Genetic variants in <i>DDX53</i> contribute to Autism Spectrum Disorder associated with the Xp22.11 locus
Bibliographic record
Abstract
Summary Autism Spectrum Disorder (ASD) exhibits an ∼4:1 male-to-female sex bias and is characterized by early-onset impairment of social/communication skills, restricted interests, and stereotyped behaviors. Disruption of the Xp22.11 locus has been associated with ASD in males. This locus includes the three-exon PTCHD1 gene, an adjacent multi-isoform long noncoding RNA (lncRNA) named PTCHD1-AS (spanning ∼1Mb), and a poorly characterized single-exon RNA helicase named DDX53 that is intronic to PTCHD1-AS . While the relationship between PTCHD1/PTCHD1-AS and ASD is being studied, the role of DDX53 has not been examined, in part because there is no apparent functional murine orthologue. Through clinical testing, here, we identified 6 males and 1 female with ASD from 6 unrelated families carrying rare, predicted-damaging or loss-of-function variants in DDX53 . Then, we examined databases, including the Autism Speaks MSSNG and Simons Foundation Autism Research Initiative, as well as population controls. We identified 24 additional individuals with ASD harboring rare, damaging DDX53 variations, including the same variants detected in two families from the original clinical analysis. In this extended cohort of 31 participants with ASD (28 male, 3 female), we identified 25 mostly maternally-inherited variations in DDX53 , including 18 missense changes, 2 truncating variants, 2 in-frame variants, 2 deletions in the 3’ UTR and 1 copy number deletion. Our findings in humans support a direct link between DDX53 and ASD, which will be important in clinical genetic testing. These same autism-related findings, coupled with the observation that a functional orthologous gene is not found in mouse, may also influence the design and interpretation of murine-modelling of ASD.
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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 | 0.000 |
| 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) | 0.005 | 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".