Genetic associations with sporadic neuroendocrine tumor risk
Bibliographic record
Abstract
Genetic risk factors for sporadic neuroendocrine tumors (NET) are poorly understood. We tested risk associations in patients with sporadic NET and non-cancer controls, using a custom array containing 1536 single-nucleotide polymorphisms (SNPs) in 355 candidate genes. We identified 18 SNPs associated with NET risk at a P-value <0.01 in a discovery set of 261 cases and 319 controls. Two of these SNPs were found to be significantly associated with NET risk in an independent replication set of 235 cases and 113 controls, at a P value ≤0.05. An SNP in interleukin 12A (IL12A rs2243123), a gene implicated in inflammatory response, replicated with an adjusted odds ratio (95% confidence interval) (aOR) = 1.47 (1.03, 2.11) P-trend = 0.04. A second SNP in defender against cell death, (DAD1 rs8005354), a gene that modulates apoptosis, replicated at aOR = 1.43 (1.02, 2.02) P-trend = 0.04. Consistent with our observations, a pathway analysis, performed in the discovery set, suggested that genetic variation in inflammatory pathways or apoptosis pathways is associated with NET risk. Our findings support further investigation of the potential role of IL12A and DAD1 in the etiology of NET.
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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 | 0.000 |
| 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) | 0.000 | 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".