Genetics of osteonecrosis in children and adults with systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVES: Genetics plays an important role in SLE risk, as well as osteonecrosis (ON), a significant and often debilitating complication of SLE. We aimed to identify genetic risk loci for ON in people with childhood-onset (cSLE) and adult-onset (aSLE) SLE. METHODS: We enrolled participants from two tertiary care centres who met classification criteria for SLE. Participants had prospectively collected clinical data and were genotyped on a multiethnic array. Un-genotyped single nucleotide polymorphisms (SNPs) were imputed, and ancestry was inferred using principal components (PCs). Our outcome was symptomatic ON confirmed by imaging. We completed time-to-ON and logistic regression of ON genome-wide association studies (GWASs) with covariates for sex, age of SLE diagnosis, five PCs for ancestry, corticosteroid use and selected SLE manifestations. We conducted separate analyses for cSLE and aSLE and meta-analysed results using inverse-variance weighting. Genome-wide significance was P < 5 × 10-8. RESULTS: The study included 940 participants with SLE, 87% female and 56% with cSLE. ON was present in 7.6% (n = 71). Median age of SLE diagnosis was 16.9 years (interquartile range [IQR]: 13.5, 29.3), with median follow-up of 8.0 years (IQR: 4.2, 15.7). Meta-GWAS of cSLE and aSLE time-to-ON of 4 431 911 SNPs identified a significant Chr.2 SNP, rs34118383 (minor allele frequency = 0.18), intronic to WIPF1 (hazard ratio = 3.2 [95% CI: 2.2, 4.8]; P = 1.0 × 10-8). CONCLUSION: We identified an intronic WIPF1 variant associated with a 3.2 times increased hazard for ON (95% CI: 2.2, 4.8; P = 1.0 × 10-8) during SLE follow-up, independent of corticosteroid exposure. The effect of the SNP on time-to-ON was similar in cSLE and aSLE. This novel discovery represents a potential ON risk locus. Our results warrant replication.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".