Exploring the phenotypic spectrum and osteopenia mechanisms in Yunis-Varón syndrome
Bibliographic record
Abstract
Purpose Biallelic variants in FIG4 or VAC14 are associated with Yunis-Varón syndrome (YVS), which is characterized by multisystem involvement including skeletal findings, craniofacial dysmorphisms and central nervous system anomalies. Pathogenic variants in those same genes have also been associated with a predominantly neurological phenotype and with nonsyndromic conditions, such as Charcot-Marie-Tooth disease and amyotrophic lateral sclerosis. By describing 5 new cases of FIG4 -associated YVS and reviewing the literature, we better delineate the clinical phenotype associated with loss of function of those genes. We also explore osteopenia mechanisms by assessing bone physiologic parameters in a mouse model. Methods Exome sequencing or Sanger sequencing was performed in 5 unrelated individuals. Bone histomorphometry was performed in Fig4 plt/plt mice and compared with wild type. Relevant literature from the last 10 years was reviewed. Results All individuals presented a phenotype overlapping the typical YVS and the brain anomalies and neurologic syndrome. Clinical features included developmental delay, structural brain malformations, and skeletal anomalies, such as osteopenia. Biallelic FIG4 variants were identified in each individual. In mice, bone histomorphometry parameters suggested that osteopenia might be secondary to reduced bone formation rather than increased bone degradation. Conclusion This study contributes to a better understanding of the phenotypic variability caused by pathogenic variants in FIG4 or VAC14 and suggests an important overlap between previously described phenotypes. The brain anomalies and neurologic syndrome is likely in the same spectrum as classical YVS. Further studies are still needed to clarify the effects of partial loss-of-function (hypomorphic) variants and to identify genotype-phenotype correlations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".