Browse by author
Lookup NU author(s): Dr Laura Yates
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2026.Copy number variants (CNV) contribute significantly to the pathogenic variation associated with developmental disorders. CNV detection is often not included in standard exome sequencing (ES) analysis. Complementary methods such as chromosomal microarray are typically offered in diagnostic laboratories to diagnose pathogenic CNV. In this study, we aimed to develop an effective approach for incorporating CNV detection within our ES analysis process for the Deciphering Developmental Disorders in Africa (DDD-Africa) cohort. We analyzed ES data from 505 probands with a developmental disorder, applying a CNV detection approach that assessed data generated using the tools CANOES and XHMM. When available, parental ES data was used to assess inheritance patterns. We confirmed a diagnosis in 41/505 (8,1%) patients with 43 pathogenic CNV identified in the probands. There were 31 deletions and 12 duplications. Among the 26 probands with parental data, all identified CNV were de novo. The addition of CNV analysis to our ES analysis pipeline resulted in an 8.1% increase in diagnostic yield in the DDD-Africa cohort without additional laboratory cost. This offers a feasible approach which is likely to reduce analytical cost and is suitable for low- and middle-income countries where funding and resources for genomic medicine initiatives are limited.
Author(s): Louw N, Makay P, Mpangase PT, Shingwenyana B, Goliath Z, Naicker T, Yates LM, Honey E, Mubungu G, Van Den Bogaert K, Firth HV, Hurles ME, Lukusa Tshilobo P, Devriendt K, Krause A, Carstens N, Lumaka A, Lombard Z
Publication type: Article
Publication status: Published
Journal: European Journal of Human Genetics
Year: 2026
Pages: epub ahead of print
Print publication date: 09/07/2026
Online publication date: 09/07/2026
Acceptance date: 26/06/2026
Date deposited: 20/07/2026
ISSN (print): 1018-4813
ISSN (electronic): 1476-5438
Publisher: Springer Nature
URL: https://doi.org/10.1038/s41431-026-02179-7
DOI: 10.1038/s41431-026-02179-7
Data Access Statement: This research generated genomic data (CNV) and clinical data. The CNV will be submitted to ClinVar. In accordance with funder agreements, the complete dataset from the DDD-Africa study, including all phenotypic data, is available on the European Genome-phenome Archive (EGAS00001008319) to ensure public access.
Altmetrics provided by Altmetric
