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

Lara Maleyeff¹, Jane W Newburger^{2

3}, David Wypij^{1

2

3}, Nina H Thomas^{4

5}, Evdokia Anagnoustou⁶, Martina Brueckner^{7

8}, Wendy K Chung^{9

10}, John Cleveland^{11

12}, Sean Cunningham¹³, Bruce D Gelb¹⁴, Elizabeth Goldmuntz¹⁵, Donald J Hagler Jr^{16

17}, Hao Huang¹⁸, Eileen King^{19

20}, Patrick McQuillen^{21

22}, Thomas A Miller^{23

24}, Ami Norris-Brilliant²⁵, George A Porter Jr²⁶, Amy E Roberts^{2

3

27}, P Ellen Grant^{2

28

29

30}, Kiho Im^#^{2

28

29}, Sarah U Morton^#^{2

28

29}

Affiliations

¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
² Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
³ Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA.
⁴ Department of Child and Adolescent Psychiatry and Behavioral Sciences and Center for Human Phenomic Science, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁵ Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁶ Department of Pediatrics, Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, Ontario, Canada.
⁷ Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.
⁸ Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA.
⁹ Department of Pediatrics, Columbia University Medical Center, New York, New York, USA.
¹⁰ Department of Medicine, Columbia University Medical Center, New York, New York, USA.
¹¹ Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
¹² Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
¹³ Division of General Pediatrics, Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA.
¹⁴ Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
¹⁵ Division of Cardiology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁶ Center for Multimodal Imaging and Genetics, University of California San Diego, San Diego, California, USA.
¹⁷ Department of Radiology, School of Medicine, University of California San Diego, San Diego, California, USA.
¹⁸ Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁹ Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio, USA.
²⁰ Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
²¹ Department of Pediatrics, University of California, San Francisco, California, USA.
²² Department of Neurology, University of California, San Francisco, California, USA.
²³ Department of Pediatrics, Primary Children's Hospital, University of Utah, Salt Lake City, Utah, USA.
²⁴ Division of Pediatric Cardiology, Maine Medical Center, Portland, Maine, USA.
²⁵ Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
²⁶ Department of Pediatrics, University of Rochester Medical Center, Rochester, New York, USA.
²⁷ Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁸ Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁹ Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA.
³⁰ Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA.

^# Contributed equally.

PMID: 38009418
PMCID: PMC10863927
DOI: 10.1002/acn3.51950

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

Lara Maleyeff et al. Ann Clin Transl Neurol. 2024 Feb.

. 2024 Feb;11(2):278-290.

doi: 10.1002/acn3.51950. Epub 2023 Nov 27.

Authors

Affiliations

¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
² Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
³ Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA.
⁴ Department of Child and Adolescent Psychiatry and Behavioral Sciences and Center for Human Phenomic Science, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁵ Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁶ Department of Pediatrics, Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, Ontario, Canada.
⁷ Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.
⁸ Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA.
⁹ Department of Pediatrics, Columbia University Medical Center, New York, New York, USA.
¹⁰ Department of Medicine, Columbia University Medical Center, New York, New York, USA.
¹¹ Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
¹² Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
¹³ Division of General Pediatrics, Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA.
¹⁴ Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
¹⁵ Division of Cardiology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁶ Center for Multimodal Imaging and Genetics, University of California San Diego, San Diego, California, USA.
¹⁷ Department of Radiology, School of Medicine, University of California San Diego, San Diego, California, USA.
¹⁸ Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁹ Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio, USA.
²⁰ Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
²¹ Department of Pediatrics, University of California, San Francisco, California, USA.
²² Department of Neurology, University of California, San Francisco, California, USA.
²³ Department of Pediatrics, Primary Children's Hospital, University of Utah, Salt Lake City, Utah, USA.
²⁴ Division of Pediatric Cardiology, Maine Medical Center, Portland, Maine, USA.
²⁵ Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
²⁶ Department of Pediatrics, University of Rochester Medical Center, Rochester, New York, USA.
²⁷ Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁸ Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁹ Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA.
³⁰ Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA.

^# Contributed equally.

PMID: 38009418
PMCID: PMC10863927
DOI: 10.1002/acn3.51950

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.

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Conflict of interest statement

The authors have no relevant commercial activities to report.

Figures

**Figure 1**
Pearson correlation coefficient matrix between all sulcal similarity measures.

**Figure 2**
Regression trees predicting category switching accuracy with various candidate predictors. Tree (A) (n = 97, R ² = 0.12, RMSE = 3.08, cross‐validation RMSE = 3.12) considers only patient demographic characteristics and genetic variants while Tree (B) (n = 92, R ² = 0.30, RMSE = 2.76, cross‐validation RMSE = 3.12) additionally considers all sulcal measures. Each node indicates the mean category switching accuracy (top number) and sample size (bottom number) for participants with the characteristics along the paths above the node. For example, in tree A, 7 individuals aged <25 with an NDD LoF variant had the lowest mean score of 8.6 and 13 individuals aged >25 had the highest mean score of 13.2. LoF, loss‐of‐function; NDD, neurodevelopmental disability; RMSE, root mean squared error.

See this image and copyright information in PMC

References

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

Affiliations

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

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical