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The Effect of Exogenous Ketone Monoester Ingestion on Plasma BDNF during an Oral Glucose Tolerance Test

2020· article· en· W3016971330 on OpenAlexaff
Jeremy J. Walsh, Étienne Myette‐Côté, Jonathan P. Little

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversité de SherbrookeUniversity of British Columbia
Fundersnot available
KeywordsIngestionEndocrinologyInternal medicineMedicineGlycemicPlaceboBrain-derived neurotrophic factorObesityAnalysis of variancePlasma glucoseDiabetes mellitusNeurotrophic factors

Abstract

fetched live from OpenAlex

Brain‐derived neurotrophic factor (BDNF) is important for the maintenance of healthy brain function. Plasma BDNF is lower in people with obesity compared to their lean counterparts, potentially due to differences in metabolic control as acute hyperglycemia reduces cerebral output of BDNF in young, healthy adults. Ingestion of a ketone monoester (KME) drink containing beta‐hydroxybutyrate (β‐OHB) attenuates the glycemic response during an oral‐glucose tolerance test (OGTT) in humans, and increases neuronal expression of BDNF in rodents. Whether ingestion of a KME affects plasma BDNF in humans is currently unknown. The purpose of this study was to examine the effect of KME ingestion before an OGTT on plasma BDNF in normal‐weight adults and adults with obesity. Methods Secondary analyses of two separate studies were performed. Study 1 included lean adults (n=18; M age =25.3 ± 4.3 years; BMI=22.2 ± 2.3 kg/m 2 ) and Study 2 included adults with obesity (n=12; M age =48.8 ± 9.5 years; BMI = 33.7 ± 5.0 kg/m 2 ). In both studies, participants ingested 0.45 mL/kg −1 body weight KME or Placebo 30 minutes prior to completing a 75 g OGTT. β‐OHB, and BDNF were measured via blood samples at fasting baseline (BSL) and 120 min post‐OGTT. Plasma glucose was measured at BSL and every 30 minutes during the OGTT. A 2‐factor repeated measures ANOVA was computed to assess β‐OHB and BDNF responses by time and condition. A paired t‐test was computed to compare glucose area under the curve (AUC). An independent sample t‐test was used to compare fasting plasma BDNF between lean and obese participants. Results Study 1 KME ingestion significantly increased β‐OHB by 800 ± 454% (p<0.001) and blunted plasma glucose AUC by 15.3 ± 12.7% (p<0.001) compared to Placebo. Plasma BDNF significantly decreased post‐OGTT compared to BSL in the Placebo condition (389.3 ± 595.8 pg/mL vs. 718.6 ± 830.8 pg/mL; p=0.018), whereas it was unchanged in the KME condition (469.2 ± 791.8 pg/mL vs. 560.2 ± 689.6 pg/mL; p=0.28). Study 2 KME ingestion significantly increased β‐OHB by 1586 ± 602% (p<0.001) and blunted plasma glucose AUC by 12.3 ± 7.9% (p=0.001) compared to Placebo. In the KME condition, plasma BDNF significantly increased post‐OGTT compared to BSL (188.9 ± 138.2 pg/mL vs. 122.6 ± 129.3 pg/mL; p=0.037), whereas it was unchanged in the Placebo condition (126.4 ± 134.0 pg/mL vs. 143.9 ± 161.9 pg/mL; p=0.18). Fasting plasma BDNF was significantly lower in adults with obesity compared to lean adults (132.8 ± 142.8 pg/mL vs. 639.4 ± 756.8 pg/mL; p=0.002). Conclusions Plasma BDNF is differentially impacted by acute KME ingestion and an OGTT in adults with obesity compared to lean adults. Our findings suggest that KME ingestion may increase BDNF during an OGTT in adults with obesity, whereas KME may protect against hyperglycemia‐induced reductions in BDNF in lean adults. The difference in basal BDNF between groups may suggest that long‐term differences in metabolism and/or body composition impact BDNF. KME may be a strategy for altering plasma BDNF responses during hyperglycemia. Support or Funding Information NSERC Discovery

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.262
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations3
Published2020
Admission routes1
Has abstractyes

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