Yoga Modulates Alzheimer's Disease Pathophysiology by Targeting Key Biomarkers, Oxidative Stress, Inflammation, and Neurocognition
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is characterized by cognitive decline, neuroinflammation, and synaptic dysfunction. This study explores the impact of a 12-week yoga intervention on cognitive function, mood, biomarkers, inflammatory responses, and oxidative stress in AD patients. METHOD: Out of 60 patients initially enrolled, 50% were lost to follow-up, resulting in the evaluation of 30 AD patients (mean age 66.4 ± 3.80 years) and 20 healthy controls (HC; mean age 64.4 ± 2.40 years). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS). AD biomarkers, including amyloid-beta (Aβ), pTau proteins (pTau 181 and pTau 217), APOE, APOE4, and inflammatory markers (IL-6, IL-11, IL-15, IL-37, TNF-α, TGF-β1, CRP, BDNF), were measured. Oxidative stress was assessed by 8-hydroxy-2-deoxyguanosine (8-OHdG). Further analyses included ROC curves and Pearson correlations between biomarkers and cognitive scales. RESULT: The AD group showed significant cognitive improvement post-intervention, with MoCA scores increasing and GDS scores decreasing (p < 0.01). Cognitive domains such as language, attention, and memory were enhanced. Biomarker analysis revealed reductions in Aβ-40 (p < 0.05), pTau 181, pTau 217, CRP, APOE, and 8-OHdG, while Aβ-42 (p < 0.05), Aβ-42/Aβ-40 ratio (p < 0.05), and BDNF increased (p < 0.05). Inflammatory markers IL-6, TNF-α, IL11, IL15, IL37, and IL-11 decreased, while TGF-β1 increased (p < 0.05). Correlations revealed cognitive improvement (MoCA) positively associated with Aβ-42 (r = 0.65, p < 0.01) and inversely with IL-6 (r = -0.58, p < 0.05). Mood improvements (GDS) were inversely correlated with APOE levels (r = -0.62, p < 0.01). CONCLUSION: Yoga intervention significantly enhanced cognition, mood, and biomarker profiles, including reductions in inflammatory markers, APOE, and oxidative stress, with positive correlations between cognitive improvement and Aβ-42, and inverse associations with IL-6. These findings support yoga as a promising therapeutic strategy in AD.
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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 | 0.000 |
| 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".