The Acute Effect of a Ketone Monoester Supplement on Metabolic Control in Individuals with Obesity
Bibliographic record
Abstract
OBJECTIVES To determine whether acute ingestion of ketone monoester (KE; (R)‐3‐hydroxybutyl (R)‐3‐hydroxybutyrate) impacts plasma glucose and free fatty acid levels during a standard 75‐gram oral glucose tolerance test (OGTT) in individuals with obesity. METHODS Fifteen participants (age = 47±10 years) with a body mass index > 27 kg/m 2 and a waist circumference >88 cm (female) or >102 cm (male) took part in a randomized crossover study. After an overnight fast, participants consumed a KE supplement (DeltaG®; 0.45 ml/kg body weight) or taste‐matched placebo 30 minutes before completing a 2‐hour OGTT with blood samples collected every 15–30 minutes. Participants and study personnel performing laboratory analyses were blinded to condition. RESULTS KE acutely raised blood D‐beta‐hydroxybutyrate to an average concentration of 2.4±1.2 mM within 30 minutes with levels remaining elevated throughout the entire OGTT. Compared to placebo, KE significantly decreased glucose area under the curve (AUC; −11%, P = 0.002), glucose incremental area under the curve (AUC; −23%, P = 0.008) and non‐esterified fatty acid (AUC; −21%, P = 0.009). Insulin and C‐peptide levels increased significantly over the 30 minutes period prior to the OGTT ( P = 0.001 and 0.003 respectively) but no differences in total AUCs were observed as compared to placebo. No significant changes in lactate or triglycerides were observed. CONCLUSION In conclusion, a KE supplement that acutely increased D‐beta‐hydroxybutyrate levels attenuated the glycemic response to an OGTT in individuals with obesity. The reduction in glycemic response was accompanied by a reduction in non‐esterified fatty acids. These results suggest that ketone ester supplements could have therapeutic potential in the management and prevention of metabolic diseases. Support or Funding Information This project was funded by a Heart and Stroke Foundation of Canada Grant‐in‐Aid. JPL is supported by a Canadian Institutes of Health Research (CIHR) New Investigator Salary Award (MSH‐141980) and a Michael Smith Foundation for Health Research (MSFHR) Scholar Award (16890). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".