Lack of association between type 2 diabetes and major depression: epidemiologic and genetic evidence in a multiethnic population
Bibliographic record
Abstract
The positive association between depression and type 2 diabetes (T2D) has been controversial, and little is known about the molecular determinants linking these disorders. Here we investigated the association between T2D and depression at the clinical and genetic level in a multiethnic cohort. We studied 17,404 individuals from EpiDREAM (3209 depression cases and 14,195 controls) who were at risk for T2D and had both phenotypic and genotypic information available at baseline. The glycemic status was determined using the 2003 American Diabetes Association criteria and an oral glucose tolerance test. Major depressive episode during the previous 12 months was diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic criteria. Twenty single-nucleotide polymorphisms (SNPs) previously associated with T2D were genotyped using the cardiovascular gene-centric 50-K SNP array and were analyzed separately and in combination using an unweighted genotype score (GS). Multivariate logistic regression models adjusted for age, sex, ethnicity and body mass index were performed. Newly diagnosed impaired fasting glucose (IFG)/impaired glucose tolerance (IGT), T2D and dysglycemia status were not associated with major depression (0.30 ⩽ P ⩽ 0.65). Twelve out of twenty SNPs and the GS were associated with IFG/IGT, T2D and/or dysglycemia status (6.0 × 10(-35) ⩽ P ⩽ 0.048). In contrast, the 20 SNPs and GS were not associated with depression (P ⩾ 0.09). Our cross-sectional data do not support an association between T2D and depression at the clinical and genetic level in a multiethnic population at risk for T2D.
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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 | 0.000 |
| 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".