IDENTIFICAZIONE DI NUOVI GENI RESPONSABILI DI MALATTIE RARE DEL NEUROSVILUPPO TRAMITE HOMOZYGOSITY MAPPING E/O SEQUENZIAMENTO DI NUOVA GENERAZIONE

The genetics of most common single-gene neurological disorders has been dissected in the last twenty years. However, the aetiology of several rare Mendelian neurological conditions is still unknown, with significant implications for diagnosis, genetic counselling and therapy. So far the identification of genes for these rare conditions have been constrained by methodological issues, such as the shortage of informative families for linkage analysis, the lack of very dense maps of polymorphic markers and the availability of efficient and low-cost platforms for genotyping and sequencing. Recently, the high-throughput sequencing of the coding DNA (i.e. exome) has been successfully applied to identify causative mutations by comparing the genome-wide profile of non-synonymous variants among unrelated patients affected by the same disease. Thus, exome sequencing may not be readily applicable to patients affected by rare unclassified conditions who cannot be grouped into genetically homogenous pools. To dissect the heterogenous genetic etiology of rare neurological phenotypes, we decided to combine exome sequencing with homozygosity mapping, a robust approach to localize disease genes involved in autosomal recessive (AR) Mendelian disorders in discrete genomic regions. We focused our attention on 7 phenotypic heterogeneity families that they have not been genetically diagnosed of the our Pediatric Neurological Unit. We analyzed variants with standard bioinformatic pipeline and databases of populations as ExAC, GnomaAD, and in-house database (200 normal controls). We confirmed the selected variants by Sanger Sequencing in probands and parents. We excluded the negative variants by Sanger sequencing in affected subjects and parents. In more cases, we demonstrated the pathogenetic role for these variants with functional studies as WesternBlot, staning of tissue and immunofluorescence of the patients’ cells. We generated the Zebrafish model to evaluate the pathogenetic role of some variants. We highlighted the importance of the bioinformatic analysis, which selected the effective genetic causes of pathology in these families. We identified different genes, adding important genotype-phenotype correlations to literature data. In conclusion, this study highlighted a powerful approach for clarify the genetic basis of rare neurological recessive diseases. Furthermore, this genome-wide approach allowed to highlight new genotype-phenotype correlations and expanded the clinical phenotypic spectrum in specificgenetic conditions