Systemic Sclerosis (Scleroderma): Specific Autoantigen Genes Are Selectively Overexpressed in Scleroderma Fibroblasts
Bibliographic record
Abstract
The pathogenesis of systemic sclerosis (SSc) involves complex interactions between activated fibroblasts eventually leading to fibrosis, and impaired immune tolerance characterized by a variety of circulating SSc-specific autoantibodies. The expression of autoantigens in fibroblasts, a key target tissue in SSc, may play an important role in this process. To obtain a global view of this process, we examined gene expression profiles of SSc dermal fibroblasts using cDNA microarrays. The results show that dermal fibroblasts from SSc patients obtained from either affected or unaffected skin displayed a characteristic pattern of increased SSc autoantigen gene expression compared with that from normal controls. In particular, fibrillarin (p = 0.028), centromeric protein B (p = 0.01), centromeric autoantigen P27 (p = 0.042), and RNA polymerase II (220 kDa; p = 0.02) were significantly overexpressed in SSc fibroblasts. Quantitative RT-PCR confirmed overexpression of these autoantigens and also revealed increased levels of DNA topoisomerase I transcripts in SSc fibroblasts compared with normal control fibroblasts (p = 0.0318). The polymyositis/scleroderma autoantigen gene was overexpressed in some SSc patients (p = 0.09). To examine the specificity of these overexpressed autoantigen genes for SSc and its tissue specificity for fibroblasts, cDNA microarrays of dermal fibroblasts from patients with eosinophilic fasciitis and scleromyxedema were studied as well as PBMC and muscle biopsies from SSc patients. None of these tissues showed significant alterations in gene expression of SSc-specific autoantigens. Therefore, SSc-associated autoantigen genes are selectively overexpressed in SSc dermal fibroblasts, a major tissue involved in disease 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".