The Spectrum of MORC2-Related Disorders: A Potential Link to Cockayne Syndrome
Bibliographic record
Abstract
BACKGROUND: Cockayne syndrome (CS) is a DNA repair disorder primarily associated with pathogenic variants in ERCC6 and ERCC8. As in other Mendelian disorders, there are a number of genetically unsolved CS cases. METHODS: We ascertained five individuals with monoallelic pathogenic variants in MORC2, previously associated with three dominantly inherited phenotypes: an axonal form of Charcot-Marie-Tooth disease type 2Z; a syndrome of developmental delay, impaired growth, dysmorphic facies, and axonal neuropathy; and a rare form of spinal muscular atrophy. RESULTS: One of these individuals bore a strong phenotypic resemblance to CS. We then identified monoallelic pathogenic MORC2 variants in three of five genetically unsolved individuals with a clinical diagnosis of CS. In total, we identified eight individuals with MORC2-related disorder, four of whom had clinical features strongly suggestive of CS. CONCLUSIONS: Our findings indicate that some forms of MORC2-related disorder have phenotypic similarities to CS, including features of accelerated aging. Unlike classic DNA repair disorders, MORC2-related disorder does not appear to be associated with a defect in transcription-coupled nucleotide excision repair and follows a dominant pattern of inheritance with variants typically arising de novo. Such de novo pathogenic variants present particular challenges with regard to both initial gene discovery and diagnostic evaluations. MORC2 should be included in diagnostic genetic test panels targeting the evaluation of microcephaly and/or suspected DNA repair disorders. Future studies of MORC2 and its protein product, coupled with further phenotypic characterization, will help to optimize the diagnosis, understanding, and therapy of the associated disorders.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".