32Do the risks of Lynch syndrome-related cancers depend on the parent-of-origin of the mutation?
Bibliographic record
Abstract
Abstract Background Individuals who carry pathogenic mutations in DNA mismatch repair (MMR) genes have high risks of cancer, and small studies have suggested that these risks depend on the sex of the parent from whom the mutation was inherited. We have conducted the first large study of such a parent-of-origin effect (POE). Methods Our study was based on all MMR gene mutation carriers and their relatives in the Colon Cancer Family Registry, comprising 18,226 people. The POE was estimated as a hazard ratio (HR) using a segregation analysis approach that adjusted for ascertainment. HR = 1 corresponds to no POE and HR > 1 corresponds to higher risks for maternal mutations. Results For all MMR genes combined, the estimated POE HRs were 1.02 (95% confidence interval (CI) 0.75-1.39, p = 0.9) for male colorectal cancer, 1.12 (95% CI 0.81-1.54, p = 0.5) for female colorectal cancer and 0.84 (95% CI 0.52-1.36, p = 0.5) for endometrial cancer. Separate results for each MMR gene were similar. Conclusions Despite being well-powered, our study did not find any evidence that cancer risks for MMR gene mutation carriers depend on the parent-of-origin of the mutation. Based on current evidence, we don’t recommend that POEs be incorporated into the clinical guidelines or advice for such carriers. Key messages MMR gene mutations inherited from the maternal and paternal side confer similar risks of developing colorectal and endometrial cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".