Synaptic Dysfunction in Human Neurons With Autism-Associated Deletions in PTCHD1-AS
Bibliographic record
Abstract
BACKGROUND: The Xp22.11 locus that encompasses PTCHD1, DDX53, and the long noncoding RNA PTCHD1-AS is frequently disrupted in male subjects with autism spectrum disorder (ASD), but the functional consequences of these genetic risk factors for ASD are unknown. METHODS: To evaluate the functional consequences of PTCHD1 locus deletions, we generated induced pluripotent stem cells (iPSCs) from unaffected control subjects and 3 subjects with ASD with microdeletions affecting PTCHD1-AS/PTCHD1, PTCHD1-AS/DDX53, or PTCHD1-AS alone. Function of iPSC-derived cortical neurons was assessed using molecular approaches and electrophysiology. We also compiled novel and known genetic variants of the PTCHD1 locus to explore the roles of PTCHD1 and PTCHD1-AS in genetic risk for ASD and other neurodevelopmental disorders. Finally, genome editing was used to explore the functional consequences of deleting a single conserved exon of PTCHD1-AS. RESULTS: iPSC-derived neurons from subjects with ASD exhibited reduced miniature excitatory postsynaptic current frequency and N-methyl-D-aspartate receptor hypofunction. We found that 35 ASD-associated deletions mapping to the PTCHD1 locus disrupted exons of PTCHD1-AS. We also found a novel ASD-associated deletion of PTCHD1-AS exon 3 and showed that exon 3 loss altered PTCHD1-AS splicing without affecting expression of the neighboring PTCHD1 coding gene. Finally, targeted disruption of PTCHD1-AS exon 3 recapitulated diminished miniature excitatory postsynaptic current frequency, supporting a role for the long noncoding RNA in the etiology of ASD. CONCLUSIONS: Our genetic findings provide strong evidence that PTCHD1-AS deletions are risk factors for ASD, and human iPSC-derived neurons implicate these deletions in the neurophysiology of excitatory synapses and in ASD-associated synaptic impairment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".