A Multicenter Analysis of Abnormal Chromosomal Microarray Findings in Congenital Heart Disease

• Type of Material: Article
• Authors: Benjamin J Landis, Indiana University; Lindsey R Helvaty, Indiana University; Gabrielle C Geddes, Indiana University; Jiuann‐Huey Ivy Lin, University of Pittsburgh; Svetlana A Yatsenko, University of Pittsburgh; Cecilia W Lo, University of Pittsburgh; William L Border, Emory University; Stephanie Burns Wechsler, Emory University; Chaya N Murali, Baylor College of Medicine; Mahshid S Azamian, Baylor College of Medicine; Seema R Lalani, Baylor College of Medicine; Robert B Hinton, Cincinnati Children’s Hospital Medical Center; Vidu Garg, Ohio State University; Kim L McBride, Ohio State University; Jennelle C Hodge, Indiana University; Stephanie M Ware, Indiana University
• Language: English
• Date: 2023-09-08
• Publisher: Wiley
• Publication Version: Final Published Version
• Copyright Statement: © 2023 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
• License: Creative Commons Attribution-NonCommercial 4.0 International
• Final Published Version (URL): https://doi.org/10.1161/JAHA.123.029340
• Title of Journal or Parent Work: Journal of the American Heart Association
• Volume: 12
• Issue: 18
• Start Page: e029340
• Grant/Funding Information: This work was supported by the American Heart Association Transformational Award AHA 19TPA34850054 (SMW); and National Institutes of Health K23 award HL141667 (BJL).
• Keywords: neurodevelopment; conotruncal defects; genetics; chromosomal microarray; congenital heart disease; genomics
• Research Categories: Biology, Neuroscience; Biology, Genetics; Health Sciences, Medicine and Surgery

Abstract

Background Chromosomal microarray analysis (CMA) provides an opportunity to understand genetic causes of congenital heart disease (CHD). The methods for describing cardiac phenotypes in patients with CMA abnormalities have been inconsistent, which may complicate clinical interpretation of abnormal testing results and hinder a more complete understanding of genotype–phenotype relationships. Methods and Results Patients with CHD and abnormal clinical CMA were accrued from 9 pediatric cardiac centers. Highly detailed cardiac phenotypes were systematically classified and analyzed for their association with CMA abnormality. Hierarchical classification of each patient into 1 CHD category facilitated broad analyses. Inclusive classification allowing multiple CHD types per patient provided sensitive descriptions. In 1363 registry patients, 28% had genomic disorders with well‐recognized CHD association, 67% had clinically reported copy number variants (CNVs) with rare or no prior CHD association, and 5% had regions of homozygosity without CNV. Hierarchical classification identified expected CHD categories in genomic disorders, as well as uncharacteristic CHDs. Inclusive phenotyping provided sensitive descriptions of patients with multiple CHD types, which occurred commonly. Among CNVs with rare or no prior CHD association, submicroscopic CNVs were enriched for more complex types of CHD compared with large CNVs. The submicroscopic CNVs that contained a curated CHD gene were enriched for left ventricular obstruction or septal defects, whereas CNVs containing a single gene were enriched for conotruncal defects. Neuronal‐related pathways were over‐represented in single‐gene CNVs, including top candidate causative genes NRXN3, ADCY2, and HCN1. Conclusions Intensive cardiac phenotyping in multisite registry data identifies genotype–phenotype associations in CHD patients with abnormal CMA.