BIOM-50. GENETIC PREDISPOSITION TO LONGER TELOMERE LENGTH AND RISK OF CHILDHOOD, ADOLESCENT AND ADULT-ONSET EPENDYMOMA
Bibliographic record
Abstract
Abstract INTRODUCTION Ependymoma is the third most common brain tumor in children, with well-described molecular characterization but poorly understood underlying germline risk factors. Telomerase reactivation in somatic cells has been linked to ependymoma progression, recurrence, and survival, and has been implicated as an important prognostic marker and potential therapeutic target. METHODS To investigate whether inherited predisposition to longer telomere length influences ependymoma risk, we utilized case-control data from three studies: 1) a population-based pediatric and adolescent ependymoma case-control sample from California (153 cases, 696 controls), 2) a hospital-based pediatric posterior fossa type A ependymoma (EPN-PF-A) case-control study from Toronto’s Hospital for Sick Children and the Children’s Hospital of Philadelphia (83 cases, 332 controls), and 3) a multicenter adult-onset ependymoma case-control dataset nested within the Glioma International Case-Control Consortium (GICC) (103 cases, 3287 controls). We investigated the individual effect of telomere-length associated SNPs on ependymoma risk, as well as the combined effect of these SNPs through polygenic score and Mendelian randomization analyses. RESULTS We observed an association between genetic predisposition to longer LTL and increased risk of adolescent-onset (P= 3.97x10-3) and adult-onset (P =0.042) ependymoma, but not ependymoma diagnosed in children < 12 years old (P=0.21), or among the pediatric EPN-PF-A sample (P=0.59). Comparing ependymoma patients ages 12–19 to those under 12 years of age demonstrated that age significantly modified the association between longer telomere length and ependymoma risk (P=0.021). CONCLUSIONS These findings complement emerging literature suggesting that dysregulated telomere maintenance is important for ependymoma pathogenesis and that longer telomere length is a risk factor for various neoplasms of the peripheral and central nervous system.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".