Targeted Gene Resequencing (Astrochip) to Explore the Tripartite Synapse in Autism-Epilepsy Phenotype with
Maria Marchese1, Giulia Valvo2, Francesca Moro1
1Molecular Medicine, IRCCS Stella Maris Foundation, Viale del Tirreno 331, via dei Giacinti 2, 56128, Calambrone, Pisa, Italy.
Abstract:
The frequent co-occurrence of autism spectrum disorders (ASD) and epilepsy, or paroxysmal EEG abnormalities, defines a condition termed autism-epilepsy phenotype (AEP). This condition results, in some cases , from dysfunctions of glial inwardly rectifying potassium channels (Kir), which are mainly expressed in astrocytes where they mediate neuron-glia communication. Macrocephaly is also often comorbid with autism-epilepsy (autism-epilepsy phenotype with macrocephaly, MAEP), and it is tempting to hypothesize that shared pathogenic mechanisms might explain concurrence of these conditions. In the present study, we assessed whether protein pathways involved, along with Kir channels, in astrocyte-neuron interaction at the tripartite synapse play a role in the etiopathogenesis of MAEP. Using a targeted resequencing methodology, we investigated the coding regions of 35 genes in 61 patients and correlated genetic results with clinical features. Variants were subdivided into 12 classes and clustered into four groups. We detected rare or previously unknown predicted deleterious missense changes in GJA1, SLC12A2, SNTA1, EFNA3, CNTNAP2, EPHA4, and STXBP1 in seven patients and two high-frequency variants in DLG1 in six individuals. We also found that a group of variants (predicted deleterious and non-coding), segregating with the comorbid MAEP/AEP subgroups, belong to proteins specifically involved in glutamate transport and metabolism (namely, SLC17A6, GRM8, and GLUL), as well as in potassium conductance (KCNN3). This "endophenotype-oriented" study, performed using a targeted strategy, helped to further delineate part of the complex genetic background of ASD, particularly in the presence of coexisting macrocephaly and/or epilepsy/paroxysmal EEG, and suggests that use of stringent clinical clustering might be an approach worth adopting in order to unravel the complex genomic data in neurodevelopmental disorders.
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