Metabolome-wide Mendelian randomisation reveals causal links between circulating metabolites and type 1 diabetes
Bibliographic record
Abstract
BACKGROUND: Type 1 diabetes (T1D) is an autoimmune disease that causes destruction of the insulin-producing pancreatic beta cell, resulting in high levels of blood glucose and profound alterations in carbohydrate, lipid, and protein metabolism if untreated. We aimed to identify if circulating metabolites are causally linked to risk of T1D, using two-sample Mendelian Randomisation (MR). METHODS: For our discovery and replication MR analyses, we used SNP-instruments for circulating metabolites measured in seven large GWAS in Europeans. The corresponding effects of the SNP-instruments on T1D were derived from GWAS in multiple ancestries. The MR effects were estimated using the Wald Ratio or the Inverse Weighted Variance method. We then tested the presence of shared causal variants between the candidate metabolites and T1D and performed sensitivity analyses for pleiotropy and direction of causality. FINDINGS: Of the 1679 tested metabolite-T1D associations, 46 metabolites showed effects on T1D accounting for multiple testing. Among the 14 metabolites replicated using independent T1D GWAS, 7 of these metabolites shared a causal variant with T1D. The metabolite with the most important MR effect, vanillactate, showed a strong negative association with T1D risk in 3 T1D GWAS. The SNP-instrument of vanillactate is an eQTL of the TH gene which is itself coexpressed with the INS gene, a major T1D locus. INTERPRETATION: Combining evidence from MR and various follow-up analyses, we identified causal circulating metabolites for T1D, highlighting the role of specific metabolic signatures in the pathogenesis of this disease. FUNDING: Fonds de Recherche du Quebec-Santé (FRQS).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".