Human Craniosynostosis Atlas (HuCA) : Standardizing & Establishing a Public Repository for Genomic and Imaging data

R21: Human Craniosynostosis Atlas (HuCA) : Standardizing & Establishing a Public Repository for Genomic and Imaging data. Project Abstract: Craniosynostosis is a premature fusion of the cranial sutures which affects approximately 1 in 2000 babies each year. Left untreated, significant skeletal, respiratory, ocular, and neurocognitive abnormalities can result.

Surgical treatment is usually offered in the first year of life to mitigate these consequences. There is a wide genotypic and phenotypic presentation and to date there is insufficient characterization of the disease in children, and its effects on the brain. The Human Craniosynostosis Atlas (HuCA) as put forth in this proposal

seeks to remedy this gap in knowledge by creating community resource with standards for data acquisition, which will allow for a diverse array of sites to gather CT, multi-contrast MRI, and genomic data in individual patients, which can be analyzed in concert. We ultimately seek to improve the characterization &

understanding of all types of craniosynostosis through systematic neuroimaging and genotyping shared with the scientific community through the existing NIH-NIDCR biorepository, FaceBase 3. We propose to create the first publicly accessible repository of comprehensive human data for the purpose of broadly, yet deeply

characterizing all types of craniosynostosis. Specific Aim 1 will focus on neuroimaging and establish low dose head CT protocols to verify diagnosis and allow head shape analysis. Brain structure and function will be assayed with MRI based on the Healthy Brain and Child Development (HBCD) protocol for developing brains

and will be extended to the craniosynostosis population. Sequences will include anatomical imaging (T1, T2), functional (resting state fMRI), and microstructural (multi-shell HARDI) imaging. Specific Aim 2 will focus on a genomic characterization of the affected child and biological parents ( a trio) using a standard protocol of

acquisition from subjects’ cheek swab to whole genome sequencing (WGS) with standard coverage, (99%) & depth (30x). Output will be standardized file formats to include VCF, FASTQ and BAM files and transferred to FaceBase for preliminary variant analysis. Aim 3 will focus on HIPPA compliant data transfer to Facebase of

neuroimaging and genomic information data of babies with all types of infants with craniosynostosis. It will also codify and publicize the data acquisition protocols and quality standards as a pre-requisite for contribution to HuCA. A new web landing page for HuCA will be built allowing permitted researchers to access the data in an

intuitive and interactive way, filterable by metadata. The synergy of CT, MRI and genomic data will enable Facebase to house and share an unprecedented complement of multi-dimensional information about craniosynostosis that can improve fundamental knowledge and classification of disease. A clear pathway and

protocol for data contribution and sharing will enable the large- sample size study needed for both conventional and AI/ML/DL analysis. When a clinician is newly faced with a baby with craniosynostosis, they will benefit from a vastly improved understanding of the condition at baseline and thus may be able to better predict and

optimize outcomes given a particular treatment.