Gene expression analysis of macrophages derived from ankylosing spondylitis patients reveals interferon‐γ dysregulation
Bibliographic record
Abstract
OBJECTIVE: To determine whether macrophages, a type of cell implicated in the pathogenesis of ankylosing spondylitis (AS), exhibit a characteristic gene expression pattern. METHODS: Macrophages were derived from the peripheral blood of 8 AS patients (median disease duration 13 years [range <1-43 years]) and 9 healthy control subjects over 7 days with the use of granulocyte-macrophage colony-stimulating factor. Cells were stimulated for 24 hours with interferon-gamma (IFN gamma; 100 units/ml), were left untreated for 24 hours, or were treated for 3 hours with lipopolysaccharide (LPS; 10 ng/ml). RNA was isolated and examined by microarray and real-time quantitative reverse transcription-polymerase chain reaction analysis. RESULTS: Microarray analysis revealed 198 probe sets detecting the differential expression of 141 unique genes in untreated macrophages from AS patients compared with healthy controls. Clustering and principal components analysis clearly distinguished AS patients and controls. Of the differentially expressed genes, 78 (55%) were IFN-regulated, and their relative expression indicated a "reverse" IFN signature in AS patient macrophages, where IFN gamma-up-regulated genes were underexpressed and down-regulated genes were overexpressed. Treatment of macrophages with exogenous IFN gamma normalized the expression of these genes between patients and controls. In addition, the messenger RNA encoded by the IFN gamma gene was approximately 2-fold lower in AS patient macrophages at baseline (P = 0.004) and was poorly responsive to LPS (P = 0.018), as compared with healthy controls. CONCLUSIONS: Our findings reveal consistent differences in gene expression in macrophages from AS patients, with evidence of a striking "reverse" IFN signature. Together with poor expression and responsiveness of the IFN gamma gene, these results suggest that there may be a relative defect in IFN gamma gene regulation, with autocrine consequences and implications for 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 | 0.000 | 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 | 0.000 |
| 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 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".