Copy number variant analysis by exome sequencing is an effective approach to optimize diagnostic yield for developmental disorders-the DDD-Africa study.
TL;DR
The addition of CNV analysis to the ES analysis pipeline resulted in an 8.1% increase in diagnostic yield in the DDD-Africa cohort without additional laboratory cost, 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.
Abstract
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.