Plasma Protein Fluctuation Trajectories Over 15 Years Before Rheumatoid Arthritis Onset
Bibliographic record
Abstract
Rheumatoid arthritis (RA) causes long-term functional disability, aggravating physical and mental stress to patients. However, the dynamic pathogenesis before RA onset remains unclear. Here we examined the associations between 2923 plasma proteins and incident RA in the UK Biobank cohort. Over a 15-year follow-up period, 433 RA cases were identified, revealing 460 significant protein-RA associations. These RA-related proteins were predominantly involved in immune responses, such as leukocyte migration, T cell activation, and lymphocyte activation. Sixty five proteins were significantly associated with both long-term and near-term risk of RA. Among them, 26 proteins exhibited changes as early as over 15 years prior to RA onset with progressively fluctuating, such as IL6 and IFI30. Others, such as CDCP1 and TGFA, showed inconsistent fluctuation patterns, while proteins like GDF15 and EDA2R began to fluctuate closer to the onset of RA. Furthermore, these proteins demonstrated robust predictive performance, with an area under the curve (AUC) of 0.818 in the training set and 0.766 in the test set. When combined with demographic measures, the predictive model showed further improvement, achieving an AUC of 0.871 in the training set and 0.919 in the test set. Our findings characterise plasma protein fluctuation trajectories over 15 years before RA onset and deepen our understanding of early-stage pathogenesis.
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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 | 0.000 | 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 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".