More CLEC16A gene variants associated with multiple sclerosis
Bibliographic record
Abstract
Nischwitz S, Cepok S, Kroner A, Wolf C, Knop M, Müller-Sarnowski F, Pfister H, Rieckmann P, Hemmer B, Ising M, Uhr M, Bettecken T, Holsboer F, Müller-Myhsok B, Weber F. More CLEC16A gene variants associated with multiple sclerosis.Acta Neurol Scand: 2011: 123: 400–406.© 2010 John Wiley & Sons A/S. Objectives – Recently, associations of several single-nucleotide polymorphisms (SNPs) within the CLEC16A gene with multiple sclerosis (MS), type-I diabetes, and primary adrenal insufficiency were reported. Methods – We performed linkage disequilibrium (LD) fine mapping with 31 SNPs from this gene, searching for the region of highest association with MS in a German sample consisting of 603 patients and 825 controls. Results – Four SNPs located in intron 19 of the CLEC16A gene were found associated. We could replicate the finding for SNP rs725613 and were able to show for the first time the association of rs2041670, rs2080272 and rs998592 with MS. Conclusion – All described base polymorphisms are mapping to one LD block of approximately 50 kb within intron 19 of the CLEC16A gene, suggesting a pivotal role of this region for susceptibility of MS and possibly also for other autoimmune diseases.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".