Lipid peroxidation mediates the relationship between cardiopulmonary fitness and depressive symptoms in people with coronary artery disease
Bibliographic record
Abstract
Abstract Background Emerging evidence suggests that poor cardiorespiratory fitness levels are related to greater depressive symptoms. In those with coronary artery disease (CAD) depressive symptoms are common and are associated with an increased risk of mortality. Exercise intervention is suggested to have positive effects on depressive symptoms and counteract oxidative stress (OS) in the body. However, a mechanistic link between cardiorespiratory fitness (CRF) and depressive symptoms has not been identified in CAD individuals. We aim to investigate if OS explains the relationship between poor cardiorespiratory fitness and higher depressive symptoms in CAD individuals. Method CAD participants were recruited and OS was measured via serum lipid peroxidation marker 8‐isoprostane (8‐ISO), lipid hydroperoxides (LPH), and 4‐hydroxyneoneal (4‐HNE). CRF was assessed by peak oxygen uptake (VO2peak) and depressive symptoms measured via Center for Epidemiological Studies‐Depression (CES‐D) scale. Analyses were controlled for age, hypertension, hypercholesterolemia, and antidepressant use. Mediation effects of OS markers on the relationship between CRF and depressive symptoms were tested. A bias‐corrected inferential bootstrapping with 10,000 permutations was used to obtain a 95% confidence interval (CI) for the indirect effect. Result Among CAD individuals (n=224), lower VO2peak was associated with higher 8‐ISO (β=0.31, p<0.001) and greater depressive symptoms (β=‐0.143, p=0.038). LPH (B=‐0.172 p=0.017) was associated with greater CES‐D score, but not VO2peak levels (B=‐0.122, p=0.109), when controlling for the same covariates. 4‐HNE was not a significant predictor of CES‐D scores (B=0.059, p=0.372) or VO2peak levels (B=‐0.052, p=0.440). 8‐ISO mediated the relationship between VO2peak (β=0.02, p=0.01) and CES‐D (β=7.13, p=0.001), and LPH did not (‐0.0098, 95% CI [‐0.0314, 0.0042]). Bootstrapping produced a significant unstandardized indirect effect for 8‐ISO (β=‐0.20, SE=0.05, 95% CI=‐0.32, ‐0.01). Conclusion In those with CAD, poor CRF and greater OS levels were associated with higher depressive symptoms, and this relationship was mediated by 8‐ISO, but not LPH or 4‐HNE. These findings provide greater understanding of the mechanistic reasoning for the link between poor CRF and depressive symptoms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".