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实验分析 AIDS 功能对预测性计算工具的临床意义:错义变异的挑战。

Clinical implications of experimental analyses of AID function on predictive computational tools: Challenge of missense variants.

机构信息

Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden.

BGI-Shenzhen, Shenzhen, China.

出版信息

Clin Genet. 2020 Jun;97(6):844-856. doi: 10.1111/cge.13737. Epub 2020 Mar 22.

DOI:10.1111/cge.13737
PMID:32162335
Abstract

Due to the increased usage of high throughput sequencing for the diagnosis of genetically inherited disorders, it is vital to evaluate the risk of new variants and novel genes before accepting them in clinical practice. However, discordant in silico and in vitro results, challenge estimations of the effect of an identified genetic variant. We aimed to comprehensively evaluate pathogenic and polymorphic variants using the activation-induced-cytidine-deaminase (AICDA) gene as a model. We systematically searched and identified patients with confirmed AICDA-mutations. Population-based-databases were screened for germline-polymorphic-AICDA-variants. Activity of AICDA-mutant and severity of the clinical and immunologic-phenotype were showed comparing 108 population-based-variants with 48 pathogenic mutations (12 overlapping-variants). Discordant predictions of different algorithms were observed on average in 38% of the population-database variants, mainly for missense mutations. Functional activity in mutations observed only in patients was significantly lower than variants in the population databases and overlapping-variants between patients and the general-population. Surprisingly, overlapping-variants had an even higher functional activity than the most common polymorphic-variants; however, their pathogenicity was still distinguishable when their function was compared with wild-type AICDA. Classifications of genetic variants cannot readily be translated into a clinical implication. Combined databases of functional and computational assays should therefore be developed for each specific gene.

摘要

由于高通量测序在遗传性疾病诊断中的应用日益增多,在将新变异和新基因纳入临床实践之前,评估其风险至关重要。然而,体外和体内结果的不一致,对所鉴定的遗传变异效应的估计提出了挑战。我们旨在以激活诱导胞苷脱氨酶(AICDA)基因为模型,全面评估致病性和多态性变异。我们系统地搜索并确定了已确诊的 AICDA 突变患者。筛选了基于人群的数据库,以寻找种系多态性 AICDA 变异。通过比较 108 个基于人群的变异与 48 个致病性突变(12 个重叠变异),显示了 AICDA 突变体的活性和临床及免疫表型的严重程度。平均而言,在 38%的人群数据库变异中观察到不同算法的预测不一致,主要是错义突变。仅在患者中观察到的突变的功能活性明显低于人群数据库中的变体和患者与一般人群之间的重叠变体。令人惊讶的是,重叠变体的功能活性甚至高于最常见的多态变体;然而,当将其功能与野生型 AICDA 进行比较时,它们的致病性仍然可以区分。遗传变异的分类不能轻易转化为临床意义。因此,应针对每个特定基因开发包含功能和计算分析的综合数据库。

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