Bitan Joan, Poncet Anaïs F, Lecigne Claire, Devos Aurore, Meunier Isabelle, Zanlonghi Xavier, Grunewald Olivier, Smirnov Vasily, Dhaenens Claire-Marie
University of Lille, INSERM, CHU-Lille, U1172 - Lille Neuroscience & Cognition Research Center (LilNCog), Lille, France.
Institute for Neurosciences of Montpellier, University of Montpellier, INSERM, Montpellier, France.
Invest Ophthalmol Vis Sci. 2025 Sep 2;66(12):4. doi: 10.1167/iovs.66.12.4.
To update knowledge on bestrophin-1 structure and function with the aim of assessing the pathogenicity of variants reported in the Leiden Open Variation Database (LOVD) and in a large French cohort of bestrophinopathies.
All unique variants reported in the latest version (October 2024) of the BEST1-LOVD database were uploaded and curated. We described all BEST1 variants identified in French patients analyzed at Lille University Hospital, between 2008 and 2024. A comprehensive analysis of each variant was performed based on in silico tools (at DNA, RNA, and protein levels), as well as a literature review providing clinical data and functional assays. All of these data were used to classify the variant pathogenicity according to the American College of Medical Genetics and Genomics (ACMG) criteria.
We detailed 488 variants from the LOVD. Among 450 French patients, we identified 150 different variants, 40 of which were novel. We classified only eight variants as variants of unknown significance, four of which were already in the LOVD. We identified specific recurrent variants in the French population: p.(Gly26Asp), p.(Val90Met), p.(Val137Met), and p.(Ile230del), the last of which was present in 17 patients (3.8%). All new variants cause changes in chemical interactions within the protein and are associated with clinical pictures of bestrophinopathy.
The study and comparison of these two large cohorts highlight variants specific to the French population, as well as differences in protein distribution, which are undoubtedly influenced by several population-specific factors. Through multiple in silico analyses, we were able to reclassify 93.3% of variants as likely pathogenic or pathogenic, thereby strengthening clinical diagnoses.
更新关于贝斯特罗芬-1结构和功能的知识,以评估莱顿开放变异数据库(LOVD)和一个大型法国贝斯特罗芬病队列中报告的变异的致病性。
上传并整理了BEST1-LOVD数据库最新版本(2024年10月)中报告的所有独特变异。我们描述了2008年至2024年在里尔大学医院分析的法国患者中鉴定出的所有BEST1变异。基于计算机工具(在DNA、RNA和蛋白质水平)对每个变异进行了全面分析,并进行了文献综述以提供临床数据和功能测定。所有这些数据都用于根据美国医学遗传学与基因组学学会(ACMG)标准对变异致病性进行分类。
我们详细研究了LOVD中的488个变异。在450名法国患者中,我们鉴定出150个不同的变异,其中40个是新的。我们仅将8个变异分类为意义未明的变异,其中4个已在LOVD中。我们在法国人群中鉴定出特定的复发性变异:p.(Gly26Asp)、p.(Val90Met)、p.(Val137Met)和p.(Ile230del),最后一个变异出现在17名患者中(3.8%)。所有新变异都会导致蛋白质内化学相互作用的改变,并与贝斯特罗芬病的临床表现相关。
对这两个大型队列的研究和比较突出了法国人群特有的变异以及蛋白质分布的差异,这些差异无疑受到多种人群特异性因素的影响。通过多次计算机分析,我们能够将93.3%的变异重新分类为可能致病或致病,从而加强临床诊断。