Summary We have created a mouse genetic model that mimics a human mutation of Shank3 that deletes the C-terminus and is associated with autism. Expressed as a single copy [Shank3(+/ΔC) mice], Shank3ΔC protein interacts with the WT gene product and results in >90 % reduction of Shank3 at synapses. This “gain of function” phenotype is linked to increased polyubiquitination of WT Shank3 and its redistribution into proteasomes. Similarly, the NR1 subunit of the NMDA receptor is reduced at synapses with increased polyubiquitination. Assays of post-synaptic density proteins, spine morphology and synapse number are unchanged in Shank3(+/ΔC) mice, but the amplitude of NMDAR responses is reduced together with reduced NMDAR-dependent LTP and LTD. Reciprocally, mGluR-dependent LTD is markedly enhanced. Shank3(+/ΔC) mice show behavioral deficits suggestive of autism and reduced NMDA receptor function. These studies reveal a mechanism distinct from haploinsufficiency by which mutations of Shank3 can evoke an autism-like disorder.

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The genetic and phenotypic heterogeneity of autism spectrum disorders (ASD) presents a substantial challenge for diagnosis, classification, research, and treatment. Investigations into the underlying molecular etiology of ASD have often yielded mixed and at times opposing findings. Defining the molecular and biochemical underpinnings of heterogeneity in ASD is crucial to our understanding of the pathophysiological development of the disorder, and has the potential to assist in diagnosis and the rational design of clinical trials. In this review, we propose that genetically diverse forms of ASD may be usefully parsed into entities resulting from converse patterns of growth regulation at the molecular level, which lead to the correlates of general synaptic and neural overgrowth or undergrowth. Abnormal brain growth during development is a characteristic feature that has been observed both in children with autism and in mouse models of autism. We review evidence from syndromic and non-syndromic ASD to suggest that entities currently classified as autism may fundamentally differ by underlying pro- or anti-growth abnormalities in key biochemical pathways, giving rise to either excessive or reduced synaptic connectivity in affected brain regions. We posit that this classification strategy has the potential not only to aid research efforts, but also to ultimately facilitate early diagnosis and direct appropriate therapeutic interventions.