ArticleAnnals of laboratory medicine2026
High-resolution Chromosomal Microarray with Diagnostic Potential for Detecting Exon-level Copy Number Variations Using Targeted and Non-targeted Approaches.
Article in Annals of laboratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Protein S Levels to Guide Exon-Level Copy Number Variant Analysis ofAnnals of laboratory medicine · 2026Article
- Lipid metabolism, neuroinflammation, and oxidative stress in Alzheimer disease: an integrated mechanistic review.Acta neurologica Belgica · 2026Review
- Toward Comprehensive Clinical Genomics: Integrating Exon-Level Analysis for Detecting Monogenic Copy Number Variations.Annals of laboratory medicine · 2026Article
- The Application Value of Chromosome Microarray Analysis in Prenatal Diagnosis of Clinically Relevant Copy Number Variations in Fetuses.International journal of women's health · 2026Article
- Klinefelter Syndrome Identified by Next-generation Sequencing as a Risk Factor for Venous Thromboembolism: A Single-institution Study.Annals of laboratory medicine · 2026Article
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Authors and funding
10 authors.
Funding
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Abstract
Background: Copy number variations (CNVs) play an important role in human genetic disorders. Detection of exon-level CNVs is crucial for accurate clinical diagnosis. The CytoScan XON Array, a high-resolution microarray, was recently developed to detect exonic CNVs of various genes. Methods: We evaluated the clinical performance of the CytoScan XON Array using 59 patient samples with previously identified CNVs, confirmed via methods including multiple ligation-dependent probe amplification (MLPA), gene-dose PCR, and mRNA assay. Concordance between CytoScan XON and orthogonal methods was evaluated in target regions, and diagnostic utility was compared with that of genome sequencing (GS)-based CNV calling tools through analysis of false-positive CNVs in non-target genomic regions. Results: For target regions, the CytoScan XON Array achieved concordance rates of 89.8% and 92.5% at the exon and gene levels, respectively, for all CNV calls. Concordance was higher for multi-exon CNVs (100%) than that for single-exon CNVs (82.6%, Conclusions: The CytoScan XON Array, a reliable tool for detecting exon-level CNVs in target regions, can serve as a complementary approach to GS-based CNV calling tools for genome-wide CNV screening with high resolution. However, its performance for single-exon CNVs requires further optimization. Cross-validation with GS-based CNV calling tools is recommended to improve diagnostic accuracy.
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