| Literature DB >> 27142713 |
Martial Mallaret1,2,3, Mathilde Renaud2,3,4, Claire Redin2, Nathalie Drouot2, Jean Muller2,5, Francois Severac6, Jean Louis Mandel2,5,7, Wahiba Hamza8, Traki Benhassine8, Lamia Ali-Pacha9, Meriem Tazir9,10, Alexandra Durr11,12, Marie-Lorraine Monin13, Cyril Mignot13, Perrine Charles14, Lionel Van Maldergem15, Ludivine Chamard16, Christel Thauvin-Robinet17, Vincent Laugel18, Lydie Burglen19, Patrick Calvas20, Marie-Céline Fleury3, Christine Tranchant2,3,4, Mathieu Anheim21,22,23, Michel Koenig24.
Abstract
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.Entities:
Keywords: Electromyography; Neurogenetics; Next generation sequencing; Recessive ataxia
Mesh:
Year: 2016 PMID: 27142713 DOI: 10.1007/s00415-016-8112-5
Source DB: PubMed Journal: J Neurol ISSN: 0340-5354 Impact factor: 4.849