Identification of a novel synaptic protein, TMTC3, involved in periventricular nodular heterotopia with intellectual disability and epilepsy
Bibliographic record
Abstract
Defects in neuronal migration cause brain malformations, which are associated with intellectual disability (ID) and epilepsy. Using exome sequencing, we identified compound heterozygous variants (p.Arg71His and p. Leu729ThrfsTer6) in TMTC3, encoding transmembrane and tetratricopeptide repeat containing 3, in four siblings with nocturnal seizures and ID. Three of the four siblings have periventricular nodular heterotopia (PVNH), a common brain malformation caused by failure of neurons to migrate from the ventricular zone to the cortex. Expression analysis using patient-derived cells confirmed reduced TMTC3 transcript levels and loss of the TMTC3 protein compared to parental and control cells. As TMTC3 function is currently unexplored in the brain, we gathered support for a neurobiological role for TMTC3 by generating flies with post-mitotic neuron-specific knockdown of the highly conserved Drosophila melanogaster TMTC3 ortholog, CG4050/tmtc3. Neuron-specific knockdown of tmtc3 in flies resulted in increased susceptibility to induced seizures. Importantly, this phenotype was rescued by neuron-specific expression of human TMTC3, suggesting a role for TMTC3 in seizure biology. In addition, we observed co-localization of TMTC3 in the rat brain with vesicular GABA transporter (VGAT), a presynaptic marker for inhibitory synapses. TMTC3 is localized at VGAT positive pre-synaptic terminals and boutons in the rat hypothalamus and piriform cortex, suggesting a role for TMTC3 in the regulation of GABAergic inhibitory synapses. TMTC3 did not co-localize with Vglut2, a presynaptic marker for excitatory neurons. Our data identified TMTC3 as a synaptic protein that is involved in PVNH with ID and epilepsy, in addition to its previously described association with cobblestone lissencephaly.
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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 | 0.001 | 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".