Evidence for Genetic Association and Interaction Between the <i>TYK2</i> and <i>IRF5</i> Genes in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Several candidate genes have been implicated in susceptibility for systemic lupus erythematosus (SLE), a complex autoimmune disease. The proposed genes include members of the type I interferon (IFN) pathway and genes involved in immunological defense functions. Our aim was to systematically replicate 6 such genes, TYK2, IRF5, CTLA4, PDCD1, FCGR2A, and NOD2. METHODS: Single-nucleotide polymorphisms in TYK2, IRF5, CTLA4, PDCD1, FCGR2A, and NOD2 were genotyped in 277 SLE patients and 356 healthy controls from Finland, giving a power of 42%-70% for different genes at published allele frequencies. RESULTS: Significant association was seen for rs2304256 (p = 0.0001) and rs12720270 (p = 0.0031) in TYK2 and rs10954213 (p = 0.0043) in IRF5 in our samples, but not for the other genes. We found evidence for genetic interaction (p = 0.014) between rs2304256 in TYK2 and rs10954213 in IRF5, both members of the type I IFN pathway, strengthening the role of the type I IFN pathway in the pathogenesis of SLE. CONCLUSION: The IFN pathway genes IRF5 and TYK2 may act epistatically in increasing risk for SLE, but our lack of replication does not exclude effects of the other genes studied.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".