Neu–Laxova syndrome presenting prenatally with increased nuchal translucency and cystic hygroma: The utility of exome sequencing in deciphering the diagnosis
Bibliographic record
Abstract
Neu-Laxova syndrome (NLS) is a lethal autosomal recessive microcephaly syndrome associated with intrauterine growth restriction (IUGR) and multiple congenital anomalies. Clinical features include central nervous system malformations, joint contractures, ichthyosis, edema, and dysmorphic facial features. Biallelic pathogenic variants in either the PHGDH or PSAT1 genes have been shown to cause NLS. Using exome sequencing, we aimed to identify the underlying genetic diagnosis in three fetuses (from one family) with prenatal skin edema, severe IUGR, micrognathia, renal anomalies, and arthrogryposis and identified a homozygous c.1A>C (p.Met1?, NM_006623.3) variant in the PHGDH gene. Loss of the translation start codon is a novel genetic mechanism for the development of NLS. Prenatal diagnosis of NLS is challenging and few reports describe the fetal pathology. Fetal neuropathologic examination revealed: delayed brain development, congenital agenesis of the corticospinal tracts, and hypoplasia of the hippocampus, cerebellum and brainstem. Each pregnancy also showed increased nuchal translucency (NT) or cystic hygroma. While NLS is rare, it may be a cause of recurrent increased NT/cystic hygroma. This finding provides further support that cystic hygroma has many different genetic causes and that exome sequencing may shed light on the underlying genetic diagnoses in this group of prenatal patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".