Nonadditive Effects of Common Genetic Variants Have a Negligent Contribution to Cancer Heritability
Bibliographic record
Abstract
BACKGROUND: Contribution of dominance effects to cancer heritability is unknown. We leveraged existing genome-wide association data for seven cancers to estimate the contribution of dominance effects to the heritability of individual cancer types. METHODS: We estimated the proportion of phenotypic variation caused by dominance genetic effects using genome-wide association data for seven cancers (breast, colorectal, lung, melanoma, nonmelanoma skin, ovarian, and prostate) in a total of 166,772 cases and 284,824 controls. RESULTS: We observed no evidence of a meaningful contribution of dominance effects to cancer heritability. By contrast, additive effects ranged between 0.11 and 0.34. CONCLUSIONS: In line with studies of other human traits, the dominance effects of common genetic variants play a minimal role in cancer etiology. IMPACT: These results support the assumption of an additive inheritance model when conducting cancer association studies with common genetic variants.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".