Biallelic mutations in the death domain of PIDD1 impair caspase-2 activation and are associated with intellectual disability
Bibliographic record
Abstract
Abstract PIDD1 encodes p53-Induced Death Domain protein 1, which acts as a sensor surveilling centrosome numbers and p53 activity in mammalian cells. Early results also suggest a role in DNA damage response where PIDD1 may act as a cell-fate switch, through interaction with RIP1 and NEMO/IKKg, activating NF-κB signaling for survival, or as an apoptosis-inducing protein by activating caspase-2. Biallelic truncating mutations in CRADD—the protein bridging PIDD1 and caspase-2—have been reported in intellectual disability (ID), and in a form of lissencephaly. Here, we identified five families with ID from Iran, Pakistan, and India, with four different biallelic mutations in PIDD1 , all disrupting the Death Domain (DD), through which PIDD1 interacts with CRADD or RIP1. Nonsense mutations Gln863* and Arg637* directly disrupt the DD, as does a missense mutation, Arg815Trp. A homozygous splice mutation in the fifth family is predicted to disrupt splicing upstream of the DD, as confirmed using an exon trap. In HEK293 cells, we show that both Gln863* and Arg815Trp mutants fail to co-localize with CRADD, leading to its aggregation and mis-localization, and fail to co-precipitate CRADD. Using genome-edited cell lines, we show that these three PIDD1 mutations all cause loss of PIDDosome function. Pidd1 null mice show decreased anxiety, but no motor abnormalities. Together this indicates that PIDD1 mutations in humans may cause ID (and possibly lissencephaly) either through gain of function or secondarily, due to altered scaffolding properties, while complete loss of PIDD1, as modeled in mice, may be well tolerated or is compensated for.
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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) | 0.001 | 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".