谷歌浏览器插件
订阅小程序
在清言上使用

Evidence of Two Novel LAMA2 Variants in a Patient with Muscular Dystrophy: Facing the Challenges of a Certain Diagnosis

Frontiers in neurology(2022)

引用 0|浏览28
暂无评分
摘要
BackgroundBenefits and challenges resulting from advances in genetic diagnostics are two sides of the same coin. Facilitation of a correct and timely diagnosis is paralleled by challenges in interpretation of variants of unknown significance (VUS). Focusing on an individual VUS-re-classification pipeline, this study offers a diagnostic approach for clinically suspected hereditary muscular dystrophy by combining the expertise of an interdisciplinary team.MethodsIn a multi-step approach, a thorough phenotype assessment including clinical examination, laboratory work, muscle MRI and histopathological evaluation of muscle was performed in combination with advanced Next Generation Sequencing (NGS). Different in-silico tools and prediction programs like Alamut, SIFT, Polyphen, MutationTaster and M-Cap as well as 3D- modeling of protein structure and RNA-sequencing were employed to determine clinical significance of the LAMA2 variants.ResultsTwo previously unknown sequence alterations in LAMA2 were detected, a missense variant was classified initially according to ACMG guidelines as a VUS (class 3) whereas a second splice site variant was deemed as likely pathogenic (class 4). Pathogenicity of the splice site variant was confirmed by mRNA sequencing and nonsense mediated decay (NMD) was detected. Combination of the detected variants could be associated to the LGMDR23-phenotype based on the MRI matching and literature research.DiscussionTwo novel variants in LAMA2 associated with LGMDR23-phenotype are described. This study illustrates challenges of the genetic findings due to their VUS classification and elucidates how individualized diagnostic procedure has contributed to the accurate diagnosis in the spectrum of LGMD.
更多
查看译文
关键词
muscular dystrophy,LGMDR23,hereditary myopathy,merosin,next generation sequencing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要