Trimethylamine-N-oxide: A Novel Biomarker for the Identification of Inflammatory Bowel Disease
Bibliographic record
Abstract
Introduction: The gastrointestinal (GI) microbiome is recognized for potential clinical relevance in inflammatory bowel disease (IBD). Data suggest there is a disease-dependent loss of microbial diversity in IBD. Trimethylamine-N-oxide (TMAO) is generated by GI anaerobes through the digestion of dietary phosphatidylcholine and carnitine in a microbial-mammalian co-metabolic pathway. Elevated levels have been linked to heart disease, yet little is known regarding TMAO in IBD. Aim: To determine if TMAO plasma levels in IBD are altered compared to controls and if they correlate with disease presence or activity. Methods: Liquid chromatography-tandem mass spectrometry was used to measure TMAO, choline and carnitine plasma levels in 479 subjects (373 non-IBD controls, 106 IBD). Subjects were also genotyped for the flavin monooxygenase (FMO) 3 variants E158K and E308G. Results: Plasma TMAO levels were 2.27μM lower in the IBD population compared to the control population (p= 0.0001). Lower TMAO levels were similarly seen in active ulcerative colitis (UC) (1.56μM) versus inactive disease (3.40μM) (p= 0.002). No difference was seen in active Crohn's disease (CD) versus inactive CD. No inter-group variation existed in plasma TMAO levels based on FMO3 genotype. Choline levels were higher in IBD, while carnitine levels were similar between the two groups suggesting lower TMAO levels in IBD were not due to dietary differences. Conclusion: Decreased TMAO levels are seen in IBD compared to a non-IBD population. These data suggest that TMAO may have potential as a biomarker to support IBD diagnosis as well as to assess disease activity in UC.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".