Copy number variant analysis improves diagnostic yield in a diverse pediatric exome sequencing cohort

Exome sequencing is the current standard for diagnosing Mendelian disorders; however, it is generally not considered the first-line test for detecting copy number variants (CNVs). We retrospectively investigated the additional diagnostic yield by performing concurrent CNV analysis using exome data in a large and diverse pediatric cohort. Patients were referred from various sources with variable phenotypes. Human Phenotype Ontology terms were used to prioritize variants for analysis. Ancestry and CNV analyses were performed using Somalier and NxClinical, respectively. A total of 1538 patients were tested, with the majority being Admixed Americans. Diagnostic CNVs were identified in 70 patients (4.6%), ranging from exonic deletions to large, unbalanced rearrangements, aneuploidies, and mosaic findings. While no significant differences were identified in diagnostic yield, or rates of negative or uncertain diagnoses, between ancestries, our study demonstrates the feasibility and increased yield of CNV analysis of exome data, across multiple phenotypes, referral sources, and ancestries.

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Publication Details

Journal
npj Genomic Medicine
Published
2025-02-21
DOI
https://doi.org/10.1038/s41525-025-00478-4
Citations
3
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
5.45

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Copy number variant analysis improves diagnostic yield in a diverse pediatric exome sequencing cohort

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npj Genomic Medicine
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Copy number variant analysis improves diagnostic yield in a diverse pediatric exome sequencing cohort

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article en
3 citations

Abstract

Exome sequencing is the current standard for diagnosing Mendelian disorders; however, it is generally not considered the first-line test for detecting copy number variants (CNVs). We retrospectively investigated the additional diagnostic yield by performing concurrent CNV analysis using exome data in a large and diverse pediatric cohort. Patients were referred from various sources with variable phenotypes. Human Phenotype Ontology terms were used to prioritize variants for analysis. Ancestry and CNV analyses were performed using Somalier and NxClinical, respectively. A total of 1538 patients were tested, with the majority being Admixed Americans. Diagnostic CNVs were identified in 70 patients (4.6%), ranging from exonic deletions to large, unbalanced rearrangements, aneuploidies, and mosaic findings. While no significant differences were identified in diagnostic yield, or rates of negative or uncertain diagnoses, between ancestries, our study demonstrates the feasibility and increased yield of CNV analysis of exome data, across multiple phenotypes, referral sources, and ancestries.

npj Genomic MedicineVol. 10(1)
University of Southern California (US), Children's Hospital of Los Angeles (US), University of Toronto (CA), Shenandoah University (US), Medical College of Wisconsin (US), BioNano Genomics (United States) (US), Sinai Health System (CA)
Children's Hospital Los Angeles
Zero hunger
Openalex Percentile: Top 6%
Genomics and Rare Diseases
5.45
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