Ataxia Clinical Trial
— BASE-AAROfficial title:
Exploitation of a BAse of Genetic Data (Obtained by Next Generation SEquencing) for the Validation of a Clinical Algorithm for the Diagnosis of Recessive Cerebellar Ataxias
Verified date | April 2022 |
Source | University Hospital, Montpellier |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The field of clinical diagnosis of recessive cerebellar ataxias (ARCA) is particularly complex and Next Generation Sequencing (NGS) techniques have revolutionized this neuro-genetic field. The current challenge is to optimize the analysis of genetic data generated by NGS because: the processing of data remains very laborious; diagnostic yeld less than 50%; the interpretation of the variants sometimes very difficult. For this purpose of optimization, the team of the University Hospital of Strasbourg has developed a computer algorithm based on 124 clinical and para-clinical parameters (derived from the data of the literature), useful to guide the genes to be targeted in priority by genetic analysis, in the context of a suspicion of ARCA (> 60 known genes); this algorithm was validated retrospectively in 834 patients with genetically confirmed ARCA (92% Sense, 95% Spec). However, these 834 patients are often the same as those described in the literature and used for the elaboration of the algorithm. This introduces a bias in the initial evaluation of the algorithm, which therefore requires validation in clinical practice, from a cohort of patients referred for suspected ARCA (with or without a found genetic mutation). At the same time, Montpellier's genetics laboratory has developed a bioinformatic method for the search for copy number variations (CNV) that can be applied in a targeted manner to the genes predicted by the algorithm. The principal aim of this study is the validation of a semi-automated clinical algorithm for NGS molecular diagnosis of ARCA; the secondary objective is to evaluate if the application of this algorithm coupled with a targeted bioinformatic analysis can increase the diagnostic yield of the NGS analysis.
Status | Completed |
Enrollment | 150 |
Est. completion date | March 30, 2022 |
Est. primary completion date | March 30, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion criteria: - having a predominant phenotype of pure or complex cerebellar ataxia of probable genetic origin (after exclusion of acquired, inflammatory, tumoral, infectious or toxic forms) - having started before the age of 50; - evoking a modality of recessive transmission (sporadic cases, brothers or sister affected, consanguinity of the parents) - in which dominant genetic forms due to CAG expansion (SCA1, SCA2, SCA3, SCA6, SCA7) and pre-mutation of the FMR1 gene (if onset after age 45) Exclusion criteria: - objecting to the computer processing of the data contained in the medical file. |
Country | Name | City | State |
---|---|---|---|
France | Uh Montpellier | Montpellier |
Lead Sponsor | Collaborator |
---|---|
University Hospital, Montpellier | Genetic Department , CHU Montpellier-France, Neurology Department, CHU de Strasbourg-France |
France,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Agreement between the prediction of the algorithm and the result of the standard NGS analysis | In order to validate in clinical practice a semi-automated clinical algorithm designed to guide the molecular diagnosis obtained by Next Generation Sequencing (NGS) in patients with suspected Autosomal Recessive Cerebellar Ataxia (ARCA), we will measure the agreement between the prediction of the algorithm and the result of the standard NGS analysis. For each patient the agreement is defined as: 1) one of the first 5 gene predicted with the highest probability by the algorithm is also the mutated gene found after the NGS analysis; 2) if no gene is predicted by the algorithm (= none of the gene has a prediction score > 20) and no mutation is found after NGS analyses. | 1 day | |
Secondary | Percentage of patients for whom the prediction based on the algorithm suggested the right diagnosis, while the standard NGS analysis was not informative | The secondary objective is to evaluate whether the application of this algorithm, coupled with a targeted bioinformatic analysis, changes the diagnostic yield compared to a NGS analysis performed in a conventional manner. Therefore, the secondary outcome will be the percentage of patients for whom the prediction based on the algorithm suggested the corrected diagnosis (confirmed in a second time after the review of the genetic data derived from NGS after the application of a targeted bioinformatic analysis), while the standard NGS analysis (blinded to algorithm prediction) was not informative | 1 day |
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