A familial modeling framework for advancing precision medicine for children with neuropsychiatric disorders.

Abstract

Aim: To provide individualized estimates of expected child neuropsychiatric and neuroanatomical outcomes by using parent cognitive and behavioral traits in a predictive framework.

Method: Predictive modeling was applied to 52 families of children with Noonan syndrome, a neurogenetic syndrome affecting the Ras/mitogen-activated protein kinase (MAPK) pathway.

Results: Parent cognition (specifically visuospatial and motor abilities), depression, anxiety, and attention-deficit/hyperactivity disorder symptoms were significantly associated with child outcomes in these domains. Parent cognition was also significantly associated with child neuroanatomical variability. The middle temporal cortex was weighted strongly in the model predicting child neuroanatomy and not identified in previous work, but was correlated with parent cognition, suggesting a larger familial effect in this region.

Interpretation: Using parent traits provides a more individualized estimate of expected child cognitive, behavioral, and neuroanatomical outcomes. Understanding how parent traits influence neuroanatomical outcomes helps to further a mechanistic understanding of the impact of Ras/MAPK on neurodevelopmental outcomes. Further refinement of predictive modeling to estimate individualized child outcomes will advance a precision medicine approach to treating Noonan syndrome, other neurogenetic syndromes, and neuropsychiatric disorders more broadly.