This pilot study aims to develop an integrative analysis method that allows for an increased diagnosis success rate of rare genetic mutations. Moreover, identification of novel genes associated with Episodic Ataxia (EA) and evaluation of new AI-generated prediction algorithm, for a more robust variant examination, will ensue from the investigation.

Characterized by sporadic loss of voluntary movement coordination, EA typically manifest with a late onset as well as high clinical and genetic heterogeneity, setting additional hurdles to diagnosis. While four genes have been linked to the eight subtypes of EA, many patients are left without molecular diagnosis due to the limitations of individual DNA-sequencing methods, which can be mitigated by the functional overview that RNA-seq offers.

EA patients lacking molecular diagnosis despite in-depth examination were recruited in Montreal. Whole-Genome and RNA-sequencing was performed on blood samples to identify variants, differential expression, splicing events and repeat expansion. Multiple recent pathogenicity prediction algorithms were chosen to be tested concurrently to standard ones.   

Candidate variants were identified for each patients according to pathogenicity scores, rarity of the genetic events, and known functional as well as clinical information for a given altered gene. Among the findings are truncations, missenses, and alternative splicing in genes already associated to either Spinocerebellar Ataxia or Spastic Paraplegia. While validation of these interesting genomic events is still pending, variants have been confirmed in both datasets, and the available functional information from RNAseq supports abnormal mRNA expression. A meta-analysis of our patients’ transcriptomic profiles could also uncover commonly affected pathways in EA development.

This project should provide more defined diagnosis, leading to better quality of life, better understanding of prognosis and better management of care for patients. It will also promote the integrative approach for a larger spectrum of disorders and might eventually lead to new therapeutic strategies.