Lipoxygenase-derived oxylipins are enriched in anti-citrullinated protein antibody (ACPA)-positive individuals at risk for developing rheumatoid arthritis
Bibliographic record
Abstract
BACKGROUND: Rheumatoid arthritis (RA) is typically preceded by an extended preclinical period where circulating autoantibodies, particularly anti-citrullinated protein antibodies (ACPA), are detectable in the absence of clinical arthritis. Increased dietary intake of anti-inflammatory omega-3 (ω3) polyunsaturated fatty acids (PUFA) has been shown to be associated with a lower the risk of developing incident RA in large epidemiological studies. It is currently not known how changes in fatty acid (FA) metabolism may impact on the progression towards RA in at-risk individuals. To begin to address this question, we profiled serum FAs and oxylipins in an established cohort of at-risk ACPA-positive first-degree relatives (FDR) of RA patients (N = 31), some of whom developed RA (N = 4), and compared their profile to ACPA-negative FDR from the same population (N = 10). METHODS: Gas chromatography (GC) was used for FA quantitation. Oxylipins were extracted and quantified using high-performance liquid chromatography-tandem mass spectrometry (HPLC/MS/MS). RESULTS: Although we did not detect any meaningful differences in overall FA content between ACPA + and ACPA - FDR, the levels of oxylipins derived from FA metabolism demonstrated significant differences between the two groups, with the ACPA + group demonstrating enrichment in circulating arachidonic acid- and eicosapentaenoic acid-derived molecules. Compared with the ACPA - FDR group, the ACPA + FDR, including those who progressed into inflammatory arthritis, displayed higher levels of LOX-derived oxylipins. CONCLUSION: ACPA seropositivity in otherwise unaffected individuals at-risk for developing future RA based on family history (FDR) is associated with alterations in the serum oxylipin profile that suggests dysregulated LOX activity.
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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 | 0.001 | 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".