Interactive relationships of Type 2 diabetes and bipolar disorder with cognition: evidence of putative premature cognitive ageing in the UK Biobank Cohort
Bibliographic record
Abstract
Type 2 diabetes (T2D) is disproportionately prevalent in bipolar disorder (BD) and is associated with cognitive deficits in psychiatrically healthy cohorts. Whether there is an interaction effect between T2D and BD on cognition remains unclear. Using the UK Biobank, we explored interactions between T2D, BD and cognition during mid and later life; and examined age-related cognitive performance effects in BD as a function of T2D. Data were available for 1511 participants with BD (85 T2D), and 81,162 psychiatrically healthy comparisons (HC) (3430 T2D). BD and T2D status were determined by validated measures created specifically for the UK Biobank. Diagnostic and age-related associations between T2D status and cognition were tested using analyses of covariance or logistic regression. There was a negative association of T2D with visuospatial memory that was specific to BD. Processing speed and prospective memory performance were negatively associated with T2D, irrespective of BD diagnosis. Cognitive deficits were evident in BD patients with T2D compared to those without, with scores either remaining the same (processing speed) or improving (visuospatial memory) as a function of participant age. In contrast, cognitive performance in BD patients without T2D was worse as participant age increased, although the age-related trajectory remained broadly equivalent to the HC group. BD and T2D associated with cognitive performance deficits across the mid-life period; indicating comorbid T2D as a potential risk factor for cognitive dysfunction in BD. In comparison to BD participants without T2D and HCs, age-independent cognitive impairments in BD participants with comorbid T2D suggest a potential premature deterioration of cognitive functioning compared to what would normally be expected.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".