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利用遗传变异的参考数据库评估候选疾病变异的潜在致病性。

Using reference databases of genetic variation to evaluate the potential pathogenicity of candidate disease variants.

机构信息

Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland.

出版信息

Hum Mutat. 2013 Jun;34(6):836-41. doi: 10.1002/humu.22303. Epub 2013 Mar 26.

DOI:10.1002/humu.22303
PMID:23447461
Abstract

The potential pathogenicity of genetic variants identified in disease-based resequencing studies is often overlooked where variants have previously been reported in dbSNP, the 1000 genomes project, or the National Heart, Lung and Blood Institute Exome Sequencing Project (ESP). In this work, we estimate that collectively, these databases capture ∼52% of mutations (dbSNP 50.4%; 1000 genomes 4.8%; and ESP 10.2%) reported as disease causing within phenotype-based locus-specific databases (LSDBs). To investigate whether these mutations may simply represent benign population variants, we evaluated whether the carrier frequencies associated with mutations implicated in amyotrophic lateral sclerosis were higher than what could be accounted for by high-penetrance disease models. In doing so, we have questioned the veracity of 51 mutations, but also demonstrated that each of the three databases included credible disease variants. Our results demonstrate the benefits of using databases such as dbSNP, the 1000 genomes project, and the ESP to evaluate the pathogenicity of putative disease variants, and suggest that many disease mutations reported across LSDBs may not actually be pathogenic. However, they also demonstrate that even in the context of rare Mendelian disorders, the potential pathogenicity of variants reported by these databases should not be overlooked without proper evaluation.

摘要

在基于疾病的重测序研究中发现的遗传变异的潜在致病性,通常会被忽视,因为这些变异之前已在 dbSNP、1000 基因组计划或美国国立心肺血液研究所外显子测序计划 (ESP) 中报道过。在这项工作中,我们估计这些数据库总共捕获了约 52%的突变(dbSNP 占 50.4%,1000 基因组占 4.8%,ESP 占 10.2%),这些突变被报道为表型特异性基因座数据库(LSDB)中的疾病致病突变。为了研究这些突变是否可能仅仅代表良性的人群变异,我们评估了与肌萎缩侧索硬化症相关的突变的携带者频率是否高于高外显率疾病模型所能解释的频率。通过这样做,我们对 51 个突变的真实性提出了质疑,但也证明了这三个数据库中的每一个都包含可信的疾病变异。我们的研究结果表明,利用 dbSNP、1000 基因组计划和 ESP 等数据库来评估潜在疾病变异的致病性是有益的,并表明 LSDB 中报告的许多疾病突变可能实际上并不是致病性的。然而,它们也表明,即使在罕见的孟德尔疾病的背景下,如果没有适当的评估,也不应忽视这些数据库报告的变异的潜在致病性。

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