An expansion of the phenotype in individuals with SYNCRIP-Related Neurodevelopmental Disorder
Bibliographic record
Abstract
Disruption of genes within the HNRNP gene family has been observed in neurodevelopmental and neurodegenerative diseases . The HNRNP-Related Neurodevelopmental Disorders (HNRNP-RNDDs), while each unique, have been recently described with similar clinical and molecular features across variation in several genes. However, the phenotypic information on these patients is still lacking. In this case series we aim to describe the phenotypes that are associated with SYNCRIP-Related Neurodevelopmental Disorder (SYNCRIP-RNDD). We describe in depth ten novel individuals and one previously published individual with mostly de novo and predicted damaging variants in SYNCRIP , consistent with a diagnosis of SYNCRIP-RNDD. We also describe previously published patients, many of which are from large cohort studies , as well as individuals from patient databases. Here, we expand the phenotype of SYNCRIP-RNDD beyond a generic neurodevelopmental disorder to a variable syndrome consisting of mild to borderline developmental delay/intellectual disability, speech and language delay, behavioral differences such as autism spectrum disorder , structural brain anomalies , hypotonia , and seizures . Inconsistent dysmorphic features were also observed, with the few recurrent findings including long eyelashes , mildly deep-set eyes, prominent ears, and thin or thick lips. This study increases our understanding of SYNCRIP-RNDD, as well as HNRNP-RNDDs broadly.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".