Association of genetic and sulcal traits with executive function in congenital heart disease

Lara Maleyeff, Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Jane W. Newburger, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
David Wypij, Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Nina H. Thomas, Department of Child and Adolescent Psychiatry and Behavioral Sciences and Center for Human Phenomic Science, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Evdokia Anagnoustou, Department of Pediatrics, Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, Ontario, Canada.
Martina Brueckner, Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.
Wendy K. Chung, Department of Pediatrics, Columbia University Medical Center, New York, New York, USA.
John Cleveland, Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Sean Cunningham, Division of General Pediatrics, Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA.
Bruce D. Gelb, Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Elizabeth Goldmuntz, Division of Cardiology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Donald J. Hagler, Center for Multimodal Imaging and Genetics, University of California San Diego, San Diego, California, USA.
Hao Huang, Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Eileen King, Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio, USA.
Patrick McQuillen, Department of Pediatrics, University of California, San Francisco, California, USA.
Thomas A. Miller, Department of Pediatrics, Primary Children's Hospital, University of Utah, Salt Lake City, Utah, USA.
Ami Norris-Brilliant, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
George A. Porter, Department of Pediatrics, University of Rochester Medical Center, Rochester, New York, USA.
Amy E. Roberts, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
P Ellen Grant, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
Kiho Im, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
Sarah U. Morton, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.

Abstract

OBJECTIVE: Persons with congenital heart disease (CHD) are at increased risk of neurodevelopmental disabilities, including impairments to executive function. Sulcal pattern features correlate with executive function in adolescents with single-ventricle heart disease and tetralogy of Fallot. However, the interaction of sulcal pattern features with genetic and participant factors in predicting executive dysfunction is unknown. METHODS: We studied sulcal pattern features, participant factors, and genetic risk for executive function impairment in a cohort with multiple CHD types using stepwise linear regression and machine learning. RESULTS: Genetic factors, including predicted damaging de novo or rare inherited variants in neurodevelopmental disabilities risk genes, apolipoprotein E genotype, and principal components of sulcal pattern features were associated with executive function measures after adjusting for age at testing, sex, mother's education, and biventricular versus single-ventricle CHD in a linear regression model. Using regression trees and bootstrap validation, younger participant age and larger alterations in sulcal pattern features were consistently identified as important predictors of decreased cognitive flexibility with left hemisphere graph topology often selected as the most important predictor. Inclusion of both sulcal pattern and genetic factors improved model fit compared to either alone. INTERPRETATION: We conclude that sulcal measures remain important predictors of cognitive flexibility, and the model predicting executive outcomes is improved by inclusion of potential genetic sources of neurodevelopmental risk. If confirmed, measures of sulcal patterning may serve as early imaging biomarkers to identify those at heightened risk for future neurodevelopmental disabilities.