Description of neurodevelopmental phenotypes associated with 10 genetic neurodevelopmental disorders: A scoping review
Bibliographic record
Abstract
Neurodevelopmental disorders (NDDs) are a heterogeneous group of conditions including intellectual disability, global developmental delay, autism spectrum disorder, and attention deficit hyperactivity disorder. Advances in genetic diagnostic technology have led to the identification of a number of NDD-associated genes, but reports of cognitive and developmental outcomes in affected individuals have been variable. The objective of this scoping review is to synthesize available information pertaining to the developmental outcomes of individuals with pathogenic variants in ten emerging recurrent NDD-associated genes identified from large scale sequencing studies; ADNP, ANKRD11, ARID1B, CHD2, CHD8, CTNNB1, DDX3X, DYRK1A, SCN2A, and SYNGAP1. After a comprehensive search, 260 articles were selected that reported on neurodevelopmental measures or diagnoses. We identify the spectrum of developmental outcomes for each genetic NDD, including prevalence of intellectual disability, frequency of co-morbid NDDs such as ADHD and autism, and commonly reported medical issues that can help inform diagnosis and treatment. There are significant gaps in our understanding of the natural history of these conditions. Future research focusing on barriers to assessment, the development of modified assessment tools appropriate for long-term outcomes in genetic NDD, and collection of longitudinal data will increase understanding of prognosis in these conditions and inform evaluations of treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".