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Trimethylamine‐ <i>N</i> ‐oxide biomarker response is a function of dietary precursor intake and gut microbiota composition in healthy young men

2016· article· en· W2911691845 on OpenAlexaboutno aff
Clara E. Cho, Siraphat Taesuwan, Olga Malysheva, Erica Bender, Nathan F. Tulchinsky, Jian Yan, Jessica L. Sutter, Marie A. Caudill

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsTrimethylamine N-oxideGut floraTrimethylamineFood scienceFirmicutesAnimal scienceChemistryBiomarkerCholineUrineBiologyBiochemistry16S ribosomal RNA

Abstract

fetched live from OpenAlex

Trimethylamine‐ N ‐oxide (TMAO) has recently emerged as a novel risk factor for chronic diseases but the contribution of diet and gut microbiota to TMAO production has received limited attention. The objective of this study was to compare TMAO biomarker response to foods that contain TMAO (fish) or its dietary precursors, choline and carnitine (eggs and beef), and to determine whether TMAO response was modified by the gut microbiota. As part of a crossover feeding trial with one‐week washout intervals, healthy young men (n = 40) were randomized to study meals representing animal sources of TMAO (i.e., eggs, beef and fish) and a fruit control. Blood and urine samples were collected at baseline and throughout the 6 h study period, and a one‐time baseline stool was provided. TMAO concentrations in plasma and urine were greatly influenced by dietary precursor intake with fish yielding 50–55 times higher TMAO (P < 0.0001), 11–12 times higher trimethylamine (P < 0.0001) and 5–6 times higher dimethylamine (P < 0.0001) than eggs or beef. Notably, circulating TMAO concentrations in response to the fish study meal were increased within 15 min of consumption suggesting that TMAO itself can be absorbed without undergoing processing by the gut microbes. Analysis of 16S rRNA genes indicated that high‐TMAO producers (those with >20% increase in urinary TMAO response to eggs and beef) had more Firmicutes than Bacteroidetes (P = 0.04), and showed less richness (P = 0.03) in gut microbiota composition than low‐TMAO producers (those with <20% increase in TMAO response). Given the inverse relationship between fish consumption and heart disease, the robust increase in circulating TMAO in response to the fish study meal suggests that TMAO may not contribute to the development of heart disease in humans. In addition, TMAO response to dietary TMAO precursors (eggs and beef) appears to be dependent on the gut microbes demonstrating that TMAO may be a biomarker of the gut microbiota composition. Overall, our data raise questions about the utility of lowering circulating concentrations of TMAO, via dietary or pharmaceutical approaches, as a means to improve human health. Support or Funding Information Egg Nutrition Center, Beef Checkoff through the National Cattlemen's Beef Association, Canadian Institutes of Health Research Postdoctoral Fellowship

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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".

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

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