Parent-of-origin effect in multiple sclerosis: observations from interracial matings.
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is a complex neurologic disease with a striking geographical distribution. In Canada, prevalence is high in Caucasians of Northern European ancestry and uncommon in North American Aboriginals, many of whom now have Caucasian admixture. METHODS: The population-based Canadian Collaborative Project on the Genetic Susceptibility to MS provided the characteristics of 58 individuals with 1 Caucasian and 1 North American Aboriginal parent from a database of 30,000 MS index cases. RESULTS: We found that MS index cases with a Caucasian mother and a North American Aboriginal father had a higher sib recurrence risk and greater F:M sex ratio (p = 0.043) than patients with a North American Aboriginal mother and Caucasian father. CONCLUSIONS: Maternal parent-of-origin effects in multiple sclerosis disease etiology previously seen in studies of half-siblings and avuncular pairs are also seen in Caucasian-North American Aboriginal admixture matings and warrant further investigation. A differential influence of maternal risk transmission on the sex ratio of affected offspring is implied. The method of analysis used may have broader implications for detection of parent-of-origin effects in admixture cohorts.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".