Next generation sequencing analysis reveals complex genetic architecture of childhood-onset systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVES: Our current understanding of the genetic architecture of childhood-onset SLE (cSLE) is limited by a dearth of comprehensive genomic studies in cSLE. We have quantified the number of known rare and common SLE risk variants in a diverse cSLE cohort. We characterised type I interferon (IFN) gene expression scores along with genomic data. METHODS: We performed whole genome sequencing on 83 patients with cSLE and 109 unaffected parents and analysed sequences for known common and rare SLE-associated risk variants. Type I IFN gene expression was quantified on a subset of patients. We investigated the relationship between clinical phenotype, genomic profile and type I IFN signatures in this cohort. RESULTS: Patients with cSLE were enriched for common SLE risk variants compared with unaffected parents and controls. We identified rare SLE risk variants in 11% of individuals with cSLE; those with rare variants had earlier disease onset (<12 years) than those without variants. Patients with cSLE had elevated type I IFN gene expression compared with unaffected parents and controls, even though most patients were treated with immunosuppressive therapy. CONCLUSIONS: Patients with cSLE from this ancestrally and geographically diverse cohort are enriched for common cSLE risk variants compared with controls, and 11% carry a rare variant in known monogenic SLE risk genes. The relationship between rare and common risk variant burden is more complex than previously hypothesised. Our findings indicate that studying patients with cSLE is important for understanding genetic contributions to SLE 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".