Accelerated aging of the putamen in patients with major depressive disorder
Bibliographic record
Abstract
Background: Growing evidence indicates that major depressive disorder (MDD) is characterized by accelerated biological aging, including greater age-related changes in physiological functioning. The disorder is also associated with abnormal neural reward circuitry, particularly in the basal ganglia (BG). Here we assessed age-related changes in BG volume in both patients with MDD and healthy control participants. Methods: We obtained whole-brain T1-weighted images from patients with MDD and healthy controls. We estimated grey matter volumes of the BG, including the nucleus accumbens, caudate, pallidum and putamen. Volumes were assessed using multivariate analysis of covariance (MANCOVA) with age as a covariate, followed by appropriate post hoc tests. Results: We included 232 individuals (116 patients with MDD) in our analysis. The MANCOVA yielded a significant group × age interaction ( p = 0.043). Analyses for each region yielded a significant group × age interaction in the putamen (univariate test, p = 0.005; permutation test, p = 0.004); this effect was not significant in the other regions. The negative association between age and putamen volume was twice as large in the MDD than in the control group (−35.2 v. −16.7 mm3/yr), indicating greater age-related volumetric decreases in the putamen in individuals with MDD than in controls. Limitations: These findings are cross-sectional; future studies should assess the longitudinal impact of accelerated aging on anhedonia and neural indices of reward processing. Conclusion: Our results indicate that putamen aging is accelerated in patients with MDD. Thus, the putamen may uniquely contribute to the adverse long-term effects of depressive psychopathology and may be a useful target for the treatment of MDD across the lifespan.
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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 | 0.000 | 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) | 0.001 | 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".