Neonatal social communication and single genes predict the variability of post-pubertal social behavior in a mouse model of paternal 15q11-13 duplication

ABSTRACT Mental illnesses associated with high-risk copy number variations (CNVs) are characterized by incomplete penetrance and variable severity, with their underlying mechanisms remaining inadequately understood. We hypothesized that such phenotypic variability is evident from the neonatal stage and is, at least in part, attributable to individual differences in the expression levels of CNV-encoded genes in the brain. We conducted an analysis of the quantitative and functional structure of neonatal social communication, assessed post-pubertal social interaction, and evaluated the brain expression levels of genes within the same cohort of a mouse model of paternal human 15q11-13 duplication, a high-risk factor variably associated with neurodevelopmental disorders. Subsequently, computational methods were utilized to identify predictive variables for the variability of post-pubertal social interaction. Mice harboring the 15q11-13 duplication exhibited distinctive call sequences characterized by diverse connections, which lacked the incentive value necessary for effective social communication with mother mice. The neonatal call sequences and the expression levels of Magel2, along with, to a lesser extent, Herc2 and Ndn, in the prefrontal cortex of the 15q11-13 duplication model were predictive of post-pubertal social interaction. Our findings demonstrate that variability in post-pubertal social interaction—a dimensional characteristic of neurodevelopmental disorders—can be predicted by the variability of neonatal social communication and is influenced by the expression levels of specific CNV-encoded genes in the prefrontal cortex. This computational approach has the potential to predict the developmental trajectories of various dimensions of mental illness among CNV carriers in humans and to identify CNV-encoded driver genes in preclinical models, thereby providing potential mechanistic bases for the development of gene-based therapeutic strategies. Competing Interest Statement The authors have declared no competing interest.