Copy Number Variant Detection by Exome/Genome Sequencing Versus Chromosomal Microarray: A Comparative Study of Over 9,000 Clinical Cases.

Comparison of copy number variant detection by exome/genome sequencing and by chromosomal microarray, with review of discordant results, in a clinical cohort of over 9,000 individuals

Copy number variants (CNVs) are implicated in many health conditions, and chromosomal microarray (CMA) has traditionally been the first-tier test for detecting them, whereas exome and genome sequencing (ES/GS) identify them alongside other variant types. The authors compared CNV calls from CMA and ES/GS in a diverse cohort of over 9,000 individuals tested in a high-throughput clinical laboratory, evaluating concordance between platforms and reviewing discordant findings to determine their nature and causes. ES/GS showed more than 99% concordance with CMA; CMA results not detected on ES/GS were typically CNVs of fewer than three exons, CNVs outside regions of interest, or low-level mosaicism. Conversely, 0.68% of cases had a CNV reported by ES/GS only, usually below the CMA detection limit, whereas CMA added at most 1% of further CNV detections after ES/GS. When non-CNV findings are considered, the added yield of ES/GS exceeds 41%, and the authors conclude that ES/GS matched or exceeded CMA performance for CNV detection, which supports its adoption as a first-tier test.

Synthesis written by Geno'X. For the full original abstract, please refer to the source publication.

The figure that matters is not the concordance above 99% but the nature of the discordances: CNVs of fewer than three exons, CNVs outside regions of interest and low-level mosaicism define precisely what CMA still contributes, at most 1% after ES/GS. The case for ES/GS as a first-line test is solid for CNV detection, but it depends on the pipeline and on the definition of regions of interest of a single high-throughput laboratory, and is not transferable to any analysis chain. As for the gain above 41% attributed to non-CNV variants, it reflects the breadth of the test rather than its CNV performance and should not be read as an advantage for CNV detection.

Analysis by Dr Thibaut Benquey