Comment on “Defining the Genetic Landscape of Congenital Mirror Movements in 80 Affected Individuals”
Bibliographic record
Abstract
Collins Hutchinson and colleagues1 reported a large clinical-genetic series of 43 index patients of congenital mirror movements (CMM), comprising 10 probands with familial CMM and 33 probands with sporadic CMM. They tested all the probands for variants in genes that have previously been associated with CMM (DCC, RAD51, NTN1, ARHGEF7, and DNAL4) to determine the genetic landscape of CMM. As CMM is a rare disease, we thought it would be interesting to compare the genetic data of this cohort with ours, which includes 92 probands, divided into 28 familial CMM and 64 sporadic CMM cases (Table 1). We identified 30 variants classified as pathogenic or likely pathogenic in known genes, according to the American College of Medical Genetics classification criteria.2 As in Collins Hutchinson's study, we were able to find a genetic cause in one third of our cases (33%). We identified 19 variants in DCC, 9 in RAD51, and 2 in NTN1. DCC remains the most implicated gene in CMM (21% of cases in our cohort vs. 28%). We identified 10% of cases with variants in the RAD51 gene (25% for familial cases), making it the second most common gene responsible for this disease in our cohort.3 By contrast, Collins Hutchinson et al included RAD51 variants among the rare genetic causes of CMM, along with the two most recently discovered genes,4, 5 NTN1 and ARHGRF7. In our cohort, we did not identify any variants in the ARHGEF7 gene, newly identified in a CMM family,5 further indicating that variants in this gene represent a rare genetic cause of CMM. A single biallelic variant in the DNAL4 gene was reported in one consanguineous CMM family.6 As in the Collins Hutchinson's cohort, we did not find any variant in the DNAL4 gene.7 Finally, genetic causes in both these large CMM cohorts were found in only a third of cases (45 of 135), suggesting that other CMM genes remain to be discovered or that nongenetic causes are frequently involved, especially in sporadic cases. Indeed, in familial cases of CMM, the genetic cause is identified in 73% of cases (28 of 38). The DCC gene is the most implicated gene in CMM in both cohorts, representing 23% (31 of 135) of all cases. The genetic data provided by our cohort show that the RAD51 gene cannot be considered as a rare genetic cause of CMM, because it is involved in 10% of cases. Altogether, the RAD51 gene is implicated in 7% (10 of 135) of cases in the two cohorts, making it the second most common gene responsible for this disease. The only pathogenic RAD51 variant reported by Collins Hutchinson et al was identified in a family not of Canadian but of Turkish origin. Ethnic origin could be one of the explanations for the lower representation of RAD51 variants in the mostly Canadian Collins Hutchinson's cohort, whereas ours gathers mainly cases of European origins. (1) Research project: Conception and design; (2) Data acquisition and analysis; (3) Manuscript: A. Writing of the first draft, B. Review and critique. O.T.: 2; 3A A.M.: 2; 3B Ma.D.: 2; 3B Mo.D.: 2; 3B I.D.: 1; 3B C.D.: 1; 3B E.R.: 1; 3B The data that support the findings of this study are available from the corresponding author upon reasonable request.
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.028 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".