Suppr超能文献

罕见病中变异致病性相互冲突解读的主要原因:一项系统分析

Major Causes of Conflicting Interpretations of Variant Pathogenicity in Rare Disease: A Systematic Analysis.

作者信息

Lazareva Tatyana E, Barbitoff Yury A, Nasykhova Yulia A, Glotov Andrey S

机构信息

Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya Line 3, 199034 St. Petersburg, Russia.

Bioinformatics Institute, Kantemirovskaya St. 2A, 197342 St. Petersburg, Russia.

出版信息

J Pers Med. 2024 Aug 15;14(8):864. doi: 10.3390/jpm14080864.

Abstract

The identification of the genetic causes of inherited disorders from next-generation sequencing (NGS) data remains a complicated process, in particular due to challenges in interpretation of the vast amount of generated data and hundreds of candidate variants identified. Inconsistencies in variant classification, where genetic centers classify the same variant differently, can hinder accurate diagnoses for rare diseases. Publicly available databases that collect data on human genetic variations and their association with diseases provide ample opportunities to discover conflicts in variant interpretation worldwide. In this study, we explored patterns of variant classification discrepancies using data from ClinVar, a public archive of variant interpretations. We found that 5.7% of variants have conflicting interpretations (COIs) reported, and the vast majority of interpretation conflicts arise for variants of uncertain significance (VUS). As many as 78% of clinically relevant genes harbor variants with COIs, and genes with high COI rates tended to have more exons and longer transcripts, with a greater proportion of genes linked to several distinct conditions. The enrichment analysis of COI-enriched genes revealed that the products of these genes are involved in cardiac disorders, muscle development, and function. To improve diagnoses, we believe that specific variant interpretation rules could be developed for such genes. Additionally, our findings underscore the need for the publication of variant pathogenicity evidence and the importance of considering every variant as VUS unless proven otherwise.

摘要

从下一代测序(NGS)数据中识别遗传性疾病的遗传病因仍然是一个复杂的过程,尤其是因为在解释大量生成的数据以及识别出的数百个候选变异体方面存在挑战。变异体分类不一致,即不同遗传中心对同一变异体的分类不同,可能会阻碍罕见病的准确诊断。收集人类遗传变异及其与疾病关联数据的公开数据库为发现全球变异体解释中的冲突提供了充足的机会。在本研究中,我们使用来自ClinVar(一个变异体解释的公共存档库)的数据,探索了变异体分类差异的模式。我们发现,有5.7%的变异体报告了相互冲突的解释(COI),并且绝大多数解释冲突出现在意义未明的变异体(VUS)中。多达78%的临床相关基因含有具有COI的变异体,且COI率高的基因往往有更多外显子和更长的转录本,与几种不同疾病相关的基因比例更大。对富含COI的基因进行富集分析表明,这些基因的产物参与心脏疾病、肌肉发育和功能。为了改善诊断,我们认为可以针对此类基因制定特定的变异体解释规则。此外,我们的研究结果强调了公布变异体致病性证据的必要性,以及在未得到其他证明之前将每个变异体视为VUS的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5fd/11355203/dae49057178a/jpm-14-00864-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验