Neurological Disorders Associated with WWOX Germline Mutations—A Comprehensive Overview
Bibliographic record
Abstract
The transcriptional regulator WW domain-containing oxidoreductase (WWOX) is a key player in a number of cellular and biological processes including tumor suppression. Recent evidence has emerged associating WWOX with non-cancer disorders. Patients harboring pathogenic germline bi-allelic WWOX variants have been described with the rare devastating neurological syndromes autosomal recessive spinocerebellar ataxia 12 (SCAR12) (6 patients) and WWOX-related epileptic encephalopathy (DEE28 or WOREE syndrome) (56 patients). Individuals with these syndromes present with a highly heterogenous clinical spectrum, the most common clinical symptoms being severe epileptic encephalopathy and profound global developmental delay. Knowledge of the underlying pathophysiology of these syndromes, the range of variants of the WWOX gene and its genotype-phenotype correlations is limited, hampering therapeutic efforts. Therefore, there is a critical need to identify and consolidate all the reported variants in WWOX to distinguish between disease-causing alleles and their associated severity, and benign variants, with the aim of improving diagnosis and increasing therapeutic efforts. Here, we provide a comprehensive review of the literature on WWOX, and analyze the pathogenic variants from published and unpublished reports by collecting entries from the ClinVar, DECIPHER, VarSome, and PubMed databases to generate the largest dataset of WWOX pathogenic variants. We estimate the correlation between variant type and patient phenotype, and delineate the impact of each variant, and used GnomAD to cross reference these variants found in the general population. From these searches, we generated the largest published cohort of WWOX individuals. We conclude with a discussion on potential personalized medicine approaches to tackle the devastating disorders associated with WWOX mutations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".