Wiedemann‐Steiner syndrome (WSS) is an autosomal dominant disorder caused by monoallelic variants in KMT2A and characterized by intellectual disability and hypertrichosis. We performed a retrospective, multicenter, observational study of 104 individuals with WSS from five continents to characterize the clinical and molecular spectrum of WSS in diverse populations, to identify physical features that may be more prevalent in White versus Black Indigenous People of Color individuals, to delineate genotype–phenotype correlations, to define developmental milestones, to describe the syndrome through adulthood, and to examine clinicians' differential diagnoses. Sixty‐nine of the 82 variants (84%) observed in the study were not previously reported in the literature. Common clinical features identified in the cohort included: developmental delay or intellectual disability (97%), constipation (63.8%), failure to thrive (67.7%), feeding difficulties (66.3%), hypertrichosis cubiti (57%), short stature (57.8%), and vertebral anomalies (46.9%). The median ages at walking and first words were 20 months and 18 months, respectively. Hypotonia was associated with loss of function (LoF) variants, and seizures were associated with non‐LoF variants. This study identifies genotype–phenotype correlations as well as race‐facial feature associations in an ethnically diverse cohort, and accurately defines developmental trajectories, medical comorbidities, and long‐term outcomes in individuals with WSS.

Glutamatergic neurotransmission governs excitatory signaling in the mammalian brain, and abnormalities of glutamate signaling have been shown to contribute to both epilepsy and hyperkinetic movement disorders. The etiology of many severe childhood movement disorders and epilepsies remains uncharacterized. We describe a neurological disorder with epilepsy and prominent choreoathetosis caused by biallelic pathogenic variants in FRRS1L, which encodes an AMPA receptor outer-core protein. Loss of FRRS1L function attenuates AMPA-mediated currents, implicating chronic abnormalities of glutamatergic neurotransmission in this monogenic neurological disease of childhood.

The neurodiagnostic criteria of Leigh syndrome have not yet been clearly redefined based on the expanding of molecular etiologies. We aimed to analyze 20 years of clinical, genetic, and magnetic resonance studies from our Leigh syndrome cohort to provide a detailed description of central nervous system lesions in Leigh syndrome and their biological evolution in view of their genetic and clinical findings. Our study adds new neurodiagnostic insights to the current knowledge of Leigh syndrome, including association with overlapping syndromes, and the correlation of pathogenic genetic variants with neuroimaging phenotypes. ANN NEUROL 2020;88:218–232.

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and disease. MSeqDR-LSDB is a locus specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar-compliant variant annotations. PhenoTips is used for phenotypic data submission on de-identified patients using human phenotype ontology terminology. Development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources.