Targeting the Gut-brain Axis to Facilitate Weight Loss in High Fat Diet Consumers

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The proposed work takes a precision medicine approach to obesity treatment and focuses specifically on weight loss maintenance. We propose to optimize a stratification strategy, using neural, metabolic and behavioral measures to identify individuals who will maintain clinically significant weight lo...

The proposed work takes a precision medicine approach to obesity treatment and focuses specifically on weight loss maintenance. We propose to optimize a stratification strategy, using neural, metabolic and behavioral measures to identify individuals who will maintain clinically significant weight loss by daily supplementation with the fatty acid amide, oleoylthanolamide (OEA) following a gold-standard behavioral weight loss program. We will also test a model underlying the efficacy of our intervention to provide insight for the further development of therapeutic avenues. Our first aim is to conduct a randomized double-blind placebo-controlled trial to determine if fat intake moderates the ability of OEA to improve weight loss maintenance after the (LEARN®) weight loss program. We predict fat intake will strongly moderate the ability of OEA to produce clinically significant weight loss and weight loss maintenance 4- and 12-months) after LEARN and that this should not be influenced by sex. Our second aim is to test if the Dietary Fat and Sugar intake questionnaire (DFS) is associated with measures of saturated fat intake and to optimize a clinically useful stratification strategy. Towards this end we will: (1) perform a neuroimaging study to assess brain response to a high fat milkshake (2) assess blood-based biomarkers of fat intake and synthesis; and (3) collect dietary intake records and food frequency questionnaires (FFQs). We predict that (1) the DFS predicts measures of saturated fat intake (2) that baseline dorsal striatal (DS) response to milkshake predicts weight loss in the OEA but not the placebo group and that connectome based predictive modeling (CPM) reveals a "neural fingerprint" that predicts weight loss on OEA; and (3) LASSO regression will identify baseline measures that best predict outcome to inform selection of a practical clinical stratification recommendation. Our third aim is to test a model of OEA effectiveness. We predict that weight loss outcome is associated with shifts in fat preference and intake and these effects are mediated by increases in DS response to milkshake in the OEA but not placebo group. We will also test whether HFD is associated with performance on reinforcement and cognitive measures or changes in energy expenditure or substrate utilization. If so, we will test whether these associations and their reversal by OEA contribute to outcome mediation.

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