Prevalence of ABCA4 Deep-Intronic Variants and Related Phenotype in An Unsolved “One-Hit” Cohort with Stargardt Disease

Author:

Nassisi ,Mohand-Saïd ,Andrieu ,Antonio ,Condroyer ,Méjécase ,Varin ,Wohlschlegel ,Dhaenens ,Sahel ,Zeitz ,Audo

Abstract

We investigated the prevalence of reported deep-intronic variants in a French cohort of 70 patients with Stargardt disease harboring a monoallelic pathogenic variant on the exonic regions of ABCA4. Direct Sanger sequencing of selected intronic regions of ABCA4 was conducted. Complete phenotypic analysis and correlation with the genotype was performed in case a known intronic pathogenic variant was identified. All other variants found on the analyzed sequences were queried for minor allele frequency and possible pathogenicity by in silico predictions. The second mutated allele was found in 14 (20%) subjects. The three known deep-intronic variants found were c.5196+1137G>A in intron 36 (6 subjects), c.4539+2064C>T in intron 30 (4 subjects) and c.4253+43G>A in intron 28 (4 subjects). Even though the phenotype depends on the compound effect of the biallelic variants, a genotype-phenotype correlation suggests that the c.5196+1137G>A was mostly associated with a mild phenotype and the c.4539+2064C>T with a more severe one. A variable effect was instead associated with the variant c.4253+43G>A. In addition, two novel variants, c.768+508A>G and c.859-245_859-243delinsTGA never associated with Stargardt disease before, were identified and a possible splice defect was predicted in silico. Our study calls for a larger cohort analysis including targeted locus sequencing and 3D protein modeling to better understand phenotype-genotype correlations associated with deep-intronic changes and patients’ selection for clinical trials.

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3