Novel BEST1 Variant Characterization in a Large French Cohort in Light of Updated Bestrophin-1 Structure-Function...

Area of Science:

• Genetics
• Molecular Biology
• Ophthalmology

Background:

• Bestrophin-1 (BEST1) gene variants are linked to bestrophinopathies, a group of inherited retinal diseases.
• Accurate variant classification is crucial for diagnosing and understanding these conditions.
• Existing databases and patient cohorts offer opportunities for updated knowledge synthesis.

Purpose of the Study:

• To update the understanding of bestrophin-1 (BEST1) structure and function.
• To assess the pathogenicity of variants reported in the BEST1-Leiden Open Variation Database (LOVD) and a French cohort.
• To identify population-specific variants and improve diagnostic accuracy for bestrophinopathies.

Main Methods:

• Curated unique variants from the latest BEST1-LOVD database (October 2024).
• Analyzed BEST1 variants from 450 French patients (2008-2024).
• Performed comprehensive in silico analyses (DNA, RNA, protein levels) and literature reviews, classifying variants using American College of Medical Genetics and Genomics (ACMG) criteria.

Main Results:

• Detailed 488 variants from LOVD; identified 150 variants in French patients, including 40 novel ones.
• Classified only eight variants as of unknown significance.
• Identified recurrent French population variants (e.g., p.(Ile230del) in 3.8% of patients), all associated with bestrophinopathy clinical features.

Conclusions:

• Highlighted population-specific variants in the French cohort, impacting protein distribution.
• Reclassified 93.3% of variants as likely pathogenic or pathogenic through in silico analyses.
• Strengthened clinical diagnoses of bestrophinopathies by refining variant pathogenicity assessment.