Unraveling the choline pathway in heart failure risk and outcomes: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The objectives of this systematic review and meta-analysis were to (i) evaluate the relationship between circulating levels choline and its metabolites, phosphatidylcholine (PC), trimethylamine N-oxide (TMAO), betaine, and dimethylglycine (DMG) with heart failure (HF) development and its adverse clinical outcomes (ii) explore potential mechanisms that link them to HF. METHODS: A systematic search of MEDLINE, EMBASE, and PubMed was conducted. RESULTS: Nine prospective cohort studies (n = 267,569) were analysed. Elevated choline and PC were significantly associated with an increased incidence of HF respectively HR 1.33 (95 % CI 1.07-1.66, p = 0.0107) and HR 1.25 (95 % CI 1.16-1.34, p < 0.0001). In established HF, elevated betaine levels were significantly associated with a composite of adverse clinical outcomes (HR 1.15, 95 % CI 1.02-1.30, p = 0.0206). The molecular mechanisms linking choline and PC to HF include the hydrolysis of PC into lysophosphatidylcholine which can produce inflammation and cardiomyocyte apoptosis. Several metabolites and pathways are intriguing therapeutic targets, including lysophosphatidylcholine acyltransferase 1, phospholipase A2, choline trimethylamine lyase, and the phosphatidylethanolamine N-methyltransferase pathway. CONCLUSIONS: Choline metabolites are implicated in HF development and progression. Understanding the mechanism whereby choline metabolism leads to HF may lead to novel therapeutic targets for HF management and prevention.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.024 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".