Pathogenic variants in KCNA2, encoding for the voltage-gated potassium channel K_v1.2, have been identified as the cause for an evolving spectrum of neurological disorders. Affected individuals show early-onset developmental and epileptic encephalopathy, intellectual disability, and movement disorders resulting from cerebellar dysfunction. In addition, individuals with a milder course of epilepsy, complicated hereditary spastic paraplegia, and episodic ataxia have been reported. By analyzing phenotypic, functional, and genetic data from published reports and novel cases, we refine and further delineate phenotypic as well as functional subgroups of KCNA2-associated disorders. Carriers of variants, leading to complex and mixed channel dysfunction that are associated with a gain- and loss-of-potassium conductance, more often show early developmental abnormalities and an earlier onset of epilepsy compared to individuals with variants resulting in loss- or gain-of-function. We describe seven additional individuals harboring three known and the novel KCNA2 variants p.(Pro407Ala) and p.(Tyr417Cys). The location of variants reported here highlights the importance of the proline(405)–valine(406)–proline(407) (PVP) motif in transmembrane domain S6 as a mutational hotspot. A novel case of self-limited infantile seizures suggests a continuous clinical spectrum of KCNA2-related disorders. Our study provides further insights into the clinical spectrum, genotype–phenotype correlation, variability, and predicted functional impact of KCNA2 variants.

Purpose TUBA1A and TUBB2B tubulinopathies are rare neurodevelopmental disorders characterized by cortical and extracortical malformations and heterogenic phenotypes. There is a need for quantitative clinical endpoints that will be beneficial for future diagnostic and therapeutic trials. Methods Quantitative natural history modeling of individuals with TUBA1A and TUBB2B tubulinopathies from clinical reports and database entries of DECIPHER and ClinVar. Main outcome measures were age at disease onset, survival, and diagnostic delay. Phenotypical, neuroradiological, and histopathological features were descriptively illustrated. Results Mean age at disease onset was 4 (TUBA1A) and 6 months (TUBB2B), respectively. Mortality was equally estimated with 7% at 3.2 (TUBA1A) and 8.0 years (TUBB2B). Diagnostic delay was significantly higher in TUBB2B (12.3 years) compared with TUBA1A tubulinopathy (4.2 years). We delineated the isotype-dependent clinical, neuroradiological, and histopathological phenotype of affected individuals and present brain malformations associated with epilepsy and an unfavorable course of disease. Conclusion The natural history of tubulinopathies is defined by the genotype and associated brain malformations. Defined data on estimated survival, diagnostic delay, and disease characteristics of TUBA1A and TUBB2B tubulinopathy will help to raise disease awareness and encourage future clinical trials to optimize genetic testing, family counseling, and supportive care.

TUBA1A tubulinopathy is a rare neurodevelopmental disorder associated with brain malformations as well as early-onset and intractable epilepsy. As pathomechanisms and genotype-phenotype correlations are not completely understood, we aimed to provide further insights into the phenotypic and genetic spectrum. We here present a multicenter case series of ten unrelated individuals from four European countries using systematic MRI re-evaluation, protein structure analysis, and prediction score modeling. In two cases, pregnancy was terminated due to brain malformations. Amongst the eight living individuals, the phenotypic range showed various severity. Global developmental delay and severe motor impairment with tetraparesis was present in 63% and 50% of the subjects, respectively. Epilepsy was observed in 75% of the cases, which showed infantile onset in 83% and a refractory course in 50%. One individual presented a novel TUBA1A-associated electroclinical phenotype with evolvement from early myoclonic encephalopathy to continuous spike-and-wave during sleep. Neuroradiological features comprised a heterogeneous spectrum of cortical and extracortical malformations including rare findings such as cobblestone lissencephaly and subcortical band heterotopia. Two individuals developed hydrocephalus with subsequent posterior infarction. We report four novel and five previously published TUBA1A missense variants whose resulting amino acid substitutions likely affect longitudinal, lateral, and motor protein interactions as well as GTP binding. Assessment of pathogenic and benign variant distributions in synopsis with prediction scores revealed sections of variant enrichment and intolerance to missense variation. We here extend the clinical, neuroradiological, and genetic spectrum of TUBA1A tubulinopathy and provide insights into residue-specific pathomechanisms and genotype-phenotype correlations.

