Neonatal Encephalopathy
Bibliographic record
Abstract
Background and Objectives Neonatal encephalopathy (NE) is characterized by an abnormal level of consciousness with or without seizures in the neonatal period. It affects 1–6/1,000 live term newborns. We applied genome sequencing (GS) in term newborns with NE to investigate the underlying genetic causes. Methods We enrolled term newborns according to inclusion/exclusion criteria during their Neonatal Intensive Care admission. We performed GS trio and applied bioinformatic tools. We developed pipelines for manual filters. We applied in silico prediction tools, protein 3D modeling, and functional characterization to assess the pathogenicity of variants. Results Seventeen newborns fulfilled inclusion criteria. We identified 12 variants in 10 genes. We classified 4 variants in PPP2R5D , BCOR , CFL2 , and SCN2A (previously established disease genes) as pathogenic/likely pathogenic; 7 variants in DST (previously established disease gene), STAB2 , CELF4 , SORCS2 , CTNND2 , and ASTN1 (5 candidate genes) as variants of uncertain significance (VUS); and one variant in STAB2 as likely benign. The CELF4 and ASTN1 copy number variants (CNVs) resulted in structural changes in protein 3D models. The functional characterization of SORCS2 VUS revealed disruption of SorCS2 dimer formation and confirmed its pathogenicity. The functional characterization of STAB2 variants updated their characterization from VUS/likely benign to benign. The CTNND2 VUS resulted in a shift in 3D protein structure. We were not able to perform protein 3D modeling and functional characterization of two DST VUS. We are not certain whether CTNND2 and DST variants may be causative of NE in our study. Discussion The diagnostic rate of research GS was 41% in our prospective study. We broaden the phenotypic spectrum of PPP2R5D -associated Hogue-Janssens syndrome 1, CFL2 -associated nemaline myopathy 7, and BCOR -associated oculo-facio-cardio-dental syndrome to include NE and/or neonatal seizures. We identified 3 candidate genes ( SORCS2, CELF4, ASTN1 ) that may cause NE. We believe that protein 3D modeling is an important tool to assess the pathogenicity of CNVs and may advance the discoveries of novel genetic diseases. However, functional characterization of missense variants is essential for discoveries of novel genetic diseases. It seems that GS can help identify more candidate genes compared with ES.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".