Type I Interferon Status and Clinical Manifestations in a Large Cohort of Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
Objectives Type I interferons (IFN) are pivotal in the pathogenesis of SLE, with high IFN gene signature (IGS) status associated with certain organ manifestations, autoantibody profiles, and disease severity. With novel medications targeting the interferon pathway, an enhanced understanding of the IGS in patients with SLE is necessary. Recent studies have shown IFN levels remain stable overtime despite changes in disease activity and treatment. In this study, we investigated the IGS in relation to clinical characteristics in patients with SLE. Methods Patients who met 2019 EULAR/ACR classification criteria for SLE, from a single center, were included. The whole blood collected was analyzed for IGS by the DxTerity assay, categorizing patients into IFN high or IFN low status. SLEDAI-2K organ domains were cumulatively characterized from 5 years prior to whole blood collection to last available visit. Clinical characteristics, including SLICC/ACR damage index (SDI), cumulative antibody status, glucocorticoid and immunosuppressive use, were analyzed according to IFN status. Results Five-hundred-six patients with median age of 49.53 years (IQR 37.27-60.54) were included, with 291 (57.5%) IFN high and 215 (42.5%) IFN low (Table 1). The median duration of SLE disease was longer in the IFN low group (22.7 years [IQR 11.58-21.05]) than in the IFN high group (14.06 [QR 7.90-24.71]) (p<0.001). There was no difference in the proportion any of the individual SLEDAI-2K organ domains between the IFN high and low groups, though there was a numerical difference in the hematologic domain (IFN high 82.8% versus 73.0% [p=0.011]). The median SLEDAI-2K score was higher in the IFN high group (2.00 [IQR 0.00-4.00]) than in the IFN low group (0.00 [IQR 0.00-4.00]) (<0.001). More patients in the IFN high group had positive Smith (56.7% vs 32.6% [p<0.001]), RNP (66.7% vs 49.3% [p<0.001]), Ro (67.4% vs 47.0% [p<0.001]), La (30.9% vs 17.2% [p=0.001]), chromatin (75.6% vs 41.9% [p<0.001]), dsDNA (61.2% vs 38.1% [p<0.001]) and ribosomal P (27.1% vs 7.9% [p<0.001]) autoantibodies, with no differences in levels of C3 and C4 or in the presence of antiphospholipid antibodies. More patients with IFN high status were on glucocorticoids (112; 38.5%) than were patients with IFN low status (58, 27%) (p=0.009). More IFN high patients were on immunosuppressants (185; 63.6%) vs the IFN low group (98; 45.6%) (p<0.001). Table 1. Clinical characteristics of SLE patients based on IFN levels Conclusion In this large cohort of patients with SLE, IGS status may help to predict disease severity, use of glucocorticoids, and overall use of immunomodulatory therapy, though IFN level did not predict presence of SLEDAI-2K organ domains.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".