Major depression and enhanced molecular senescence abnormalities in young and middle-aged adults
Bibliographic record
Abstract
Abstract Recent evidence suggests a significant overlap in biological changes between major depression and aging across the lifespan. We aim to evaluate the impact of a major depressive episode on the Senescence-Associated Secretory Phenotype (SASP) index, a dynamic secretory molecular pattern indicative of cellular senescence. We also tested the potential moderators of the association between major depression and the SASP index. We included 1165 young and middle-aged adults (527 with a current major depressive episode (cMDE) and 638 with no lifetime history of depression) from a community-based cohort from the Netherlands. We calculated the SASP index based on a previously developed composite index involving 19 biomarkers. cMDE had higher SASP index values (t(1163) = 2.93, p = 0.003) compared to controls in the univariate analysis. After controlling for sociodemographic and somatic health covariates, there was no significant association between cMDE and SASP index (F(1,1158) = 1.09, p = 0.29). Those with the most severe depressive episodes had significantly higher SASP indices compared to those with mild-to-moderate cMDE and controls (F(2,1162) = 6.73, p = 0.001). We found a significant interaction between cMDE and overweight (F(1,1164) = 5.1, p = 0.028): those with comorbid cMDE and overweight had the highest SASP index. Our study demonstrated a complex interaction between cMDE and medical morbidity, especially overweight, on the SASP index, suggesting that their coexistence aggravate age-related biological processes. Moreover, higher SASP index can be a biomarker for more severe depressive episodes.
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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".