Validation of a clinical practice-based algorithm for the diagnosis of autosomal recessive cerebellar ataxias based on NGS identified cases

Martial Mallaret, Mathilde Renaud, Claire Redin, Nathalie Drouot, Jean Muller, Francois Severac, Jean Louis Mandel, Wahiba Hamza, Traki Benhassine, Lamia Ali-Pacha, Meriem Tazir, Alexandra Durr, Marie-Lorraine Monin, Cyril Mignot, Perrine Charles, Lionel Van Maldergem, Ludivine Chamard, Christel Thauvin-Robinet, Vincent Laugel, Lydie Burglen, Patrick Calvas, Marie-Céline Fleury, Christine Tranchant, Mathieu Anheim, Michel Koenig

Establishing a molecular diagnosis of autosomal recessive cerebellar ataxias (ARCA) is challenging due to phenotype and genotype heterogeneity. We report the validation of a previously published clinical practice-based algorithm to diagnose ARCA. Two assessors performed a blind analysis to determine the most probable mutated gene based on comprehensive clinical and paraclinical data, without knowing the molecular diagnosis of 23 patients diagnosed by targeted capture of 57 ataxia genes and high-throughput sequencing coming from a 145 patients series. The correct gene was predicted in 61 and 78 % of the cases by the two assessors, respectively. There was a high inter-rater agreement [K = 0.85 (0.55-0.98) p < 0.001] confirming the algorithm's reproducibility. Phenotyping patients with proper clinical examination, imaging, biochemical investigations and nerve conduction studies remain crucial for the guidance of molecular analysis and to interpret next generation sequencing results. The proposed algorithm should be helpful for diagnosing ARCA in clinical practice.