Utility of Baseline Transcriptomic Analysis of Rheumatoid Arthritis Synovium as an Indicator for Long-Term Clinical Outcomes
Bibliographic record
Abstract
Objective: Rheumatoid arthritis is a chronic inflammatory autoimmune disease that can lead to synovial damage, persistent joint pain, and functional disability. Our objective was to evaluate baseline synovial transcriptome from early inflammatory arthritis patients (EIA) and identify pretreatment biomarkers that could potentially provide insights into long-term functional outcomes of rheumatoid arthritis (RA). Methods Synovial biopsies from clinically inflamed knee joints were procured from either 17 EIA patients before initiation of disease modifying anti-rheumatic drug (DMARD) therapy (DMARD-naïve EIA) using the minimally invasive closed needle biopsy technique or advanced RA patients undergoing arthroplasty. Affymetrix Human Genome U133 Plus 2 microarray platform was used to profile the synovial transcriptome. The cohort was followed clinically for a median of 12.3 years, and patient data was collected at each visit. Short-term and long-term clinical outcomes were determined by assessing RA-associated clinical parameters Statistical adjustments were made to account for asynchronous clinical visits and duration of follow up. Results Based on the transcriptomic analysis, we identified 5 differentially expressed genes (DEGs), including matrix metalloproteinase (MMP)-1 (fibroblast collagenase) and MMP-3 (stromelysin-1) in DMARD-naïve EIA patients, relative to advanced RA patients (q < 0.05). Dichotomous expression of MMP-1 and MMP-3 mRNA and protein was confirmed by qPCR and immunohistochemistry respectively, based on which DMARD-naïve EIA subjects were classified as MMP-high or MMP-low. Hierarchical clustering of transcriptomic data identified 947 DEGs between MMP-high and MMP-low cohorts. Co-expression and IPA analysis of DEGs in the MMP-high cohort showed an enrichment of genes that participated in metabolic or biochemical functions and intracellular immune signaling were regulated through NF-κB and β-catenin complexes and correlated with markers of systemic inflammation. Analysis of short-term clinical outcomes in MMP-high cohort showed a significant reduction in the DAS-CRP scores relative to baseline (P <0.001), whereas area under the curve analyses of modified HAQ (mHAQ) scores correlated negatively with baseline MMP-1 (R = −0.59, P = 0.03). Further, longitudinal mHAQ scores, number of swollen joints, number of DMARDs and median follow-up duration appeared to be higher in MMP-low cohort. Conclusion Overall, our results indicate that the gene expression profiling of synovial biopsies obtained at the DMARD-naive stage in patients with EIA categorizes them into subsets with varying degrees of inflammation and can predict the future of long-term clinical outcome.
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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 | 0.001 | 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 | 0.001 | 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".