A meta-analysis of genomic screens in multiple sclerosis
Bibliographic record
Abstract
We combined the raw genotyping data from three large multiple sclerosis genome screens and performed a global meta-analysis in order to compare and summarize the linkage results from the different studies. In alphabetical order, the screens provided data from 442 markers typed in 52 multiplex families with a total of 133 affected individuals (the American screen), 314 markers typed in 128 families with 264 affecteds (the British screen) and 257 markers typed in 61 families with a total of 139 affected subjects (the Canadian screen). Multipoint analysis of these data was performed using the GENEHUNTER program. The highest non-parametric linkage (NPL) score in the meta-analysis was observed on chromosome 17q11 (NPL score 2.58), although this score falls short of genome-wide significance. A total of eight regions had NPL scores greater than 2.0. One of the regions with an NPL score greater than 2.0 was the HLA region on chromosome 6p21 (NPL=2.2). This region is known, from association studies, to be involved in MS susceptibility, but the modest linkage result observed here suggests the encoded susceptibility effect is not large compared with the high familial recurrence in MS (lambda approximately 20). Overall, our linkage results suggest that MS is likely to be multigenic in its genetic susceptibility.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.018 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".