Dissecting Causal Associations of Diet-Derived Circulating Antioxidants with Six Major Mental Disorders: A Mendelian Randomization Study
Bibliographic record
Abstract
Although observational studies have suggested associations between circulating antioxidants and many mental disorders, causal inferences have not been confirmed. Mendelian randomization (MR) analyses were conducted using summary-level statistics from genome-wide association studies (GWASs) to explore whether genetically determined absolute circulating antioxidants (i.e., ascorbate, retinol, β-carotene, and lycopene) and metabolites (i.e., α- and γ-tocopherol, ascorbate, and retinol) were causally associated with the risk of six major mental disorders, including anxiety disorders (AD), major depressive disorder (MDD), bipolar disorder (BIP), schizophrenia (SCZ), post-traumatic stress disorder (PTSD), and obsessive-compulsive disorder (OCD). MR analyses were performed per specific-outcome databases, including the largest GWAS published to date (from 9725 for OCD to 413,466 for BIP participants), UK Biobank (over 370,000 participants), and FinnGen (over 270,000 participants), followed by meta-analyses. We found no significant evidence that genetically determined diet-derived circulating antioxidants were significantly causally associated with the risk of the six above-mentioned major mental disorders. For absolute antioxidant levels, the odds ratios (ORs) ranged from 0.91 (95% CI, 0.67-1.23) for the effect of β-carotene on OCD to 1.18 (95% CI, 0.90-1.54) for the effect of ascorbate on OCD. Similarly, for antioxidant metabolites, ORs ranged from 0.87 (95% CI, 0.55-1.38) for the effect of ascorbate on MDD to 1.08 (95% CI, 0.88-1.33) for the effect of ascorbate on OCD. Our study does not support significant causal associations of genetically determined diet-derived circulating antioxidants with the risk of major mental disorders.
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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 | 0.059 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".