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.

A general protocol for the preparation of ¹⁸F-labeled AAAs and α-methyl-AAAs applying alcohol-enhanced Cu-mediated radiofluorination of Bpin-substituted chiral complexes using Ni/Cu-BPX templates as double protecting groups is reported. The chiral...

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Purpose: The preclinical evaluation of 3-l- and 3-d-[18F]FPhe in comparison to [18F]FET, an established tracer for tumor imaging. Methods: In vitro studies were conducted with MCF-7, PC-3, and U87 MG human tumor cell lines. In vivo µPET studies were conducted in healthy rats with/without the inhibition of peripheral aromatic l-amino acid decarboxylase by benserazide pretreatment (n = 3 each), in mice bearing subcutaneous MCF-7 or PC-3 tumor xenografts (n = 10), and in rats bearing orthotopic U87 MG tumor xenografts (n = 14). Tracer accumulation was quantified by SUVmax, SUVmean and tumor-to-brain ratios (TBrR). Results: The uptake of 3-l-[18F]FPhe in MCF-7 and PC-3 cells was significantly higher relative to [18F]FET. The uptake of all three tracers was significantly reduced by the suppression of amino acid transport systems L or ASC. 3-l-[18F]FPhe but not 3-d-[18F]FPhe exhibited protein incorporation. In benserazide-treated healthy rats, brain uptake after 42–120 min was significantly higher for 3-d-[18F]FPhe vs. 3-l-[18F]FPhe. [18F]FET showed significantly higher uptake into subcutaneous MCF-7 tumors (52–60 min p.i.), while early uptake into orthotopic U87 MG tumors was significantly higher for 3-l-[18F]FPhe (SUVmax: 3-l-[18F]FPhe, 107.6 ± 11.3; 3-d-[18F]FPhe, 86.0 ± 4.3; [18F]FET, 90.2 ± 7.7). Increased tumoral expression of LAT1 and ASCT2 was confirmed immunohistologically. Conclusion: Both novel tracers enable accurate tumor delineation with an imaging quality comparable to [18F]FET.

Intellectual disability encompasses a wide spectrum of neurodevelopmental disorders, with many linked genetic loci. However, the underlying molecular mechanism for more than 50% of the patients remains elusive. We describe pathogenic variants in SMARCA5, encoding the ATPase motor of the ISWI chromatin remodeler, as a cause of a previously unidentified neurodevelopmental disorder, identifying 12 individuals with de novo or dominantly segregating rare heterozygous variants. Accompanying phenotypes include mild developmental delay, frequent postnatal short stature and microcephaly, and recurrent dysmorphic features. Loss of function of the SMARCA5 Drosophila ortholog Iswi led to smaller body size, reduced sensory dendrite complexity, and tiling defects in larvae. In adult flies, Iswi neural knockdown caused decreased brain size, aberrant mushroom body morphology, and abnormal locomotor function. Iswi loss of function was rescued by wild-type but not mutant SMARCA5. Our results demonstrate that SMARCA5 pathogenic variants cause a neurodevelopmental syndrome with mild facial dysmorphia.

Coiled‐Coil Domain Containing Protein 186 (CCDC186) is hypothesized to play an important role in the biogenesis of dense‐core vesicles in neurons and endocrine cells. Biallelic loss‐of‐function variants in the encoding gene CCDC186 have been suggested as a candidate gene for a neurodevelopmental phenotype, but only one patient has been described so far. We report a second patient with a CCDC186‐associated phenotype presenting with developmental delay, epileptic encephalopathy, and failure to thrive. Exome sequencing identified a homozygous loss‐of‐function variant in CCDC186 (NM_018017.2) c.767C> G; p.(Ser256Ter) thus providing further evidence to support CCDC186 as a new disease gene for an autosomal recessive neurodevelopmental disorder.

Intellectual disability (ID) encompasses a wide spectrum of neurodevelopmental disorders, with many linked genetic loci. However, the underlying molecular mechanism for over 50% of the patients remains elusive. We describe mutations in SMARCA5, encoding the ATPase motor of the ISWI chromatin remodeler, as a cause of a novel neurodevelopmental disorder, identifying twelve individuals with de novo or dominantly segregating rare heterozygous variants. Accompanying phenotypes include mild developmental delay, frequent postnatal short stature, and microcephaly, and recurrent dysmorphic features. Loss of function of the SMARCA5 Drosophila ortholog Iswi led to smaller body size, reduced dendrite complexity, and tiling defects in larvae. In adult flies, Iswi neural knockdown caused decreased brain size, aberrant mushroom body morphology and abnormal locomotor function. Iswi loss of function was rescued by wild-type but not mutant SMARCA5. Our results demonstrate that SMARCA5 pathogenic variants cause a neurodevelopmental syndrome with mild facial dysmorphia.

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.