Prospective, phenotype-driven selection of critically ill neonates for rapid exome sequencing is associated with high diagnostic yield

To investigate the impact of rapid-turnaround exome sequencing in critically ill neonates using phenotype-based subject selection criteria. Intensive care unit babies aged <6 months with hypotonia, seizures, a complex metabolic phenotype, and/or multiple congenital malformations were prospectivel...

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Published inGenetics in medicine Vol. 22; no. 4; pp. 736 - 744
Main Authors Gubbels, Cynthia S., VanNoy, Grace E., Madden, Jill A., Copenheaver, Deborah, Yang, Sandra, Wojcik, Monica H., Gold, Nina B., Genetti, Casie A., Stoler, Joan, Parad, Richard B., Roumiantsev, Sergei, Bodamer, Olaf, Beggs, Alan H., Juusola, Jane, Agrawal, Pankaj B., Yu, Timothy W.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.04.2020
Elsevier Limited
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Summary:To investigate the impact of rapid-turnaround exome sequencing in critically ill neonates using phenotype-based subject selection criteria. Intensive care unit babies aged <6 months with hypotonia, seizures, a complex metabolic phenotype, and/or multiple congenital malformations were prospectively enrolled for rapid (<7 day) trio-based exome sequencing. Genomic variants relevant to the presenting phenotype were returned to the medical team. A genetic diagnosis was attained in 29 of 50 (58%) sequenced cases. Twenty-seven (54%) patients received a molecular diagnosis involving known disease genes; two additional cases (4%) were solved with pathogenic variants found in novel disease genes. In 24 of the solved cases, diagnosis had impact on patient management and/or family members. Management changes included shift to palliative care, medication changes, involvement of additional specialties, and the consideration of new experimental therapies. Phenotype-based patient selection is effective at identifying critically ill neonates with a high likelihood of receiving a molecular diagnosis via rapid-turnaround exome sequencing, leading to faster and more accurate diagnoses, reducing unnecessary testing and procedures, and informing medical care.
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These authors contributed equally: Grace E. VanNoy, Jill A. Madden
These authors contributed equally: Pankaj B. Agrawal, Timothy W. Yu
ISSN:1098-3600
1530-0366
DOI:10.1038/s41436-019-0708-6