P.135 Autism-associated mutations in SHANK2 increase synaptic connectivity and dendrite complexity in human neurons
Bibliographic record
Abstract
Background: Heterozygous loss-of-function mutations in the synaptic scaffolding gene SHANK2 are strongly associated with autism spectrum disorder (ASD). However, their impact on the function of human neurons is unknown. Derivation of induced pluripotent stem cells (iPSC) from affected individuals permits generation of live neurons to answer this question. Methods: We generated iPSCs by reprogramming dermal fibroblasts of neurotypic and ASD-affected donors. To isolate the effect of SHANK2, we used CRISPR/Cas9 to knock out SHANK2 in control iPSCs and correct a heterozygous nonsense mutation in ASD-affected donor iPSCs. We then derived cortical neurons from SOX1+ neural precursor cells differentiated from these iPSCs. Using a novel assay that overcomes line-to-line variability, we compared neuronal morphology, total synapse number, and electrophysiological properties between SHANK2 mutants and controls. Results: Relative to controls, SHANK2 mutant neurons have increased dendrite complexity, dendrite length, total synapse number (1.5-2-fold), and spontaneous excitatory postsynaptic current (sEPSC) frequency (3-7.6-fold). Conclusions: ASD-associated heterozygous loss-of-function mutations in SHANK2 increase synaptic connectivity among human neurons by increasing synapse number and sEPSC frequency. This is partially supported by increased dendrite length and complexity, providing evidence that SHANK2 functions as a suppressor of dendrite branching during neurodevelopment.
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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) | 0.008 | 0.001 |
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".