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Record W4391611911 · doi:10.1002/mds.29669

Defining the Genetic Landscape of Congenital Mirror Movements in 80 Affected Individuals

2024· article· en· W4391611911 on OpenAlexafffund
Meagan Collins, Judith St‐Onge, Sabrina Schlienger, Nassima Boudrahem‐Addour, Lina Mougharbel, Clara Frances Lloyd, Elena Bruneau, Cedric Roux, Ahmed N. Sahly, Bradley Osterman, Kenneth A. Myers, Guy A. Rouleau, Daniel Alexander Jimenez Cruz, Jean‐Baptiste Rivière, Andrea Accogli, Frédéric Charron, Myriam Srour

Bibliographic record

VenueMovement Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversité de MontréalMcGill Genome CentreMontreal Neurological Institute and HospitalMcGill UniversityMontreal Clinical Research InstituteMcGill University Health Centre
FundersCanadian Institutes of Health ResearchCanada Foundation for InnovationChildren's Hospital FoundationMcGill UniversityFaculty of Medicine, McGill UniversityCourtois Foundation
KeywordsMissense mutationPenetranceProbandGeneticsBiologyGeneNetrinMutationPhenotype

Abstract

fetched live from OpenAlex

BACKGROUND: Congenital mirror movements (CMM) is a rare neurodevelopmental disorder characterized by involuntary movements from one side of the body that mirror voluntary movements on the opposite side. To date, five genes have been associated with CMM, namely DCC, RAD51, NTN1, ARHGEF7, and DNAL4. OBJECTIVE: The aim of this study is to characterize the genetic landscape of CMM in a large group of 80 affected individuals. METHODS: We screened 80 individuals with CMM from 43 families for pathogenic variants in CMM genes. In large CMM families, we tested for presence of pathogenic variants in multiple affected and unaffected individuals. In addition, we evaluated the impact of three missense DCC variants on binding between DCC and Netrin-1 in vitro. RESULTS: Causal pathogenic/likely pathogenic variants were found in 35% of probands overall, and 70% with familial CMM. The most common causal gene was DCC, responsible for 28% of CMM probands and 80% of solved cases. RAD51, NTN1, and ARHGEF7 were rare causes of CMM, responsible for 2% each. Penetrance of CMM in DCC pathogenic variant carriers was 68% and higher in males than females (74% vs. 54%). The three tested missense variants (p.Ile164Thr; p.Asn176Ser; and p.Arg1343His) bind Netrin-1 similarly to wild type DCC. CONCLUSIONS: A genetic etiology can be identified in one third of CMM individuals, with DCC being the most common gene involved. Two thirds of CMM individuals were unsolved, highlighting that CMM is genetically heterogeneous and other CMM genes are yet to be discovered. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.260
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2024
Admission routes2
Has abstractyes

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