Skip to main navigation Skip to search Skip to main content

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure

  • Marlee M. Vandewouw
  • , Ami Norris-Brilliant
  • , Anum Rahman
  • , Stephania Assimopoulos
  • , Sarah U. Morton
  • , Azadeh Kushki
  • , Sean Cunningham
  • , Eileen King
  • , Elizabeth Goldmuntz
  • , Thomas A. Miller
  • , Nina H. Thomas
  • , Heather R. Adams
  • , John Cleveland
  • , James F. Cnota
  • , P. Ellen Grant
  • , Caren S. Goldberg
  • , Hao Huang
  • , Jennifer S. Li
  • , Patrick McQuillen
  • , George A. Porter
  • Amy E. Roberts, Mark W. Russell, Christine E. Seidman, Madalina E. Tivarus, Wendy K. Chung, Donald J. Hagler, Jane W. Newburger, Ashok Panigrahy, Jason P. Lerch, Bruce D. Gelb, Evdokia Anagnostou

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish
Article number120721
JournalNeuroImage
Volume297
DOIs
StatePublished - 15 Aug 2024

Keywords

  • Brain structure
  • Congenital heart disease
  • Genetics
  • Neurodevelopmental outcomes
  • Unsupervised methods

Fingerprint

Dive into the research topics of 'Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure'. Together they form a unique fingerprint.

Cite this