An extended genome scan in 442 Canadian multiple sclerosis-affected sibships: a report from the Canadian Collaborative Study Group
Bibliographic record
Abstract
Multiple sclerosis (MS) is a complex trait with a sibling relative risk (lambda(sibs)) between 18 and 36. We report a multistage genome scan of 552 sibling pairs from 442 families, the largest MS family sample assessed for linkage. The first stage consisted of a genome scan for linkage with 498 microsatellite markers at an average spacing of 7 cM in 219 sibling pairs. The second stage involved further genotyping of markers from positive regions in an independent sample of 333 affected sibling pairs. The global distribution of allele sharing for all markers showed a shift towards greater sharing within the affected sibling pair group but not in the discordant sibling pair group. This shift indicates that the number of contributing genetic factors is likely to be moderate to large. Only markers at chromosome 6p showed significant evidence for linkage (MLOD=4.40), while other regions were only suggestive (1p, 2q, 5p, 9q, 11p, 12q, 18p, 18q and 21q) with MLODs greater than 1.0. The replication analysis involving all 552 affected sibling pairs confirmed suggestive evidence for five locations, namely, 2q27 (MLOD=2.27), 5p15 (MLOD=2.09), 18p11 (MLOD=1.68), 9q21 (MLOD=1.58) and 1p31 (MLOD=1.33). Suggestive linkage evidence for a previously reported location on chromosome 17q (MLOD=1.67) and a prior association with marker D17S789 was replicated. We showed that the overall excess allele sharing we observed for the entire sample was due to increased allele sharing within the DRB1*15 negative subgroup alone. This observation is most consistent with a model of genetic heterogeneity between HLA and other genetic loci. These findings offer guidance for future genetic studies including dense SNP linkage disequilibrium analysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 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".