Up to 40% of neurodevelopmental disorders (NDDs) such as intellectual disability, developmental delay, autism spectrum disorder, and developmental motor abnormalities have a documented underlying monogenic defect, primarily due to de novo variants. Still, the overall burden of de novo variants as well as novel disease genes in NDDs await discovery. We performed parent‐offspring trio exome sequencing in 231 individuals with NDDs. Phenotypes were compiled using human phenotype ontology terms. The overall diagnostic yield was 49.8% (n = 115/231) with de novo variants contributing to more than 80% (n = 93/115) of all solved cases. De novo variants affected 72 different—mostly constrained—genes. In addition, we identified putative pathogenic variants in 16 genes not linked to NDDs to date. Reanalysis performed in 80 initially unsolved cases revealed a definitive diagnosis in two additional cases. Our study consolidates the contribution and genetic heterogeneity of de novo variants in NDDs highlighting trio exome sequencing as effective diagnostic tool for NDDs. Besides, we illustrate the potential of a trio‐approach for candidate gene discovery and the power of systematic reanalysis of unsolved cases.

In patients with evaluable data, there was an 80% success rate for treatment of OSA using a custom-fabricated adjustable MAD including substantial numbers of patients with moderate and severe disease.

Most individuals with rare diseases initially consult their primary care physician. For a subset of rare diseases, efficient diagnostic pathways are available. However, ultra-rare diseases often require both expert clinical knowledge and comprehensive genetic diagnostics, which poses structural challenges for public healthcare systems. To address these challenges within Germany, a novel structured diagnostic concept, based on multidisciplinary expertise at established university hospital centers for rare diseases (CRDs), was evaluated in the three year prospective study TRANSLATE NAMSE. A key goal of TRANSLATE NAMSE was to assess the clinical value of exome sequencing (ES) in the ultra-rare disease population. The aims of the present study were to perform a systematic investigation of the phenotypic and molecular genetic data of TRANSLATE NAMSE patients who had undergone ES in order to determine the yield of both ultra-rare diagnoses and novel gene-disease associations; and determine whether the complementary use of machine learning and artificial intelligence (AI) tools improved diagnostic effectiveness and efficiency. ES was performed for 1,577 patients (268 adult and 1,309 pediatric). Molecular genetic diagnoses were established in 499 patients (74 adult and 425 pediatric). A total of 370 distinct molecular genetic causes were established. The majority of these concerned known disorders, most of which were ultra-rare. During the diagnostic process, 34 novel and 23 candidate genotype-phenotype associations were delineated, mainly in individuals with neurodevelopmental disorders. To determine the likelihood that ES will lead to a molecular diagnosis in a given patient, based on the respective clinical features only, we developed a statistical framework called YieldPred. The genetic data of a subcohort of 224 individuals that also gave consent to the computer-assisted analysis of their facial images were processed with the AI tool Prioritization of Exome Data by Image Analysis (PEDIA) and showed superior performance in variant prioritization. The present analyses demonstrated that the novel structured diagnostic concept facilitated the identification of ultra-rare genetic disorders and novel gene-disease associations on a national level and that the machine learning and AI tools improved diagnostic effectiveness and efficiency for ultra-rare genetic disorders.