Sequence variants in HECTD1 result in a variable neurodevelopmental disorder
Bibliographic record
Abstract
Dysregulation of genes encoding the homologous to E6AP C-terminus (HECT) E3 ubiquitin ligases has been linked to cancer and structural birth defects. One member of this family, the HECT-domain-containing protein 1 (HECTD1), mediates developmental pathways, including cell signaling, gene expression, and embryogenesis. Through GeneMatcher, we identified 14 unrelated individuals with 15 different variants in HECTD1 (10 missense, 3 frameshift, 1 nonsense, and 1 splicing variant) with neurodevelopmental disorders (NDDs), including autism, attention-deficit/hyperactivity disorder, and epilepsy. Of these 15 HECTD1 variants, 10 occurred de novo, 3 had unknown inheritance, and 2 were compound heterozygous. While all individuals in this cohort displayed NDDs, no genotype-phenotype correlation was apparent. Conditional knockout of Hectd1 in the neural lineage in mice resulted in microcephaly, severe hippocampal malformations, and complete agenesis of the corpus callosum, supporting a role for Hectd1 in embryonic brain development. Functional studies of select variants in C. elegans revealed dominant effects, including either change-of-function or loss-of-function/haploinsufficient mechanisms, which may explain phenotypic heterogeneity. Significant enrichment of de novo variants in HECTD1 was also shown in an independent cohort of 53,305 published trios with NDDs or congenital heart disease. Thus, our clinical and functional data support a critical requirement of HECTD1 for human brain development.
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 | 0.000 | 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 | 0.001 | 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) | 0.003 | 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".