P118 Rare CFTR variants: knowing them to target them more successfully - Université de Reims Champagne-Ardenne Access content directly
Conference Poster Year : 2024

P118 Rare CFTR variants: knowing them to target them more successfully

R. Chiron
  • Function : Author
A. Coudrat
  • Function : Author
A. Ronayette
  • Function : Author
L. Sonnet
  • Function : Author
C. Bareil
  • Function : Author
S. Sasorith
  • Function : Author
C. Audousset
  • Function : Author
M. Auffret
  • Function : Author
A. Blondé
  • Function : Author
C. Bluteau
  • Function : Author
S. Bui
  • Function : Author
C. Choubrac
  • Function : Author
P. de Carli
  • Function : Author
C. Delattre
  • Function : Author
N. Dufeu
  • Function : Author
L. Gueganton
  • Function : Author
R. Hamidfar
  • Function : Author
A. Ka
  • Function : Author
S. Leroy
  • Function : Author
C. Martin
  • Function : Author
S. Mazur
  • Function : Author
S. Orsero
  • Function : Author
J. Pengam
  • Function : Author
J. Quentin
  • Function : Author
S. Ramel
  • Function : Author
C. Raynal
  • Function : Author
P. Reix
  • Function : Author
T. Roussey-Bihouée
  • Function : Author
M. Savadogo
  • Function : Author
D. Tembely
  • Function : Author
G. Thouvenin
  • Function : Author
N. Wizla
  • Function : Author

Abstract

To pave the way to future clinical trials, the French National Clinical Research Network (PNRC) has initiated a project which aims to characterize patients with rare CFTR variants with no CFTR modulators and evaluate their needs in terms of clinical research by using the French CF registry (RFM). The first step is to have an exhaustive, high-quality genetic database at your disposal. CFTR France database records patients with rare CFTR variants and describes their different phenotypes. A verification process is set up between CFTR France and RFM, leading to some corrections to confirm the nature of the CFTR variant. Objective: To identify and correct potential genotype errors in the RFM. Methods: We checked all data by cross-referencing patient genotype data in both databases. For each inconsistency, we carried out a case-by-case analysis and contacted the patient’s CF clinician and clinical research coordinator to reach an agreement regarding genotype and correct the RFM. Results: To date, 78 patients with at least 1 variant inconsistency have been identified among the 7070 patients recorded in the RFM before 2017. Some inconsistencies were aberrant, with genotypes that did not match, while others were errors due to data entry. The evaluation of errors between 2017 and 2023 is ongoing and results will be presented. Conclusions: Thanks to this quality control, we identified and corrected around 1% of errors in the RFM regarding patients’ genotype. The entire cohort still needs to be checked. After this careful correction work and waiting results of the total cohort, it was decided to lock this crucial data in the RFM. It was important to first perform this quality control assessment on genetic data, in order to reach our main objective of characterizing patients with rare variants. The second stage of our project is to describe their health evolution, identify their requirements in terms of therapeutic options and assess if future developments match their needs.
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Dates and versions

hal-04609400 , version 1 (12-06-2024)

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Cite

R. Chiron, A. Coudrat, A. Ronayette, L. Sonnet, C. Bareil, et al.. P118 Rare CFTR variants: knowing them to target them more successfully. ECFC (European Cystic Fibrosis Conference), Jun 2024, Glasgow, United Kingdom. 23, pp.S121-S122, 2024, ⟨10.1016/S1569-1993(24)00476-4⟩. ⟨hal-04609400⟩

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