Association of SGLT2 inhibition with psychiatric disorders: A Mendelian randomization study
Bibliographic record
Abstract
Background: Some observational studies have reported that sodium-glucose cotransporter 2 (SGLT2) inhibitors may have an impact on psychiatric disorders. This Mendelian randomization (MR) study aims to explore the causal relationship between SGLT2 inhibition and five types of psychiatric disorders. Methods: Genetic variants associated with the SLC5A2 gene and glycated hemoglobin were selected from the eQTLGen Consortium and Genotype-Tissue Expression datasets. Type 2 diabetes served as a positive control in the application of MR and colocalization analyses to investigate potential causal relationships between SGLT2 inhibition and depression, anxiety disorder, schizophrenia, obsessive-compulsive disorder, and bipolar affective disorder. The impact of glycated hemoglobin on psychiatric disorders was additionally analyzed. Results: SGLT2 inhibition was associated with an increased risk of anxiety disorder, obsessive-compulsive disorder, and bipolar affective disorder. The effect of SGLT2 inhibition on depression did not reach Bonferroni-corrected significance levels. No association was found between SGLT2 inhibition and schizophrenia. Conclusions: This study provides genetic evidence supporting that SGLT2 inhibitors increase the risk of obsessive-compulsive disorder, anxiety disorder, and bipolar affective disorder.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".