Deep phenotyping and whole-exome sequencing improved the diagnostic yield for nuclear pedigrees with neurodevelopmental disorders

Abstract

Background: Neurodevelopmental disorders, a group of early-onset neurological disorders with significant clinical and genetic heterogeneity, remain a diagnostic challenge for clinical genetic evaluation. Therefore, we assessed the diagnostic yield by combining standard phenotypes and whole-exome sequencing in families with these disorders that were “not yet diagnosed” by the traditional testing methods. Methods: Using a standardized vocabulary of phenotypic abnormalities from human phenotype ontology (HPO), we performed deep phenotyping for 45 “not yet diagnosed” pedigrees to characterize multiple clinical features extracted from Chinese electronic medical records (EMRs). By matching HPO terms with known human diseases and phenotypes from model organisms, together with whole-exome sequencing data, we prioritized candidate mutations/genes. We made probable genetic diagnoses for the families. Results: We obtained a diagnostic yield of 29% (13 out of 45) with probably genetic diagnosis, of which compound heterozygosity and de novo mutations accounted for 77% (10/13) of the diagnosis. Of note, these pedigrees are accompanied by a more significant number of non-neurological features. Conclusions: Deep phenotyping and whole-exome sequencing improve the etiological evaluation for neurodevelopmental disorders in the clinical setting.