Physical Activity Associates With Lower Systemic Inflammatory Gene Expression in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: While general population studies have shown inverse associations between physical activity and common inflammatory biomarkers, the effects of physical activity on inflammatory gene expression and signaling pathways in rheumatoid arthritis (RA) remain unknown. We aimed to determine whether physical activity independently associates with expression of inflammatory genes among people with RA. METHODS: This was a prospective observational study of adults with RA. Physical activity was measured by quantitative actigraphy over 7 consecutive days, and peripheral blood collected during the same time period was used for RNA sequencing followed by differential gene expression, pathway, and network analyses. RESULTS: < 0.1) between patients in the greatest vs lowest physical activity tertiles, after adjusting for sex, age, race, and ethnicity. The most active patients exhibited dose-dependent downregulation of several immune signaling pathways implicated in RA pathogenesis. These included CD40, STAT3, TREM-1, interleukin (IL)-17A, IL-8, Toll-like receptor, and interferon (IFN) signaling pathways. Upstream cytokine activation state analysis predicted reduced activation of tumor necrosis factor-α and IFN in the most active group. In sensitivity analyses, we adjusted for RA disease activity and physical function and found consistent results. CONCLUSION: Patients with RA who were more physically active had lower expression of immune signaling pathways implicated in RA pathogenesis, even after adjusting for disease activity, suggesting that physical activity may confer a protective effect in RA.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".