Meta-analysis and multidisciplinary consensus statement: exome sequencing is a first-tier clinical diagnostic test for individuals with neurodevelopmental disorders

Purpose For neurodevelopmental disorders (NDDs), etiological evaluation can be a diagnostic odyssey involving numerous genetic tests, underscoring the need to develop a streamlined algorithm maximizing molecular diagnostic yield for this clinical indication. Our objective was to compare the yield of...

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Published inGenetics in medicine Vol. 21; no. 11; pp. 2413 - 2421
Main Authors Srivastava, Siddharth, Love-Nichols, Jamie A., Dies, Kira A., Ledbetter, David H., Martin, Christa L., Chung, Wendy K., Firth, Helen V., Frazier, Thomas, Hansen, Robin L., Prock, Lisa, Brunner, Han, Hoang, Ny, Scherer, Stephen W., Sahin, Mustafa, Miller, David T.
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.11.2019
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Summary:Purpose For neurodevelopmental disorders (NDDs), etiological evaluation can be a diagnostic odyssey involving numerous genetic tests, underscoring the need to develop a streamlined algorithm maximizing molecular diagnostic yield for this clinical indication. Our objective was to compare the yield of exome sequencing (ES) with that of chromosomal microarray (CMA), the current first-tier test for NDDs. Methods We performed a PubMed scoping review and meta-analysis investigating the diagnostic yield of ES for NDDs as the basis of a consensus development conference. We defined NDD as global developmental delay, intellectual disability, and/or autism spectrum disorder. The consensus development conference included input from genetics professionals, pediatric neurologists, and developmental behavioral pediatricians. Results After applying strict inclusion/exclusion criteria, we identified 30 articles with data on molecular diagnostic yield in individuals with isolated NDD, or NDD plus associated conditions (such as Rett-like features). Yield of ES was 36% overall, 31% for isolated NDD, and 53% for the NDD plus associated conditions. ES yield for NDDs is markedly greater than previous studies of CMA (15–20%). Conclusion Our review demonstrates that ES consistently outperforms CMA for evaluation of unexplained NDDs. We propose a diagnostic algorithm placing ES at the beginning of the evaluation of unexplained NDDs.
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ISSN:1098-3600
1530-0366
DOI:10.1038/s41436-019-0554-6