SUMMARY Together with GTP and the initiator methionyl-tRNA, the translation initiation factor eIF2 forms a ternary complex that binds the 40S ribosome and then scans an mRNA to select the AUG start codon for protein synthesis. Here, we show that a human X-chromosomal neurological disorder characterized by intellectual disability and microcephaly is caused by a missense mutation in eIF2γ (encoded by EIF2S3), the core subunit of the heterotrimeric eIF2 complex. Biochemical studies of human cells overexpressing the eIF2γ mutant and of yeast eIF2γ with the analogous mutation revealed a defect in binding the eIF2β subunit to eIF2γ. Consistent with this loss of eIF2 integrity, the mutation in yeast eIF2γ impaired translation start codon selection and eIF2 function in vivo in a manner that was suppressed by overexpression of eIF2β. These findings directly link intellectual disability to impaired translation initiation, and provide a mechanistic basis for the human disease due to partial loss of eIF2 function.

Given the known function of the SYCE1 gene, we suggest that the nonsense mutation identified accounts for the POI phenotype. These results highlight the importance of the synaptonemal complex and meiosis in ovarian function.

Epileptic encephalopathies are genetically heterogeneous severe disorders in which epileptic activity contributes to neurological deterioration. We studied two unrelated children presenting with a distinctive early-onset epileptic encephalopathy characterized by refractory epilepsy and absent developmental milestones, as well as thick and short corpus callosum and persistent cavum septum pellucidum on brain MRI. Using whole-exome sequencing, we identified biallelic mutations in seizure threshold 2 (SZT2) in both affected children. The causative mutations include a homozygous nonsense mutation and a nonsense mutation together with an exonic splice-site mutation in a compound-heterozygous state. The latter mutation leads to exon skipping and premature termination of translation, as shown by RT-PCR in blood RNA of the affected boy. Thus, all three mutations are predicted to result in nonsense-mediated mRNA decay and/or premature protein truncation and thereby loss of SZT2 function. Although the molecular role of the peroxisomal protein SZT2 in neuronal excitability and brain development remains to be defined, Szt2 has been shown to influence seizure threshold and epileptogenesis in mice, consistent with our findings in humans. We conclude that mutations in SZT2 cause a severe type of autosomal-recessive infantile encephalopathy with intractable seizures and distinct neuroradiological anomalies.

PurposePhenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists.MethodsHere, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds.ResultsThe additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene.ConclusionImage analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.

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