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

Siddharth Srivastava(Boston Children's Hospital), Jamie Love‐Nichols(Boston Children's Hospital), Kira A. Dies(Boston Children's Hospital), David H. Ledbetter(Autism & Developmental Medicine Institute), Christa Lese Martin(Autism & Developmental Medicine Institute), Wendy K. Chung(Columbia University), Helen V. Firth(Cambridge University Hospitals NHS Foundation Trust), Thomas Frazier(Autism Speaks), Robin Hansen(University of California, Davis), Lisa M. Prock(Harvard University), Han G. Brunner(Maastro Clinic), Ny Hoang(University of Toronto), Stephen W. Scherer(Hospital for Sick Children), Mustafa Şahin(Boston Children's Hospital), David T. Miller(Boston Children's Hospital)
Genetics in Medicine
June 10, 2019
Cited by 707Open Access
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Abstract

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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