European genetic ancestry associated with risk of childhood ependymoma
Bibliographic record
Abstract
BACKGROUND: Ependymoma is a histologically defined central nervous system tumor most commonly occurring in childhood. Population-level incidence differences by race/ethnicity are observed, with individuals of European ancestry at highest risk. We aimed to determine whether extent of European genetic ancestry is associated with ependymoma risk in US populations. METHODS: In a multi-ethnic study of Californian children (327 cases, 1970 controls), we estimated the proportions of European, African, and Native American ancestry among recently admixed Hispanic and African American subjects and estimated European admixture among non-Hispanic white subjects using genome-wide data. We tested whether genome-wide ancestry differences were associated with ependymoma risk and performed admixture mapping to identify associations with local ancestry. We also evaluated race/ethnicity-stratified ependymoma incidence data from the Central Brain Tumor Registry of the United States (CBTRUS). RESULTS: CBTRUS data revealed that African American and Native American children have 33% and 36%, respectively, reduced incidence of ependymoma compared with non-Hispanic whites. In genetic analyses, a 20% increase in European ancestry was associated with a 1.31-fold higher odds of ependymoma among self-reported Hispanics and African Americans (95% CI: 1.08-1.59, Pmeta = 6.7 × 10-3). Additionally, eastern European ancestral substructure was associated with increased ependymoma risk in non-Hispanic whites (P = 0.030) and in Hispanics (P = 0.043). Admixture mapping revealed a peak at 20p13 associated with increased local European ancestry, and targeted fine-mapping identified a lead variant at rs6039499 near RSPO4 (odds ratio = 1.99; 95% CI: 1.45-2.73; P = 2.2 × 10-5) but which was not validated in an independent set of posterior fossa type A patients. CONCLUSIONS: Interethnic differences in ependymoma risk are recapitulated in the genomic ancestry of ependymoma patients, implicating regions to target in future association studies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".