High rate of hypomorphic variants as the cause of inherited ataxia and related diseases: study of a cohort of 366 families.

PURPOSE: Diagnosis of inherited ataxia and related diseases represents a real challenge given the tremendous heterogeneity and clinical overlap of the various causes. We evaluated the efficacy of molecular diagnosis of these diseases by sequencing a large cohort of undiagnosed families. METHODS: We analyzed 366 unrelated consecutive patients with undiagnosed ataxia or related disorders by clinical exome-capture sequencing. In silico analysis was performed with an in-house pipeline that combines variant ranking and copy-number variant (CNV) searches. Variants were interpreted according to American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines. RESULTS: We established the molecular diagnosis in 46% of the cases. We identified 35 mildly affected patients with causative variants in genes that are classically associated with severe presentations. These cases were explained by the occurrence of hypomorphic variants, but also rarely suspected mechanisms such as C-terminal truncations and translation reinitiation. CONCLUSION: A significant fraction of the clinical heterogeneity and phenotypic overlap is explained by hypomorphic variants that are difficult to identify and not readily predicted. The hypomorphic C-terminal truncation and translation reinitiation mechanisms that we identified may only apply to few genes, as it relies on specific domain organization and alterations. We identified PEX10 and FASTKD2 as candidates for translation reinitiation accounting for mild disease presentation.

Mini-Exome Coupled to Read-Depth Based Copy Number Variation Analysis in Patients with Inherited Ataxias.

Next-generation sequencing (NGS) has an established diagnostic value for inherited ataxia. However, the need of a rigorous process of analysis and validation remains challenging. Moreover, copy number variations (CNV) or dynamic expansions of repeated sequence are classically considered not adequately detected by exome sequencing technique. We applied a strategy of mini-exome coupled to read-depth based CNV analysis to a series of 33 patients with probable inherited ataxia and onset <50 years. The mini-exome consisted of the capture of 4,813 genes having associated clinical phenotypes. Pathogenic variants were found in 42% and variants of uncertain significance in 24% of the patients. These results are comparable to those from whole exome sequencing and better than previous targeted NGS studies. CNV and dynamic expansions of repeated CAG sequence were identified in three patients. We identified both atypical presentation of known ataxia genes (ATM, NPC1) and mutations in genes very rarely associated with ataxia (ERCC4, HSD17B4). We show that mini-exome bioinformatics data analysis allows the identification of CNV and dynamic expansions of repeated sequence. Our study confirms the diagnostic value of the proposed genetic analysis strategy. We also provide an algorithm for the multidisciplinary process of analysis, interpretation, and validation of NGS data.