Analysis of Canadian multiple sclerosis patients does not support a role for FKBP6 in disease
Bibliographic record
Abstract
We read with interest a recent article by Mescheriakova et al.1 entitled Linkage analysis and whole exome sequencing identify a novel candidate gene in a Dutch multiple sclerosis family. In this study, the authors described a missense variant in FKBP6 (p.R183C, rs147213094) co-segregating with multiple sclerosis (MS) in eight individuals from a large Dutch multi-incident family. Four healthy family members were also found to harbour this mutation, and it was not observed in one family member diagnosed with MS. Reduced penetrance and the presence of phenocopies does not detract from the authors’ claim as familial forms of complex diseases, including MS, frequently are genetically heterogeneous.2–5 In addition, albeit not statistically significant, the authors reported an elevated minor allele frequency (MAF) for FKBP6 p.R183C in MS patients (1.27%) compared to controls (0.95%), particularly for those with a family history of MS (2.53%).1
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".