Potential Mechanisms Leading to the Abnormal Lipid Profile in Patients With Rheumatoid Arthritis Versus Healthy Volunteers and Reversal by Tofacitinib
Bibliographic record
Abstract
OBJECTIVE: Tofacitinib is an oral JAK inhibitor for the treatment of rheumatoid arthritis (RA). Systemic inflammation is proposed to play a fundamental role in the altered lipid metabolism associated with RA; however, the underlying mechanisms are unknown. We undertook this study to compare cholesterol and lipoprotein kinetics in patients with active RA with those in matched healthy volunteers. METHODS: This was a phase I open-label mechanism-of-action study. Cholesterol and lipoprotein kinetics were assessed with (13) C-cholesterol and (13) C-leucine infusions. RA patients were reevaluated after receiving oral tofacitinib 10 mg twice daily for 6 weeks. RESULTS: Levels of high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and apolipoprotein A-I (Apo A-I) as well as HDL cholesterol particle number were lower in RA patients (n = 36) than in healthy volunteers (n = 33). In contrast, the cholesterol ester fractional catabolic rate was higher in RA patients, but no differences were observed in cholesterol ester transfer protein, cholesterol ester production rate, HDL-associated Apo A-I fractional catabolic rate, or LDL-associated Apo B fractional catabolic rate. Following tofacitinib treatment in RA patients, the cholesterol ester fractional catabolic rate decreased and cholesterol levels increased. The decrease in cholesterol ester fractional catabolic rate correlated significantly with the increase in HDL cholesterol. Additionally, HDL cholesterol particle number increased and markers of HDL cholesterol function improved. CONCLUSION: This is the first study to assess cholesterol and lipoprotein kinetics in patients with active RA and matched healthy volunteers. The data suggest that low cholesterol levels in patients with active RA may be driven by increases in cholesterol ester catabolism. Tofacitinib treatment reduced cholesterol ester catabolism, thereby increasing cholesterol levels toward those in healthy volunteers, and markers of antiatherogenic HDL function improved.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".