Exercise as an Adjunctive Treatment Modality for Major Depressive Disorder: A Multi-Omics Perspective
Bibliographic record
Abstract
Major Depressive Disorder (MDD) is characterized by genetic and environmental factors. Current interventions, including selective serotonin reuptake inhibitors and cognitive-behavioural therapy, are often effective yet prone to the development of treatment resistance. A major mechanism for MDD pathogenesis involves dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, which results in chronic elevation of cortisol. Cortisol has been linked to MDD symptomology through downstream cellular effects, which can be elucidated through multi-omics analyses such as genomics (NR3C1, FKBP5), proteomics (pro-inflammatory cytokines), and metabolomics (shifted kynurenine pathway). A systematic literature search of OVID Medline and similar databases was conducted over the past 10 years to identify studies investigating exercise interventions targeting multi-omics markers in MDD. Inclusion criteria required independent MDD cohorts and included a minimum of two omics levels, and their relationship to exercise as an intervention. Existing literature demonstrates that aerobic exercise can regulate cortisol levels, increasing NR3C1 and FKBP5 gene expression, while reducing proinflammatory cytokines, and shifting tryptophan metabolism towards the neuroprotective kynurenic acid and away from neurotoxic metabolites. A change in these biomarkers suggests that regular physical activity can exert widespread biological and neurological effects, regulating molecular dysfunctions at a multi-omic level in MDD. Exercise, when prescribed as an adjunct to conventional MDD therapies, may improve clinical outcomes by modulating stress-responsive and inflammatory pathways at multiple omics levels. Further large-scale and longer-term randomized trials are required to validate specific biomarkers for personalized medicine, and additional work should investigate sex-based differences in exercise efficacy. Exercise offers significant promise for optimizing MDD management and promotes greater physiological resistance to depressive symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".