Genetic predisposition to longer telomere length and risk of childhood, adolescent and adult-onset ependymoma
Bibliographic record
Abstract
Abstract Ependymoma is the third most common brain tumor in children, with well-described molecular characterization but poorly understood underlying germline risk factors. To investigate whether genetic predisposition to longer telomere length influences ependymoma risk, we utilized case–control data from three studies: a population-based pediatric and adolescent ependymoma case–control sample from California (153 cases, 696 controls), a hospital-based pediatric posterior fossa type A (EPN-PF-A) ependymoma case–control study from Toronto’s Hospital for Sick Children and the Children’s Hospital of Philadelphia (83 cases, 332 controls), and a multicenter adult-onset ependymoma case–control dataset nested within the Glioma International Case-Control Consortium (GICC) (103 cases, 3287 controls). In the California case–control sample, a polygenic score for longer telomere length was significantly associated with increased risk of ependymoma diagnosed at ages 12–19 (P = 4.0 × 10 −3 ), but not with ependymoma in children under 12 years of age (P = 0.94). Mendelian randomization supported this observation, identifying a significant association between genetic predisposition to longer telomere length and increased risk of adolescent-onset ependymoma (OR PRS = 1.67; 95% CI 1.18–2.37; P = 3.97 × 10 −3 ) and adult-onset ependymoma (P MR-Egger = 0.042), but not with risk of ependymoma diagnosed before age 12 (OR = 1.12; 95% CI 0.94–1.34; P = 0.21), nor with EPN-PF-A (P MR-Egger = 0.59). These findings complement emerging literature suggesting that augmented telomere maintenance is important in ependymoma pathogenesis and progression, and that longer telomere length is a risk factor for diverse nervous system malignancies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".