SYNCRIP encodes for the Synaptotagmin-binding cytoplasmic RNA-interacting protein, involved in RNA-binding and regulation of multiple cellular pathways. It has been proposed as a candidate gene for neurodevelopmental disorders (NDDs) with autism spectrum disorder (ASD), intellectual disability (ID), and epilepsy. We ascertained genetic, clinical, and neuroradiological data of three additional individuals with novel de novo SYNCRIP variants. All individuals had ID. Autistic features were observed in two. One individual showed myoclonic-atonic epilepsy. Neuroradiological features comprised periventricular nodular heterotopia and widening of subarachnoid spaces. Two frameshift variants in the more severely affected individuals, likely result in haploinsufficiency. The third missense variant lies in the conserved RNA recognition motif (RRM) 2 domain likely affecting RNA-binding. Our findings support the importance of RRM domains for SYNCRIP functionality and suggest genotype-phenotype correlations. Our study provides further evidence for a SYNCRIP-associated NDD characterized by ID and ASD sporadically accompanied by malformations of cortical development and myoclonic-atonic epilepsy.

Brain organoids represent a useful tool for modeling of neurodevelopmental disorders and can recapitulate brain volume alterations such as microcephaly. To monitor organoid growth, brightfield microscopy images are frequently used and evaluated manually which is time-consuming and prone to observer-bias. Recent software applications for organoid evaluation address this issue using classical or AI-based methods. These pipelines have distinct strengths and weaknesses that are not evident to external observers. We provide a dataset of more than 1,400 images of 64 trackable brain organoids from four clones differentiated from healthy and diseased patients. This dataset is especially powerful to test and compare organoid analysis pipelines because of (1) trackable organoids (2) frequent imaging during development (3) clone diversity (4) distinct clone development (5) cross sample imaging by two different labs (6) common imaging distractors, and (6) pixel-level ground truth organoid annotations. Therefore, this dataset allows to perform differentiated analyses to delineate strengths, weaknesses, and generalizability of automated organoid analysis pipelines as well as analysis of clone diversity and similarity.

Glutaric aciduria type 1 (GA1) is a rare neurometabolic disease caused by pathogenic variants in the gene encoding the enzyme glutaryl‐CoA dehydrogenase (GCDH). We performed an extensive literature search to collect data on GA1 patients, together with unpublished cases, to provide an up‐to‐date genetic landscape of GCDH pathogenic variants and to investigate potential genotype‐phenotype correlation, as this is still poorly understood. From this search, 421 different GCDH pathogenic variants have been identified, including four novel variants; c.179T>C (p.Leu60Pro), c.214C>T (p.Arg72Cys), c.309G>C (p.Leu103Phe), and c.665T>C (p.Phe222Ser).The variants are mostly distributed across the entire gene; although variant frequency in GA1 patients is relatively high in the regions encoding for active domains of GCDH. To investigate potential genotype‐phenotype correlations, phenotypic descriptions of 532 patients have been combined and evaluated using novel combinatorial analyses. To do so, various clinical phenotypes were determined for each pathogenic variant by combining the information of all GA1 patients reported with this pathogenic variant, and subsequently mapped onto the 2D and 3D GCDH protein structure. In addition, the predicted pathogenicity of missense variants was analyzed using different in silico prediction score models. Both analyses showed an almost similar distribution of the highly pathogenic variants across the GCDH protein, although some hotspots, including the active domain, were observed. Moreover, it was demonstrated that highly pathogenic variants are significantly correlated with lower residual enzyme activity and the most accurate estimation was achieved by the REVEL score. A clear correlation of the genotype and the clinical phenotype however is still lacking.