and -0.16±0.24% (p=0.007) in the MED diet and PPT diet groups, respectively. We conclude that a PPT diet is more effective than the commonly used Mediterranean-style diet for improving glycemic control in adults with prediabetes. (ClinicalTrials.gov number, NCT03222791)
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