A familial modeling framework for advancing precision medicine in neuropsychiatric disorders: A study in children with RASopathies

Objective: Despite the significant and growing burden of childhood psychiatric disorders, treatment is hindered by lack of evidence-based precision approaches. We utilized parent cognitive and behavioral traits in a predictive framework to provide a more individualized estimate of expected child neuropsychiatric and neuroanatomical outcomes relative to traditional case-control studies. We examined children with Noonan Syndrome, a neurogenetic syndrome affecting the Ras/mitogen-activated protein kinase (Ras/MAPK), as a model for developing precision medicine approaches in childhood neuropsychiatric disorders. Methods: Participants included 53 families of children with Noonan syndrome (age 4-12.9 years, mean = 8.48, SD = 2.12, 34 female). This cross-sectional study utilized univariate regression to examine the association between non carrier parent traits (cognition and behavior) and corresponding child traits. We also used multivariate machine learning to examine the correspondence between parent cognition and child multivariate neuroanatomical outcomes. Main outcome measures included child and parent cognition, anxiety, depression, attention-deficit hyperactivity (ADHD) and somatic symptoms. We also included child neuroanatomy measured via structural MRI. Results: Parent cognition (especially visuospatial/motor abilities), depression, anxiety and ADHD symptoms were significantly associated with child outcomes in these domains. Parent cognition was also significantly associated with child neuroanatomical variability. Several temporal, parietal and subcortical regions that were weighted most strongly in the multivariate model were previously identified as morphologically different when children with NS were compared to typically developing children. In contrast, temporal regions, and the amygdala, which were also weighted strongly in the model, were not identified in previous work but were correlated with parent cognition in post-hoc analysis suggesting a larger familial effect on these regions. Conclusions: Utilizing parent traits in a predictive framework affords control for familial factors and thus 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 Ras/MAPK's impact on neurodevelopmental outcomes. Further refinement of predictive modeling to estimate individualized child outcomes will advance a precision medicine approach to treating NS, other neurogenetic syndromes, and neuropsychiatric disorders more broadly. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the National Institute of Child Health and Human Development (#HD090209 K23 and #HD108684 R01). Tamar Green was also supported by the Stephen Bechtel Endowed Faculty Scholar in Pediatric Translational Medicine, Stanford Maternal & Child Health Research Institute and by funding from the Neurofibromatosis Therapeutic Acceleration Program (NTAP) at the Johns Hopkins University School of Medicine. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of The Johns Hopkins University School of Medicine. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Research was approved by the Stanford University Institutional Review Board. Written, informed consent was obtained from a legal guardian for all participants. All participants over 7 years provided assent. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The final dataset will be stripped of all identifiers and made available to qualified investigators upon request.