Analysis of Complement Gene Expression, Clinical Associations, and Biodistribution of Complement Proteins in the Synovium of Early Rheumatoid Arthritis Patients Reveals Unique Pathophysiologic Features
Bibliographic record
Abstract
Abstract Rheumatoid arthritis (RA) is an autoimmune disease characterized by synovial hyperplasia and inflammation. The finding of autoantibodies in seropositive RA suggests that complement system activation might play a pathophysiologic role due to the local presence of immune complexes in the joints. Our first objective was to explore the Pathobiology of Early Arthritis Cohort (PEAC) mRNA sequencing data for correlations between clinical disease severity as measured by DAS28-ESR (disease activity score in 28 joints for erythrocyte sedimentation rate) and complement system gene expression, both in the synovium and in blood. Our second objective was to determine the biodistribution using multiplex immunohistochemical staining of specific complement activation proteins and inhibitors from subjects in the Accelerating Medicines Partnership (AMP) RA/SLE study. In the PEAC study, there were significant positive correlations between specific complement gene mRNA expression levels in the synovium and DAS28-ESR for the following complement genes: C2, FCN1, FCN3, CFB, CFP, C3AR1, C5AR1, and CR1. Additionally, there were significant negative correlations between DAS28-ESR and Colec12, C5, C6, MASP-1, CFH, and MCP. In the synovium there were also significant positive correlations between DAS28-ESR and FcγR1A, FcγR1B, FcγR2A, and FcγR3A. Notably, CFHR4 synovial expression was positively correlated following treatment with the DAS28-ESR at 6 mo, suggesting a role in worse therapeutic responses. The inverse correlation of C5 RNA expression in the synovium may underlie the failure of significant benefit from C5/C5aR inhibitors in clinical trials performed in patients with RA. Multiplex immunohistochemical analyses of early RA synovium reveal significant evidence of regional alterations of activation and inhibitory factors that likely promote local complement activation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".