Molecular Genetics & Genomic MedicineGeneticsPeer-reviewed journal article
Structural analysis of pathogenic missense mutations in GABRA2 and identification of a novel de novo variant in the desensitization gate
Alba Sanchis‐JuaniD, Marcia Anahí HasenahueriD, James Alexander BakeriD, Amy McTagueiD, Katy E BarwickiD, Manju A. KurianiD, Sofia Temudo DuarteiD, NIHR BioResource, Keren CarssiD, Janet M. ThorntoniD, Frances Lucy RaymondiD
Abstract
Cys-loop receptors are vital for controlling neuronal excitability in the brain and their dysfunction results in numerous neurological disorders. Recently, six de novo missense variants in GABRA2 gene, a member of this family, have been associated with early infantile epileptic encephalopathy (EIEE) and intellectual disability with seizures. Here, using whole-genome sequencing we identified a de novo missense variant in GABRA2 gene in a patient with EIEE and developmental delay. We perform protein structural analysis of the seven variants and show that all the mutations are in the transmembrane domain, either close to the desensitization gate, the activation gate or in inter-subunit interfaces. Further investigations demonstrated that the majority of pathogenic variants reported are at equivalent positions in other Cys-loop receptors, emphasizing the importance of these residues for the adequate function of the receptor. Also, a comparison of the distribution of the mutations in all the Cys-loop receptors showed that pathogenic variants are more common in the transmembrane helices, more specifically in the M2 helix, highlighting the importance of this segment. Our study expands the clinical spectrum of individuals with pathogenic missense mutations in GABRA2, defines the regions where pathogenic mutations are in the protein structure, and highlights the value of considering sequence, evolutionary, and structural information from other Cys-loop receptors as a strategy for variant interpretation of novel missense mutations in GABRA2.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 9
- FWCI
- 1.02
- Field percentile
- top 27%
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