Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure
Document Type
Article
Publication Date
7-4-2024
Institution/Department
Pediatrics
Journal Title
NeuroImage
Abstract
Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.
First Page
120721
Recommended Citation
Vandewouw MM, Norris-Brilliant A, Rahman A, et al. Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure. Neuroimage. Published online July 4, 2024. doi:10.1016/j.neuroimage.2024.120721