EFFECT OF COMORBIDITY AND STANDARD THERAPY ON INTERFERON STATUS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Bibliographic record
Abstract
PV035 / #122 Poster Topic: AS04 - Biomarkers Background/Purpose Type I interferon (IFN-I) play a central role in the pathogenesis of Systemic lupus erythematosus (SLE). Overexpression of IFN-I occurs in 60-80% patients with SLE. Type I IFN-inducible gene expression, measured using the IFN gene signature (IFGNS), provides a method to assess IFN-I pathway activation in individual patients. Against a background of genetic predisposition, a trigger stimulus, possibly microbial, induces the production of IFN-I and autoantibodies leading to inflammation. Can only the clinical and immunological manifestations of SLE affect on IFNGS? The aim of our study was to describe any conditions, comorbidities and standard therapy of SLE depending on IFN gene signature. Methods This observational retrospective-prospective study included 76 patients (86% women, median aged 33 [25;43] years (median [interquartile range 25;75%]), with a definite diagnosis of SLE (SLICC 2012) attending a routine visit at our Clinic between February 2021 and June 2024. Baseline demographics, family history of immune-inflammatory rheumatic diseases among the first-line relatives, triggers, body mass index, smoking status, cardiovascular disease/stroke risk factors, renal disease, cancer, standard therapy (glucocorticoids, antimalarial, immunosuppressants) and IFNGS status (high/low) were analyzed in SLE patients. IFN status was assessed by the expression of IFN-inducible genes (MX1, RSAD2, EPSTI1) using real-time polymerase chain reaction. IFNGS was calculated as the average expression value of 3 selected genes. In patients, IFNGS was considered high when the average value of gene expression exceeded the average value of gene expression in donors. The control group consisted of 20 healthy donors comparable in sex and age with the SLE patients. Results The median disease duration was 2.3 [0.2;11.0] years, SLEDAI-2K 7 [4;11] score, SDI 0 [0;2] score. At the time of inclusion in the study, SLE patients had the following manifestations: hematological disorders - 49%, most commonly leucopenia – 45%, inflammatory arthritis - 39%, nephritis - 33% (most commonly class IV), cutaneous lupus - 28%, serositis -18%, mucosal ulcers - 8%, nervous system involvement - 7%. Among ‘non-criteria’ symptoms the most common were: livedo – 20%, Raynaud’s phenomenon - 12%, interstitial lung disease - 12%, lymphadenopathy - 8%, unexplained fever - 7%. Concomitant APS and Sjögren’s syndrome were found in 12% and 38% of patients, respectively. The majority of patients at the time of inclusion were taking glucocorticoids (83%) at low doses (10.0 [7.5; 20.0] mg/day prednisolone) in combination with hydroxychloroquine (80%) at a dose of 200 mg/day. Immunosuppressants were used less frequently (in 36% of patients), mainly - mycophenolate mofetil (18%), cyclophosphamide, methotrexate and azathioprine in single cases. In addition, 13/76 (17%) patients were not receiving any therapy. Anti-B cell biologic (mainly rituximab) according to the inclusion criteria were used more than 2 years ago in 8% of patients. IFNGS-high was detected in 72% of SLE patients. IFNGS-high patients were younger at the time of inclusion (31 [25; 41] and 40 [32; 49] years, p<0.05). We identified less hypertension (24% and 52%) and dyslipidemia (13% and 38%) in IFGNS-high patients vs IFNGS-low patients with SLE. No effect of standard therapy for SLE on IFN-inducible genes expression was found. Conclusions In SLE patients, IFN-I is independent of family history of autoimmune disease, any provoking factors, gender, weight, smoking, and any comorbidity. The lower incidence of hypertension and dyslipidemia in IFNGS-high patients is due to the younger age of them. Standard therapy has no significant effect on the expression of certain IFN-inducible genes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".