PTCHD1: Identification and Neurodevelopmental Contributions of an Autism Spectrum Disorder and Intellectual Disability Susceptibility Gene
Bibliographic record
Abstract
Over the last one and a half decades, copy number variation and whole-genome sequencing studies have illuminated the considerable genetic heterogeneity that underlies the etiologies of autism spectrum disorder (ASD) and intellectual disability (ID). These investigations support the idea that ASD may result from complex interactions between susceptibility-related genetic variants (single nucleotide variants or copy number variants) and the environment. This review outlines the identification and neurobiological characterization of two such genes located in Xp22.11, Patched domain-containing 1 (PTCHD1), and its antisense lncRNA PTCHD1-AS. Animal models of Ptchd1 disruption have recapitulated a subset of clinical symptoms related to ASD as well as to ID. Furthermore, these Ptchd1 mouse knockout studies implicate the expression of Ptchd1 in both the thalamic and the hippocampal brain regions as being crucial for proper neurodevelopment and cognitive function. Altered kynurenine metabolic signalling has been postulated as a disease mechanism in one of these animal studies. Additionally, ASD patient-derived induced pluripotent stem cells (iPSCs) carrying a copy number loss impacting the antisense non-coding RNA PTCHD1-AS have been used to generate 2D neuronal cultures. While copy number loss of PTCHD1-AS does not affect the transcription of PTCHD1, the neurons exhibit diminished miniature excitatory postsynaptic current frequency, supporting its role in ASD etiology. A more thorough understanding of risk factor genes, such as PTCHD1 and PTCHD1-AS, will help to clarify the intricate genetic and biological mechanisms that underlie ASD and ID, providing a foundation for meaningful therapeutic interventions to enhance the quality of life of individuals who experience these conditions.
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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 | 0.000 | 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) | 0.001 | 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".