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Detection of copy number variants associated with late-onset conditions in ~16 200 pregnancies: parameters for disclosure and pregnancy outcome

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Background Copy number variants (CNVs) associated with late-onset medical conditions are rare but important secondary findings in chromosomal microarray analysis (CMA) performed during pregnancy. Here, we critically review the cases… Click to show full abstract

Background Copy number variants (CNVs) associated with late-onset medical conditions are rare but important secondary findings in chromosomal microarray analysis (CMA) performed during pregnancy. Here, we critically review the cases at two tertiary centres to assess the criteria which guide the disclosure of such findings and develop a disclosure decision tool (DDT) aimed at facilitating disclosure decision. Parental decisions on receiving CNVs associated with risks for late-onset conditions were also recorded. Methods Prenatal CMAs in Hadassah and Shaare Zedek Medical Centers from November 2013 to October 2021 were reviewed for CNVs associated with late-onset conditions. The DDT proposed uses a five-parameter scoring system, which considers the severity, median age of onset, penetrance, understanding of genotype-phenotype correlation and actionability of the finding. Results Out of 16 238 prenatal CMAs, 16 (0.1%) harboured CNVs associated with late-onset conditions, 15 of which were disclosed. Outcome information was available on 13 of the 16 pregnancies, all of which continued to delivery. Conclusions Our suggested DDT will help clinicians to quantitatively weigh the variables associated with CNVs of this type and arrive at a well thought out clinical decision regarding disclosure. Although the prevalence of late-onset conditions as a major finding in the prenatal setup is low, it is expected to rise with the increasing use of non-invasive CMA testing and whole exome and genome sequencing.

Keywords: onset conditions; onset; number variants; copy number; late onset; associated late

Journal Title: Journal of Medical Genetics
Year Published: 2022

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