Erythritol as a Potential Causal Contributor to Cardiometabolic Disease: A Mendelian Randomization Study
Bibliographic record
Abstract
People with type 2 diabetes frequently use low-calorie sweeteners to manage glycemia and reduce caloric intake. Use of erythritol, a low-calorie sweetener, has increased recently. Higher circulating concentration associates with major cardiac events and metabolic disease in observational data, prompting some concern. As observational data may be prone to confounding and reverse causality, we undertook bidirectional Mendelian randomization (MR) to investigate potential causal associations between erythritol and coronary artery disease (CAD), BMI, waist-hip-ratio (WHR), and glycemic and renal traits in cohorts of European ancestry. Analyses were undertaken using instruments comprising genome-wide significant variants from three cohorts with erythritol measurement. Across instruments, we did not find supportive evidence that increased erythritol increases CAD (b = -0.033 ± 0.02, P = 0.14; b = 0.46 ± 0.37, P = 0.23). MR indicates erythritol may decrease BMI (b = -0.04 ± 0.018, P = 0.03; b = -0.04 ± 0.0085, P = 1.23 × 10-5; b = -0.083 ± 0.092, P = 0.036), with potential evidence from one instrument of increased BMI adjusted for WHR (b = 0.046 ± 0.022, P = 0.035). No evidence of causal association was found with other traits. In conclusion, we did not find supportive evidence from MR that erythritol increases cardiometabolic disease. These findings await confirmation in well-designed prospective studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".